format files and adjust architecture

.gitignore

@@ -96,3 +96,6 @@ metal/paddle-mobile/paddle-mobile/CPU/libpaddle-mobile.a
 
 metal/paddle-mobile-demo/paddle-mobile-demo/images
 metal/paddle-mobile-demo/paddle-mobile-demo/models
+metal/paddle-mobile-demo/paddle-mobile-demo/Resources
+metal/paddle-mobile-demo/paddle-mobile-demo/Resources/images
+metal/paddle-mobile-demo/paddle-mobile-demo/Resources/models

metal/paddle-mobile-demo/paddle-mobile-demo.xcodeproj/project.pbxproj

@@ -10,13 +10,26 @@
 		30D0ED21F392CFA3885B1002 /* Pods_paddle_mobile_demo.framework in Frameworks */ = {isa = PBXBuildFile; fileRef = 18896810981724F8A0FED62A /* Pods_paddle_mobile_demo.framework */; };
 		C2CBB49021B778EA0020DC6C /* libc++.tbd in Frameworks */ = {isa = PBXBuildFile; fileRef = FC4FD97B2140EE250073E130 /* libc++.tbd */; };
 		C2E67E5E21524E460013F575 /* LoadPointerViewController.m in Sources */ = {isa = PBXBuildFile; fileRef = C2E67E5D21524E460013F575 /* LoadPointerViewController.m */; };
-		FC013928210204A3008100E3 /* PreProcessKernel.metal in Sources */ = {isa = PBXBuildFile; fileRef = FC013927210204A3008100E3 /* PreProcessKernel.metal */; };
 		FC039B8220E11C550081E9F8 /* AppDelegate.swift in Sources */ = {isa = PBXBuildFile; fileRef = FC039B8120E11C550081E9F8 /* AppDelegate.swift */; };
 		FC039B8420E11C550081E9F8 /* ViewController.swift in Sources */ = {isa = PBXBuildFile; fileRef = FC039B8320E11C550081E9F8 /* ViewController.swift */; };
 		FC039B8720E11C550081E9F8 /* Main.storyboard in Resources */ = {isa = PBXBuildFile; fileRef = FC039B8520E11C550081E9F8 /* Main.storyboard */; };
 		FC039B8920E11C560081E9F8 /* Assets.xcassets in Resources */ = {isa = PBXBuildFile; fileRef = FC039B8820E11C560081E9F8 /* Assets.xcassets */; };
 		FC039B8C20E11C560081E9F8 /* LaunchScreen.storyboard in Resources */ = {isa = PBXBuildFile; fileRef = FC039B8A20E11C560081E9F8 /* LaunchScreen.storyboard */; };
 		FC203FB221CBFDBA00B37166 /* test.jpg in Resources */ = {isa = PBXBuildFile; fileRef = FC203FA921CBFDBA00B37166 /* test.jpg */; };
+		FC2BFCBC21DF0A8600C262B2 /* 00001.jpg in Resources */ = {isa = PBXBuildFile; fileRef = FC2BFCBB21DF0A8600C262B2 /* 00001.jpg */; };
+		FC2BFCBE21DF15D900C262B2 /* 123.jpg in Resources */ = {isa = PBXBuildFile; fileRef = FC2BFCBD21DF15D900C262B2 /* 123.jpg */; };
+		FC2BFCC021DF279900C262B2 /* classify-img-output.png in Resources */ = {isa = PBXBuildFile; fileRef = FC2BFCBF21DF279900C262B2 /* classify-img-output.png */; };
+		FC2BFD3021DF3FEA00C262B2 /* MobilenetSSD_AR.swift in Sources */ = {isa = PBXBuildFile; fileRef = FC2BFD2A21DF3FE900C262B2 /* MobilenetSSD_AR.swift */; };
+		FC2BFD3121DF3FEA00C262B2 /* Genet.swift in Sources */ = {isa = PBXBuildFile; fileRef = FC2BFD2B21DF3FE900C262B2 /* Genet.swift */; };
+		FC2BFD3221DF3FEA00C262B2 /* MobileNetSSD.swift in Sources */ = {isa = PBXBuildFile; fileRef = FC2BFD2C21DF3FE900C262B2 /* MobileNetSSD.swift */; };
+		FC2BFD3321DF3FEA00C262B2 /* YoloNet.swift in Sources */ = {isa = PBXBuildFile; fileRef = FC2BFD2D21DF3FE900C262B2 /* YoloNet.swift */; };
+		FC2BFD3421DF3FEA00C262B2 /* MobileNetCombined.swift in Sources */ = {isa = PBXBuildFile; fileRef = FC2BFD2E21DF3FEA00C262B2 /* MobileNetCombined.swift */; };
+		FC2BFD3521DF3FEA00C262B2 /* MobileNet.swift in Sources */ = {isa = PBXBuildFile; fileRef = FC2BFD2F21DF3FEA00C262B2 /* MobileNet.swift */; };
+		FC2BFD3821DF46DE00C262B2 /* OCDemoViewController.m in Sources */ = {isa = PBXBuildFile; fileRef = FC2BFD3721DF46DE00C262B2 /* OCDemoViewController.m */; };
+		FC2BFD3C21DF480400C262B2 /* CPUCompute.mm in Sources */ = {isa = PBXBuildFile; fileRef = FC2BFD3B21DF480400C262B2 /* CPUCompute.mm */; };
+		FC2BFD3E21DF5CE800C262B2 /* PreProcessKernel.metal in Sources */ = {isa = PBXBuildFile; fileRef = FC2BFD3D21DF5CE800C262B2 /* PreProcessKernel.metal */; };
+		FC2BFD4321DF5E1E00C262B2 /* PaddleMobileGPU.m in Sources */ = {isa = PBXBuildFile; fileRef = FC2BFD4021DF5E1E00C262B2 /* PaddleMobileGPU.m */; };
+		FC2BFD4421DF5E1E00C262B2 /* SuperResolutionNet.swift in Sources */ = {isa = PBXBuildFile; fileRef = FC2BFD4221DF5E1E00C262B2 /* SuperResolutionNet.swift */; };
 		FC5E03B221DCE8D90016C137 /* mingren_input_data in Resources */ = {isa = PBXBuildFile; fileRef = FC5E03B121DCE8D90016C137 /* mingren_input_data */; };
 		FC704C1921D2375300F98BAB /* super_params in Resources */ = {isa = PBXBuildFile; fileRef = FC704C1721D2375300F98BAB /* super_params */; };
 		FC704C1A21D2375300F98BAB /* super_model in Resources */ = {isa = PBXBuildFile; fileRef = FC704C1821D2375300F98BAB /* super_model */; };
@@ -31,7 +44,6 @@
 		FC9797C321D608E000F2FD90 /* mobilenet_params in Resources */ = {isa = PBXBuildFile; fileRef = FC9797C121D608DF00F2FD90 /* mobilenet_params */; };
 		FC9797C721D609FB00F2FD90 /* synset.txt in Resources */ = {isa = PBXBuildFile; fileRef = FC9797C621D609FB00F2FD90 /* synset.txt */; };
 		FC9797CF21D6506F00F2FD90 /* mingren.jpg in Resources */ = {isa = PBXBuildFile; fileRef = FC9797CE21D6506F00F2FD90 /* mingren.jpg */; };
-		FC9797D121D6616600F2FD90 /* BufferToTexture.metal in Sources */ = {isa = PBXBuildFile; fileRef = FC9797D021D6616600F2FD90 /* BufferToTexture.metal */; };
 		FCBCCC552122EF5500D94F7E /* MetalHelper.swift in Sources */ = {isa = PBXBuildFile; fileRef = FCBCCC542122EF5400D94F7E /* MetalHelper.swift */; };
 		FCCED60521D7646E00BE8D5F /* test_image_super in Resources */ = {isa = PBXBuildFile; fileRef = FCCED60421D7646E00BE8D5F /* test_image_super */; };
 		FCEBEC2C20E1391F00C0B14D /* paddle_mobile.framework in Frameworks */ = {isa = PBXBuildFile; fileRef = FCEBEC2B20E1391F00C0B14D /* paddle_mobile.framework */; };
@@ -59,7 +71,6 @@
 		878829884E1A14D7044721D5 /* Pods-paddle-mobile-demo.debug.xcconfig */ = {isa = PBXFileReference; includeInIndex = 1; lastKnownFileType = text.xcconfig; name = "Pods-paddle-mobile-demo.debug.xcconfig"; path = "../Pods/Target Support Files/Pods-paddle-mobile-demo/Pods-paddle-mobile-demo.debug.xcconfig"; sourceTree = "<group>"; };
 		C2E67E5C21524E460013F575 /* LoadPointerViewController.h */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.c.h; path = LoadPointerViewController.h; sourceTree = "<group>"; };
 		C2E67E5D21524E460013F575 /* LoadPointerViewController.m */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.c.objc; path = LoadPointerViewController.m; sourceTree = "<group>"; };
-		FC013927210204A3008100E3 /* PreProcessKernel.metal */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.metal; path = PreProcessKernel.metal; sourceTree = "<group>"; };
 		FC039B7E20E11C550081E9F8 /* paddle-mobile-demo.app */ = {isa = PBXFileReference; explicitFileType = wrapper.application; includeInIndex = 0; path = "paddle-mobile-demo.app"; sourceTree = BUILT_PRODUCTS_DIR; };
 		FC039B8120E11C550081E9F8 /* AppDelegate.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = AppDelegate.swift; sourceTree = "<group>"; };
 		FC039B8320E11C550081E9F8 /* ViewController.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = ViewController.swift; sourceTree = "<group>"; };
@@ -69,6 +80,23 @@
 		FC039B8D20E11C560081E9F8 /* Info.plist */ = {isa = PBXFileReference; lastKnownFileType = text.plist.xml; path = Info.plist; sourceTree = "<group>"; };
 		FC203FA921CBFDBA00B37166 /* test.jpg */ = {isa = PBXFileReference; lastKnownFileType = image.jpeg; path = test.jpg; sourceTree = "<group>"; };
 		FC27991121343A39000B6BAD /* paddle-mobile-demo-Bridging-Header.h */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.c.h; path = "paddle-mobile-demo-Bridging-Header.h"; sourceTree = "<group>"; };
+		FC2BFCBB21DF0A8600C262B2 /* 00001.jpg */ = {isa = PBXFileReference; lastKnownFileType = image.jpeg; path = 00001.jpg; sourceTree = "<group>"; };
+		FC2BFCBD21DF15D900C262B2 /* 123.jpg */ = {isa = PBXFileReference; lastKnownFileType = image.jpeg; path = 123.jpg; sourceTree = "<group>"; };
+		FC2BFCBF21DF279900C262B2 /* classify-img-output.png */ = {isa = PBXFileReference; lastKnownFileType = image.png; path = "classify-img-output.png"; sourceTree = "<group>"; };
+		FC2BFD2A21DF3FE900C262B2 /* MobilenetSSD_AR.swift */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.swift; path = MobilenetSSD_AR.swift; sourceTree = "<group>"; };
+		FC2BFD2B21DF3FE900C262B2 /* Genet.swift */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.swift; path = Genet.swift; sourceTree = "<group>"; };
+		FC2BFD2C21DF3FE900C262B2 /* MobileNetSSD.swift */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.swift; path = MobileNetSSD.swift; sourceTree = "<group>"; };
+		FC2BFD2D21DF3FE900C262B2 /* YoloNet.swift */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.swift; path = YoloNet.swift; sourceTree = "<group>"; };
+		FC2BFD2E21DF3FEA00C262B2 /* MobileNetCombined.swift */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.swift; path = MobileNetCombined.swift; sourceTree = "<group>"; };
+		FC2BFD2F21DF3FEA00C262B2 /* MobileNet.swift */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.swift; path = MobileNet.swift; sourceTree = "<group>"; };
+		FC2BFD3621DF46DE00C262B2 /* OCDemoViewController.h */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.c.h; path = OCDemoViewController.h; sourceTree = "<group>"; };
+		FC2BFD3721DF46DE00C262B2 /* OCDemoViewController.m */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.c.objc; path = OCDemoViewController.m; sourceTree = "<group>"; };
+		FC2BFD3A21DF480300C262B2 /* CPUCompute.h */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.c.h; path = CPUCompute.h; sourceTree = "<group>"; };
+		FC2BFD3B21DF480400C262B2 /* CPUCompute.mm */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.cpp.objcpp; path = CPUCompute.mm; sourceTree = "<group>"; };
+		FC2BFD3D21DF5CE800C262B2 /* PreProcessKernel.metal */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.metal; path = PreProcessKernel.metal; sourceTree = "<group>"; };
+		FC2BFD4021DF5E1E00C262B2 /* PaddleMobileGPU.m */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.c.objc; path = PaddleMobileGPU.m; sourceTree = "<group>"; };
+		FC2BFD4121DF5E1E00C262B2 /* PaddleMobileGPU.h */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.c.h; path = PaddleMobileGPU.h; sourceTree = "<group>"; };
+		FC2BFD4221DF5E1E00C262B2 /* SuperResolutionNet.swift */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.swift; path = SuperResolutionNet.swift; sourceTree = "<group>"; };
 		FC4FD97B2140EE250073E130 /* libc++.tbd */ = {isa = PBXFileReference; lastKnownFileType = "sourcecode.text-based-dylib-definition"; name = "libc++.tbd"; path = "usr/lib/libc++.tbd"; sourceTree = SDKROOT; };
 		FC5E03B121DCE8D90016C137 /* mingren_input_data */ = {isa = PBXFileReference; lastKnownFileType = file; path = mingren_input_data; sourceTree = "<group>"; };
 		FC704C1721D2375300F98BAB /* super_params */ = {isa = PBXFileReference; lastKnownFileType = file; path = super_params; sourceTree = "<group>"; };
@@ -84,7 +112,6 @@
 		FC9797C121D608DF00F2FD90 /* mobilenet_params */ = {isa = PBXFileReference; lastKnownFileType = file; path = mobilenet_params; sourceTree = "<group>"; };
 		FC9797C621D609FB00F2FD90 /* synset.txt */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = text; path = synset.txt; sourceTree = "<group>"; };
 		FC9797CE21D6506F00F2FD90 /* mingren.jpg */ = {isa = PBXFileReference; lastKnownFileType = image.jpeg; path = mingren.jpg; sourceTree = "<group>"; };
-		FC9797D021D6616600F2FD90 /* BufferToTexture.metal */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.metal; path = BufferToTexture.metal; sourceTree = "<group>"; };
 		FCBCCC542122EF5400D94F7E /* MetalHelper.swift */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.swift; path = MetalHelper.swift; sourceTree = "<group>"; };
 		FCCED60421D7646E00BE8D5F /* test_image_super */ = {isa = PBXFileReference; lastKnownFileType = file; path = test_image_super; sourceTree = "<group>"; };
 		FCEBEC2B20E1391F00C0B14D /* paddle_mobile.framework */ = {isa = PBXFileReference; explicitFileType = wrapper.framework; path = paddle_mobile.framework; sourceTree = BUILT_PRODUCTS_DIR; };
@@ -145,8 +172,11 @@
 		FC039B8020E11C550081E9F8 /* paddle-mobile-demo */ = {
 			isa = PBXGroup;
 			children = (
-				FC203FA821CBFDBA00B37166 /* images */,
-				FC203FAA21CBFDBA00B37166 /* models */,
+				FC2BFD4F21DF892500C262B2 /* Resources */,
+				FCBCCC542122EF5400D94F7E /* MetalHelper.swift */,
+				FC2BFD3F21DF5DDF00C262B2 /* OCInterface */,
+				FC27991121343A39000B6BAD /* paddle-mobile-demo-Bridging-Header.h */,
+				FC2BFD3921DF46F000C262B2 /* OCDemo */,
 				FC803BCA214D27920094B8E5 /* VideoCapture */,
 				FC8CFED2213519540094D569 /* Net */,
 				FC039B8120E11C550081E9F8 /* AppDelegate.swift */,
@@ -155,10 +185,7 @@
 				FC039B8820E11C560081E9F8 /* Assets.xcassets */,
 				FC039B8A20E11C560081E9F8 /* LaunchScreen.storyboard */,
 				FC039B8D20E11C560081E9F8 /* Info.plist */,
-				FC27991121343A39000B6BAD /* paddle-mobile-demo-Bridging-Header.h */,
 				FCF437E7214B6DDB00943429 /* MultiPredictViewController.swift */,
-				C2E67E5C21524E460013F575 /* LoadPointerViewController.h */,
-				C2E67E5D21524E460013F575 /* LoadPointerViewController.m */,
 			);
 			path = "paddle-mobile-demo";
 			sourceTree = "<group>";
@@ -166,14 +193,16 @@
 		FC203FA821CBFDBA00B37166 /* images */ = {
 			isa = PBXGroup;
 			children = (
+				FC2BFCBF21DF279900C262B2 /* classify-img-output.png */,
+				FC2BFCBD21DF15D900C262B2 /* 123.jpg */,
+				FC2BFCBB21DF0A8600C262B2 /* 00001.jpg */,
 				FC5E03B121DCE8D90016C137 /* mingren_input_data */,
 				FCCED60421D7646E00BE8D5F /* test_image_super */,
 				FC9797CE21D6506F00F2FD90 /* mingren.jpg */,
 				FC9797BD21D6045B00F2FD90 /* banana.jpeg */,
 				FC203FA921CBFDBA00B37166 /* test.jpg */,
 			);
-			name = images;
-			path = ../../images;
+			path = images;
 			sourceTree = "<group>";
 		};
 		FC203FAA21CBFDBA00B37166 /* models */ = {
@@ -183,8 +212,37 @@
 				FC704C1B21D237FC00F98BAB /* vision_model */,
 				FC704C1621D2375300F98BAB /* superresoltion */,
 			);
-			name = models;
-			path = ../../models;
+			path = models;
+			sourceTree = "<group>";
+		};
+		FC2BFD3921DF46F000C262B2 /* OCDemo */ = {
+			isa = PBXGroup;
+			children = (
+				C2E67E5C21524E460013F575 /* LoadPointerViewController.h */,
+				C2E67E5D21524E460013F575 /* LoadPointerViewController.m */,
+				FC2BFD3621DF46DE00C262B2 /* OCDemoViewController.h */,
+				FC2BFD3721DF46DE00C262B2 /* OCDemoViewController.m */,
+			);
+			path = OCDemo;
+			sourceTree = "<group>";
+		};
+		FC2BFD3F21DF5DDF00C262B2 /* OCInterface */ = {
+			isa = PBXGroup;
+			children = (
+				FC2BFD4121DF5E1E00C262B2 /* PaddleMobileGPU.h */,
+				FC2BFD4021DF5E1E00C262B2 /* PaddleMobileGPU.m */,
+				FC2BFD4221DF5E1E00C262B2 /* SuperResolutionNet.swift */,
+			);
+			path = OCInterface;
+			sourceTree = "<group>";
+		};
+		FC2BFD4F21DF892500C262B2 /* Resources */ = {
+			isa = PBXGroup;
+			children = (
+				FC203FA821CBFDBA00B37166 /* images */,
+				FC203FAA21CBFDBA00B37166 /* models */,
+			);
+			path = Resources;
 			sourceTree = "<group>";
 		};
 		FC704C1621D2375300F98BAB /* superresoltion */ = {
@@ -235,9 +293,15 @@
 		FC8CFED2213519540094D569 /* Net */ = {
 			isa = PBXGroup;
 			children = (
-				FC013927210204A3008100E3 /* PreProcessKernel.metal */,
-				FCBCCC542122EF5400D94F7E /* MetalHelper.swift */,
-				FC9797D021D6616600F2FD90 /* BufferToTexture.metal */,
+				FC2BFD3A21DF480300C262B2 /* CPUCompute.h */,
+				FC2BFD3B21DF480400C262B2 /* CPUCompute.mm */,
+				FC2BFD3D21DF5CE800C262B2 /* PreProcessKernel.metal */,
+				FC2BFD2B21DF3FE900C262B2 /* Genet.swift */,
+				FC2BFD2F21DF3FEA00C262B2 /* MobileNet.swift */,
+				FC2BFD2E21DF3FEA00C262B2 /* MobileNetCombined.swift */,
+				FC2BFD2A21DF3FE900C262B2 /* MobilenetSSD_AR.swift */,
+				FC2BFD2C21DF3FE900C262B2 /* MobileNetSSD.swift */,
+				FC2BFD2D21DF3FE900C262B2 /* YoloNet.swift */,
 			);
 			path = Net;
 			sourceTree = "<group>";
@@ -319,16 +383,19 @@
 				FC9797CF21D6506F00F2FD90 /* mingren.jpg in Resources */,
 				FC704C2221D237FC00F98BAB /* combined_mobilenet_params in Resources */,
 				FC704C1921D2375300F98BAB /* super_params in Resources */,
+				FC2BFCBE21DF15D900C262B2 /* 123.jpg in Resources */,
 				FC039B8920E11C560081E9F8 /* Assets.xcassets in Resources */,
 				FC9797C721D609FB00F2FD90 /* synset.txt in Resources */,
 				FC5E03B221DCE8D90016C137 /* mingren_input_data in Resources */,
 				FC704C1A21D2375300F98BAB /* super_model in Resources */,
 				FC039B8720E11C550081E9F8 /* Main.storyboard in Resources */,
 				FC9797C221D608E000F2FD90 /* mobilenet_model in Resources */,
+				FC2BFCC021DF279900C262B2 /* classify-img-output.png in Resources */,
 				FC203FB221CBFDBA00B37166 /* test.jpg in Resources */,
 				FC704C2321D237FC00F98BAB /* combined_mobilenet_model in Resources */,
 				FC9797C321D608E000F2FD90 /* mobilenet_params in Resources */,
 				FC704C2421D237FC00F98BAB /* yolo_params in Resources */,
+				FC2BFCBC21DF0A8600C262B2 /* 00001.jpg in Resources */,
 				FC9797BE21D6045B00F2FD90 /* banana.jpeg in Resources */,
 				FC704C2521D237FC00F98BAB /* yolo_model in Resources */,
 			);
@@ -380,15 +447,24 @@
 			isa = PBXSourcesBuildPhase;
 			buildActionMask = 2147483647;
 			files = (
+				FC2BFD3221DF3FEA00C262B2 /* MobileNetSSD.swift in Sources */,
+				FC2BFD3C21DF480400C262B2 /* CPUCompute.mm in Sources */,
+				FC2BFD4321DF5E1E00C262B2 /* PaddleMobileGPU.m in Sources */,
 				FC039B8420E11C550081E9F8 /* ViewController.swift in Sources */,
 				FC803BCE214D27930094B8E5 /* VideoCapture.swift in Sources */,
-				FC013928210204A3008100E3 /* PreProcessKernel.metal in Sources */,
 				FCF437E8214B6DDB00943429 /* MultiPredictViewController.swift in Sources */,
+				FC2BFD3021DF3FEA00C262B2 /* MobilenetSSD_AR.swift in Sources */,
+				FC2BFD3321DF3FEA00C262B2 /* YoloNet.swift in Sources */,
+				FC2BFD3421DF3FEA00C262B2 /* MobileNetCombined.swift in Sources */,
 				FCBCCC552122EF5500D94F7E /* MetalHelper.swift in Sources */,
 				FC803BCD214D27930094B8E5 /* FPSCounter.swift in Sources */,
+				FC2BFD3521DF3FEA00C262B2 /* MobileNet.swift in Sources */,
 				C2E67E5E21524E460013F575 /* LoadPointerViewController.m in Sources */,
+				FC2BFD3121DF3FEA00C262B2 /* Genet.swift in Sources */,
 				FC039B8220E11C550081E9F8 /* AppDelegate.swift in Sources */,
-				FC9797D121D6616600F2FD90 /* BufferToTexture.metal in Sources */,
+				FC2BFD4421DF5E1E00C262B2 /* SuperResolutionNet.swift in Sources */,
+				FC2BFD3E21DF5CE800C262B2 /* PreProcessKernel.metal in Sources */,
+				FC2BFD3821DF46DE00C262B2 /* OCDemoViewController.m in Sources */,
 			);
 			runOnlyForDeploymentPostprocessing = 0;
 		};

metal/paddle-mobile-demo/paddle-mobile-demo/Base.lproj/Main.storyboard

 <?xml version="1.0" encoding="UTF-8"?>
-<document type="com.apple.InterfaceBuilder3.CocoaTouch.Storyboard.XIB" version="3.0" toolsVersion="14113" targetRuntime="iOS.CocoaTouch" propertyAccessControl="none" useAutolayout="YES" useTraitCollections="YES" useSafeAreas="YES" colorMatched="YES" initialViewController="BYZ-38-t0r">
+<document type="com.apple.InterfaceBuilder3.CocoaTouch.Storyboard.XIB" version="3.0" toolsVersion="14460.31" targetRuntime="iOS.CocoaTouch" propertyAccessControl="none" useAutolayout="YES" useTraitCollections="YES" useSafeAreas="YES" colorMatched="YES" initialViewController="BYZ-38-t0r">
     <device id="retina4_7" orientation="portrait">
         <adaptation id="fullscreen"/>
     </device>
     <dependencies>
         <deployment identifier="iOS"/>
-        <plugIn identifier="com.apple.InterfaceBuilder.IBCocoaTouchPlugin" version="14088"/>
-        <capability name="Aspect ratio constraints" minToolsVersion="5.1"/>
+        <plugIn identifier="com.apple.InterfaceBuilder.IBCocoaTouchPlugin" version="14460.20"/>
         <capability name="Safe area layout guides" minToolsVersion="9.0"/>
         <capability name="documents saved in the Xcode 8 format" minToolsVersion="8.0"/>
     </dependencies>
@@ -20,7 +19,7 @@
                         <autoresizingMask key="autoresizingMask" widthSizable="YES" heightSizable="YES"/>
                         <subviews>
                             <button opaque="NO" contentMode="scaleToFill" contentHorizontalAlignment="center" contentVerticalAlignment="center" buttonType="roundedRect" lineBreakMode="middleTruncation" translatesAutoresizingMaskIntoConstraints="NO" id="TQt-X9-PdF">
-                                <rect key="frame" x="164" y="318" width="46" height="30"/>
+                                <rect key="frame" x="164.5" y="318.5" width="46" height="30"/>
                                 <state key="normal" title="Button"/>
                                 <connections>
                                     <action selector="predictAct:" destination="Vwd-lt-764" eventType="touchUpInside" id="d4z-Cv-6jY"/>
@@ -60,7 +59,7 @@
                                 <nil key="highlightedColor"/>
                             </label>
                             <pickerView contentMode="scaleToFill" translatesAutoresizingMaskIntoConstraints="NO" id="DlO-dk-RMr">
-                                <rect key="frame" x="55" y="510.5" width="320" height="80"/>
+                                <rect key="frame" x="55" y="510" width="320" height="80"/>
                                 <constraints>
                                     <constraint firstAttribute="height" constant="80" id="Sbi-05-Mwd"/>
                                 </constraints>
@@ -83,6 +82,9 @@
                             <button opaque="NO" contentMode="scaleToFill" contentHorizontalAlignment="center" contentVerticalAlignment="center" buttonType="roundedRect" showsTouchWhenHighlighted="YES" lineBreakMode="middleTruncation" translatesAutoresizingMaskIntoConstraints="NO" id="wUL-9N-u1V">
                                 <rect key="frame" x="16" y="597" width="63.5" height="30"/>
                                 <color key="backgroundColor" white="0.0" alpha="1" colorSpace="custom" customColorSpace="genericGamma22GrayColorSpace"/>
+                                <constraints>
+                                    <constraint firstAttribute="width" secondItem="wUL-9N-u1V" secondAttribute="height" multiplier="21:10" id="cp7-bd-CvU"/>
+                                </constraints>
                                 <state key="normal" title="Image">
                                     <color key="titleColor" white="1" alpha="1" colorSpace="custom" customColorSpace="genericGamma22GrayColorSpace"/>
                                 </state>

metal/paddle-mobile-demo/paddle-mobile-demo/LoadPointerViewController.h

-//
-//  LoadPointerViewController.h
-//  paddle-mobile-demo
-//
-//  Created by Xiao,Haichun on 2018/9/19.
-//  Copyright © 2018年 orange. All rights reserved.
-//
-
-#import <UIKit/UIKit.h>
-
-@interface LoadPointerViewController : UIViewController
-
-@end

metal/paddle-mobile-demo/paddle-mobile-demo/Net/MetalHelper.swift → metal/paddle-mobile-demo/paddle-mobile-demo/MetalHelper.swift

@@ -27,7 +27,4 @@ public class MetalHelper {
     queue = device.makeCommandQueue()!
     textureLoader = MTKTextureLoader.init(device: device)
   }
-  
-
 }
-

metal/paddle-mobile/paddle-mobile/CustomNet/Genet.swift → metal/paddle-mobile-demo/paddle-mobile-demo/Net/Genet.swift

@@ -13,41 +13,35 @@
  limitations under the License. */
 
 import Foundation
+import paddle_mobile
 
 public class Genet: Net {
   @objc public override init(device: MTLDevice) {
     super.init(device: device)
-    means = [128.0, 128.0, 128.0]
-    scale = 0.017
-    except = 0
     modelPath = Bundle.main.path(forResource: "genet_model", ofType: nil) ?! "model null"
     paramPath = Bundle.main.path(forResource: "genet_params", ofType: nil) ?! "para null"
-    modelDir = ""
     preprocessKernel = GenetPreProccess.init(device: device)
-    inputDim_ = Dim.init(inDim: [1, 128, 128, 3])
+    inputDim = Dim.init(inDim: [1, 128, 128, 3])
   }
   
-  @objc override public init(device: MTLDevice,paramPointer: UnsafeMutableRawPointer, paramSize:Int, modePointer: UnsafeMutableRawPointer, modelSize: Int) {
-    super.init(device:device,paramPointer:paramPointer,paramSize:paramSize,modePointer:modePointer,modelSize:modelSize)
-    means = [128.0, 128.0, 128.0]
-    scale = 0.017
-    except = 0
-    modelPath = ""
-    paramPath = ""
-    modelDir = ""
+  @objc override public init(device: MTLDevice, paramPointer: UnsafeMutableRawPointer, paramSize:Int, modePointer: UnsafeMutableRawPointer, modelSize: Int) {
+    super.init(device: device,
+               paramPointer: paramPointer,
+               paramSize: paramSize,
+               modePointer: modePointer,
+               modelSize: modelSize)
     preprocessKernel = GenetPreProccess.init(device: device)
-    inputDim_ = Dim.init(inDim: [1, 128, 128, 3])
+    inputDim = Dim.init(inDim: [1, 128, 128, 3])
   }
 
   class GenetPreProccess: CusomKernel {
     init(device: MTLDevice) {
       let s = Shape.init(inWidth: 128, inHeight: 128, inChannel: 3)
-      super.init(device: device, inFunctionName: "genet_preprocess", outputDim: s, usePaddleMobileLib: false)
+      super.init(device: device, inFunctionName: "genet_preprocess", outputDim: s, metalLoadModel: .LoadMetalInDefaultLib, metalLibPath: nil)
     }
   }
   
   override  public func resultStr(res: ResultHolder) -> String {
-//    fatalError()
     return " \(res.result[0]) ... "
   }
   

metal/paddle-mobile/paddle-mobile/CustomNet/MobileNet.swift → metal/paddle-mobile-demo/paddle-mobile-demo/Net/MobileNet.swift

@@ -13,13 +13,14 @@
  limitations under the License. */
 
 import Foundation
+import paddle_mobile
 
 public class MobileNet: Net{
   
   class MobilenetPreProccess: CusomKernel {
     init(device: MTLDevice) {
       let s = Shape.init(inWidth: 224, inHeight: 224, inChannel: 3)
-      super.init(device: device, inFunctionName: "mobilenet_preprocess", outputDim: s, usePaddleMobileLib: false)
+      super.init(device: device, inFunctionName: "mobilenet_preprocess", outputDim: s, metalLoadModel: .LoadMetalInDefaultLib, metalLibPath: nil)
     }
   }
   
@@ -53,14 +54,13 @@ public class MobileNet: Net{
     
   override public init(device: MTLDevice) {
     super.init(device: device)
-    means = [123.68, 116.78, 103.94]
-    scale = 0.017
     except = 0
     modelPath = Bundle.main.path(forResource: "mobilenet_model", ofType: nil) ?! "model null"
-    paramPath = Bundle.main.path(forResource: "mobilenet_params", ofType: nil) ?! "para null"
-    modelDir = ""
+    paramPath = Bundle.main.path(forResource: "mobilenet_params", ofType: nil) ?! "para null"    
+//    metalLoadMode = .LoadMetalInCustomMetalLib
+//    metalLibPath = Bundle.main.path(forResource: "PaddleMobileMetal", ofType: "metallib") ?! " can't be nil "
     preprocessKernel = MobilenetPreProccess.init(device: device)
-    inputDim_ = Dim.init(inDim: [1, 224, 224, 3])
+    inputDim = Dim.init(inDim: [1, 224, 224, 3])
   }
 }
 

metal/paddle-mobile-demo/paddle-mobile-demo/Net/MobileNetCombined.swift

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+ 
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+ 
+ http://www.apache.org/licenses/LICENSE-2.0
+ 
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
+
+import Foundation
+import paddle_mobile
+
+public class MobileNetCombined: Net {
+  @objc public override init(device: MTLDevice) {
+    super.init(device: device)
+    except = 0
+    modelPath = Bundle.main.path(forResource: "combined_mobilenet_model", ofType: nil) ?! "model null"
+    paramPath = Bundle.main.path(forResource: "combined_mobilenet_params", ofType: nil) ?! "para null"
+    inputDim = Dim.init(inDim: [1, 224, 224, 3])
+//    metalLoadMode = .LoadMetalInCustomMetalLib
+//    metalLibPath = Bundle.main.path(forResource: "PaddleMobileMetal", ofType: "metallib") ?! " can't be nil "
+  }
+  
+  override  public func resultStr(res: ResultHolder) -> String {
+    return " \(res.result[0]) ... "
+  }
+  
+}

metal/paddle-mobile/paddle-mobile/CustomNet/MobileNetSSD.swift → metal/paddle-mobile-demo/paddle-mobile-demo/Net/MobileNetSSD.swift

@@ -13,36 +13,35 @@
  limitations under the License. */
 
 import Foundation
+import paddle_mobile
 
-public class MobileNet_ssd_hand: Net{
+public class MobileNet_ssd_hand: Net {
   @objc public override init(device: MTLDevice) {
     super.init(device: device)
-    means = [123.68, 116.78, 103.94]
-    scale = 0.017
     except = 2
     modelPath = Bundle.main.path(forResource: "ssd_hand_model", ofType: nil) ?! "model null"
     paramPath = Bundle.main.path(forResource: "ssd_hand_params", ofType: nil) ?! "para null"
-    modelDir = ""
+//    metalLoadMode = .LoadMetalInCustomMetalLib
+//    metalLibPath = Bundle.main.path(forResource: "PaddleMobileMetal", ofType: "metallib") ?! " can't be nil "
     preprocessKernel = MobilenetssdPreProccess.init(device: device)
-    inputDim_ = Dim.init(inDim: [1, 300, 300, 3])
+    inputDim = Dim.init(inDim: [1, 300, 300, 3])
   }
   
   @objc override public init(device: MTLDevice,paramPointer: UnsafeMutableRawPointer, paramSize:Int, modePointer: UnsafeMutableRawPointer, modelSize: Int) {
     super.init(device:device,paramPointer:paramPointer,paramSize:paramSize,modePointer:modePointer,modelSize:modelSize)
-    means = [123.68, 116.78, 103.94]
-    scale = 0.017
     except = 2
     modelPath = ""
     paramPath = ""
-    modelDir = ""
+//    metalLoadMode = .LoadMetalInCustomMetalLib
+//    metalLibPath = Bundle.main.path(forResource: "PaddleMobileMetal", ofType: "metallib") ?! " can't be nil "
     preprocessKernel = MobilenetssdPreProccess.init(device: device)
-    inputDim_ = Dim.init(inDim: [1, 300, 300, 3])
+    inputDim = Dim.init(inDim: [1, 300, 300, 3])
   }
   
   class MobilenetssdPreProccess: CusomKernel {
     init(device: MTLDevice) {
       let s = Shape.init(inWidth: 300, inHeight: 300, inChannel: 3)
-      super.init(device: device, inFunctionName: "mobilenet_ssd_preprocess", outputDim: s, usePaddleMobileLib: false)
+      super.init(device: device, inFunctionName: "mobilenet_ssd_preprocess", outputDim: s, metalLoadModel: .LoadMetalInDefaultLib, metalLibPath: nil)
     }
   }
   
@@ -50,7 +49,7 @@ public class MobileNet_ssd_hand: Net{
     return " \(res)"
   }
   
-  override func fetchResult(paddleMobileRes: GPUResultHolder) -> ResultHolder {
+  override public func fetchResult(paddleMobileRes: GPUResultHolder) -> ResultHolder {
 
 //    guard let interRes = paddleMobileRes.intermediateResults else {
 //      fatalError(" need have inter result ")

metal/paddle-mobile/paddle-mobile/CustomNet/MobilenetSSD_AR.swift → metal/paddle-mobile-demo/paddle-mobile-demo/Net/MobilenetSSD_AR.swift

@@ -13,36 +13,29 @@
  limitations under the License. */
 
 import Foundation
+import paddle_mobile
 
-public class MobileNet_ssd_AR: Net{
+public class MobileNet_ssd_AR: Net {
   @objc public override init(device: MTLDevice) {
     super.init(device: device)
-    means = [103.94, 116.78, 123.68]
-    scale = 1
     except = 2
     modelPath = Bundle.main.path(forResource: "ar_model", ofType: nil) ?! "model null"
     paramPath = Bundle.main.path(forResource: "ar_params", ofType: nil) ?! "para null"
-    modelDir = ""
     preprocessKernel = MobilenetssdPreProccess.init(device: device)
-    inputDim_ = Dim.init(inDim: [1, 160, 160, 3])
+    inputDim = Dim.init(inDim: [1, 160, 160, 3])
   }
   
   @objc override public init(device: MTLDevice,paramPointer: UnsafeMutableRawPointer, paramSize:Int, modePointer: UnsafeMutableRawPointer, modelSize: Int) {
     super.init(device:device,paramPointer:paramPointer,paramSize:paramSize,modePointer:modePointer,modelSize:modelSize)
-    means = [103.94, 116.78, 123.68]
-    scale = 1
     except = 2
-    modelPath = ""
-    paramPath = ""
-    modelDir = ""
     preprocessKernel = MobilenetssdPreProccess.init(device: device)
-    inputDim_ = Dim.init(inDim: [1, 160, 160, 3])
+    inputDim = Dim.init(inDim: [1, 160, 160, 3])
   }
   
   class MobilenetssdPreProccess: CusomKernel {
-    init(device: MTLDevice) {
+    init(device: MTLDevice)  {
       let s = Shape.init(inWidth: 160, inHeight: 160, inChannel: 3)
-      super.init(device: device, inFunctionName: "mobilent_ar_preprocess", outputDim: s, usePaddleMobileLib: false)
+      super.init(device: device, inFunctionName: "mobilent_ar_preprocess", outputDim: s, metalLoadModel: .LoadMetalInDefaultLib, metalLibPath: nil)
     }
   }
   
@@ -50,18 +43,19 @@ public class MobileNet_ssd_AR: Net{
     return " \(res.result[0])"
   }
   
-  override func fetchResult(paddleMobileRes: GPUResultHolder) -> ResultHolder {
-    guard let interRes = paddleMobileRes.intermediateResults else {
-      fatalError(" need have inter result ")
-    }
-    
-    guard let scores = interRes["Scores"], scores.count > 0, let score = scores[0] as?  FetchHolder else {
-      fatalError(" need score ")
-    }
-    
-    guard let bboxs = interRes["BBoxes"], bboxs.count > 0, let bbox = bboxs[0] as? FetchHolder else {
-      fatalError()
-    }
+  override public func fetchResult(paddleMobileRes: GPUResultHolder) -> ResultHolder {
+    fatalError()
+//    guard let interRes = paddleMobileRes.intermediateResults else {
+//      fatalError(" need have inter result ")
+//    }
+//
+//    guard let scores = interRes["Scores"], scores.count > 0, let score = scores[0] as?  FetchHolder else {
+//      fatalError(" need score ")
+//    }
+//
+//    guard let bboxs = interRes["BBoxes"], bboxs.count > 0, let bbox = bboxs[0] as? FetchHolder else {
+//      fatalError()
+//    }
     
 //    let startDate = Date.init()
     
@@ -72,19 +66,19 @@ public class MobileNet_ssd_AR: Net{
 //
 //    print((0..<bbox.capacity).map{ bbox.result[$0] }.strideArray())
     
-    let nmsCompute = NMSCompute.init()
-    nmsCompute.scoreThredshold = 0.25
-    nmsCompute.nmsTopK = 100
-    nmsCompute.keepTopK = 100
-    nmsCompute.nmsEta = 1.0
-    nmsCompute.nmsThreshold = 0.449999988
-    nmsCompute.background_label = 0;
-    nmsCompute.scoreDim = [NSNumber.init(value: score.dim[0]), NSNumber.init(value: score.dim[1]), NSNumber.init(value: score.dim[2])]
-    nmsCompute.bboxDim = [NSNumber.init(value: bbox.dim[0]), NSNumber.init(value: bbox.dim[1]), NSNumber.init(value: bbox.dim[2])]
-    guard let result = nmsCompute.compute(withScore: score.result, andBBoxs: bbox.result) else {
-      fatalError( " result error " )
-    }
-    let resultHolder = ResultHolder.init(inResult: result.output, inCapacity: Int(result.outputSize))
+//    let nmsCompute = NMSCompute.init()
+//    nmsCompute.scoreThredshold = 0.25
+//    nmsCompute.nmsTopK = 100
+//    nmsCompute.keepTopK = 100
+//    nmsCompute.nmsEta = 1.0
+//    nmsCompute.nmsThreshold = 0.449999988
+//    nmsCompute.background_label = 0;
+//    nmsCompute.scoreDim = [NSNumber.init(value: score.dim[0]), NSNumber.init(value: score.dim[1]), NSNumber.init(value: score.dim[2])]
+//    nmsCompute.bboxDim = [NSNumber.init(value: bbox.dim[0]), NSNumber.init(value: bbox.dim[1]), NSNumber.init(value: bbox.dim[2])]
+//    guard let result = nmsCompute.compute(withScore: score.result, andBBoxs: bbox.result) else {
+//      fatalError( " result error " )
+//    }
+//    let resultHolder = ResultHolder.init(inResult: result.output, inCapacity: Int(result.outputSize))
 //    for i in 0..<Int(result.outputSize) {
 //
 //      print("i \(i) : \(result.output[i])")
@@ -92,10 +86,11 @@ public class MobileNet_ssd_AR: Net{
 //    print(Date.init().timeIntervalSince(startDate))
 
 //    print(resultHolder.result![0])
-    return resultHolder
+//    return resultHolder
   }
   
-  override func updateProgram(program: Program) {
+//  override func updateProgram(program: Program) {
+  
 //    for i in [56, 66, 76, 86, 93, 99] {
 //      let opDesc = program.programDesc.blocks[0].ops[i]
 //      let output = opDesc.outputs["Out"]!.first!
@@ -148,6 +143,6 @@ public class MobileNet_ssd_AR: Net{
 //      print(" split axis \(opDesc.attrs["axis"])")
 //    }
     // 99
-  }
+//  }
   
 }

metal/paddle-mobile-demo/paddle-mobile-demo/Net/PaddleMobile.swift

-//
-//  PaddleMobile.swift
-//  paddle-mobile-demo
-//
-//  Created by liuRuiLong on 2018/9/5.
-//  Copyright © 2018年 orange. All rights reserved.
-//
-
-import Foundation

metal/paddle-mobile-demo/paddle-mobile-demo/Net/PreProcessKernel.metal

@@ -115,23 +115,3 @@ kernel void mobilent_ar_preprocess_half(texture2d<half, access::read> inTexture
   const half4 inColor = (inTexture.read(gid) * 255.0 - means) * 0.017;
   outTexture.write(half4(inColor.z, inColor.y, inColor.x, 0.0f), gid);
 }
-
-kernel void scale(texture2d<float, access::sample> inTexture [[texture(0)]], texture2d<float, access::write> outTexture [[texture(1)]], uint2 gid [[thread_position_in_grid]]) {
-  if (gid.x >= outTexture.get_width() ||
-      gid.y >= outTexture.get_height()) return;
-  float w_stride = inTexture.get_width() / outTexture.get_width();
-  float h_stride = inTexture.get_height() / outTexture.get_height();
-  constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
-  float4 input = inTexture.sample(sample, float2(gid.x * w_stride,    gid.y * h_stride), 0);
-  outTexture.write(input, gid);
-}
-
-kernel void scale_half(texture2d<float, access::sample> inTexture [[texture(0)]], texture2d<half, access::write> outTexture [[texture(1)]], uint2 gid [[thread_position_in_grid]]) {
-  if (gid.x >= outTexture.get_width() ||
-      gid.y >= outTexture.get_height()) return;
-  float w_stride = inTexture.get_width() / outTexture.get_width();
-  float h_stride = inTexture.get_height() / outTexture.get_height();
-  constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
-  float4 input = inTexture.sample(sample, float2(gid.x * w_stride,    gid.y * h_stride), 0);
-  outTexture.write(half4(input), gid);
-}

metal/paddle-mobile-demo/paddle-mobile-demo/Net/YoloNet.swift

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+ 
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+ 
+ http://www.apache.org/licenses/LICENSE-2.0
+ 
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
+
+import Metal
+import Foundation
+import paddle_mobile
+
+public class YoloNet: Net {
+  @objc public override init(device: MTLDevice) {
+    super.init(device: device)
+    except = 0
+    modelPath = Bundle.main.path(forResource: "yolo_model", ofType: nil) ?! "model null"
+    paramPath = Bundle.main.path(forResource: "yolo_params", ofType: nil) ?! "para null"
+    inputDim = Dim.init(inDim: [1, 416, 416, 3])
+//    metalLoadMode = .LoadMetalInCustomMetalLib
+//    metalLibPath = Bundle.main.path(forResource: "PaddleMobileMetal", ofType: "metallib") ?! " can't be nil "
+  }
+
+  override  public func resultStr(res: ResultHolder) -> String {
+    return " \(res.result[0]) ... "
+  }
+  
+}

metal/paddle-mobile-demo/paddle-mobile-demo/OCDemo/LoadPointerViewController.h

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+ 
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+ 
+ http://www.apache.org/licenses/LICENSE-2.0
+ 
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
+
+#import <UIKit/UIKit.h>
+
+@interface LoadPointerViewController : UIViewController
+
+@end

metal/paddle-mobile-demo/paddle-mobile-demo/LoadPointerViewController.m → metal/paddle-mobile-demo/paddle-mobile-demo/OCDemo/LoadPointerViewController.m

-//
-//  LoadPointerViewController.m
-//  paddle-mobile-demo
-//
-//  Created by Xiao,Haichun on 2018/9/19.
-//  Copyright © 2018年 orange. All rights reserved.
-//
+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+ 
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+ 
+ http://www.apache.org/licenses/LICENSE-2.0
+ 
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
 
+#import "PaddleMobileGPU.h"
 #import "LoadPointerViewController.h"
-#import <Metal/Metal.h>
 #import "paddle-mobile-demo-Bridging-Header.h"
 
+#import <Metal/Metal.h>
+
 @interface LoadPointerViewController ()
 
 @property (strong, nonatomic) id<MTLDevice> device;

metal/paddle-mobile-demo/paddle-mobile-demo/OCDemo/OCDemoViewController.h

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+ 
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+ 
+ http://www.apache.org/licenses/LICENSE-2.0
+ 
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
+#import <Foundation/Foundation.h>
+
+NS_ASSUME_NONNULL_BEGIN
+
+@interface OCDemoViewController : NSObject
+
+@end
+
+NS_ASSUME_NONNULL_END

metal/paddle-mobile-demo/paddle-mobile-demo/OCDemo/OCDemoViewController.m

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+ 
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+ 
+ http://www.apache.org/licenses/LICENSE-2.0
+ 
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
+
+#import "OCDemoViewController.h"
+
+@implementation OCDemoViewController
+
+@end

metal/paddle-mobile/paddle-mobile/PaddleMobileGPU.h → metal/paddle-mobile-demo/paddle-mobile-demo/OCInterface/PaddleMobileGPU.h

@@ -16,9 +16,8 @@
 #import <Foundation/Foundation.h>
 
 typedef enum : NSUInteger {
-  MobileNetType,
-  MobileNetSSDType,
-  GenetType,
+  SuperResolutionNetType,
+  MobileNetSSDType
 } NetType;
 
 @interface PaddleMobileGPUResult: NSObject

metal/paddle-mobile/paddle-mobile/PaddleMobileGPU.m → metal/paddle-mobile-demo/paddle-mobile-demo/OCInterface/PaddleMobileGPU.m

@@ -12,11 +12,10 @@
  See the License for the specific language governing permissions and
  limitations under the License. */
 
-#import "paddle_mobile.h"
 #import "PaddleMobileGPU.h"
 
 #import <Foundation/Foundation.h>
-#import <paddle_mobile/paddle_mobile-Swift.h>
+#import <paddle_mobile_demo-Swift.h>
 
 @implementation ModelConfig
 @end
@@ -53,12 +52,10 @@
   self = [super init];
   if (self) {
     Net *net = nil;
-    if (netType == GenetType) {
-      net = [[Genet alloc] initWithDevice:queue.device paramPointer:config.paramPointer paramSize:config.paramSize modePointer:config.modelPointer modelSize:config.modelSize];
+    if (netType == SuperResolutionNetType) {
+      net = [[SuperResolutionNet alloc] initWithDevice:queue.device];
     } else if (netType == MobileNetSSDType) {
       net = [[MobileNet_ssd_AR alloc] initWithDevice:queue.device paramPointer:config.paramPointer paramSize:config.paramSize modePointer:config.modelPointer modelSize:config.modelSize];
-    } else if (netType == MobileNetType) {
-      
     }
     runner = [[Runner alloc] initInNet:net commandQueue:queue];
   }

metal/paddle-mobile/paddle-mobile/CustomNet/SuperResolutionNet.swift → metal/paddle-mobile-demo/paddle-mobile-demo/OCInterface/SuperResolutionNet.swift

@@ -13,31 +13,25 @@
  limitations under the License. */
 
 import Foundation
+import paddle_mobile
 
-
-public class SuperResolutionNet: Net{
+@objc public class SuperResolutionNet: Net{
   override public func resultStr(res: ResultHolder) -> String {
     return "未实现"
   }
   
-  override public init(device: MTLDevice) {
+  @objc override public init(device: MTLDevice) {
     super.init(device: device)
-    means = [0.0, 0.0, 0.0]
-    scale = 1.0
     except = 0
     modelPath = Bundle.main.path(forResource: "super_model", ofType: nil) ?! "model null"
     paramPath = Bundle.main.path(forResource: "super_params", ofType: nil) ?! "para null"
-    modelDir = ""
     preprocessKernel = nil
-//    inputDim_ = Dim.init(inDim: [1, Int(552 * 1.414), Int(310 * 1.414), 1])
-    inputDim_ = Dim.init(inDim: [1, 224, 224, 1])
+    inputDim = Dim.init(inDim: [1, 224, 224, 1])
+//    metalLoadMode = .LoadMetalInCustomMetalLib
+//    metalLibPath = Bundle.main.path(forResource: "PaddleMobileMetal", ofType: "metallib") ?! " can't be nil "
   }
   
-  override func updateProgram(program: Program) {
-    guard needUpdateProgram else {
-      return
-    }
-    
+  override public func updateProgram(program: Program) {
     // n h w c
     for block in program.programDesc.blocks {
       for varDesc in block.vars {
@@ -47,8 +41,9 @@ public class SuperResolutionNet: Net{
             if let texture = varEle as? Texture {
               let newDim = Dim.init(inDim: [texture.dim[0],  inputDim[1], inputDim[2], texture.tensorDim[1]])
               print(" var desc name " + varDesc.name + " new dim" + "\(newDim)")
+              
               texture.updateDims(inTensorDim: Dim.init(inDim: [texture.tensorDim[0], texture.tensorDim[1], inputDim[1], inputDim[2]]), inDim: newDim)
-              texture.initTexture(device: device, inTranspose: [0, 1, 2, 3], computePrecision: computePrecision)
+              texture.initTexture(device: device, inTranspose: [0, 1, 2, 3], computePrecision: GlobalConfig.shared.computePrecision)
               
               let output: FetchHolder = program.scope.output() as! FetchHolder
               output.dim = newDim
@@ -60,7 +55,6 @@ public class SuperResolutionNet: Net{
         }
       }
     }
-    needUpdateProgram = false
   }
 }
 

metal/paddle-mobile-demo/paddle-mobile-demo/ViewController.swift

@@ -18,7 +18,6 @@ import CoreMedia
 import paddle_mobile
 import MetalPerformanceShaders
 
-
 class FileReader {
   let file: UnsafeMutablePointer<FILE>
   let fileSize: Int
@@ -53,16 +52,12 @@ enum Platform {
 let platformSupport: [(Platform, String)] = [(.GPU, "GPU")]
 
 enum SupportModel: String{
-  //  case mobilenet = "mobilenet"
-  //  case mobilenet_ssd    = "mobilenetssd"
   case yolo               = "yolo"
   case mobilenet_combined = "mobilenet_combined"
   case super_resolution   = "superresoltion"
   case mobilenet          = "mobilenet"
   
   static func supportedModels() -> [SupportModel] {
-    // .mobilenet,
-    // .mobilenet_ssd,
     return [.super_resolution, .yolo, .mobilenet_combined, .mobilenet]
   }
 }
@@ -94,24 +89,25 @@ class ViewController: UIViewController {
   @IBAction func loadAct(_ sender: Any) {
     runner = Runner.init(inNet: netSupport[modelType]!, commandQueue: MetalHelper.shared.queue)
     if platform == .GPU {
-      let filePath = Bundle.main.path(forResource: "mingren_input_data", ofType: nil)
-      let fileReader = try! FileReader.init(paramPath: filePath!)
-      let pointer: UnsafeMutablePointer<Float32> = fileReader.read()
-      
-      
-      let buffer = MetalHelper.shared.device.makeBuffer(length: fileReader.fileSize, options: .storageModeShared)
-      
-      buffer?.contents().copyMemory(from: pointer, byteCount: fileReader.fileSize)
+//      let filePath = Bundle.main.path(forResource: "mingren_input_data", ofType: nil)
+//      let fileReader = try! FileReader.init(paramPath: filePath!)
+//      let pointer: UnsafeMutablePointer<Float32> = fileReader.read()
+//      
+//      
+//      let buffer = MetalHelper.shared.device.makeBuffer(length: fileReader.fileSize, options: .storageModeShared)
+//      
+//      buffer?.contents().copyMemory(from: pointer, byteCount: fileReader.fileSize)
       
       
       if self.toPredictTexture == nil {
         
-        runner.getTexture(inBuffer: buffer!) { [weak self] (texture) in
+//        runner.getTexture(inBuffer: buffer!) { [weak self] (texture) in
+//          self?.toPredictTexture = texture
+//        }
+        
+        runner.getTexture(image: selectImage!.cgImage!) { [weak self] (texture) in
           self?.toPredictTexture = texture
         }
-        
-//        runner.getTexture(image: selectImage!.cgImage!) { [weak self] (texture) in
-//        }
       }
     } else {
       fatalError( " unsupport " )
@@ -178,13 +174,14 @@ class ViewController: UIViewController {
     modelPickerView.dataSource = self
     threadPickerView.delegate = self
     threadPickerView.dataSource = self
-    if let image = UIImage.init(named: "test.jpg") {
+    if let image = UIImage.init(named: "classify-img-output.png") {
       selectImage = image
       selectImageView.image = image
     } else {
       print("请添加测试图片")
     }
     
+    GlobalConfig.shared.computePrecision = .Float32
     
     //    if platform == .CPU {
     //      inputPointer = runner.preproccess(image: selectImage!.cgImage!)

metal/paddle-mobile/paddle-mobile.xcodeproj/project.pbxproj

@@ -28,8 +28,6 @@
 		4AF9287921341661005B6C3A /* Softmax.metal in Sources */ = {isa = PBXBuildFile; fileRef = 4AF9287821341661005B6C3A /* Softmax.metal */; };
 		4AF928822135673D005B6C3A /* ConcatKernel.metal in Sources */ = {isa = PBXBuildFile; fileRef = 4AF928812135673D005B6C3A /* ConcatKernel.metal */; };
 		4AF9288421357BE3005B6C3A /* Elementwise.metal in Sources */ = {isa = PBXBuildFile; fileRef = 4AF9288321357BE3005B6C3A /* Elementwise.metal */; };
-		C28FDF8421B7858F0054EFAC /* MobileNetCombined.swift in Sources */ = {isa = PBXBuildFile; fileRef = C28FDF8221B7858F0054EFAC /* MobileNetCombined.swift */; };
-		C28FDF8521B7858F0054EFAC /* YoloNet.swift in Sources */ = {isa = PBXBuildFile; fileRef = C28FDF8321B7858F0054EFAC /* YoloNet.swift */; };
 		C28FE02F21BA68C00054EFAC /* Metal.framework in Frameworks */ = {isa = PBXBuildFile; fileRef = C28FE02C21BA68C00054EFAC /* Metal.framework */; };
 		C28FE03021BA68C00054EFAC /* MetalPerformanceShaders.framework in Frameworks */ = {isa = PBXBuildFile; fileRef = C28FE02D21BA68C00054EFAC /* MetalPerformanceShaders.framework */; };
 		C28FE03121BA68C00054EFAC /* MetalKit.framework in Frameworks */ = {isa = PBXBuildFile; fileRef = C28FE02E21BA68C00054EFAC /* MetalKit.framework */; };
@@ -64,18 +62,16 @@
 		FC0E2DC020EE461F009C1FAC /* ElementwiseAddKernel.swift in Sources */ = {isa = PBXBuildFile; fileRef = FC0E2DBF20EE461F009C1FAC /* ElementwiseAddKernel.swift */; };
 		FC1B16B320EC9A4F00678B91 /* Kernels.metal in Sources */ = {isa = PBXBuildFile; fileRef = FC1B16B220EC9A4F00678B91 /* Kernels.metal */; };
 		FC1CF3F721D4B4C400F7392E /* Runner.swift in Sources */ = {isa = PBXBuildFile; fileRef = FC1CF3F621D4B4C400F7392E /* Runner.swift */; };
-		FC292C5421421B2F00CF622F /* PaddleMobileGPU.h in Headers */ = {isa = PBXBuildFile; fileRef = FC292C5321421B2E00CF622F /* PaddleMobileGPU.h */; settings = {ATTRIBUTES = (Public, ); }; };
-		FC292C5621421B4600CF622F /* PaddleMobileGPU.m in Sources */ = {isa = PBXBuildFile; fileRef = FC292C5521421B4600CF622F /* PaddleMobileGPU.m */; };
-		FC292C81214255BD00CF622F /* CPUCompute.mm in Sources */ = {isa = PBXBuildFile; fileRef = FC292C7C214255BC00CF622F /* CPUCompute.mm */; };
-		FC292C82214255BD00CF622F /* MobileNetSSD.swift in Sources */ = {isa = PBXBuildFile; fileRef = FC292C7E214255BC00CF622F /* MobileNetSSD.swift */; };
-		FC292C872142624800CF622F /* Genet.swift in Sources */ = {isa = PBXBuildFile; fileRef = FC292C862142624800CF622F /* Genet.swift */; };
-		FC33B0F02147659000714A93 /* MobileNet.swift in Sources */ = {isa = PBXBuildFile; fileRef = FC33B0EF2147659000714A93 /* MobileNet.swift */; };
+		FC2BFCC221DF2F9100C262B2 /* GlobalConfig.swift in Sources */ = {isa = PBXBuildFile; fileRef = FC2BFCC121DF2F9100C262B2 /* GlobalConfig.swift */; };
+		FC2BFD4621DF685F00C262B2 /* Scale.swift in Sources */ = {isa = PBXBuildFile; fileRef = FC2BFD4521DF685F00C262B2 /* Scale.swift */; };
+		FC2BFD4A21DF81DE00C262B2 /* Kernel.swift in Sources */ = {isa = PBXBuildFile; fileRef = FC2BFD4921DF81DE00C262B2 /* Kernel.swift */; };
+		FC2BFD4E21DF820B00C262B2 /* ConvAddBatchNormReluOp.swift in Sources */ = {isa = PBXBuildFile; fileRef = FC2BFD4D21DF820A00C262B2 /* ConvAddBatchNormReluOp.swift */; };
+		FC2BFD5121DF8E0400C262B2 /* Scale.metal in Sources */ = {isa = PBXBuildFile; fileRef = FC2BFD5021DF8E0400C262B2 /* Scale.metal */; };
 		FC3602CC2108819F00FACB58 /* PaddleMobileUnitTest.swift in Sources */ = {isa = PBXBuildFile; fileRef = FC3602CB2108819F00FACB58 /* PaddleMobileUnitTest.swift */; };
 		FC4CB74920F0B954007C0C6D /* ConvKernel.metal in Sources */ = {isa = PBXBuildFile; fileRef = FC4CB74820F0B954007C0C6D /* ConvKernel.metal */; };
 		FC4CB74B20F12C30007C0C6D /* ProgramOptimize.swift in Sources */ = {isa = PBXBuildFile; fileRef = FC4CB74A20F12C30007C0C6D /* ProgramOptimize.swift */; };
 		FC5163F620EF556E00636C28 /* Texture2DTo2DArrayKernel.swift in Sources */ = {isa = PBXBuildFile; fileRef = FC5163F520EF556E00636C28 /* Texture2DTo2DArrayKernel.swift */; };
 		FC60DB8920E9AAA500FF203F /* MetalExtension.swift in Sources */ = {isa = PBXBuildFile; fileRef = FC60DB8820E9AAA500FF203F /* MetalExtension.swift */; };
-		FC704C2721D2385100F98BAB /* SuperResolutionNet.swift in Sources */ = {isa = PBXBuildFile; fileRef = FC704C2621D2385100F98BAB /* SuperResolutionNet.swift */; };
 		FC803BBF214CB65A0094B8E5 /* ConvAddPreluOp.swift in Sources */ = {isa = PBXBuildFile; fileRef = FC803BBE214CB65A0094B8E5 /* ConvAddPreluOp.swift */; };
 		FC803BC1214CB77A0094B8E5 /* ConvAddPreluKernel.swift in Sources */ = {isa = PBXBuildFile; fileRef = FC803BC0214CB77A0094B8E5 /* ConvAddPreluKernel.swift */; };
 		FC803BC3214CB79C0094B8E5 /* ConvAddPreluKernel.metal in Sources */ = {isa = PBXBuildFile; fileRef = FC803BC2214CB79C0094B8E5 /* ConvAddPreluKernel.metal */; };
@@ -85,8 +81,6 @@
 		FC82735920E3C04200BE430A /* OpCreator.swift in Sources */ = {isa = PBXBuildFile; fileRef = FC82735820E3C04200BE430A /* OpCreator.swift */; };
 		FC9797C921D6101D00F2FD90 /* ResizeBilinearOp.swift in Sources */ = {isa = PBXBuildFile; fileRef = FC9797C821D6101D00F2FD90 /* ResizeBilinearOp.swift */; };
 		FC9797CB21D6102D00F2FD90 /* ResizeBilinearKernel.swift in Sources */ = {isa = PBXBuildFile; fileRef = FC9797CA21D6102D00F2FD90 /* ResizeBilinearKernel.swift */; };
-		FC9797CD21D61B2E00F2FD90 /* CPUCompute.h in Headers */ = {isa = PBXBuildFile; fileRef = FC292C7D214255BC00CF622F /* CPUCompute.h */; settings = {ATTRIBUTES = (Public, ); }; };
-		FC9A19E32148C31300CD9CBF /* MobilenetSSD_AR.swift in Sources */ = {isa = PBXBuildFile; fileRef = FC9A19E22148C31300CD9CBF /* MobilenetSSD_AR.swift */; };
 		FC9C2A0D21D3D185005856C6 /* FetchKernel.inc.metal in Sources */ = {isa = PBXBuildFile; fileRef = FC9C2A0C21D3D185005856C6 /* FetchKernel.inc.metal */; };
 		FC9D037920E229E4000F735A /* OpParam.swift in Sources */ = {isa = PBXBuildFile; fileRef = FC9D037820E229E4000F735A /* OpParam.swift */; };
 		FC9D038020E22FBB000F735A /* FeedOp.swift in Sources */ = {isa = PBXBuildFile; fileRef = FC9D037F20E22FBB000F735A /* FeedOp.swift */; };
@@ -138,9 +132,7 @@
 		FCE9D7B9214FAA4800B520C3 /* NMSFetchResultKernel.metal in Sources */ = {isa = PBXBuildFile; fileRef = FCE9D7B8214FAA4800B520C3 /* NMSFetchResultKernel.metal */; };
 		FCEB684A212F00DB00D2448E /* PreluKernel.metal in Sources */ = {isa = PBXBuildFile; fileRef = FCEB6849212F00DB00D2448E /* PreluKernel.metal */; };
 		FCEB684C212F093800D2448E /* PreluOp.swift in Sources */ = {isa = PBXBuildFile; fileRef = FCEB684B212F093800D2448E /* PreluOp.swift */; };
-		FCEBC0F420F1FDD90099DBAF /* ConvAddBatchNormReluOp.swift in Sources */ = {isa = PBXBuildFile; fileRef = FCEBC0F320F1FDD90099DBAF /* ConvAddBatchNormReluOp.swift */; };
 		FCEBC0F620F1FE120099DBAF /* ConvAddBatchNormReluKernel.swift in Sources */ = {isa = PBXBuildFile; fileRef = FCEBC0F520F1FE120099DBAF /* ConvAddBatchNormReluKernel.swift */; };
-		FCF2D73820E64E70007AC5F5 /* Kernel.swift in Sources */ = {isa = PBXBuildFile; fileRef = FCF2D73720E64E70007AC5F5 /* Kernel.swift */; };
 /* End PBXBuildFile section */
 
 /* Begin PBXFileReference section */
@@ -166,8 +158,6 @@
 		4AF9287821341661005B6C3A /* Softmax.metal */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.metal; path = Softmax.metal; sourceTree = "<group>"; };
 		4AF928812135673D005B6C3A /* ConcatKernel.metal */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.metal; path = ConcatKernel.metal; sourceTree = "<group>"; };
 		4AF9288321357BE3005B6C3A /* Elementwise.metal */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.metal; path = Elementwise.metal; sourceTree = "<group>"; };
-		C28FDF8221B7858F0054EFAC /* MobileNetCombined.swift */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.swift; path = MobileNetCombined.swift; sourceTree = "<group>"; };
-		C28FDF8321B7858F0054EFAC /* YoloNet.swift */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.swift; path = YoloNet.swift; sourceTree = "<group>"; };
 		C28FE02C21BA68C00054EFAC /* Metal.framework */ = {isa = PBXFileReference; lastKnownFileType = wrapper.framework; name = Metal.framework; path = System/Library/Frameworks/Metal.framework; sourceTree = SDKROOT; };
 		C28FE02D21BA68C00054EFAC /* MetalPerformanceShaders.framework */ = {isa = PBXFileReference; lastKnownFileType = wrapper.framework; name = MetalPerformanceShaders.framework; path = System/Library/Frameworks/MetalPerformanceShaders.framework; sourceTree = SDKROOT; };
 		C28FE02E21BA68C00054EFAC /* MetalKit.framework */ = {isa = PBXFileReference; lastKnownFileType = wrapper.framework; name = MetalKit.framework; path = System/Library/Frameworks/MetalKit.framework; sourceTree = SDKROOT; };
@@ -206,20 +196,17 @@
 		FC0E2DBF20EE461F009C1FAC /* ElementwiseAddKernel.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = ElementwiseAddKernel.swift; sourceTree = "<group>"; };
 		FC1B16B220EC9A4F00678B91 /* Kernels.metal */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.metal; path = Kernels.metal; sourceTree = "<group>"; };
 		FC1CF3F621D4B4C400F7392E /* Runner.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = Runner.swift; sourceTree = "<group>"; };
-		FC292C5321421B2E00CF622F /* PaddleMobileGPU.h */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.c.h; path = PaddleMobileGPU.h; sourceTree = "<group>"; };
-		FC292C5521421B4600CF622F /* PaddleMobileGPU.m */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.c.objc; path = PaddleMobileGPU.m; sourceTree = "<group>"; };
-		FC292C7C214255BC00CF622F /* CPUCompute.mm */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.cpp.objcpp; path = CPUCompute.mm; sourceTree = "<group>"; };
-		FC292C7D214255BC00CF622F /* CPUCompute.h */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.c.h; path = CPUCompute.h; sourceTree = "<group>"; };
-		FC292C7E214255BC00CF622F /* MobileNetSSD.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = MobileNetSSD.swift; sourceTree = "<group>"; };
-		FC292C862142624800CF622F /* Genet.swift */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.swift; path = Genet.swift; sourceTree = "<group>"; };
-		FC33B0EF2147659000714A93 /* MobileNet.swift */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.swift; path = MobileNet.swift; sourceTree = "<group>"; };
+		FC2BFCC121DF2F9100C262B2 /* GlobalConfig.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = GlobalConfig.swift; sourceTree = "<group>"; };
+		FC2BFD4521DF685F00C262B2 /* Scale.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = Scale.swift; sourceTree = "<group>"; };
+		FC2BFD4921DF81DE00C262B2 /* Kernel.swift */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.swift; path = Kernel.swift; sourceTree = "<group>"; };
+		FC2BFD4D21DF820A00C262B2 /* ConvAddBatchNormReluOp.swift */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.swift; path = ConvAddBatchNormReluOp.swift; sourceTree = "<group>"; };
+		FC2BFD5021DF8E0400C262B2 /* Scale.metal */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.metal; path = Scale.metal; sourceTree = "<group>"; };
 		FC3602CB2108819F00FACB58 /* PaddleMobileUnitTest.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = PaddleMobileUnitTest.swift; sourceTree = "<group>"; };
 		FC4CB74820F0B954007C0C6D /* ConvKernel.metal */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.metal; path = ConvKernel.metal; sourceTree = "<group>"; };
 		FC4CB74A20F12C30007C0C6D /* ProgramOptimize.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = ProgramOptimize.swift; sourceTree = "<group>"; };
 		FC4FD97D2140F2C30073E130 /* libstdc++.tbd */ = {isa = PBXFileReference; lastKnownFileType = "sourcecode.text-based-dylib-definition"; name = "libstdc++.tbd"; path = "usr/lib/libstdc++.tbd"; sourceTree = SDKROOT; };
 		FC5163F520EF556E00636C28 /* Texture2DTo2DArrayKernel.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = Texture2DTo2DArrayKernel.swift; sourceTree = "<group>"; };
 		FC60DB8820E9AAA500FF203F /* MetalExtension.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = MetalExtension.swift; sourceTree = "<group>"; };
-		FC704C2621D2385100F98BAB /* SuperResolutionNet.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = SuperResolutionNet.swift; sourceTree = "<group>"; };
 		FC803BBE214CB65A0094B8E5 /* ConvAddPreluOp.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = ConvAddPreluOp.swift; sourceTree = "<group>"; };
 		FC803BC0214CB77A0094B8E5 /* ConvAddPreluKernel.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = ConvAddPreluKernel.swift; sourceTree = "<group>"; };
 		FC803BC2214CB79C0094B8E5 /* ConvAddPreluKernel.metal */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.metal; path = ConvAddPreluKernel.metal; sourceTree = "<group>"; };
@@ -229,7 +216,6 @@
 		FC82735820E3C04200BE430A /* OpCreator.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = OpCreator.swift; sourceTree = "<group>"; };
 		FC9797C821D6101D00F2FD90 /* ResizeBilinearOp.swift */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.swift; path = ResizeBilinearOp.swift; sourceTree = "<group>"; };
 		FC9797CA21D6102D00F2FD90 /* ResizeBilinearKernel.swift */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.swift; path = ResizeBilinearKernel.swift; sourceTree = "<group>"; };
-		FC9A19E22148C31300CD9CBF /* MobilenetSSD_AR.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = MobilenetSSD_AR.swift; sourceTree = "<group>"; };
 		FC9C2A0C21D3D185005856C6 /* FetchKernel.inc.metal */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.metal; path = FetchKernel.inc.metal; sourceTree = "<group>"; };
 		FC9D037820E229E4000F735A /* OpParam.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = OpParam.swift; sourceTree = "<group>"; };
 		FC9D037F20E22FBB000F735A /* FeedOp.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = FeedOp.swift; sourceTree = "<group>"; };
@@ -281,9 +267,7 @@
 		FCE9D7B8214FAA4800B520C3 /* NMSFetchResultKernel.metal */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.metal; path = NMSFetchResultKernel.metal; sourceTree = "<group>"; };
 		FCEB6849212F00DB00D2448E /* PreluKernel.metal */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.metal; path = PreluKernel.metal; sourceTree = "<group>"; };
 		FCEB684B212F093800D2448E /* PreluOp.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = PreluOp.swift; sourceTree = "<group>"; };
-		FCEBC0F320F1FDD90099DBAF /* ConvAddBatchNormReluOp.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; name = ConvAddBatchNormReluOp.swift; path = "paddle-mobile/Operators/ConvAddBatchNormReluOp.swift"; sourceTree = SOURCE_ROOT; };
 		FCEBC0F520F1FE120099DBAF /* ConvAddBatchNormReluKernel.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = ConvAddBatchNormReluKernel.swift; sourceTree = "<group>"; };
-		FCF2D73720E64E70007AC5F5 /* Kernel.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; name = Kernel.swift; path = "paddle-mobile/Operators/Kernels/Base/Kernel.swift"; sourceTree = SOURCE_ROOT; };
 /* End PBXFileReference section */
 
 /* Begin PBXFrameworksBuildPhase section */
@@ -343,17 +327,10 @@
 		FC039B6C20E11C3C0081E9F8 /* paddle-mobile */ = {
 			isa = PBXGroup;
 			children = (
-				FC9797CC21D61A5500F2FD90 /* CustomNet */,
-				FCE9D7B6214F869000B520C3 /* Net.swift */,
-				FC292C5521421B4600CF622F /* PaddleMobileGPU.m */,
-				FC292C5321421B2E00CF622F /* PaddleMobileGPU.h */,
-				FC039BAE20E11CC20081E9F8 /* Program */,
-				FC039BA320E11CBC0081E9F8 /* Operators */,
-				FC039B9C20E11CB20081E9F8 /* framework */,
-				FC039B9320E11C9A0081E9F8 /* Common */,
+				FC2BFD4721DF818000C262B2 /* API */,
+				FC2BFD4821DF818000C262B2 /* Src */,
 				FC039B6D20E11C3C0081E9F8 /* paddle_mobile.h */,
 				FC039B6E20E11C3C0081E9F8 /* Info.plist */,
-				FC1CF3F621D4B4C400F7392E /* Runner.swift */,
 			);
 			path = "paddle-mobile";
 			sourceTree = "<group>";
@@ -386,10 +363,10 @@
 		FC039BA320E11CBC0081E9F8 /* Operators */ = {
 			isa = PBXGroup;
 			children = (
-				FC9797C821D6101D00F2FD90 /* ResizeBilinearOp.swift */,
 				FC086BA520E67E8500D85EF7 /* Kernels */,
 				FCD592FA20E248EC00252966 /* Base */,
-				FCEBC0F320F1FDD90099DBAF /* ConvAddBatchNormReluOp.swift */,
+				FC9797C821D6101D00F2FD90 /* ResizeBilinearOp.swift */,
+				FC2BFD4D21DF820A00C262B2 /* ConvAddBatchNormReluOp.swift */,
 				FC039BA420E11CBC0081E9F8 /* ConvOp.swift */,
 				FC039BA520E11CBC0081E9F8 /* ElementwiseAddOp.swift */,
 				FC039BA720E11CBC0081E9F8 /* BatchNormOp.swift */,
@@ -441,9 +418,9 @@
 		FC086BA520E67E8500D85EF7 /* Kernels */ = {
 			isa = PBXGroup;
 			children = (
-				FC9797CA21D6102D00F2FD90 /* ResizeBilinearKernel.swift */,
 				FCDDC6CD212FE02100E5EF74 /* Base */,
 				FCEB6837212F00B100D2448E /* metal */,
+				FC9797CA21D6102D00F2FD90 /* ResizeBilinearKernel.swift */,
 				FCDDC6C7212FA3CA00E5EF74 /* ConvTransposeKernel.swift */,
 				FC0E2DBB20EE45FE009C1FAC /* ConvKernel.swift */,
 				FC0E2DB920EE3B8D009C1FAC /* ReluKernel.swift */,
@@ -469,24 +446,30 @@
 				FC803BC0214CB77A0094B8E5 /* ConvAddPreluKernel.swift */,
 				FCE3A1AA2153DE8C00C37CDE /* ConvAddAddPreluKernel.swift */,
 				FCE3A1AE2153E8EE00C37CDE /* ElementwiseAddPreluKernel.swift */,
+				FC2BFD4521DF685F00C262B2 /* Scale.swift */,
 			);
 			path = Kernels;
 			sourceTree = "<group>";
 		};
-		FC9797CC21D61A5500F2FD90 /* CustomNet */ = {
+		FC2BFD4721DF818000C262B2 /* API */ = {
 			isa = PBXGroup;
 			children = (
-				FC292C7C214255BC00CF622F /* CPUCompute.mm */,
-				FC292C7D214255BC00CF622F /* CPUCompute.h */,
-				FC704C2621D2385100F98BAB /* SuperResolutionNet.swift */,
-				C28FDF8221B7858F0054EFAC /* MobileNetCombined.swift */,
-				C28FDF8321B7858F0054EFAC /* YoloNet.swift */,
-				FC9A19E22148C31300CD9CBF /* MobilenetSSD_AR.swift */,
-				FC33B0EF2147659000714A93 /* MobileNet.swift */,
-				FC292C862142624800CF622F /* Genet.swift */,
-				FC292C7E214255BC00CF622F /* MobileNetSSD.swift */,
+				FCE9D7B6214F869000B520C3 /* Net.swift */,
+				FC1CF3F621D4B4C400F7392E /* Runner.swift */,
+				FC2BFCC121DF2F9100C262B2 /* GlobalConfig.swift */,
+			);
+			path = API;
+			sourceTree = "<group>";
+		};
+		FC2BFD4821DF818000C262B2 /* Src */ = {
+			isa = PBXGroup;
+			children = (
+				FC039BAE20E11CC20081E9F8 /* Program */,
+				FC039BA320E11CBC0081E9F8 /* Operators */,
+				FC039B9C20E11CB20081E9F8 /* framework */,
+				FC039B9320E11C9A0081E9F8 /* Common */,
 			);
-			path = CustomNet;
+			path = Src;
 			sourceTree = "<group>";
 		};
 		FCD592FA20E248EC00252966 /* Base */ = {
@@ -502,7 +485,7 @@
 		FCDDC6CD212FE02100E5EF74 /* Base */ = {
 			isa = PBXGroup;
 			children = (
-				FCF2D73720E64E70007AC5F5 /* Kernel.swift */,
+				FC2BFD4921DF81DE00C262B2 /* Kernel.swift */,
 			);
 			path = Base;
 			sourceTree = "<group>";
@@ -547,6 +530,7 @@
 				FCE3A1B02153E90F00C37CDE /* ElementwiseAddPreluKernel.inc.metal */,
 				FCE3A1B22153E91900C37CDE /* ElementwiseAddPreluKernel.metal */,
 				FC9C2A0C21D3D185005856C6 /* FetchKernel.inc.metal */,
+				FC2BFD5021DF8E0400C262B2 /* Scale.metal */,
 			);
 			path = metal;
 			sourceTree = "<group>";
@@ -558,9 +542,7 @@
 			isa = PBXHeadersBuildPhase;
 			buildActionMask = 2147483647;
 			files = (
-				FC292C5421421B2F00CF622F /* PaddleMobileGPU.h in Headers */,
 				FC039B6F20E11C3C0081E9F8 /* paddle_mobile.h in Headers */,
-				FC9797CD21D61B2E00F2FD90 /* CPUCompute.h in Headers */,
 			);
 			runOnlyForDeploymentPostprocessing = 0;
 		};
@@ -678,7 +660,6 @@
 				FCE3A1AB2153DE8C00C37CDE /* ConvAddAddPreluKernel.swift in Sources */,
 				FC9D037920E229E4000F735A /* OpParam.swift in Sources */,
 				FC3602CC2108819F00FACB58 /* PaddleMobileUnitTest.swift in Sources */,
-				FCF2D73820E64E70007AC5F5 /* Kernel.swift in Sources */,
 				FCDDC6CC212FDFDB00E5EF74 /* ReluKernel.metal in Sources */,
 				FC0226562138F33800F395E2 /* TransposeKernel.metal in Sources */,
 				FCDDC6C6212F9FB800E5EF74 /* PreluKernel.swift in Sources */,
@@ -686,13 +667,10 @@
 				FCA67CD52138272900BD58AA /* ConvAddMetal.metal in Sources */,
 				FCBCCC5B2122F66F00D94F7E /* ConvBNReluKernel.swift in Sources */,
 				4AA1EA8C2146640900D0F791 /* SplitOp.swift in Sources */,
-				FC292C81214255BD00CF622F /* CPUCompute.mm in Sources */,
-				FCEBC0F420F1FDD90099DBAF /* ConvAddBatchNormReluOp.swift in Sources */,
 				4AA1EAAC214F55C800D0F791 /* Softmax.inc.metal in Sources */,
 				FC0E2DC020EE461F009C1FAC /* ElementwiseAddKernel.swift in Sources */,
 				4AF928772133F1DB005B6C3A /* BoxCoder.metal in Sources */,
 				FC803BBF214CB65A0094B8E5 /* ConvAddPreluOp.swift in Sources */,
-				FC33B0F02147659000714A93 /* MobileNet.swift in Sources */,
 				FCEB684C212F093800D2448E /* PreluOp.swift in Sources */,
 				4AA1EAA8214B7AFB00D0F791 /* BilinearInterp.inc.metal in Sources */,
 				FCA67CD92138287B00BD58AA /* ConvBNReluKernel.metal in Sources */,
@@ -704,17 +682,19 @@
 				FC039BBA20E11CC20081E9F8 /* TensorDesc.swift in Sources */,
 				FC039BA020E11CB20081E9F8 /* Dim.swift in Sources */,
 				FC039BB820E11CC20081E9F8 /* framework.pb.swift in Sources */,
-				C28FDF8521B7858F0054EFAC /* YoloNet.swift in Sources */,
 				FC039B9920E11C9A0081E9F8 /* Types.swift in Sources */,
 				FC4CB74920F0B954007C0C6D /* ConvKernel.metal in Sources */,
 				FCA3A1632132A4AC00084FE5 /* ReshapeKernel.metal in Sources */,
 				FCBCCC592122F42700D94F7E /* ConvBNReluOp.swift in Sources */,
 				FC039BA920E11CBC0081E9F8 /* ConvOp.swift in Sources */,
 				FCCED5E121D71FC000BE8D5F /* PoolKernel.inc.metal in Sources */,
+				FC2BFD4A21DF81DE00C262B2 /* Kernel.swift in Sources */,
 				FC9D038420E23B01000F735A /* Texture.swift in Sources */,
 				FCE3A1B32153E91900C37CDE /* ElementwiseAddPreluKernel.metal in Sources */,
+				FC2BFD4E21DF820B00C262B2 /* ConvAddBatchNormReluOp.swift in Sources */,
 				4AA1EAA2214912CD00D0F791 /* FlattenKernel.swift in Sources */,
 				4AA1EA982146666500D0F791 /* FlattenOp.swift in Sources */,
+				FC2BFCC221DF2F9100C262B2 /* GlobalConfig.swift in Sources */,
 				FCBCCC652122FCD700D94F7E /* TransposeOp.swift in Sources */,
 				4AA1EAA6214B5F6800D0F791 /* Shape.metal in Sources */,
 				FCD04E6E20F31B4B0007374F /* ReshapeOp.swift in Sources */,
@@ -724,13 +704,11 @@
 				FCD04E7420F3437E0007374F /* ConvAddKernel.swift in Sources */,
 				FC1CF3F721D4B4C400F7392E /* Runner.swift in Sources */,
 				FC039BB920E11CC20081E9F8 /* Scope.swift in Sources */,
-				FC292C5621421B4600CF622F /* PaddleMobileGPU.m in Sources */,
 				FCD04E6620F314C50007374F /* PoolOp.swift in Sources */,
 				FCE9D7B9214FAA4800B520C3 /* NMSFetchResultKernel.metal in Sources */,
 				FC039BAC20E11CBC0081E9F8 /* BatchNormOp.swift in Sources */,
 				FCBCCC6F2123097100D94F7E /* MulticlassNMSOp.swift in Sources */,
 				FC039BBC20E11CC20081E9F8 /* VarDesc.swift in Sources */,
-				FC292C872142624800CF622F /* Genet.swift in Sources */,
 				FC803BC5214CB8F00094B8E5 /* ConvAddPrelu.inc.metal in Sources */,
 				4AF928822135673D005B6C3A /* ConcatKernel.metal in Sources */,
 				FCBCCC632122FCC000D94F7E /* TransposeKernel.swift in Sources */,
@@ -748,23 +726,20 @@
 				FCBCCC5D2122F8A100D94F7E /* DepthwiseConvOp.swift in Sources */,
 				FCE3A1AF2153E8EE00C37CDE /* ElementwiseAddPreluKernel.swift in Sources */,
 				FCE9D7B7214F869000B520C3 /* Net.swift in Sources */,
-				FC704C2721D2385100F98BAB /* SuperResolutionNet.swift in Sources */,
 				FC0E2DBE20EE460D009C1FAC /* BatchNormKernel.swift in Sources */,
 				FC039BAB20E11CBC0081E9F8 /* Operator.swift in Sources */,
-				C28FDF8421B7858F0054EFAC /* MobileNetCombined.swift in Sources */,
 				FCD04E6A20F319EC0007374F /* SoftmaxOp.swift in Sources */,
-				FC292C82214255BD00CF622F /* MobileNetSSD.swift in Sources */,
 				FCBCCC612122FBDF00D94F7E /* PriorBoxKernel.swift in Sources */,
 				FCBCCC5F2122FB3B00D94F7E /* PriorBoxOp.swift in Sources */,
 				FC9D038220E2312E000F735A /* FetchOp.swift in Sources */,
 				FCA67B1721364EF000BD58AA /* ConvTransposeKernel.metal in Sources */,
 				FC039BBD20E11CC20081E9F8 /* Program.swift in Sources */,
+				FC2BFD5121DF8E0400C262B2 /* Scale.metal in Sources */,
 				FC039BA220E11CB70081E9F8 /* Loader.swift in Sources */,
 				FCBCCC67212306B000D94F7E /* ConcatOp.swift in Sources */,
 				FCD04E6C20F31A280007374F /* SoftmaxKernel.swift in Sources */,
 				FCEB684A212F00DB00D2448E /* PreluKernel.metal in Sources */,
 				4AA1EAA02148DEEE00D0F791 /* ReshapeKernel.inc.metal in Sources */,
-				FC9A19E32148C31300CD9CBF /* MobilenetSSD_AR.swift in Sources */,
 				FCDDC6CF212FE14700E5EF74 /* PriorBoxKernel.metal in Sources */,
 				FC4CB74B20F12C30007C0C6D /* ProgramOptimize.swift in Sources */,
 				FCE3A1A92153DE5100C37CDE /* ConvAddAddPreluOp.swift in Sources */,
@@ -780,6 +755,7 @@
 				FC039BBE20E11CC20081E9F8 /* OpDesc.swift in Sources */,
 				FC9797C921D6101D00F2FD90 /* ResizeBilinearOp.swift in Sources */,
 				4AA1EA88214662BD00D0F791 /* BilinearInterpKernel.swift in Sources */,
+				FC2BFD4621DF685F00C262B2 /* Scale.swift in Sources */,
 				FC039B9720E11C9A0081E9F8 /* Extensions.swift in Sources */,
 			);
 			runOnlyForDeploymentPostprocessing = 0;
@@ -919,7 +895,7 @@
 				DYLIB_COMPATIBILITY_VERSION = 1;
 				DYLIB_CURRENT_VERSION = 1;
 				DYLIB_INSTALL_NAME_BASE = "@rpath";
-				ENABLE_BITCODE = NO;
+				ENABLE_BITCODE = YES;
 				INFOPLIST_FILE = "paddle-mobile/Info.plist";
 				INSTALL_PATH = "$(LOCAL_LIBRARY_DIR)/Frameworks";
 				IPHONEOS_DEPLOYMENT_TARGET = 9.0;
@@ -956,7 +932,7 @@
 				DYLIB_COMPATIBILITY_VERSION = 1;
 				DYLIB_CURRENT_VERSION = 1;
 				DYLIB_INSTALL_NAME_BASE = "@rpath";
-				ENABLE_BITCODE = NO;
+				ENABLE_BITCODE = YES;
 				INFOPLIST_FILE = "paddle-mobile/Info.plist";
 				INSTALL_PATH = "$(LOCAL_LIBRARY_DIR)/Frameworks";
 				IPHONEOS_DEPLOYMENT_TARGET = 9.0;

metal/paddle-mobile/paddle-mobile/API/GlobalConfig.swift

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+ 
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+ 
+ http://www.apache.org/licenses/LICENSE-2.0
+ 
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
+
+import Foundation
+
+@objc public enum MetalLoadMode: Int {
+  case
+  LoadMetalInPaddleMobile   = 1,     // 使用 paddle-mobile 中的 metal 代码
+  LoadMetalInDefaultLib     = 2,     // 使用 main bundle 中的 metal 代码
+  LoadMetalInCustomMetalLib = 3      // 使用 metal 库文件
+}
+
+@objc public enum ComputePrecision: Int {
+  case
+  Float32 = 1,
+  Float16 = 2
+}
+
+@objc public class GlobalConfig: NSObject {
+  
+  /// 单例
+  @objc public static let shared: GlobalConfig = GlobalConfig.init()
+  
+  /// 运算精度， runner 生命周期中不可变
+  @objc public var computePrecision: ComputePrecision = .Float16
+
+}

metal/paddle-mobile/paddle-mobile/Net.swift → metal/paddle-mobile/paddle-mobile/API/Net.swift

@@ -12,58 +12,52 @@
  See the License for the specific language governing permissions and
  limitations under the License. */
 
-
-import Foundation
 import Metal
+import Foundation
 
-public class ResultHolder: NSObject {
-  @objc public let result: UnsafeMutablePointer<Float32>
-  @objc public let capacity: Int
+/// 网络的基类， 参数已经给了默认值，请在子类实现中修改需要改的参数
+@objc open class Net: NSObject {
 
-  init(inResult: UnsafeMutablePointer<Float32>, inCapacity: Int) {
-    result = inResult
-    capacity = inCapacity
-  }
+  /// 默认为0， 如果指定个数， 后边 except 个op不使用 GPU 运算， 中间结果会通过 fetchResult 传参过来
+  @objc public var except: Int = 0
+      
+  /// 预处理 kernel， 如果输入图像需要预处理， 则指定预处理 kernel
+  @objc public var preprocessKernel: CusomKernel? = nil
   
-  @objc public func releasePointer() {
-    result.deinitialize(count: capacity)
-    result.deallocate()
-  }
-}
-
-public class Net: NSObject {
-  var except: Int = 0
+  // 以下四个参数为从内存中读取模型时用到的参数
+  /// 模型在内存中的指针
+  @objc public var modelPointer: UnsafeMutableRawPointer? = nil
   
-  // for CPU
-  var means: [Float] = []
-  var scale: Float = 0.0
+  /// 模型大小 单位： 字节
+  @objc public var modelSize: Int = 0
   
-  var needUpdateProgram = true
+  /// 权重参数在内存中的指针
+  @objc public var paramPointer: UnsafeMutableRawPointer? = nil
   
-  public var inputDim: Dim {
-    get{
-      return inputDim_
-    }
-    set{
-      if inputDim_ != newValue {
-        needUpdateProgram = true
-      }
-      inputDim_ = newValue
-    }
-  }
+  /// 权重大小 单位： 字节
+  @objc public var paramSize: Int = 0
   
-  var inputDim_: Dim = Dim.init(inDim: [])
-  var preprocessKernel: CusomKernel? = nil
-  var paramPointer: UnsafeMutableRawPointer? = nil
-  var paramSize: Int = 0
-  var modelPointer: UnsafeMutableRawPointer? = nil
-  var modelSize: Int = 0
-  var modelPath: String = ""
-  var paramPath: String = ""
-  var modelDir: String = ""
-  let device: MTLDevice
-  
-  @objc public init(device: MTLDevice,paramPointer: UnsafeMutableRawPointer, paramSize:Int, modePointer: UnsafeMutableRawPointer, modelSize: Int) {
+  // 以下两个为从文件中读取模型时用到的参数
+  /// 模型文件路径
+  @objc public var modelPath: String? = nil
+  
+  /// 权重文件路径
+  @objc public var paramPath: String? = nil
+  
+  /// 代表着 GPU 处理器
+  @objc public let device: MTLDevice
+  
+  /// metal 代码加载方式 注意： 如果静态库只能使用 LoadMetalInDefaultLib LoadMetalInCustomMetalLib 进行 load metal 代码
+  @objc public var metalLoadMode: MetalLoadMode = .LoadMetalInPaddleMobile
+  
+  /// 当 metalLoadMode 为 LoadMetalInCustomMetalLib 时， metal library 路径不能为空
+  @objc public var metalLibPath: String? = nil
+  
+  /// 输入维度，按照 n h w c 方式传入
+  @objc public var inputDim: Dim = Dim.init(inDim: [])
+  
+  
+  @objc public init(device: MTLDevice, paramPointer: UnsafeMutableRawPointer, paramSize:Int, modePointer: UnsafeMutableRawPointer, modelSize: Int) {
     self.paramPointer = paramPointer
     self.paramSize = paramSize
     self.modelPointer = modePointer
@@ -76,23 +70,18 @@ public class Net: NSObject {
     self.device = device
     super.init()
   }
-
-  @objc public func updateInputDim(inDim: [Int]) {
-    inputDim = Dim.init(inDim: inDim)
-  }
   
-  public func resultStr(res: ResultHolder) -> String {
+  @objc open func resultStr(res: ResultHolder) -> String {
     fatalError()
   }
   
-  func fetchResult(paddleMobileRes: GPUResultHolder) -> ResultHolder {
+  @objc open func fetchResult(paddleMobileRes: GPUResultHolder) -> ResultHolder {
     guard let inResPointer = paddleMobileRes.resultPointer else {
       fatalError()
     }
-    
     return ResultHolder.init(inResult: inResPointer, inCapacity: paddleMobileRes.capacity)
   }
   
-  func updateProgram(program: Program) {
+  open func updateProgram(program: Program) {
   }
 }

metal/paddle-mobile/paddle-mobile/Runner.swift → metal/paddle-mobile/paddle-mobile/API/Runner.swift

-//
-//  Runner.swift
-//  paddle-mobile
-//
-//  Created by liuRuiLong on 2018/12/27.
-//  Copyright © 2018 orange. All rights reserved.
-//
+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+ 
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+ 
+ http://www.apache.org/licenses/LICENSE-2.0
+ 
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
 
 import MetalKit
 import Foundation
 
-class ScaleKernel: CusomKernel {
-  init(device: MTLDevice, shape: Shape) {
-    if computePrecision == .Float32 {
-      super.init(device: device, inFunctionName: "scale", outputDim: shape, usePaddleMobileLib: false)
-    } else if computePrecision == .Float16 {
-      super.init(device: device, inFunctionName: "scale_half", outputDim: shape, usePaddleMobileLib: false)
-    } else {
-      fatalError(" unsupport ")
-    }
+@objc public class ResultHolder: NSObject {
+  @objc public let result: UnsafeMutablePointer<Float32>
+  @objc public let capacity: Int
+  
+  init(inResult: UnsafeMutablePointer<Float32>, inCapacity: Int) {
+    result = inResult
+    capacity = inCapacity
+  }
+  
+  @objc public func releasePointer() {
+    result.deinitialize(count: capacity)
+    result.deallocate()
   }
 }
 
@@ -29,15 +38,12 @@ class ScaleKernel: CusomKernel {
   public let net: Net
   let device: MTLDevice?
   let numel: Int
-  let meansNumber: [NSNumber]
   
-  // dims num nchw
-  let dimsNum: [NSNumber]
-  /**
-   * inNet:        需要运行的网络
-   * commandQueue: GPU 是需要传入
-   * inPlatform:   需要使用的平台, GPU or CPU
-   */
+  /// 初始化函数
+  ///
+  /// - Parameters:
+  ///   - inNet: 传入自定义的网络
+  ///   - commandQueue: commandQueue
   @objc public init(inNet: Net, commandQueue: MTLCommandQueue?) {
     guard inNet.inputDim.cout() == 4 else {
       fatalError(" input dim count must 4 ")
@@ -49,21 +55,12 @@ class ScaleKernel: CusomKernel {
     if let inDevice = device {
       textureLoader = MTKTextureLoader.init(device: inDevice)
     }
-
     numel = net.inputDim.numel()
-    meansNumber = net.means.map {
-      NSNumber.init(value: $0)
-    }
-    
-    dimsNum = [NSNumber.init(value: net.inputDim[0]),
-               NSNumber.init(value: net.inputDim[3]),
-               NSNumber.init(value: net.inputDim[1]),
-               NSNumber.init(value: net.inputDim[2])]
   }
   
-  /**
-   * load 模型, 返回 true 可进行预测
-   */
+  /// load 模型, 返回 true 可进行预测
+  ///
+  /// - Returns: load 成功或失败
   @objc public func load() -> Bool {
       guard let inDevice = device, let inQueue = queue else {
         print(" paddle mobile gpu load error, need MTLCommandQueue")
@@ -71,10 +68,24 @@ class ScaleKernel: CusomKernel {
       }
       let loader = Loader<Float32>.init()
       do {
-        //        program = try loader.load(device: inDevice, paramPointer: net.paramPointer!, paramSize: net.paramSize,modePointer:net.modelPointer!,modelSize:net.modelSize)
-        program = try loader.load(device: inDevice, modelPath: net.modelPath, paraPath: net.paramPath)
         
-        executor = try Executor<Float32>.init(inDevice: inDevice, inQueue: inQueue, inProgram: program!)
+        if let inParamPointer = net.paramPointer, let inModelPointer = net.modelPointer {
+          guard net.paramSize > 0 && net.modelSize > 0 else {
+            print(" load from memory param size or model size can't 0 ")
+            return false
+          }
+          program = try loader.load(device: inDevice, paramPointer: inParamPointer, paramSize: net.paramSize,modePointer:inModelPointer,modelSize:net.modelSize)
+        } else if let inModelPath = net.modelPath, let inParamPath = net.paramPath {
+          program = try loader.load(device: inDevice, modelPath: inModelPath, paraPath: inParamPath)
+        } else {
+          print(" model pointer or model file path need be specified")
+          return false
+        }
+        
+        let initContext: InitContext = InitContext.init()
+        initContext.metalLoadMode = net.metalLoadMode
+        initContext.metalLibPath = net.metalLibPath
+        executor = try Executor<Float32>.init(inDevice: inDevice, inQueue: inQueue, inProgram: program!, initContext: initContext)
         net.updateProgram(program: program!)
       } catch let error {
         print(error)
@@ -83,13 +94,12 @@ class ScaleKernel: CusomKernel {
     return true
   }
   
-  /**
-   * GPU 版本 predict
-   * texture: 需要预测的 texture 需要做过预处理
-   * ( _ success: Bool, _ time:TimeInterval, _ resultArray: [Float32]) -> Void : 回调闭包, 三个参数分别为: 是否成功, 预测耗时, 结果数组
-   */
+  /// 预测
+  ///
+  /// - Parameters:
+  ///   - texture: 输入 texture 需要使用 getTexture 获得
+  ///   - completion: 结果回调， 当 success 为 true 时 result 不为 nil
   @objc public func predict(texture: MTLTexture, completion: @escaping ( _ success: Bool, _ result: ResultHolder?) -> Void) {
-    net.updateProgram(program: program!)
     do {
       try self.executor?.predict(input: texture, dim: self.net.inputDim, completionHandle: { [weak self] (res) in
         guard let SSelf = self else {
@@ -105,23 +115,28 @@ class ScaleKernel: CusomKernel {
     }
   }
   
-  /*
-   * 清理内存, 调用此函数后, 不能再使用, 需重新 load
-   */
+  /// 清理内存, 调用此函数后, 不能再使用, 需重新 load
   @objc public func clear() {
     executor?.clear()
     executor = nil
     program = nil
   }
-
-  /*
-   * 获取 texture, 对 texture 进行预处理, GPU 预测时使用
-   */
+  
+  /// 获取 texture, 对 texture 进行预处理, 预测时使用
+  ///
+  /// - Parameters:
+  ///   - image: 输入图像
+  ///   - getTexture: 获取 texture 回调
   @objc public func getTexture(image: CGImage, getTexture: @escaping (MTLTexture) -> Void) {
     let texture = try? textureLoader?.newTexture(cgImage: image, options: [:]) ?! " texture loader error"
     scaleTexture(input: texture!, complete: getTexture)
   }
   
+  /// 通过 buffer 获取 texture， 内部会使用GPU进行转换操作
+  ///
+  /// - Parameters:
+  ///   - inBuffer: 输入buffer
+  ///   - getTexture: 结果回调
   @objc public func getTexture(inBuffer: MTLBuffer, getTexture: @escaping (MTLTexture) -> Void) {
     guard let inQueue = queue, let inDevice = device else {
       fatalError( " queue or devcie nil " )
@@ -131,7 +146,7 @@ class ScaleKernel: CusomKernel {
       fatalError( " make buffer error" )
     }
     
-    let bufferToTextureKernel = BufferToTextureKernel.init(device: inDevice, outputDim: Shape.init(inWidth: net.inputDim[2], inHeight: net.inputDim[1], inChannel: net.inputDim[3]))
+    let bufferToTextureKernel = BufferToTextureKernel.init(device: inDevice, outputDim: Shape.init(inWidth: net.inputDim[2], inHeight: net.inputDim[1], inChannel: net.inputDim[3]), metalLoadMode: net.metalLoadMode, metalLibPath: net.metalLibPath)
     do {
       try bufferToTextureKernel.compute(inputBuffer: inBuffer, commandBuffer: buffer)
     } catch {
@@ -144,6 +159,19 @@ class ScaleKernel: CusomKernel {
     
     buffer.commit()
   }
+
+  /// 更新输入维度， 针对可变长输入模型
+  ///
+  /// - Parameter inDim: 输入维度
+  @objc public func updateInputDim(inDim: Dim) {
+    if net.inputDim != inDim {
+      guard let inProgram = program else {
+        fatalError(" need load first ")
+      }
+      net.inputDim = inDim
+      net.updateProgram(program: inProgram)
+    }
+  }
   
   public func scaleTexture(input: MTLTexture , complete: @escaping (MTLTexture) -> Void) {
     
@@ -155,7 +183,7 @@ class ScaleKernel: CusomKernel {
       fatalError( " make buffer error" )
     }
     
-    let scaleKernel = ScaleKernel.init(device: inDevice, shape: Shape.init(inWidth: net.inputDim[2], inHeight: net.inputDim[1], inChannel: 3))
+    let scaleKernel = ScaleKernel.init(device: inDevice, shape: Shape.init(inWidth: net.inputDim[2], inHeight: net.inputDim[1], inChannel: 3), metalLoadMode: net.metalLoadMode, metalLibPath: net.metalLibPath)
     
     do {
       try scaleKernel.compute(inputTexuture: input, commandBuffer: buffer)

metal/paddle-mobile/paddle-mobile/CustomNet/MobileNetCombined.swift

-//
-//  MobileNetCombined.swift
-//  paddle-mobile
-//
-//  Created by Xiao,Haichun on 2018/12/5.
-//  Copyright © 2018 orange. All rights reserved.
-//
-
-import Foundation
-
-public class MobileNetCombined: Net {
-  @objc public override init(device: MTLDevice) {
-    super.init(device: device)
-    means = [0, 0, 0]
-    scale = 1
-    except = 0
-    modelPath = Bundle.main.path(forResource: "combined_mobilenet_model", ofType: nil) ?! "model null"
-    paramPath = Bundle.main.path(forResource: "combined_mobilenet_params", ofType: nil) ?! "para null"
-    modelDir = ""
-    inputDim_ = Dim.init(inDim: [1, 224, 224, 3])
-  }
-  
-  @objc override public init(device: MTLDevice,paramPointer: UnsafeMutableRawPointer, paramSize:Int, modePointer: UnsafeMutableRawPointer, modelSize: Int) {
-
-    super.init(device:device,paramPointer:paramPointer,paramSize:paramSize,modePointer:modePointer,modelSize:modelSize)
-    means = [0, 0, 0]
-    scale = 1
-    except = 0
-    modelPath = ""
-    paramPath = ""
-    modelDir = ""
-    inputDim_ = Dim.init(inDim: [1,  224, 224, 3])
-  }
-  
-  //    class GenetPreProccess: CusomKernel {
-  //        init(device: MTLDevice) {
-  //            let s = CusomKernel.Shape.init(inWidth: 128, inHeight: 128, inChannel: 3)
-  //            super.init(device: device, inFunctionName: "genet_preprocess", outputDim: s, usePaddleMobileLib: false)
-  //        }
-  //    }
-  
-  override  public func resultStr(res: ResultHolder) -> String {
-    //    fatalError()
-    return " \(res.result[0]) ... "
-  }
-  
-}

metal/paddle-mobile/paddle-mobile/CustomNet/YoloNet.swift

-//
-//  YoloNet.swift
-//  paddle-mobile
-//
-//  Created by Xiao,Haichun on 2018/12/5.
-//  Copyright © 2018 orange. All rights reserved.
-//
-
-import Foundation
-import Metal
-
-public class YoloNet: Net {
-  @objc public override init(device: MTLDevice) {
-    super.init(device: device)
-    means = [0, 0, 0]
-    scale = 1
-    except = 0
-    modelPath = Bundle.main.path(forResource: "yolo_model", ofType: nil) ?! "model null"
-    paramPath = Bundle.main.path(forResource: "yolo_params", ofType: nil) ?! "para null"
-    modelDir = ""
-//    preprocessKernel = GenetPreProccess.init(device: device)
-    inputDim_ = Dim.init(inDim: [1, 416, 416, 3])
-    
-  }
-  
-  @objc override public init(device: MTLDevice,paramPointer: UnsafeMutableRawPointer, paramSize:Int, modePointer: UnsafeMutableRawPointer, modelSize: Int) {
-    super.init(device:device,paramPointer:paramPointer,paramSize:paramSize,modePointer:modePointer,modelSize:modelSize)
-    means = [0, 0, 0]
-    scale = 1
-    except = 0
-    modelPath = ""
-    paramPath = ""
-    modelDir = ""
-    //preprocessKernel = GenetPreProccess.init(device: device)
-    inputDim_ = Dim.init(inDim: [1, 416, 416, 3])
-  }
-  
-  //    class GenetPreProccess: CusomKernel {
-  //        init(device: MTLDevice) {
-  //            let s = CusomKernel.Shape.init(inWidth: 128, inHeight: 128, inChannel: 3)
-  //            super.init(device: device, inFunctionName: "genet_preprocess", outputDim: s, usePaddleMobileLib: false)
-  //        }
-  //    }
-  
-  override  public func resultStr(res: ResultHolder) -> String {
-    return " \(res.result[0]) ... "
-  }
-  
-}

metal/paddle-mobile/paddle-mobile/Common/MetalExtension.swift → metal/paddle-mobile/paddle-mobile/Src/Common/MetalExtension.swift

@@ -18,6 +18,7 @@ import CoreMedia
 
 fileprivate var defaultMetalLibrary: MTLLibrary?
 fileprivate var paddleMobileMetalLibrary: MTLLibrary?
+fileprivate var customMetalLibrary: MTLLibrary?
 
 extension MTLDevice {
   func defaultLibrary() -> MTLLibrary {
@@ -31,6 +32,22 @@ extension MTLDevice {
     }
   }
   
+  func customLibrary(metalLibPath: String) -> MTLLibrary {
+    if customMetalLibrary == nil {
+      do {
+        customMetalLibrary = try makeLibrary(filepath: metalLibPath)
+      } catch  let error {
+        fatalError("\(error)")
+      }
+    }
+    
+    if let inMetalLib = customMetalLibrary {
+      return inMetalLib
+    } else {
+      fatalError(" customlib is nil ")
+    }
+  }
+  
   func paddleMobileLibrary() -> MTLLibrary {
     if paddleMobileMetalLibrary == nil {
       guard let path = Bundle.init(for: Kernel.self).path(forResource: "default", ofType: "metallib") else {
@@ -50,8 +67,19 @@ extension MTLDevice {
     }
   }
   
-  func pipeLine(funcName: String, inPaddleMobileLib: Bool = true) -> MTLComputePipelineState {
-    let useLib = inPaddleMobileLib ? paddleMobileLibrary() : defaultLibrary()
+  func pipeLine(funcName: String, metalLoadMode: MetalLoadMode, metalLibPath: String?) -> MTLComputePipelineState {
+    let useLib: MTLLibrary
+    switch metalLoadMode {
+    case .LoadMetalInDefaultLib:
+      useLib = defaultLibrary()
+    case .LoadMetalInPaddleMobile:
+      useLib = paddleMobileLibrary()
+    case .LoadMetalInCustomMetalLib:
+      useLib = customLibrary(metalLibPath: metalLibPath ?! " can't be nil ")
+    default:
+      fatalError()
+    }
+    
     guard let function = useLib.makeFunction(name: funcName) else {
       fatalError(" function " + funcName + " not found")
     }

metal/paddle-mobile/paddle-mobile/Common/PaddleMobileUnitTest.swift → metal/paddle-mobile/paddle-mobile/Src/Common/PaddleMobileUnitTest.swift

@@ -324,9 +324,10 @@ public class PaddleMobileUnitTest {
         
         let param = ConvAddBatchNormReluTestParam.init(inInputTexture: inputeTexture, inOutputTexture: outputTexture, inMetalParam: metalParam, inFilterBuffer: filterBuffer, inBiaseBuffer: biaseBuffer, inNewScaleBuffer: newScalueBuffer, inNewBiaseBuffer: newBiaseBuffer, inFilterSize: filterSize)
         
+      let initContext = InitContext.init()
+      initContext.metalLoadMode = .LoadMetalInDefaultLib
         
-        
-        let convAddBnReluKernel = ConvAddBatchNormReluKernel<Float32>.init(device: device, testParam: param)
+      let convAddBnReluKernel = ConvAddBatchNormReluKernel<Float32>.init(device: device, testParam: param, initContext: initContext)
         
         convAddBnReluKernel.test(commandBuffer: buffer, param: param)
         

metal/paddle-mobile/paddle-mobile/Common/Types.swift → metal/paddle-mobile/paddle-mobile/Src/Common/Types.swift

@@ -252,11 +252,11 @@ extension InputTexture: Variant {
 extension MTLTexture where Self: Variant {
 }
 
-class FetchHolder: Variant {
+public class FetchHolder: Variant {
   var resultBuffer: MTLBuffer?
-  var dim: Dim
-  var capacity: Int
-  var paddedCapacity: Int
+  public var dim: Dim
+  public var capacity: Int
+  public var paddedCapacity: Int
   
   init(inPaddedCapacity: Int, inDim: Dim) {
     paddedCapacity = inPaddedCapacity
@@ -264,7 +264,7 @@ class FetchHolder: Variant {
     dim = inDim
   }
   
-  func initBuffer(device: MTLDevice) {
+  public func initBuffer(device: MTLDevice) {
     resultBuffer = device.makeBuffer(length: paddedCapacity * 4, options: [])
   }
   
@@ -278,12 +278,12 @@ class FetchHolder: Variant {
 }
 
 extension FetchHolder: CustomStringConvertible, CustomDebugStringConvertible {
-  var description: String {
+  public var description: String {
     fatalError()
 //    return "\(result)"
   }
   
-  var debugDescription: String {
+  public var debugDescription: String {
     fatalError()
 //    return "\(result)"
   }

metal/paddle-mobile/paddle-mobile/Operators/Base/OpCreator.swift → metal/paddle-mobile/paddle-mobile/Src/Operators/Base/OpCreator.swift

@@ -27,19 +27,19 @@ class OpCreator<P: PrecisionType> {
         }
     }
     
-    func creat(device: MTLDevice, opDesc: OpDesc, scope: Scope) throws -> Runable & InferShaperable {
+  func creat(device: MTLDevice, opDesc: OpDesc, scope: Scope, initContext: InitContext) throws -> Runable & InferShaperable {
         guard let opCreator = opCreators[opDesc.type] else {
             throw PaddleMobileError.opError(message: "there is no " + opDesc.type + " yet")
         }
         
         do {
-            return try opCreator(device, opDesc, scope)
+            return try opCreator(device, opDesc, scope, initContext)
         } catch let error {
             throw error
         }
     }
     
-    let opCreators: [String : (MTLDevice, OpDesc, Scope) throws -> Runable & InferShaperable] =
+    let opCreators: [String : (MTLDevice, OpDesc, Scope, InitContext) throws -> Runable & InferShaperable] =
         [gConvType                  :     ConvOp<P>.creat,
          gBatchNormType             :     BatchNormOp<P>.creat,
          gReluType                  :     ReluOp<P>.creat,

metal/paddle-mobile/paddle-mobile/Operators/Base/Operator.swift → metal/paddle-mobile/paddle-mobile/Src/Operators/Base/Operator.swift

@@ -31,7 +31,7 @@ protocol Runable {
   func run(device: MTLDevice, buffer: MTLCommandBuffer) throws
   func runImpl(device: MTLDevice,buffer: MTLCommandBuffer) throws
   func delogOutput()
-  func inputVariant() -> [String : [Variant]]
+  func inputVariant() -> [String : [MTLBuffer]]
   func computeMiddleResult(device: MTLDevice, buffer: MTLCommandBuffer)
 }
 
@@ -44,7 +44,7 @@ extension Runable where Self: OperatorProtocol{
     }
   }
   
-  func inputVariant() -> [String : [Variant]] {
+  func inputVariant() -> [String : [MTLBuffer]] {
 //    return [:]
     fatalError(" op \(type) need implement inputVariant")
   }
@@ -59,15 +59,26 @@ extension Runable where Self: OperatorProtocol{
   }
 }
 
+public class InitContext {
+  /// metal 代码加载方式
+  var metalLoadMode: MetalLoadMode = .LoadMetalInDefaultLib
+  /// 当 metalLoadMode 为 LoadMetalInCustomMetalLib 时， metal library 路径不能为空
+  var metalLibPath: String? = nil
+  init() {
+    metalLoadMode = .LoadMetalInDefaultLib
+    metalLibPath = nil
+  }
+}
+
 protocol Creator where Self: OperatorProtocol{
   associatedtype OpType: OperatorProtocol & Runable & InferShaperable
-  static func creat(device: MTLDevice, opDesc: OpDesc, inScope: Scope) throws -> OpType
+  static func creat(device: MTLDevice, opDesc: OpDesc, inScope: Scope, initContext: InitContext) throws -> OpType
 }
 
 extension Creator where Self: OperatorProtocol {
-  static func creat(device: MTLDevice, opDesc: OpDesc, inScope: Scope) throws -> OpType {
+  static func creat(device: MTLDevice, opDesc: OpDesc, inScope: Scope, initContext: InitContext) throws -> OpType {
     do {
-      return try OpType.provide(device:device, opDesc: opDesc, inScope: inScope)
+      return try OpType.provide(device:device, opDesc: opDesc, inScope: inScope, initContext: initContext)
     } catch let error {
       throw error
     }
@@ -89,13 +100,13 @@ protocol OperatorProtocol {
   var attrs: [String : Attr] { get }
   var para: ParamType { get }
   var kernel: KerType { get }
-  init(device: MTLDevice, opDesc: OpDesc, inScope: Scope) throws
+  init(device: MTLDevice, opDesc: OpDesc, inScope: Scope, initContext: InitContext) throws
 }
 
 extension OperatorProtocol {
-  static func provide(device: MTLDevice, opDesc: OpDesc, inScope: Scope) throws -> Self {
+  static func provide(device: MTLDevice, opDesc: OpDesc, inScope: Scope, initContext: InitContext) throws -> Self {
     do {
-      return try Self.init(device: device, opDesc: opDesc, inScope: inScope)
+      return try Self.init(device: device, opDesc: opDesc, inScope: inScope, initContext: initContext)
     } catch let error {
       throw error
     }
@@ -103,18 +114,7 @@ extension OperatorProtocol {
 }
 
 class Operator <KernelType:  Computable , ParameterType>: OperatorProtocol where KernelType.ParamType == ParameterType {
-  typealias ParamType = ParameterType
-  typealias KerType = KernelType
-  let type: String
-  let inputs: [String : [String]]
-  var paraInputs: [String : [String]]
-  let outpus: [String : [String]]
-  let attrs: [String : Attr]
-  let para: ParamType
-  let scope: Scope
-  var kernel: KerType
-  required init(device: MTLDevice, opDesc: OpDesc, inScope: Scope) throws {
-//    print("create op: \(opDesc.type)")
+  required init(device: MTLDevice, opDesc: OpDesc, inScope: Scope, initContext: InitContext) throws {
     type = opDesc.type
     scope = inScope
     inputs = opDesc.inputs
@@ -126,8 +126,19 @@ class Operator <KernelType:  Computable , ParameterType>: OperatorProtocol where
     } catch let error {
       throw error
     }
-    kernel = KernelType.init(device: device, param: para)
+    kernel = KernelType.init(device: device, param: para, initContext: initContext)
   }
+  
+  typealias ParamType = ParameterType
+  typealias KerType = KernelType
+  let type: String
+  let inputs: [String : [String]]
+  var paraInputs: [String : [String]]
+  let outpus: [String : [String]]
+  let attrs: [String : Attr]
+  let para: ParamType
+  let scope: Scope
+  var kernel: KerType
 }
 
 // op infos

metal/paddle-mobile/paddle-mobile/Operators/ConvAddOp.swift → metal/paddle-mobile/paddle-mobile/Src/Operators/ConvAddOp.swift

@@ -111,6 +111,7 @@ class ConvAddOp<P: PrecisionType>: Operator<ConvAddKernel<P>, ConvAddParam<P>>,
 //    print(biase)
     
     print(" \(type) output: ")
+    print(para.output.metalTexture)
     print(para.output.metalTexture.toTensor(dim: (n: para.output.tensorDim[0], c: para.output.tensorDim[1], h: para.output.tensorDim[2], w: para.output.tensorDim[3])).strideArray())
   }
 }

metal/paddle-mobile/paddle-mobile/Operators/DepthwiseConvOp.swift → metal/paddle-mobile/paddle-mobile/Src/Operators/DepthwiseConvOp.swift

@@ -17,14 +17,6 @@ import Foundation
 class DepthConvOp<P: PrecisionType>: Operator<ConvKernel<P>, ConvParam<P>>, Runable, Creator, InferShaperable {
 
   typealias OpType = DepthConvOp<P>
-
-  required init(device: MTLDevice, opDesc: OpDesc, inScope: Scope) throws {
-    do {
-      try super.init(device: device, opDesc: opDesc, inScope: inScope)
-    } catch let error {
-      throw error
-    }
-  }
   
   func inferShape() {
     let inDims = para.input.dim

metal/paddle-mobile/paddle-mobile/Operators/ElementwiseAddOp.swift → metal/paddle-mobile/paddle-mobile/Src/Operators/ElementwiseAddOp.swift

@@ -32,7 +32,7 @@ class ElementwiseAddParam<P: PrecisionType>: OpParam {
       let device = inputX.metalTexture!.device
       inputY = Texture.init(device: device, inDim: tensorY.dim)
       let value: [P] = Array(UnsafeBufferPointer(start: tensorY.data.pointer, count: tensorY.dim.numel()))
-      inputY.metalTexture = device.tensor2texture(value: value, dim: tensorY.dim.dims, transpose: [0, 1, 2, 3], inComputePrecision: computePrecision)
+      inputY.metalTexture = device.tensor2texture(value: value, dim: tensorY.dim.dims, transpose: [0, 1, 2, 3], inComputePrecision: GlobalConfig.shared.computePrecision)
     }
     
 //    required init(device: MTLDevice, param: ElementwiseAddParam<P>) {

metal/paddle-mobile/paddle-mobile/Operators/ElementwiseAddPreluOp.swift → metal/paddle-mobile/paddle-mobile/Src/Operators/ElementwiseAddPreluOp.swift

@@ -34,7 +34,7 @@ class ElementwiseAddPreluParam<P: PrecisionType>: OpParam {
       let device = inputX.metalTexture!.device
       inputY = Texture.init(device: device, inDim: tensorY.dim)
       let value: [P] = Array(UnsafeBufferPointer(start: tensorY.data.pointer, count: tensorY.dim.numel()))
-      inputY.metalTexture = device.tensor2texture(value: value, dim: tensorY.dim.dims, transpose: [0, 1, 2, 3], inComputePrecision: computePrecision)
+      inputY.metalTexture = device.tensor2texture(value: value, dim: tensorY.dim.dims, transpose: [0, 1, 2, 3], inComputePrecision: GlobalConfig.shared.computePrecision)
     }
     
     //    required init(device: MTLDevice, param: ElementwiseAddParam<P>) {

metal/paddle-mobile/paddle-mobile/Operators/FeedOp.swift → metal/paddle-mobile/paddle-mobile/Src/Operators/FeedOp.swift

@@ -63,7 +63,7 @@ class FeedOp<P: PrecisionType>: Operator<Texture2DTo2DArrayKernel<P>, FeedParam<
   
   func delogOutput() {
     print(" \(type) output: ")
-    
+    print(para.output.metalTexture)
     print(para.output.metalTexture.toTensor(dim: (n: para.output.padToFourDim[0], c: para.output.padToFourDim[3], h: para.output.padToFourDim[2], w: para.output.padToFourDim[1])).strideArray())
   }
 }

metal/paddle-mobile/paddle-mobile/Operators/FetchOp.swift → metal/paddle-mobile/paddle-mobile/Src/Operators/FetchOp.swift

@@ -45,17 +45,17 @@ class FetchKernel<P: PrecisionType>: Kernel, Computable {
     encoder.endEncoding()
   }
   
-  required init(device: MTLDevice, param: FetchParam<P>) {
+  required init(device: MTLDevice, param: FetchParam<P>, initContext: InitContext) {
     param.output.initBuffer(device: device)
-    if computePrecision == .Float16 {
+    if GlobalConfig.shared.computePrecision == .Float16 {
       if param.input.transpose == [0, 2, 3, 1] {
-        super.init(device: device, inFunctionName: "fetch_half")
+        super.init(device: device, inFunctionName: "fetch_half", initContext: initContext)
       } else {
         fatalError(" not support ")
       }
-    } else if computePrecision == .Float32 {
+    } else if GlobalConfig.shared.computePrecision == .Float32 {
       if param.input.transpose == [0, 2, 3, 1] {
-        super.init(device: device, inFunctionName: "fetch_float")
+        super.init(device: device, inFunctionName: "fetch_float", initContext: initContext)
       } else {
         fatalError(" not support ")
       }

metal/paddle-mobile/paddle-mobile/Operators/Kernels/Base/Kernel.swift → metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/Base/Kernel.swift

@@ -21,14 +21,14 @@ public protocol TestParam {
 public protocol Testable {
   associatedtype TestParamType: TestParam
   func test(commandBuffer: MTLCommandBuffer, param: TestParamType)
-  init(device: MTLDevice, testParam: TestParamType)
+  init(device: MTLDevice, testParam: TestParamType, initContext: InitContext)
 }
 
 
 protocol Computable {
   associatedtype ParamType: OpParam
   func compute(commandBuffer: MTLCommandBuffer, param: ParamType) throws
-  init(device: MTLDevice, param: ParamType)
+  init(device: MTLDevice, param: ParamType, initContext: InitContext)
 }
 
 protocol KernelProtocol {
@@ -37,20 +37,20 @@ protocol KernelProtocol {
   
 }
 
-open class Kernel {
+@objc open class Kernel: NSObject{
   let pipline: MTLComputePipelineState
   let functionName: String
-  public init(device: MTLDevice, inFunctionName: String, usePaddleMobileLib: Bool = true) {
-    pipline = device.pipeLine(funcName: inFunctionName, inPaddleMobileLib: usePaddleMobileLib)
+  public init(device: MTLDevice, inFunctionName: String, usePaddleMobileLib: Bool = false, initContext: InitContext) {
+    pipline = device.pipeLine(funcName: inFunctionName, metalLoadMode: initContext.metalLoadMode, metalLibPath: initContext.metalLibPath)
     functionName = inFunctionName
   }
 }
 
-public struct Shape {
+@objc public class Shape: NSObject {
   public let width: Int
   public let height: Int
   public let channel: Int
-  public init(inWidth: Int, inHeight: Int, inChannel: Int){
+  @objc public init(inWidth: Int, inHeight: Int, inChannel: Int){
     width = inWidth
     height = inHeight
     channel = inChannel
@@ -60,16 +60,16 @@ public struct Shape {
 open class BufferToTextureKernel: Kernel {
   public let outputTexture: MTLTexture
   
-  public init(device: MTLDevice, outputDim: Shape, usePaddleMobileLib: Bool = false) {
+  public init(device: MTLDevice, outputDim: Shape, metalLoadMode: MetalLoadMode, metalLibPath: String?) {
     let textureDesc = MTLTextureDescriptor.init()
     textureDesc.textureType = .type2D
     textureDesc.width = outputDim.width
     textureDesc.height = outputDim.height
     textureDesc.depth = (outputDim.channel + 3) / 4
     
-    if computePrecision == .Float16 {
+    if GlobalConfig.shared.computePrecision == .Float16 {
       textureDesc.pixelFormat = .rgba16Float
-    } else if computePrecision == .Float32 {
+    } else if GlobalConfig.shared.computePrecision == .Float32 {
       textureDesc.pixelFormat = .rgba32Float
     } else {
       fatalError()
@@ -78,10 +78,13 @@ open class BufferToTextureKernel: Kernel {
     textureDesc.usage = [.shaderRead, .shaderWrite]
     textureDesc.storageMode = .shared
     outputTexture = device.makeTexture(descriptor: textureDesc) ?! " make texture error "
-    if computePrecision == .Float32 {
-      super.init(device: device, inFunctionName: "buffer_to_texture_kernel", usePaddleMobileLib: usePaddleMobileLib)
+    let initContext = InitContext.init()
+    initContext.metalLibPath = metalLibPath
+    initContext.metalLoadMode = metalLoadMode
+    if GlobalConfig.shared.computePrecision == .Float32 {
+      super.init(device: device, inFunctionName: "buffer_to_texture_kernel", initContext: initContext)
     } else {
-      super.init(device: device, inFunctionName: "buffer_to_texture_kernel_half", usePaddleMobileLib: usePaddleMobileLib)
+      super.init(device: device, inFunctionName: "buffer_to_texture_kernel_half", initContext: initContext)
     }
   }
   
@@ -98,19 +101,19 @@ open class BufferToTextureKernel: Kernel {
 
 }
 
-open class CusomKernel: Kernel {
+@objc open class CusomKernel: Kernel {
 
   public let outputTexture: MTLTexture
-  public init(device: MTLDevice, inFunctionName: String, outputDim: Shape, usePaddleMobileLib: Bool = false) {
+  public init(device: MTLDevice, inFunctionName: String, outputDim: Shape, metalLoadModel: MetalLoadMode, metalLibPath: String?) {
     let textureDesc = MTLTextureDescriptor.init()
     textureDesc.textureType = .type2D
     textureDesc.width = outputDim.width
     textureDesc.height = outputDim.height
     textureDesc.depth = (outputDim.channel + 3) / 4
     
-    if computePrecision == .Float16 {
+    if GlobalConfig.shared.computePrecision == .Float16 {
       textureDesc.pixelFormat = .rgba16Float
-    } else if computePrecision == .Float32 {
+    } else if GlobalConfig.shared.computePrecision == .Float32 {
       textureDesc.pixelFormat = .rgba32Float
     } else {
       fatalError()
@@ -120,7 +123,10 @@ open class CusomKernel: Kernel {
     textureDesc.storageMode = .shared
     outputTexture = device.makeTexture(descriptor: textureDesc) ?! " make texture error "
     
-    super.init(device: device, inFunctionName: inFunctionName, usePaddleMobileLib: usePaddleMobileLib)
+    let context = InitContext.init()
+    context.metalLoadMode = metalLoadModel
+    context.metalLibPath = metalLibPath
+    super.init(device: device, inFunctionName: inFunctionName, initContext: context)
   }
   
   public func compute(inputTexuture: MTLTexture, commandBuffer: MTLCommandBuffer) throws {

metal/paddle-mobile/paddle-mobile/Operators/Kernels/BatchNormKernel.swift → metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/BatchNormKernel.swift

@@ -15,7 +15,7 @@
 import Foundation
 
 class BatchNormKernel<P: PrecisionType>: Kernel, Computable {
-  required init(device: MTLDevice, param: BatchNormParam<P>) {
+  required init(device: MTLDevice, param: BatchNormParam<P>, initContext: InitContext) {
     let count = param.variance.dim.numel()
     let varianceP = param.variance.data.pointer
     let meanP = param.mean.data.pointer
@@ -27,13 +27,13 @@ class BatchNormKernel<P: PrecisionType>: Kernel, Computable {
       scaleP[i] = invStd * scaleP[i]
     }
 
-    param.bias.initBuffer(device: device, precision: computePrecision)
-    param.scale.initBuffer(device: device, precision: computePrecision)
-    param.output.initTexture(device: device, inTranspose: param.input.transpose, computePrecision: computePrecision)
-    if computePrecision == .Float32 {
-      super.init(device: device, inFunctionName: "batchnorm")
-    } else if computePrecision == .Float16 {
-      super.init(device: device, inFunctionName: "batchnorm_half")
+    param.bias.initBuffer(device: device, precision: GlobalConfig.shared.computePrecision)
+    param.scale.initBuffer(device: device, precision: GlobalConfig.shared.computePrecision)
+    param.output.initTexture(device: device, inTranspose: param.input.transpose, computePrecision: GlobalConfig.shared.computePrecision)
+    if GlobalConfig.shared.computePrecision == .Float32 {
+      super.init(device: device, inFunctionName: "batchnorm", initContext: initContext)
+    } else if GlobalConfig.shared.computePrecision == .Float16 {
+      super.init(device: device, inFunctionName: "batchnorm_half", initContext: initContext)
     } else {
       fatalError()
     }

metal/paddle-mobile/paddle-mobile/Operators/Kernels/BilinearInterpKernel.swift → metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/BilinearInterpKernel.swift

@@ -41,12 +41,12 @@ class BilinearInterpKernel<P: PrecisionType>: Kernel, Computable{
     encoder.endEncoding()
   }
   
-  required init(device: MTLDevice, param: BilinearInterpParam<P>) {
-    param.output.initTexture(device: device, inTranspose: param.input.transpose, computePrecision: computePrecision)
-    if computePrecision == .Float32 {
-      super.init(device: device, inFunctionName: "bilinear_interp_float")
-    } else if computePrecision == .Float16 {
-      super.init(device: device, inFunctionName: "bilinear_interp_half")
+  required init(device: MTLDevice, param: BilinearInterpParam<P>, initContext: InitContext) {
+    param.output.initTexture(device: device, inTranspose: param.input.transpose, computePrecision: GlobalConfig.shared.computePrecision)
+    if GlobalConfig.shared.computePrecision == .Float32 {
+      super.init(device: device, inFunctionName: "bilinear_interp_float", initContext: initContext)
+    } else if GlobalConfig.shared.computePrecision == .Float16 {
+      super.init(device: device, inFunctionName: "bilinear_interp_half", initContext: initContext)
     } else {
       fatalError()
     }

metal/paddle-mobile/paddle-mobile/Operators/Kernels/BoxcoderKernel.swift → metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/BoxcoderKernel.swift

@@ -32,12 +32,12 @@ class BoxcoderKernel<P: PrecisionType>: Kernel, Computable{
     encoder.endEncoding()
   }
   
-  required init(device: MTLDevice, param: BoxcoderParam<P>) {
-    param.output.initTexture(device: device, inTranspose: [0, 3, 1, 2], computePrecision: computePrecision)
-    if computePrecision == .Float32 {
-      super.init(device: device, inFunctionName: "boxcoder_float")
-    } else if computePrecision == .Float16 {
-      super.init(device: device, inFunctionName: "boxcoder_half")
+  required init(device: MTLDevice, param: BoxcoderParam<P>, initContext: InitContext) {
+    param.output.initTexture(device: device, inTranspose: [0, 3, 1, 2], computePrecision: GlobalConfig.shared.computePrecision)
+    if GlobalConfig.shared.computePrecision == .Float32 {
+      super.init(device: device, inFunctionName: "boxcoder_float", initContext: initContext)
+    } else if GlobalConfig.shared.computePrecision == .Float16 {
+      super.init(device: device, inFunctionName: "boxcoder_half", initContext: initContext)
     } else {
       fatalError()
     }

metal/paddle-mobile/paddle-mobile/Operators/Kernels/ConcatKernel.swift → metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/ConcatKernel.swift

@@ -52,8 +52,8 @@ class ConcatKernel<P: PrecisionType>: Kernel, Computable{
     encoder.endEncoding()
   }
 
-  required init(device: MTLDevice, param: ConcatParam<P>) {
-    param.output.initTexture(device: device, inTranspose: param.transpose, computePrecision: computePrecision)
+  required init(device: MTLDevice, param: ConcatParam<P>, initContext: InitContext) {
+    param.output.initTexture(device: device, inTranspose: param.transpose, computePrecision: GlobalConfig.shared.computePrecision)
     let orank = param.output.tensorDim.cout()
     let num = param.input.count
     assert(num <= 6)
@@ -133,16 +133,16 @@ class ConcatKernel<P: PrecisionType>: Kernel, Computable{
       }
     }
     pm.vdim = (Int32(vdim[0]), Int32(vdim[1]), Int32(vdim[2]), Int32(vdim[3]), Int32(vdim[4]), Int32(vdim[5]))
-    if computePrecision == .Float32 {
-      super.init(device: device, inFunctionName: "concat_\(orank)_\(num)_\(v)_float")
-    } else if computePrecision == .Float16 {
-      super.init(device: device, inFunctionName: "concat_\(orank)_\(num)_\(v)_half")
+    if GlobalConfig.shared.computePrecision == .Float32 {
+      super.init(device: device, inFunctionName: "concat_\(orank)_\(num)_\(v)_float", initContext: initContext)
+    } else if GlobalConfig.shared.computePrecision == .Float16 {
+      super.init(device: device, inFunctionName: "concat_\(orank)_\(num)_\(v)_half", initContext: initContext)
     } else {
       fatalError()
     }
   }
   
-  required init(device: MTLDevice, testParam: ConcatTestParam) {
-    super.init(device: device, inFunctionName: "concat")
+  required init(device: MTLDevice, testParam: ConcatTestParam, initContext: InitContext) {
+    super.init(device: device, inFunctionName: "concat", initContext: initContext)
   }
 }

metal/paddle-mobile/paddle-mobile/Operators/Kernels/ConvAddAddPreluKernel.swift → metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/ConvAddAddPreluKernel.swift

@@ -16,99 +16,99 @@ import Foundation
 
 class ConvAddAddPreluKernel<P: PrecisionType>: Kernel, Computable {
   var metalParam: MetalConvParam!
-  required init(device: MTLDevice, param: ConvAddAddPreluParam<P>) {
-    param.output.initTexture(device: device, inTranspose: [0, 2, 3, 1], computePrecision: computePrecision)
-    param.filter.initBuffer(device: device, precision: computePrecision)
-    param.y.initBuffer(device: device, precision: computePrecision)
-    param.alpha.initBuffer(device: device, precision: computePrecision)
+  required init(device: MTLDevice, param: ConvAddAddPreluParam<P>, initContext: InitContext) {
+    param.output.initTexture(device: device, inTranspose: [0, 2, 3, 1], computePrecision: GlobalConfig.shared.computePrecision)
+    param.filter.initBuffer(device: device, precision: GlobalConfig.shared.computePrecision)
+    param.y.initBuffer(device: device, precision: GlobalConfig.shared.computePrecision)
+    param.alpha.initBuffer(device: device, precision: GlobalConfig.shared.computePrecision)
     
-    if computePrecision == .Float16 {
+    if GlobalConfig.shared.computePrecision == .Float16 {
       if param.filter.width == 1 && param.filter.height == 1 {
         if param.mode == "channel" {
-          super.init(device: device, inFunctionName: "conv_add_1x1_prelu_channel_half")
+          super.init(device: device, inFunctionName: "conv_add_1x1_prelu_channel_half", initContext: initContext)
         } else if param.mode == "element" {
-          super.init(device: device, inFunctionName: "conv_add_1x1_prelu_element_half")
+          super.init(device: device, inFunctionName: "conv_add_1x1_prelu_element_half", initContext: initContext)
         } else {
-          super.init(device: device, inFunctionName: "conv_add_1x1_prelu_other_half")
+          super.init(device: device, inFunctionName: "conv_add_1x1_prelu_other_half", initContext: initContext)
         }
         
       } else if param.filter.channel == 1 {
         if param.mode == "channel" {
-          super.init(device: device, inFunctionName: "depthwise_conv_add_3x3_prelu_channel_half")
+          super.init(device: device, inFunctionName: "depthwise_conv_add_3x3_prelu_channel_half", initContext: initContext)
         } else if param.mode == "element" {
-          super.init(device: device, inFunctionName: "depthwise_conv_add_3x3_prelu_element_half")
+          super.init(device: device, inFunctionName: "depthwise_conv_add_3x3_prelu_element_half", initContext: initContext)
         } else {
-          super.init(device: device, inFunctionName: "depthwise_conv_add_3x3_prelu_other_half")
+          super.init(device: device, inFunctionName: "depthwise_conv_add_3x3_prelu_other_half", initContext: initContext)
         }
       } else if param.filter.width == 3 && param.filter.height == 3 {
         if param.mode == "channel" {
-          super.init(device: device, inFunctionName: "conv_add_3x3_prelu_channel_half")
+          super.init(device: device, inFunctionName: "conv_add_3x3_prelu_channel_half", initContext: initContext)
         } else if param.mode == "element" {
-          super.init(device: device, inFunctionName: "conv_add_3x3_prelu_element_half")
+          super.init(device: device, inFunctionName: "conv_add_3x3_prelu_element_half", initContext: initContext)
         } else {
-          super.init(device: device, inFunctionName: "conv_add_3x3_prelu_other_half")
+          super.init(device: device, inFunctionName: "conv_add_3x3_prelu_other_half", initContext: initContext)
         }
         
       } else if param.filter.width == 1 && param.filter.height == 5 {
         if param.mode == "channel" {
-          super.init(device: device, inFunctionName: "conv_add_5x1_prelu_channel_half")
+          super.init(device: device, inFunctionName: "conv_add_5x1_prelu_channel_half", initContext: initContext)
         } else if param.mode == "element" {
-          super.init(device: device, inFunctionName: "conv_add_5x1_prelu_element_half")
+          super.init(device: device, inFunctionName: "conv_add_5x1_prelu_element_half", initContext: initContext)
         } else {
-          super.init(device: device, inFunctionName: "conv_add_5x1_prelu_other_half")
+          super.init(device: device, inFunctionName: "conv_add_5x1_prelu_other_half", initContext: initContext)
         }
       } else if param.filter.width == 5 && param.filter.height == 1 {
         if param.mode == "channel" {
-          super.init(device: device, inFunctionName: "conv_add_1x5_prelu_channel_half")
+          super.init(device: device, inFunctionName: "conv_add_1x5_prelu_channel_half", initContext: initContext)
         } else if param.mode == "element" {
-          super.init(device: device, inFunctionName: "conv_add_1x5_prelu_element_half")
+          super.init(device: device, inFunctionName: "conv_add_1x5_prelu_element_half", initContext: initContext)
         } else {
-          super.init(device: device, inFunctionName: "conv_add_1x5_prelu_other_half")
+          super.init(device: device, inFunctionName: "conv_add_1x5_prelu_other_half", initContext: initContext)
         }
       } else {
         fatalError(" unsupport yet ")
       }
-    } else if computePrecision == .Float32 {
+    } else if GlobalConfig.shared.computePrecision == .Float32 {
       if param.filter.width == 1 && param.filter.height == 1 {
         if param.mode == "channel" {
-          super.init(device: device, inFunctionName: "conv_add_1x1_prelu_channel_float")
+          super.init(device: device, inFunctionName: "conv_add_1x1_prelu_channel_float", initContext: initContext)
         } else if param.mode == "element" {
-          super.init(device: device, inFunctionName: "conv_add_1x1_prelu_element_float")
+          super.init(device: device, inFunctionName: "conv_add_1x1_prelu_element_float", initContext: initContext)
         } else {
-          super.init(device: device, inFunctionName: "conv_add_1x1_prelu_other_float")
+          super.init(device: device, inFunctionName: "conv_add_1x1_prelu_other_float", initContext: initContext)
         }
       } else if param.filter.channel == 1 {
         if param.mode == "channel" {
-          super.init(device: device, inFunctionName: "depthwise_conv_add_3x3_prelu_channel_float")
+          super.init(device: device, inFunctionName: "depthwise_conv_add_3x3_prelu_channel_float", initContext: initContext)
         } else if param.mode == "element" {
-          super.init(device: device, inFunctionName: "depthwise_conv_add_3x3_prelu_element_float")
+          super.init(device: device, inFunctionName: "depthwise_conv_add_3x3_prelu_element_float", initContext: initContext)
         } else {
-          super.init(device: device, inFunctionName: "depthwise_conv_add_3x3_prelu_other_float")
+          super.init(device: device, inFunctionName: "depthwise_conv_add_3x3_prelu_other_float", initContext: initContext)
         }
       } else if param.filter.width == 3 && param.filter.height == 3 {
         if param.mode == "channel" {
-          super.init(device: device, inFunctionName: "conv_add_3x3_prelu_channel_float")
+          super.init(device: device, inFunctionName: "conv_add_3x3_prelu_channel_float", initContext: initContext)
         } else if param.mode == "element" {
-          super.init(device: device, inFunctionName: "conv_add_3x3_prelu_element_float")
+          super.init(device: device, inFunctionName: "conv_add_3x3_prelu_element_float", initContext: initContext)
         } else {
-          super.init(device: device, inFunctionName: "conv_add_3x3_prelu_other_float")
+          super.init(device: device, inFunctionName: "conv_add_3x3_prelu_other_float", initContext: initContext)
         }
         
       } else if param.filter.width == 1 && param.filter.height == 5 {
         if param.mode == "channel" {
-          super.init(device: device, inFunctionName: "conv_add_5x1_prelu_channel_float")
+          super.init(device: device, inFunctionName: "conv_add_5x1_prelu_channel_float", initContext: initContext)
         } else if param.mode == "element" {
-          super.init(device: device, inFunctionName: "conv_add_5x1_prelu_element_float")
+          super.init(device: device, inFunctionName: "conv_add_5x1_prelu_element_float", initContext: initContext)
         } else {
-          super.init(device: device, inFunctionName: "conv_add_5x1_prelu_other_float")
+          super.init(device: device, inFunctionName: "conv_add_5x1_prelu_other_float", initContext: initContext)
         }
       } else if param.filter.width == 5 && param.filter.height == 1 {
         if param.mode == "channel" {
-          super.init(device: device, inFunctionName: "conv_add_1x5_prelu_channel_float")
+          super.init(device: device, inFunctionName: "conv_add_1x5_prelu_channel_float", initContext: initContext)
         } else if param.mode == "element" {
-          super.init(device: device, inFunctionName: "conv_add_1x5_prelu_element_float")
+          super.init(device: device, inFunctionName: "conv_add_1x5_prelu_element_float", initContext: initContext)
         } else {
-          super.init(device: device, inFunctionName: "conv_add_1x5_prelu_other_float")
+          super.init(device: device, inFunctionName: "conv_add_1x5_prelu_other_float", initContext: initContext)
         }
       } else {
         fatalError(" unsupport yet ")

metal/paddle-mobile/paddle-mobile/Operators/Kernels/ConvAddBatchNormReluKernel.swift → metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/ConvAddBatchNormReluKernel.swift

@@ -37,44 +37,44 @@ struct ConvAddBatchNormReluTestParam: TestParam {
 }
 
 class ConvAddBatchNormReluKernel<P: PrecisionType>: Kernel, Computable, Testable {
-  required init(device: MTLDevice, testParam: ConvAddBatchNormReluTestParam) {
+  required init(device: MTLDevice, testParam: ConvAddBatchNormReluTestParam, initContext: InitContext) {
     if testParam.filterSize.width == 1 && testParam.filterSize.height == 1 {
-      super.init(device: device, inFunctionName: "conv_add_batch_norm_relu_1x1")
+      super.init(device: device, inFunctionName: "conv_add_batch_norm_relu_1x1", initContext: initContext)
     } else if testParam.filterSize.channel == 1 {
-      super.init(device: device, inFunctionName: "depthwise_conv_add_batch_norm_relu_3x3")
+      super.init(device: device, inFunctionName: "depthwise_conv_add_batch_norm_relu_3x3", initContext: initContext)
     } else {
-      super.init(device: device, inFunctionName: "conv_add_batch_norm_relu_3x3")
+      super.init(device: device, inFunctionName: "conv_add_batch_norm_relu_3x3", initContext: initContext)
     }
   }
   
   var metalParam: MetalConvParam!
   
-  required init(device: MTLDevice, param: ConvAddBatchNormReluParam<P>) {
-    param.output.initTexture(device: device, inTranspose: [0, 2, 3, 1], computePrecision: computePrecision)
-    param.filter.initBuffer(device: device, precision: computePrecision)
-    param.y.initBuffer(device: device, precision: computePrecision)
+  required init(device: MTLDevice, param: ConvAddBatchNormReluParam<P>, initContext: InitContext) {
+    param.output.initTexture(device: device, inTranspose: [0, 2, 3, 1], computePrecision: GlobalConfig.shared.computePrecision)
+    param.filter.initBuffer(device: device, precision: GlobalConfig.shared.computePrecision)
+    param.y.initBuffer(device: device, precision: GlobalConfig.shared.computePrecision)
     param.variance.initBuffer(device: device, precision: .Float32)
     param.mean.initBuffer(device: device, precision: .Float32)
     param.scale.initBuffer(device: device, precision: .Float32)
     param.bias.initBuffer(device: device, precision: .Float32)
     
-    if computePrecision == .Float32 {
+    if GlobalConfig.shared.computePrecision == .Float32 {
       if param.filter.width == 1 && param.filter.height == 1 {
-        super.init(device: device, inFunctionName: "conv_add_batch_norm_relu_1x1")
+        super.init(device: device, inFunctionName: "conv_add_batch_norm_relu_1x1", initContext: initContext)
       } else if param.filter.channel == 1 {
-        super.init(device: device, inFunctionName: "depthwise_conv_add_batch_norm_relu_3x3")
+        super.init(device: device, inFunctionName: "depthwise_conv_add_batch_norm_relu_3x3", initContext: initContext)
       } else if param.filter.width == 3 && param.filter.height == 3 {
-        super.init(device: device, inFunctionName: "conv_add_batch_norm_relu_3x3")
+        super.init(device: device, inFunctionName: "conv_add_batch_norm_relu_3x3", initContext: initContext)
       } else {
         fatalError(" unsupport ")
       }
-    } else if computePrecision == .Float16 {
+    } else if GlobalConfig.shared.computePrecision == .Float16 {
       if param.filter.width == 1 && param.filter.height == 1 {
-        super.init(device: device, inFunctionName: "conv_add_batch_norm_relu_1x1_half")
+        super.init(device: device, inFunctionName: "conv_add_batch_norm_relu_1x1_half", initContext: initContext)
       } else if param.filter.channel == 1 {
-        super.init(device: device, inFunctionName: "depthwise_conv_add_batch_norm_relu_3x3_half")
+        super.init(device: device, inFunctionName: "depthwise_conv_add_batch_norm_relu_3x3_half", initContext: initContext)
       } else if param.filter.width == 3 && param.filter.height == 3 {
-        super.init(device: device, inFunctionName: "conv_add_batch_norm_relu_3x3_half")
+        super.init(device: device, inFunctionName: "conv_add_batch_norm_relu_3x3_half", initContext: initContext)
       } else {
         fatalError(" unsupport ")
       }
@@ -120,10 +120,10 @@ class ConvAddBatchNormReluKernel<P: PrecisionType>: Kernel, Computable, Testable
     var newBiaseBuffer: MTLBuffer
     var newScaleBuffer: MTLBuffer
     
-    if computePrecision == .Float32 {
+    if GlobalConfig.shared.computePrecision == .Float32 {
       newBiaseBuffer = device.makeBuffer(bytes: newBiase, length: param.bias.buffer.length)!
       newScaleBuffer = device.makeBuffer(bytes: newScale, length: param.scale.buffer.length)!
-    } else if computePrecision == .Float16 {
+    } else if GlobalConfig.shared.computePrecision == .Float16 {
       
       newBiaseBuffer = device.makeBuffer(length: param.bias.buffer.length / 2)!
       newScaleBuffer = device.makeBuffer(length: param.bias.buffer.length / 2)!

metal/paddle-mobile/paddle-mobile/Operators/Kernels/ConvAddKernel.swift → metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/ConvAddKernel.swift

@@ -16,37 +16,37 @@ import Foundation
 
 class ConvAddKernel<P: PrecisionType>: Kernel, Computable {
   var metalParam: MetalConvParam!
-  required init(device: MTLDevice, param: ConvAddParam<P>) {
-    param.output.initTexture(device: device, inTranspose: [0, 2, 3, 1], computePrecision: computePrecision)
+  required init(device: MTLDevice, param: ConvAddParam<P>, initContext: InitContext) {
+    param.output.initTexture(device: device, inTranspose: [0, 2, 3, 1], computePrecision: GlobalConfig.shared.computePrecision)
     let padWhenOneC = !(param.filter.channel == 1 && param.filter.n == param.input.tensorDim[1])
-    param.filter.initBuffer(device: device, precision: computePrecision, padWhenOneC: padWhenOneC)
-    param.y.initBuffer(device: device, precision: computePrecision)
+    param.filter.initBuffer(device: device, precision: GlobalConfig.shared.computePrecision, padWhenOneC: padWhenOneC)
+    param.y.initBuffer(device: device, precision: GlobalConfig.shared.computePrecision)
     
-    if computePrecision == .Float16 {
+    if GlobalConfig.shared.computePrecision == .Float16 {
       if param.filter.width == 1 && param.filter.height == 1 {
-        super.init(device: device, inFunctionName: "conv_add_1x1_half")
+        super.init(device: device, inFunctionName: "conv_add_1x1_half", initContext: initContext)
       } else if param.filter.channel == 1 && param.filter.n == param.input.tensorDim[1] {
-        super.init(device: device, inFunctionName: "depthwise_conv_add_3x3_half")
+        super.init(device: device, inFunctionName: "depthwise_conv_add_3x3_half", initContext: initContext)
       } else if param.filter.width == 3 && param.filter.height == 3 {
-        super.init(device: device, inFunctionName: "conv_add_3x3_half")
+        super.init(device: device, inFunctionName: "conv_add_3x3_half", initContext: initContext)
       } else if param.filter.width == 1 && param.filter.height == 5 {
-        super.init(device: device, inFunctionName: "conv_add_5x1_half")
+        super.init(device: device, inFunctionName: "conv_add_5x1_half", initContext: initContext)
       } else if param.filter.width == 5 && param.filter.height == 1 {
-        super.init(device: device, inFunctionName: "conv_add_1x5_half")
+        super.init(device: device, inFunctionName: "conv_add_1x5_half", initContext: initContext)
       } else {
         fatalError(" unsupport yet ")
       }
-    } else if computePrecision == .Float32 {
+    } else if GlobalConfig.shared.computePrecision == .Float32 {
       if param.filter.width == 1 && param.filter.height == 1 {
-        super.init(device: device, inFunctionName: "conv_add_1x1")
+        super.init(device: device, inFunctionName: "conv_add_1x1", initContext: initContext)
       } else if param.filter.channel == 1 && param.filter.n == param.input.tensorDim[1] {
-        super.init(device: device, inFunctionName: "depthwise_conv_add_3x3")
+        super.init(device: device, inFunctionName: "depthwise_conv_add_3x3", initContext: initContext)
       } else if param.filter.width == 1 && param.filter.height == 5 {
-        super.init(device: device, inFunctionName: "conv_add_5x1")
+        super.init(device: device, inFunctionName: "conv_add_5x1", initContext: initContext)
       } else if param.filter.width == 5 && param.filter.height == 1 {
-        super.init(device: device, inFunctionName: "conv_add_1x5")
+        super.init(device: device, inFunctionName: "conv_add_1x5", initContext: initContext)
       } else if param.filter.width == 3 && param.filter.height == 3 {
-        super.init(device: device, inFunctionName: "conv_add_3x3")
+        super.init(device: device, inFunctionName: "conv_add_3x3", initContext: initContext)
       } else {
         fatalError(" unsupport yet ")
       }

metal/paddle-mobile/paddle-mobile/Operators/Kernels/ConvAddPreluKernel.swift → metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/ConvAddPreluKernel.swift

@@ -16,99 +16,99 @@ import Foundation
 
 class ConvAddPreluKernel<P: PrecisionType>: Kernel, Computable {
   var metalParam: MetalConvParam!
-  required init(device: MTLDevice, param: ConvAddPreluParam<P>) {
-    param.output.initTexture(device: device, inTranspose: [0, 2, 3, 1], computePrecision: computePrecision)
-    param.filter.initBuffer(device: device, precision: computePrecision)
-    param.y.initBuffer(device: device, precision: computePrecision)
-    param.alpha.initBuffer(device: device, precision: computePrecision)
+  required init(device: MTLDevice, param: ConvAddPreluParam<P>, initContext: InitContext) {
+    param.output.initTexture(device: device, inTranspose: [0, 2, 3, 1], computePrecision: GlobalConfig.shared.computePrecision)
+    param.filter.initBuffer(device: device, precision: GlobalConfig.shared.computePrecision)
+    param.y.initBuffer(device: device, precision: GlobalConfig.shared.computePrecision)
+    param.alpha.initBuffer(device: device, precision: GlobalConfig.shared.computePrecision)
 
-    if computePrecision == .Float16 {
+    if GlobalConfig.shared.computePrecision == .Float16 {
       if param.filter.width == 1 && param.filter.height == 1 {
         if param.mode == "channel" {
-          super.init(device: device, inFunctionName: "conv_add_1x1_prelu_channel_half")
+          super.init(device: device, inFunctionName: "conv_add_1x1_prelu_channel_half", initContext: initContext)
         } else if param.mode == "element" {
-          super.init(device: device, inFunctionName: "conv_add_1x1_prelu_element_half")
+          super.init(device: device, inFunctionName: "conv_add_1x1_prelu_element_half", initContext: initContext)
         } else {
-          super.init(device: device, inFunctionName: "conv_add_1x1_prelu_other_half")
+          super.init(device: device, inFunctionName: "conv_add_1x1_prelu_other_half", initContext: initContext)
         }
         
       } else if param.filter.channel == 1 {
         if param.mode == "channel" {
-          super.init(device: device, inFunctionName: "depthwise_conv_add_3x3_prelu_channel_half")
+          super.init(device: device, inFunctionName: "depthwise_conv_add_3x3_prelu_channel_half", initContext: initContext)
         } else if param.mode == "element" {
-          super.init(device: device, inFunctionName: "depthwise_conv_add_3x3_prelu_element_half")
+          super.init(device: device, inFunctionName: "depthwise_conv_add_3x3_prelu_element_half", initContext: initContext)
         } else {
-          super.init(device: device, inFunctionName: "depthwise_conv_add_3x3_prelu_other_half")
+          super.init(device: device, inFunctionName: "depthwise_conv_add_3x3_prelu_other_half", initContext: initContext)
         }
       } else if param.filter.width == 3 && param.filter.height == 3 {
         if param.mode == "channel" {
-          super.init(device: device, inFunctionName: "conv_add_3x3_prelu_channel_half")
+          super.init(device: device, inFunctionName: "conv_add_3x3_prelu_channel_half", initContext: initContext)
         } else if param.mode == "element" {
-          super.init(device: device, inFunctionName: "conv_add_3x3_prelu_element_half")
+          super.init(device: device, inFunctionName: "conv_add_3x3_prelu_element_half", initContext: initContext)
         } else {
-          super.init(device: device, inFunctionName: "conv_add_3x3_prelu_other_half")
+          super.init(device: device, inFunctionName: "conv_add_3x3_prelu_other_half", initContext: initContext)
         }
         
       } else if param.filter.width == 1 && param.filter.height == 5 {
         if param.mode == "channel" {
-          super.init(device: device, inFunctionName: "conv_add_5x1_prelu_channel_half")
+          super.init(device: device, inFunctionName: "conv_add_5x1_prelu_channel_half", initContext: initContext)
         } else if param.mode == "element" {
-          super.init(device: device, inFunctionName: "conv_add_5x1_prelu_element_half")
+          super.init(device: device, inFunctionName: "conv_add_5x1_prelu_element_half", initContext: initContext)
         } else {
-          super.init(device: device, inFunctionName: "conv_add_5x1_prelu_other_half")
+          super.init(device: device, inFunctionName: "conv_add_5x1_prelu_other_half", initContext: initContext)
         }
       } else if param.filter.width == 5 && param.filter.height == 1 {
         if param.mode == "channel" {
-          super.init(device: device, inFunctionName: "conv_add_1x5_prelu_channel_half")
+          super.init(device: device, inFunctionName: "conv_add_1x5_prelu_channel_half", initContext: initContext)
         } else if param.mode == "element" {
-          super.init(device: device, inFunctionName: "conv_add_1x5_prelu_element_half")
+          super.init(device: device, inFunctionName: "conv_add_1x5_prelu_element_half", initContext: initContext)
         } else {
-          super.init(device: device, inFunctionName: "conv_add_1x5_prelu_other_half")
+          super.init(device: device, inFunctionName: "conv_add_1x5_prelu_other_half", initContext: initContext)
         }
       } else {
         fatalError(" unsupport yet ")
       }
-    } else if computePrecision == .Float32 {
+    } else if GlobalConfig.shared.computePrecision == .Float32 {
       if param.filter.width == 1 && param.filter.height == 1 {
         if param.mode == "channel" {
-          super.init(device: device, inFunctionName: "conv_add_1x1_prelu_channel_float")
+          super.init(device: device, inFunctionName: "conv_add_1x1_prelu_channel_float", initContext: initContext)
         } else if param.mode == "element" {
-          super.init(device: device, inFunctionName: "conv_add_1x1_prelu_element_float")
+          super.init(device: device, inFunctionName: "conv_add_1x1_prelu_element_float", initContext: initContext)
         } else {
-          super.init(device: device, inFunctionName: "conv_add_1x1_prelu_other_float")
+          super.init(device: device, inFunctionName: "conv_add_1x1_prelu_other_float", initContext: initContext)
         }
       } else if param.filter.channel == 1 {
         if param.mode == "channel" {
-          super.init(device: device, inFunctionName: "depthwise_conv_add_3x3_prelu_channel_float")
+          super.init(device: device, inFunctionName: "depthwise_conv_add_3x3_prelu_channel_float", initContext: initContext)
         } else if param.mode == "element" {
-          super.init(device: device, inFunctionName: "depthwise_conv_add_3x3_prelu_element_float")
+          super.init(device: device, inFunctionName: "depthwise_conv_add_3x3_prelu_element_float", initContext: initContext)
         } else {
-          super.init(device: device, inFunctionName: "depthwise_conv_add_3x3_prelu_other_float")
+          super.init(device: device, inFunctionName: "depthwise_conv_add_3x3_prelu_other_float", initContext: initContext)
         }
       } else if param.filter.width == 3 && param.filter.height == 3 {
         if param.mode == "channel" {
-          super.init(device: device, inFunctionName: "conv_add_3x3_prelu_channel_float")
+          super.init(device: device, inFunctionName: "conv_add_3x3_prelu_channel_float", initContext: initContext)
         } else if param.mode == "element" {
-          super.init(device: device, inFunctionName: "conv_add_3x3_prelu_element_float")
+          super.init(device: device, inFunctionName: "conv_add_3x3_prelu_element_float", initContext: initContext)
         } else {
-          super.init(device: device, inFunctionName: "conv_add_3x3_prelu_other_float")
+          super.init(device: device, inFunctionName: "conv_add_3x3_prelu_other_float", initContext: initContext)
         }
         
       } else if param.filter.width == 1 && param.filter.height == 5 {
         if param.mode == "channel" {
-          super.init(device: device, inFunctionName: "conv_add_5x1_prelu_channel_float")
+          super.init(device: device, inFunctionName: "conv_add_5x1_prelu_channel_float", initContext: initContext)
         } else if param.mode == "element" {
-          super.init(device: device, inFunctionName: "conv_add_5x1_prelu_element_float")
+          super.init(device: device, inFunctionName: "conv_add_5x1_prelu_element_float", initContext: initContext)
         } else {
-          super.init(device: device, inFunctionName: "conv_add_5x1_prelu_other_float")
+          super.init(device: device, inFunctionName: "conv_add_5x1_prelu_other_float", initContext: initContext)
         }
       } else if param.filter.width == 5 && param.filter.height == 1 {
         if param.mode == "channel" {
-          super.init(device: device, inFunctionName: "conv_add_1x5_prelu_channel_float")
+          super.init(device: device, inFunctionName: "conv_add_1x5_prelu_channel_float", initContext: initContext)
         } else if param.mode == "element" {
-          super.init(device: device, inFunctionName: "conv_add_1x5_prelu_element_float")
+          super.init(device: device, inFunctionName: "conv_add_1x5_prelu_element_float", initContext: initContext)
         } else {
-          super.init(device: device, inFunctionName: "conv_add_1x5_prelu_other_float")
+          super.init(device: device, inFunctionName: "conv_add_1x5_prelu_other_float", initContext: initContext)
         }
       } else {
         fatalError(" unsupport yet ")

metal/paddle-mobile/paddle-mobile/Operators/Kernels/ConvBNReluKernel.swift → metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/ConvBNReluKernel.swift

@@ -38,44 +38,44 @@ struct ConvBNReluTestParam: TestParam {
 }
 
 class ConvBNReluKernel<P: PrecisionType>: Kernel, Computable, Testable {
-  required init(device: MTLDevice, testParam: ConvBNReluTestParam) {
+  required init(device: MTLDevice, testParam: ConvBNReluTestParam, initContext: InitContext) {
     if testParam.filterSize.width == 1 && testParam.filterSize.height == 1 {
-      super.init(device: device, inFunctionName: "conv_batch_norm_relu_1x1")
+      super.init(device: device, inFunctionName: "conv_batch_norm_relu_1x1", initContext: initContext)
     } else if testParam.filterSize.channel == 1 {
-      super.init(device: device, inFunctionName: "depthwise_conv_batch_norm_relu_3x3")
+      super.init(device: device, inFunctionName: "depthwise_conv_batch_norm_relu_3x3", initContext: initContext)
     } else {
-      super.init(device: device, inFunctionName: "conv_batch_norm_relu_3x3")
+      super.init(device: device, inFunctionName: "conv_batch_norm_relu_3x3", initContext: initContext)
     }
   }
   
   var metalParam: MetalConvParam!
 
-  required init(device: MTLDevice, param: ConvBNReluParam<P>) {
+  required init(device: MTLDevice, param: ConvBNReluParam<P>, initContext: InitContext) {
     
-    param.output.initTexture(device: device, inTranspose: [0, 2, 3, 1], computePrecision: computePrecision)
-    param.filter.initBuffer(device: device, precision: computePrecision)
+    param.output.initTexture(device: device, inTranspose: [0, 2, 3, 1], computePrecision: GlobalConfig.shared.computePrecision)
+    param.filter.initBuffer(device: device, precision: GlobalConfig.shared.computePrecision)
     param.variance.initBuffer(device: device, precision: .Float32)
     param.mean.initBuffer(device: device, precision: .Float32)
     param.scale.initBuffer(device: device, precision: .Float32)
     param.bias.initBuffer(device: device, precision: .Float32)
     
-    if computePrecision == .Float32 {
+    if GlobalConfig.shared.computePrecision == .Float32 {
       if param.filter.width == 1 && param.filter.height == 1 {
-        super.init(device: device, inFunctionName: "conv_batch_norm_relu_1x1")
+        super.init(device: device, inFunctionName: "conv_batch_norm_relu_1x1", initContext: initContext)
       } else if param.filter.channel == 1 {
-        super.init(device: device, inFunctionName: "depthwise_conv_batch_norm_relu_3x3")
+        super.init(device: device, inFunctionName: "depthwise_conv_batch_norm_relu_3x3", initContext: initContext)
       } else if param.filter.width == 3 && param.filter.height == 3 {
-        super.init(device: device, inFunctionName: "conv_batch_norm_relu_3x3")
+        super.init(device: device, inFunctionName: "conv_batch_norm_relu_3x3", initContext: initContext)
       } else {
         fatalError(" unsupport ")
       }
-    } else if computePrecision == .Float16 {
+    } else if GlobalConfig.shared.computePrecision == .Float16 {
       if param.filter.width == 1 && param.filter.height == 1 {
-        super.init(device: device, inFunctionName: "conv_batch_norm_relu_1x1_half")
+        super.init(device: device, inFunctionName: "conv_batch_norm_relu_1x1_half", initContext: initContext)
       } else if param.filter.channel == 1 {
-        super.init(device: device, inFunctionName: "depthwise_conv_batch_norm_relu_3x3_half")
+        super.init(device: device, inFunctionName: "depthwise_conv_batch_norm_relu_3x3_half", initContext: initContext)
       } else if param.filter.width == 3 && param.filter.height == 3 {
-        super.init(device: device, inFunctionName: "conv_batch_norm_relu_3x3_half")
+        super.init(device: device, inFunctionName: "conv_batch_norm_relu_3x3_half", initContext: initContext)
       } else {
         fatalError(" unsupport ")
       }
@@ -122,10 +122,10 @@ class ConvBNReluKernel<P: PrecisionType>: Kernel, Computable, Testable {
     var newBiaseBuffer: MTLBuffer
     var newScaleBuffer: MTLBuffer
     
-    if computePrecision == .Float32 {
+    if GlobalConfig.shared.computePrecision == .Float32 {
       newBiaseBuffer = device.makeBuffer(bytes: newBiase, length: param.bias.buffer.length)!
       newScaleBuffer = device.makeBuffer(bytes: newScale, length: param.scale.buffer.length)!
-    } else if computePrecision == .Float16 {
+    } else if GlobalConfig.shared.computePrecision == .Float16 {
       
       newBiaseBuffer = device.makeBuffer(length: param.bias.buffer.length / 2)!
       newScaleBuffer = device.makeBuffer(length: param.bias.buffer.length / 2)!

metal/paddle-mobile/paddle-mobile/Operators/Kernels/ConvKernel.swift → metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/ConvKernel.swift

@@ -26,14 +26,14 @@ public struct MetalConvParam {
 
 class ConvKernel<P: PrecisionType>: Kernel, Computable {
   var metalParam: MetalConvParam!
-  required init(device: MTLDevice, param: ConvParam<P>) {
+  required init(device: MTLDevice, param: ConvParam<P>, initContext: InitContext) {
     param.filter.initBuffer(device: device, precision: ComputePrecision.Float32)
     if param.filter.width == 1 && param.filter.height == 1 {
-      super.init(device: device, inFunctionName: "conv_1x1")
+      super.init(device: device, inFunctionName: "conv_1x1", initContext: initContext)
     } else if param.filter.channel == 1 {
-      super.init(device: device, inFunctionName: "depthwise_conv_3x3")
+      super.init(device: device, inFunctionName: "depthwise_conv_3x3", initContext: initContext)
     } else if param.filter.width == 3 && param.filter.height == 3 {
-      super.init(device: device, inFunctionName: "conv_3x3")
+      super.init(device: device, inFunctionName: "conv_3x3", initContext: initContext)
     } else {
       fatalError(" unsupport ")
     }

metal/paddle-mobile/paddle-mobile/Operators/Kernels/ConvTransposeKernel.swift → metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/ConvTransposeKernel.swift

@@ -30,18 +30,18 @@ struct MetalConvTransposeParam {
 
 class ConvTransposeKernel<P: PrecisionType>: Kernel, Computable{
   var metalParam: MetalConvTransposeParam!
-  required init(device: MTLDevice, param: ConvTransposeParam<P>) {
-    param.output.initTexture(device: device, inTranspose: param.input.transpose, computePrecision: computePrecision)
-    param.filter.initBuffer(device: device, precision: computePrecision, convertToNHWC: false, withTranspose: true)
-    if computePrecision == .Float32 {
+  required init(device: MTLDevice, param: ConvTransposeParam<P>, initContext: InitContext) {
+    param.output.initTexture(device: device, inTranspose: param.input.transpose, computePrecision: GlobalConfig.shared.computePrecision)
+    param.filter.initBuffer(device: device, precision: GlobalConfig.shared.computePrecision, convertToNHWC: false, withTranspose: true)
+    if GlobalConfig.shared.computePrecision == .Float32 {
       if param.stride == [2, 2] && param.stride == [2, 2] {
-        super.init(device: device, inFunctionName: "conv_transpose2x2_stride2")
+        super.init(device: device, inFunctionName: "conv_transpose2x2_stride2", initContext: initContext)
       } else {
         fatalError(" -- conv transpose unsupported yet -- ")
       }
-    } else if computePrecision == .Float16 {
+    } else if GlobalConfig.shared.computePrecision == .Float16 {
       if param.stride == [2, 2] && param.stride == [2, 2] {
-        super.init(device: device, inFunctionName: "conv_transpose2x2_stride2_half")
+        super.init(device: device, inFunctionName: "conv_transpose2x2_stride2_half", initContext: initContext)
       } else {
         fatalError(" -- conv transpose unsupported yet -- ")
       }

metal/paddle-mobile/paddle-mobile/Operators/Kernels/ElementwiseAddKernel.swift → metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/ElementwiseAddKernel.swift

@@ -26,8 +26,8 @@ struct ElementwiseAddMetalParam {
 
 class ElementwiseAddKernel<P: PrecisionType>: Kernel, Computable {
   var metalParam: ElementwiseAddMetalParam
-  required init(device: MTLDevice, param: ElementwiseAddParam<P>) {
-    param.output.initTexture(device: device, inTranspose: param.inputX.transpose, computePrecision: computePrecision)
+  required init(device: MTLDevice, param: ElementwiseAddParam<P>, initContext: InitContext) {
+    param.output.initTexture(device: device, inTranspose: param.inputX.transpose, computePrecision: GlobalConfig.shared.computePrecision)
     
     metalParam = ElementwiseAddMetalParam.init()
     
@@ -50,10 +50,10 @@ class ElementwiseAddKernel<P: PrecisionType>: Kernel, Computable {
       //      print("===> elementwise_add fast!!!")
       metalParam.fast = 1
     }
-    if computePrecision == .Float32 {
-      super.init(device: device, inFunctionName: "elementwise_add")
-    } else if computePrecision == .Float16 {
-      super.init(device: device, inFunctionName: "elementwise_add_half")
+    if GlobalConfig.shared.computePrecision == .Float32 {
+      super.init(device: device, inFunctionName: "elementwise_add", initContext: initContext)
+    } else if GlobalConfig.shared.computePrecision == .Float16 {
+      super.init(device: device, inFunctionName: "elementwise_add_half", initContext: initContext)
     } else {
       fatalError()
     }

metal/paddle-mobile/paddle-mobile/Operators/Kernels/ElementwiseAddPreluKernel.swift → metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/ElementwiseAddPreluKernel.swift

@@ -17,9 +17,9 @@ import Foundation
 
 class ElementwiseAddPreluKernel<P: PrecisionType>: Kernel, Computable {
   var metalParam: ElementwiseAddMetalParam
-  required init(device: MTLDevice, param: ElementwiseAddPreluParam<P>) {
-    param.output.initTexture(device: device, inTranspose: param.inputX.transpose, computePrecision: computePrecision)
-    param.alpha.initBuffer(device: device, precision: computePrecision)
+  required init(device: MTLDevice, param: ElementwiseAddPreluParam<P>, initContext: InitContext) {
+    param.output.initTexture(device: device, inTranspose: param.inputX.transpose, computePrecision: GlobalConfig.shared.computePrecision)
+    param.alpha.initBuffer(device: device, precision: GlobalConfig.shared.computePrecision)
    
     metalParam = ElementwiseAddMetalParam.init()
     
@@ -43,21 +43,21 @@ class ElementwiseAddPreluKernel<P: PrecisionType>: Kernel, Computable {
       metalParam.fast = 1
     }
     
-    if computePrecision == .Float32 {
+    if GlobalConfig.shared.computePrecision == .Float32 {
       if param.mode == "channel" {
-        super.init(device: device, inFunctionName: "elementwise_add_channel_float")
+        super.init(device: device, inFunctionName: "elementwise_add_channel_float", initContext: initContext)
       } else if param.mode == "element" {
-        super.init(device: device, inFunctionName: "elementwise_add_element_float")
+        super.init(device: device, inFunctionName: "elementwise_add_element_float", initContext: initContext)
       } else {
-        super.init(device: device, inFunctionName: "elementwise_add_prelu_float")
+        super.init(device: device, inFunctionName: "elementwise_add_prelu_float", initContext: initContext)
       }
-    } else if computePrecision == .Float16 {
+    } else if GlobalConfig.shared.computePrecision == .Float16 {
       if param.mode == "channel" {
-        super.init(device: device, inFunctionName: "elementwise_add_channel_half")
+        super.init(device: device, inFunctionName: "elementwise_add_channel_half", initContext: initContext)
       } else if param.mode == "element" {
-        super.init(device: device, inFunctionName: "elementwise_add_channel_half")
+        super.init(device: device, inFunctionName: "elementwise_add_channel_half", initContext: initContext)
       } else {
-        super.init(device: device, inFunctionName: "elementwise_add_channel_half")
+        super.init(device: device, inFunctionName: "elementwise_add_channel_half", initContext: initContext)
       }
     } else {
       fatalError()

metal/paddle-mobile/paddle-mobile/Operators/Kernels/FlattenKernel.swift → metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/FlattenKernel.swift

@@ -26,8 +26,8 @@ class FlattenKernel<P: PrecisionType>: Kernel, Computable{
   
   var metalParam: FlattenMetalParam
   
-  required init(device: MTLDevice, param: FlattenParam<P>) {
-    param.output.initTexture(device: device, computePrecision: computePrecision)
+  required init(device: MTLDevice, param: FlattenParam<P>, initContext: InitContext) {
+    param.output.initTexture(device: device, computePrecision: GlobalConfig.shared.computePrecision)
     var id: [Int32] = [1, 1, 1, 1]
     for i in 0..<param.input.tensorDim.cout() {
       id[4-param.input.tensorDim.cout()+i] = Int32(param.input.tensorDim[i])
@@ -47,10 +47,10 @@ class FlattenKernel<P: PrecisionType>: Kernel, Computable{
     let irank = param.input.tensorDim.cout()
     let orank = param.output.tensorDim.cout()
     assert(orank == 2)
-    if computePrecision == .Float32 {
-      super.init(device: device, inFunctionName: "reshape_\(irank)_2_float")
-    } else if computePrecision == .Float16 {
-      super.init(device: device, inFunctionName: "reshape_\(irank)_2_half")
+    if GlobalConfig.shared.computePrecision == .Float32 {
+      super.init(device: device, inFunctionName: "reshape_\(irank)_2_float", initContext: initContext)
+    } else if GlobalConfig.shared.computePrecision == .Float16 {
+      super.init(device: device, inFunctionName: "reshape_\(irank)_2_half", initContext: initContext)
     } else {
       fatalError()
     }

metal/paddle-mobile/paddle-mobile/Operators/Kernels/MulticlassNMSKernel.swift → metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/MulticlassNMSKernel.swift

@@ -17,16 +17,16 @@ import Foundation
 class MulticlassNMSKernel<P: PrecisionType>: Kernel, Computable{
   let pipline1: MTLComputePipelineState
 
-  required init(device: MTLDevice, param: MulticlassNMSParam<P>) {
+  required init(device: MTLDevice, param: MulticlassNMSParam<P>, initContext: InitContext) {
     
     param.middleOutput.initBuffer(device: device)
     param.bboxOutput.initBuffer(device: device)
-    if computePrecision == .Float32 {
-      pipline1 = device.pipeLine(funcName: "nms_fetch_bbox", inPaddleMobileLib: true)
-      super.init(device: device, inFunctionName: "nms_fetch_result")
-    } else if computePrecision == .Float16 {
-      pipline1 = device.pipeLine(funcName: "nms_fetch_bbox_half", inPaddleMobileLib: true)
-      super.init(device: device, inFunctionName: "nms_fetch_result_half")
+    if GlobalConfig.shared.computePrecision == .Float32 {
+      pipline1 = device.pipeLine(funcName: "nms_fetch_bbox", metalLoadMode: initContext.metalLoadMode, metalLibPath: initContext.metalLibPath)
+      super.init(device: device, inFunctionName: "nms_fetch_result", initContext: initContext)
+    } else if GlobalConfig.shared.computePrecision == .Float16 {
+      pipline1 = device.pipeLine(funcName: "nms_fetch_bbox_half", metalLoadMode: initContext.metalLoadMode, metalLibPath: initContext.metalLibPath)
+      super.init(device: device, inFunctionName: "nms_fetch_result_half", initContext: initContext)
     } else {
       fatalError( " unsupport precision " )
     }

metal/paddle-mobile/paddle-mobile/Operators/Kernels/PoolKernel.swift → metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/PoolKernel.swift

@@ -26,8 +26,8 @@ struct PoolMetalParam {
 
 class PoolKernel<P: PrecisionType>: Kernel, Computable{
   var metalParam: PoolMetalParam
-  required init(device: MTLDevice, param: PoolParam<P>) {
-    param.output.initTexture(device: device, inTranspose: param.input.transpose, computePrecision: computePrecision)
+  required init(device: MTLDevice, param: PoolParam<P>, initContext: InitContext) {
+    param.output.initTexture(device: device, inTranspose: param.input.transpose, computePrecision: GlobalConfig.shared.computePrecision)
     
     var poolType: Int32
     switch param.poolType {
@@ -48,10 +48,10 @@ class PoolKernel<P: PrecisionType>: Kernel, Computable{
       poolType: poolType
     )
     
-    if computePrecision == .Float32 {
-      super.init(device: device, inFunctionName: "pool_float")
-    } else if computePrecision == .Float16 {
-      super.init(device: device, inFunctionName: "pool_half")
+    if GlobalConfig.shared.computePrecision == .Float32 {
+      super.init(device: device, inFunctionName: "pool_float", initContext: initContext)
+    } else if GlobalConfig.shared.computePrecision == .Float16 {
+      super.init(device: device, inFunctionName: "pool_half", initContext: initContext)
     } else {
       fatalError()
     }

metal/paddle-mobile/paddle-mobile/Operators/Kernels/PreluKernel.swift → metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/PreluKernel.swift

@@ -15,24 +15,24 @@
 import Foundation
 
 class PreluKernel<P: PrecisionType>: Kernel, Computable{
-  required init(device: MTLDevice, param: PreluParam<P>) {
-    param.alpha.initBuffer(device: device, precision: computePrecision)
-    param.output.initTexture(device: device, inTranspose: param.input.transpose, computePrecision: computePrecision)
-    if computePrecision == .Float32 {
+  required init(device: MTLDevice, param: PreluParam<P>, initContext: InitContext) {
+    param.alpha.initBuffer(device: device, precision: GlobalConfig.shared.computePrecision)
+    param.output.initTexture(device: device, inTranspose: param.input.transpose, computePrecision: GlobalConfig.shared.computePrecision)
+    if GlobalConfig.shared.computePrecision == .Float32 {
       if param.mode == "channel" {
-        super.init(device: device, inFunctionName: "prelu_channel")
+        super.init(device: device, inFunctionName: "prelu_channel", initContext: initContext)
       } else if param.mode == "element" {
-        super.init(device: device, inFunctionName: "prelu_element")
+        super.init(device: device, inFunctionName: "prelu_element", initContext: initContext)
       } else {
-        super.init(device: device, inFunctionName: "prelu_other")
+        super.init(device: device, inFunctionName: "prelu_other", initContext: initContext)
       }
-    } else if computePrecision == .Float16 {
+    } else if GlobalConfig.shared.computePrecision == .Float16 {
       if param.mode == "channel" {
-        super.init(device: device, inFunctionName: "prelu_channel_half")
+        super.init(device: device, inFunctionName: "prelu_channel_half", initContext: initContext)
       } else if param.mode == "element" {
-        super.init(device: device, inFunctionName: "prelu_element_half")
+        super.init(device: device, inFunctionName: "prelu_element_half", initContext: initContext)
       } else {
-        super.init(device: device, inFunctionName: "prelu_other_half")
+        super.init(device: device, inFunctionName: "prelu_other_half", initContext: initContext)
       }
     } else {
       fatalError()

metal/paddle-mobile/paddle-mobile/Operators/Kernels/PriorBoxKernel.swift → metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/PriorBoxKernel.swift

@@ -32,29 +32,28 @@ struct PriorBoxMetalParam {
 class PriorBoxKernel<P: PrecisionType>: Kernel, Computable{
   var metalParam: PriorBoxMetalParam!
   
-  required init(device: MTLDevice, param: PriorBoxParam<P>) {
+  required init(device: MTLDevice, param: PriorBoxParam<P>, initContext: InitContext) {
     
     let originDim = param.output.tensorDim;
     
     param.output.tensorDim = Dim.init(inDim: [1, originDim[0], originDim[1], originDim[2] * originDim[3]])
     param.output.padToFourDim = Dim.init(inDim: [1, originDim[0], originDim[1], originDim[2] * originDim[3]])
     
-    param.output.initTexture(device: device, inTranspose: [0, 1, 2, 3], computePrecision: computePrecision)
-    param.outputVariances.initTexture(device: device, inTranspose: [2, 0, 1, 3], computePrecision: computePrecision)
+    param.output.initTexture(device: device, inTranspose: [0, 1, 2, 3], computePrecision: GlobalConfig.shared.computePrecision)
+    param.outputVariances.initTexture(device: device, inTranspose: [2, 0, 1, 3], computePrecision: GlobalConfig.shared.computePrecision)
     
-    
-    if computePrecision == .Float32 {
+    if GlobalConfig.shared.computePrecision == .Float32 {
       if param.min_max_aspect_ratios_order {
-        super.init(device: device, inFunctionName: "prior_box_MinMaxAspectRatiosOrder")
+        super.init(device: device, inFunctionName: "prior_box_MinMaxAspectRatiosOrder", initContext: initContext)
       } else {
-        super.init(device: device, inFunctionName: "prior_box")
+        super.init(device: device, inFunctionName: "prior_box", initContext: initContext)
       }
       
-    } else if computePrecision == .Float16 {
+    } else if GlobalConfig.shared.computePrecision == .Float16 {
       if param.min_max_aspect_ratios_order {
-        super.init(device: device, inFunctionName: "prior_box_MinMaxAspectRatiosOrder_half")
+        super.init(device: device, inFunctionName: "prior_box_MinMaxAspectRatiosOrder_half", initContext: initContext)
       } else {
-        super.init(device: device, inFunctionName: "prior_box_half")
+        super.init(device: device, inFunctionName: "prior_box_half", initContext: initContext)
       }
     } else {
       fatalError()
@@ -105,12 +104,12 @@ class PriorBoxKernel<P: PrecisionType>: Kernel, Computable{
       }
     }
     
-    if computePrecision == .Float16 {
+    if GlobalConfig.shared.computePrecision == .Float16 {
       let buffer = device.makeBuffer(length: outputAspectRatior.count * MemoryLayout<Float16>.size)
       float32ToFloat16(input: &outputAspectRatior, output:(buffer?.contents())!, count: outputAspectRatior.count)
       param.newAspectRatios = buffer
 
-    } else if computePrecision == .Float32 {
+    } else if GlobalConfig.shared.computePrecision == .Float32 {
       let buffer = device.makeBuffer(bytes: outputAspectRatior, length: outputAspectRatior.count * MemoryLayout<Float32>.size, options: [])
       param.newAspectRatios = buffer
     } else {

metal/paddle-mobile/paddle-mobile/Operators/Kernels/ReluKernel.swift → metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/ReluKernel.swift

@@ -25,11 +25,11 @@ class ReluKernel<P: PrecisionType>: Kernel, Computable{
     encoder.endEncoding()
   }
   
-  required init(device: MTLDevice, param: ReluParam<P>) {
-    if computePrecision == .Float32 {
-      super.init(device: device, inFunctionName: "relu")
-    } else if computePrecision == .Float16 {
-      super.init(device: device, inFunctionName: "relu_half")
+  required init(device: MTLDevice, param: ReluParam<P>, initContext: InitContext) {
+    if GlobalConfig.shared.computePrecision == .Float32 {
+      super.init(device: device, inFunctionName: "relu", initContext: initContext)
+    } else if GlobalConfig.shared.computePrecision == .Float16 {
+      super.init(device: device, inFunctionName: "relu_half", initContext: initContext)
     } else {
       fatalError()
     }

metal/paddle-mobile/paddle-mobile/Operators/Kernels/ReshapeKernel.swift → metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/ReshapeKernel.swift

@@ -31,8 +31,8 @@ class ReshapeKernel<P: PrecisionType>: Kernel, Computable{
   
   var metalParam: ReshapeMetalParam
   
-  required init(device: MTLDevice, param: ReshapeParam<P>) {
-    param.output.initTexture(device: device, computePrecision: computePrecision)
+  required init(device: MTLDevice, param: ReshapeParam<P>, initContext: InitContext) {
+    param.output.initTexture(device: device, computePrecision: GlobalConfig.shared.computePrecision)
     var id: [Int32] = [1, 1, 1, 1]
     for i in 0..<param.input.tensorDim.cout() {
       id[4-param.input.tensorDim.cout()+i] = Int32(param.input.tensorDim[i])
@@ -51,23 +51,23 @@ class ReshapeKernel<P: PrecisionType>: Kernel, Computable{
     )
     let irank = param.input.tensorDim.cout()
     let orank = param.output.tensorDim.cout()
-    if computePrecision == .Float32 {
-      super.init(device: device, inFunctionName: "reshape_\(irank)_\(orank)_float")
-    } else if computePrecision == .Float16 {
-      super.init(device: device, inFunctionName: "reshape_\(irank)_\(orank)_half")
+    if GlobalConfig.shared.computePrecision == .Float32 {
+      super.init(device: device, inFunctionName: "reshape_\(irank)_\(orank)_float", initContext: initContext)
+    } else if GlobalConfig.shared.computePrecision == .Float16 {
+      super.init(device: device, inFunctionName: "reshape_\(irank)_\(orank)_half", initContext: initContext)
     } else {
       fatalError()
     }
   }
   
-  required init(device: MTLDevice, testParam: ReshapeTestParam) {
+  required init(device: MTLDevice, testParam: ReshapeTestParam, initContext: InitContext) {
     metalParam = ReshapeMetalParam.init(
     idim: (0, 0, 0, 0),
     itrans: (0, 0, 0, 0),
     odim: (0, 0, 0, 0),
     otrans: (0, 0, 0, 0)
     )
-    super.init(device: device, inFunctionName: "reshape")
+    super.init(device: device, inFunctionName: "reshape", initContext: initContext)
   }
   
   func compute(commandBuffer: MTLCommandBuffer, param: ReshapeParam<P>) throws {

metal/paddle-mobile/paddle-mobile/Operators/Kernels/ResizeBilinearKernel.swift → metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/ResizeBilinearKernel.swift

@@ -20,6 +20,17 @@ struct ResizeBilinearMetalParam {
 }
 
 class ResizeBilinearKernel<P: PrecisionType>: Kernel, Computable{
+  required init(device: MTLDevice, param: ResizeBilinearParam<P>, initContext: InitContext) {
+    param.output.initTexture(device: device, inTranspose: param.input.transpose, computePrecision: GlobalConfig.shared.computePrecision)
+    if GlobalConfig.shared.computePrecision == .Float32 {
+      super.init(device: device, inFunctionName: "resize_bilinear", initContext: initContext)
+    } else if GlobalConfig.shared.computePrecision == .Float16 {
+      super.init(device: device, inFunctionName: "resize_bilinear_half", initContext: initContext)
+    } else {
+      fatalError()
+    }
+  }
+  
   func compute(commandBuffer: MTLCommandBuffer, param: ResizeBilinearParam<P>) throws {
     guard let encoder = commandBuffer.makeComputeCommandEncoder() else {
       throw PaddleMobileError.predictError(message: " encode is nil")
@@ -35,15 +46,6 @@ class ResizeBilinearKernel<P: PrecisionType>: Kernel, Computable{
     encoder.endEncoding()
   }
   
-  required init(device: MTLDevice, param: ResizeBilinearParam<P>) {
-    param.output.initTexture(device: device, inTranspose: param.input.transpose, computePrecision: computePrecision)
-    if computePrecision == .Float32 {
-      super.init(device: device, inFunctionName: "resize_bilinear")
-    } else if computePrecision == .Float16 {
-      super.init(device: device, inFunctionName: "resize_bilinear_half")
-    } else {
-      fatalError()
-    }
-  }
+
   
 }

metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/Scale.swift

+//
+//  Scale.swift
+//  paddle-mobile
+//
+//  Created by liuRuiLong on 2019/1/4.
+//  Copyright © 2019 orange. All rights reserved.
+//
+
+import Foundation
+
+class ScaleKernel: CusomKernel {
+  init(device: MTLDevice, shape: Shape, metalLoadMode: MetalLoadMode, metalLibPath: String?) {
+    if GlobalConfig.shared.computePrecision == .Float32 {
+      super.init(device: device, inFunctionName: "scale", outputDim: shape, metalLoadModel: metalLoadMode, metalLibPath: metalLibPath)
+    } else if GlobalConfig.shared.computePrecision == .Float16 {
+      super.init(device: device, inFunctionName: "scale_half", outputDim: shape, metalLoadModel: metalLoadMode, metalLibPath: metalLibPath)
+    } else {
+      fatalError(" unsupport ")
+    }
+  }
+}
+

metal/paddle-mobile/paddle-mobile/Operators/Kernels/ShapeKernel.swift → metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/ShapeKernel.swift

@@ -28,12 +28,12 @@ class ShapeKernel<P: PrecisionType>: Kernel, Computable{
 //    encoder.endEncoding()
   }
   
-  required init(device: MTLDevice, param: ShapeParam<P>) {
-    param.output.initTexture(device: device, computePrecision: computePrecision)
-    if computePrecision == .Float32 {
-      super.init(device: device, inFunctionName: "shape")
-    } else if computePrecision == .Float16 {
-      super.init(device: device, inFunctionName: "shape_half")
+  required init(device: MTLDevice, param: ShapeParam<P>, initContext: InitContext) {
+    param.output.initTexture(device: device, computePrecision: GlobalConfig.shared.computePrecision)
+    if GlobalConfig.shared.computePrecision == .Float32 {
+      super.init(device: device, inFunctionName: "shape", initContext: initContext)
+    } else if GlobalConfig.shared.computePrecision == .Float16 {
+      super.init(device: device, inFunctionName: "shape_half", initContext: initContext)
     } else {
       fatalError()
     }

metal/paddle-mobile/paddle-mobile/Operators/Kernels/SoftmaxKernel.swift → metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/SoftmaxKernel.swift

@@ -22,16 +22,16 @@ struct SoftmaxMetalParam {
 class SoftmaxKernel<P: PrecisionType>: Kernel, Computable{
   
   var metalParam: SoftmaxMetalParam
-  required init(device: MTLDevice, param: SoftmaxParam<P>) {
-    param.output.initTexture(device: device, computePrecision: computePrecision)
+  required init(device: MTLDevice, param: SoftmaxParam<P>, initContext: InitContext) {
+    param.output.initTexture(device: device, computePrecision: GlobalConfig.shared.computePrecision)
     metalParam = SoftmaxMetalParam.init(
       N: Int32(param.input.tensorDim[0]),
       K: Int32(param.input.tensorDim[1])
     )
-    if computePrecision == .Float32 {
-      super.init(device: device, inFunctionName: "softmax_float")
-    } else if computePrecision == .Float16 {
-      super.init(device: device, inFunctionName: "softmax_half")
+    if GlobalConfig.shared.computePrecision == .Float32 {
+      super.init(device: device, inFunctionName: "softmax_float", initContext: initContext)
+    } else if GlobalConfig.shared.computePrecision == .Float16 {
+      super.init(device: device, inFunctionName: "softmax_half", initContext: initContext)
     } else {
       fatalError()
     }

metal/paddle-mobile/paddle-mobile/Operators/Kernels/SplitKernel.swift → metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/SplitKernel.swift

@@ -37,13 +37,13 @@ class SplitKernel<P: PrecisionType>: Kernel, Computable{
     encoder.endEncoding()
   }
   
-  required init(device: MTLDevice, param: SplitParam<P>) {
+  required init(device: MTLDevice, param: SplitParam<P>, initContext: InitContext) {
     //     param.output.initTexture(device: device, computePrecision: computePrecision)
     let num = param.outputList.count
     let rank = param.input.tensorDim.cout()
     assert(num >= 2 && num <= 4)
     for output in param.outputList {
-      output.initTexture(device: device, inTranspose: param.input.transpose, computePrecision: computePrecision)
+      output.initTexture(device: device, inTranspose: param.input.transpose, computePrecision: GlobalConfig.shared.computePrecision)
     }
     smp = SplitMetalParam.init()
     smp.idim = (Int32(param.input.dim[0]), Int32(param.input.dim[1]), Int32(param.input.dim[2]), Int32(param.input.dim[3]))
@@ -81,10 +81,10 @@ class SplitKernel<P: PrecisionType>: Kernel, Computable{
     if v == "normal" {
       fatalError("split unsupported")
     }
-    if computePrecision == .Float32 {
-      super.init(device: device, inFunctionName: "split_\(rank)_\(num)_\(v)_float")
-    } else if computePrecision == .Float16 {
-      super.init(device: device, inFunctionName: "split_\(rank)_\(num)_\(v)_half")
+    if GlobalConfig.shared.computePrecision == .Float32 {
+      super.init(device: device, inFunctionName: "split_\(rank)_\(num)_\(v)_float", initContext: initContext)
+    } else if GlobalConfig.shared.computePrecision == .Float16 {
+      super.init(device: device, inFunctionName: "split_\(rank)_\(num)_\(v)_half", initContext: initContext)
     } else {
       fatalError()
     }

metal/paddle-mobile/paddle-mobile/Operators/Kernels/Texture2DTo2DArrayKernel.swift → metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/Texture2DTo2DArrayKernel.swift

@@ -33,12 +33,12 @@ class Texture2DTo2DArrayKernel<P: PrecisionType>: Kernel, Computable{
     encoder.endEncoding()
   }
   
-  required init(device: MTLDevice, param: FeedParam<P>) {
-    param.output.initTexture(device: device, inTranspose: [0, 2, 3, 1], computePrecision: computePrecision)
-    if computePrecision == .Float16 {
-      super.init(device: device, inFunctionName: "texture2d_to_2d_array_half")
-    } else if computePrecision == .Float32 {
-      super.init(device: device, inFunctionName: "texture2d_to_2d_array")
+  required init(device: MTLDevice, param: FeedParam<P>, initContext: InitContext) {
+    param.output.initTexture(device: device, inTranspose: [0, 2, 3, 1], computePrecision: GlobalConfig.shared.computePrecision)
+    if GlobalConfig.shared.computePrecision == .Float16 {
+      super.init(device: device, inFunctionName: "texture2d_to_2d_array_half", initContext: initContext)
+    } else if GlobalConfig.shared.computePrecision == .Float32 {
+      super.init(device: device, inFunctionName: "texture2d_to_2d_array", initContext: initContext)
     } else {
       fatalError()
     }

metal/paddle-mobile/paddle-mobile/Operators/Kernels/TransposeKernel.swift → metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/TransposeKernel.swift

@@ -22,8 +22,8 @@ struct TransposeMetalParam {
 
 class TransposeKernel<P: PrecisionType>: Kernel, Computable {
   var metalParam: TransposeMetalParam = TransposeMetalParam.init()
-  required init(device: MTLDevice, param: TransposeParam<P>) {
-    param.output.initTexture(device: device, computePrecision: computePrecision)
+  required init(device: MTLDevice, param: TransposeParam<P>, initContext: InitContext) {
+    param.output.initTexture(device: device, computePrecision: GlobalConfig.shared.computePrecision)
     let rank = param.input.tensorDim.cout()
     var axis: [Int] = [0, 1, 2, 3]
     for i in 0..<param.axis.count {
@@ -43,13 +43,13 @@ class TransposeKernel<P: PrecisionType>: Kernel, Computable {
     metalParam.oC = Int32(param.output.dim[3])
     metalParam.axis = (Int32(naxis[0]), Int32(naxis[1]), Int32(naxis[2]), Int32(naxis[3]))
     var kernelFunc = "transpose_undefined"
-    if computePrecision == .Float16 {
+    if GlobalConfig.shared.computePrecision == .Float16 {
       if param.input.transpose == axis {
         kernelFunc = "transpose_copy_half"
       } else {
         kernelFunc = "transpose_\(rank)_half"
       }
-    } else if computePrecision == .Float32 {
+    } else if GlobalConfig.shared.computePrecision == .Float32 {
       if param.input.transpose == axis {
         kernelFunc = "transpose_copy_float"
       } else {
@@ -60,7 +60,7 @@ class TransposeKernel<P: PrecisionType>: Kernel, Computable {
     }
     print("===========>", kernelFunc)
     print(metalParam)
-    super.init(device: device, inFunctionName: kernelFunc)
+    super.init(device: device, inFunctionName: kernelFunc, initContext: initContext)
   }
   
   func compute(commandBuffer: MTLCommandBuffer, param: TransposeParam<P>) throws {

metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/metal/BatchNormKernel.metal

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+ 
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+ 
+ http://www.apache.org/licenses/LICENSE-2.0
+ 
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
+
+#include <metal_stdlib>
+using namespace metal;
+
+kernel void batchnorm(texture2d_array<float, access::read> inTexture [[texture(0)]],
+                      texture2d_array<float, access::write> outTexture [[texture(1)]],
+                      const device float4 * nscale [[buffer(0)]],
+                      const device float4 * nbias [[buffer(1)]],
+                      uint3 gid [[thread_position_in_grid]]) {
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) return;
+  const float4 input = inTexture.read(gid.xy, gid.z);
+  float4 output = input * nscale[gid.z] + nbias[gid.z];
+  outTexture.write(output, gid.xy, gid.z);
+}
+
+kernel void batchnorm_half(texture2d_array<half, access::read> inTexture [[texture(0)]],
+                      texture2d_array<half, access::write> outTexture [[texture(1)]],
+                      const device half4 * newScale [[buffer(0)]],
+                      const device half4 * newBias [[buffer(1)]],
+                      uint3 gid [[thread_position_in_grid]]) {
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) return;
+  const half4 input = inTexture.read(gid.xy, gid.z);
+  half4 output = input * newScale[gid.z] + newBias[gid.z];
+  outTexture.write(output, gid.xy, gid.z);
+}

metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/metal/BatchNormRelu.metal

+//
+//  BatchNormRelu.metal
+//  paddle-mobile
+//
+
+#include <metal_stdlib>
+using namespace metal;
+
+struct MetalConvParam {
+    short offsetX;
+    short offsetY;
+    short offsetZ;
+    ushort strideX;
+    ushort strideY;
+};
+
+kernel void batch_norm_relu_3x3(texture2d_array<float, access::sample> inTexture [[texture(0)]],
+                                         texture2d_array<float, access::write> outTexture [[texture(1)]],
+                                         const device float4 *new_scale [[buffer(0)]],
+                                         const device float4 *new_biase [[buffer(1)]],
+                                         uint3 gid [[thread_position_in_grid]]) {
+    
+    if (gid.x >= outTexture.get_width() ||
+        gid.y >= outTexture.get_height() ||
+        gid.z >= outTexture.get_array_size()) {
+        return;
+    }
+    
+    float4 input;
+    float4 output;
+    constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
+    input = inTexture.sample(sample, gid.x, gid.y, gid.z);
+    output = fmax(input * new_scale[gid.z] + new_biase[gid.z], 0.0);
+    outTexture.write(output, gid.xy, gid.z);
+
+}

metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/metal/BilinearInterp.inc.metal

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+ 
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+ 
+ http://www.apache.org/licenses/LICENSE-2.0
+ 
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
+
+#ifdef P
+
+#define CONCAT2(a, b) a ## b
+#define CONCAT2_(a, b) a ## _ ## b
+
+#define FUNC(f, p) CONCAT2_(f, p)
+#define VECTOR(p, n) CONCAT2(p, n)
+
+kernel void FUNC(bilinear_interp, P)(texture2d_array<P, access::read> input [[texture(0)]],
+                     texture2d_array<P, access::write> output [[texture(1)]],
+                     constant bilinear_interp_param & pm [[buffer(0)]],
+                     uint3 gid [[thread_position_in_grid]]) {
+  VECTOR(P, 4) r;
+  if ((input.get_width() == output.get_width()) && (input.get_height() == output.get_height())) {
+    r = input.read(gid.xy, gid.z);
+  } else {
+    P w = gid.x * pm.ratio_w;
+    P h = gid.y * pm.ratio_h;
+    uint w0 = w, h0 = h;
+    uint w1 = w0 + 1, h1 = h0 + 1;
+    P w1lambda = w - w0, h1lambda = h - h0;
+    P w2lambda = 1.0 - w1lambda, h2lambda = 1.0 - h1lambda;
+    if (w1 >= input.get_width()) w1 = w0;
+    if (h1 >= input.get_height()) h1 = h0;
+    VECTOR(P, 4) r0 = input.read(uint2(w0, h0), gid.z);
+    VECTOR(P, 4) r1 = input.read(uint2(w1, h0), gid.z);
+    VECTOR(P, 4) r2 = input.read(uint2(w0, h1), gid.z);
+    VECTOR(P, 4) r3 = input.read(uint2(w1, h1), gid.z);
+    r = h2lambda * (w2lambda * r0 + w1lambda * r1)
+      + h1lambda * (w2lambda * r2 + w1lambda * r3);
+  }
+  output.write(r, gid.xy, gid.z);
+}
+
+#endif

metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/metal/BilinearInterp.metal

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+ 
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+ 
+ http://www.apache.org/licenses/LICENSE-2.0
+ 
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
+
+#include <metal_stdlib>
+using namespace metal;
+
+struct bilinear_interp_param {
+  float ratio_h;
+  float ratio_w;
+};
+
+#define P float
+#include "BilinearInterp.inc.metal"
+#undef P
+
+#define P half
+#include "BilinearInterp.inc.metal"
+#undef P

metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/metal/BoxCoder.inc.metal

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+ 
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+ 
+ http://www.apache.org/licenses/LICENSE-2.0
+ 
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
+
+#ifdef P
+
+#define CONCAT2(a, b) a ## b
+#define CONCAT2_(a, b) a ## _ ## b
+
+#define FUNC(f, p) CONCAT2_(f, p)
+#define VECTOR(p, n) CONCAT2(p, n)
+kernel void FUNC(boxcoder, P)(texture2d_array<P, access::read> priorBox [[texture(0)]],
+                     texture2d_array<P, access::read> priorBoxVar [[texture(1)]],
+                     texture2d_array<P, access::read> targetBox [[texture(2)]],
+                     texture2d_array<P, access::write> output[[texture(3)]],
+                     uint3 gid [[thread_position_in_grid]]) {
+  VECTOR(P, 4) p = priorBox.read(uint2(0, gid.x), gid.z);
+  VECTOR(P, 4) pv = priorBoxVar.read(uint2(0, gid.x), gid.z);
+  VECTOR(P, 4) t;
+  t[0] = targetBox.read(uint2(0, gid.x), gid.z)[0];
+  t[1] = targetBox.read(uint2(1, gid.x), gid.z)[0];
+  t[2] = targetBox.read(uint2(2, gid.x), gid.z)[0];
+  t[3] = targetBox.read(uint2(3, gid.x), gid.z)[0];
+  
+  P px = (p.x + p.z) / 2;
+  P py = (p.y + p.w) / 2;
+  P pw = p.z - p.x;
+  P ph = p.w - p.y;
+  
+  P tx = pv.x * t.x * pw + px;
+  P ty = pv.y * t.y * ph + py;
+  P tw = exp(pv.z * t.z) * pw;
+  P th = exp(pv.w * t.w) * ph;
+  
+  VECTOR(P, 4) r;
+  r.x = tx - tw / 2;
+  r.y = ty - th / 2;
+  r.z = tx + tw / 2;
+  r.w = ty + th / 2;
+
+  output.write(r, gid.xy, gid.z);
+}
+
+#endif

metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/metal/BoxCoder.metal

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+ 
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+ 
+ http://www.apache.org/licenses/LICENSE-2.0
+ 
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
+
+#include <metal_stdlib>
+using namespace metal;
+
+#define P float
+#include "BoxCoder.inc.metal"
+#undef P
+#define P half
+#include "BoxCoder.inc.metal"
+#undef P

metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/metal/Common.metal

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+ 
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+ 
+ http://www.apache.org/licenses/LICENSE-2.0
+ 
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
+
+#include <metal_stdlib>
+using namespace metal;
+
+
+inline void xyzn2abcd_1(int xyzn[4], int abcd[4]) {
+  abcd[0] = abcd[1] = abcd[2] = 0;
+  abcd[3] = xyzn[0] * 4 + xyzn[3];
+}
+inline void xyzn2abcd_2(int xyzn[4], int abcd[4]) {
+  abcd[0] = abcd[1] = 0;
+  abcd[2] = xyzn[1];
+  abcd[3] = xyzn[0] * 4 + xyzn[3];
+}
+inline void xyzn2abcd_3(int xyzn[4], int abcd[4]) {
+  abcd[0] = 0;
+  abcd[3] = xyzn[0];
+  abcd[2] = xyzn[1];
+  abcd[1] = xyzn[2] * 4 + xyzn[3];
+}
+inline void xyzn2abcd_4(int C, int xyzn[4], int abcd[4]) {
+  abcd[2] = xyzn[0];
+  abcd[1] = xyzn[1];
+  uint t = xyzn[2] * 4 + xyzn[3];
+  abcd[0] = t / C;
+  abcd[3] = t % C;
+}
+
+inline void abcd2xyzn_1(int abcd[4], int xyzn[4]) {
+  xyzn[1] = xyzn[2] = 0;
+  xyzn[0] = abcd[3] / 4;
+  xyzn[1] = abcd[3] % 4;
+}
+inline void abcd2xyzn_2(int abcd[4], int xyzn[4]) {
+  xyzn[2] = 0;
+  xyzn[1] = abcd[2];
+  xyzn[0] = abcd[3] / 4;
+  xyzn[3] = abcd[3] % 4;
+}
+inline void abcd2xyzn_3(int abcd[4], int xyzn[4]) {
+  xyzn[0] = abcd[3];
+  xyzn[1] = abcd[2];
+  xyzn[2] = abcd[1] / 4;
+  xyzn[3] = abcd[1] % 4;
+}
+inline void abcd2xyzn_4(int C, int abcd[4], int xyzn[4]) {
+  xyzn[0] = abcd[2];
+  xyzn[1] = abcd[1];
+  uint t = abcd[0] * C + abcd[3];
+  xyzn[2] = t / 4;
+  xyzn[3] = t % 4;
+}
+
+inline void xyzn2abcd(int C, int xyzn[4], int abcd[4]) {
+  abcd[2] = xyzn[0];
+  abcd[1] = xyzn[1];
+  uint t = xyzn[2] * 4 + xyzn[3];
+  abcd[0] = t / C;
+  abcd[3] = t % C;
+}
+
+inline void abcd2xyzn(int C, int abcd[4], int xyzn[4]) {
+  xyzn[0] = abcd[2];
+  xyzn[1] = abcd[1];
+  uint t = abcd[0] * C + abcd[3];
+  xyzn[2] = t / 4;
+  xyzn[3] = t % 4;
+}
+
+inline int32_t abcd2index(int32_t dim[4], int32_t abcd[4]) {
+  int32_t r = abcd[0];
+  r = r * dim[1] + abcd[1];
+  r = r * dim[2] + abcd[2];
+  r = r * dim[3] + abcd[3];
+  return r;
+}
+
+inline void index2abcd(int32_t dim[4], int32_t ind, int32_t abcd[4]) {
+  abcd[3] = ind % dim[3]; ind /= dim[3];
+  abcd[2] = ind % dim[2]; ind /= dim[2];
+  abcd[1] = ind % dim[1]; ind /= dim[1];
+  abcd[0] = ind;
+}
+
+inline void trans(int32_t trans[4], int32_t ipos[4], int32_t opos[4]) {
+  for (int i = 0; i < 4; i++) {
+    opos[i] = ipos[trans[i]];
+  }
+}
+
+inline void invtrans(int32_t trans[4], int32_t ipos[4], int32_t opos[4]) {
+  for (int i = 0; i < 4; i++) {
+    opos[trans[i]] = ipos[i];
+  }
+}
+
+
+struct MetalConvParam {
+  short offsetX;
+  short offsetY;
+  short offsetZ;
+  ushort strideX;
+  ushort strideY;
+  ushort dilationX;
+  ushort dilationY;
+};
+

metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/metal/ConcatKernel.inc.metal

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+ 
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+ 
+ http://www.apache.org/licenses/LICENSE-2.0
+ 
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
+
+#ifdef P
+
+#define CONCAT2(a, b) a ## b
+#define CONCAT2_(a, b) a ## _ ## b
+#define CONCAT3_(a, b, c) a ## _ ## b ## _ ## c
+#define CONCAT4_(a, b, c, d) a ## _ ## b ## _ ## c ## _ ## d
+#define CONCAT5_(a, b, c, d, e) a ## _ ## b ## _ ## c ## _ ## d ## _ ## e
+
+#define FUNC(f, r, n, v, p) CONCAT5_(f, r, n, v, p)
+#define VECTOR(p, n) CONCAT2(p, n)
+#define FUNC_R(f, r) CONCAT2_(f, r)
+
+#if V == VX
+#define VV x
+#elif V == VY
+#define VV y
+#elif V == VZ
+#define VV z
+#else
+#define VV normal
+#endif
+
+#if V == VNORMAL
+//kernel void FUNC(concat, R, N, normal, P)(array<texture2d_array<P, access::read>, N> in [[texture(0)]],
+//                                     texture2d_array<P, access::read> out_x [[texture(N)]],
+//                                     texture2d_array<P, access::write> out [[texture(N+1)]],
+//                                     constant ConcatParam & pm [[buffer(0)]],
+//                                     uint3 gid [[thread_position_in_grid]]) {
+//}
+kernel void FUNC(concat, R, N, VV, P)(texture2d_array<P, access::read> in0 [[texture(0)]],
+                                          texture2d_array<P, access::read> in1 [[texture(1)]],
+#if N >= 3
+                                          texture2d_array<P, access::read> in2 [[texture(2)]],
+#endif
+#if N >= 4
+                                          texture2d_array<P, access::read> in3 [[texture(3)]],
+#endif
+#if N >= 5
+                                          texture2d_array<P, access::read> in4 [[texture(4)]],
+#endif
+#if N >= 6
+                                          texture2d_array<P, access::read> in5 [[texture(5)]],
+#endif
+                                          texture2d_array<P, access::read> inx [[texture(N)]],
+                                          texture2d_array<P, access::write> out [[texture(N+1)]],
+                                          constant ConcatParam & pm [[buffer(0)]],
+                                          uint3 gid [[thread_position_in_grid]]) {
+
+   ConcatParam cp = pm;
+   int xyzn[4] = {int(gid.x), int(gid.y), int(gid.z), 0}, abcd[4], oxyzn[4];
+   VECTOR(P, 4) r = inx.read(gid.xy, gid.z);
+   for (int i = 0; i < 4; i++) {
+     xyzn[3] = i;
+#if R == 4
+     xyzn2abcd_4(cp.odim[3], xyzn, abcd);
+#else
+     FUNC_R(xyzn2abcd, R)(xyzn, abcd);
+#endif
+     int k = abcd[cp.axis] - cp.offset;
+     if (k < 0) continue;
+     int j = 0;
+     for (; j < N; j++) {
+       if (k < cp.vdim[j]) {
+         break;
+       }
+       k -= cp.vdim[j];
+     }
+     if (j == N) {
+       continue;
+     }
+     int ta = cp.odim[cp.axis];
+     abcd[cp.axis] = k;
+     cp.odim[cp.axis] = cp.vdim[j];
+#if R == 4
+     abcd2xyzn_4(cp.odim[3], abcd, oxyzn);
+#else
+     FUNC_R(abcd2xyzn, R)(abcd, oxyzn);
+#endif
+     cp.odim[cp.axis] = ta;
+     switch (j) {
+       case 0: r[i] = in0.read(uint2(oxyzn[0], oxyzn[1]), oxyzn[2])[oxyzn[3]]; break;
+       case 1: r[i] = in1.read(uint2(oxyzn[0], oxyzn[1]), oxyzn[2])[oxyzn[3]]; break;
+#if N >= 3
+       case 2: r[i] = in2.read(uint2(oxyzn[0], oxyzn[1]), oxyzn[2])[oxyzn[3]]; break;
+#endif
+#if N >= 4
+       case 3: r[i] = in3.read(uint2(oxyzn[0], oxyzn[1]), oxyzn[2])[oxyzn[3]]; break;
+#endif
+#if N >= 5
+       case 4: r[i] = in4.read(uint2(oxyzn[0], oxyzn[1]), oxyzn[2])[oxyzn[3]]; break;
+#endif
+#if N >= 6
+       case 5: r[i] = in5.read(uint2(oxyzn[0], oxyzn[1]), oxyzn[2])[oxyzn[3]]; break;
+#endif
+     }
+   }
+   out.write(r, gid.xy, gid.z);
+}
+
+#endif // V == NORMAL
+
+
+
+#if V == VX
+kernel void FUNC(concat, R, N, VV, P)(texture2d_array<P, access::read> in0 [[texture(0)]],
+                                          texture2d_array<P, access::read> in1 [[texture(1)]],
+#if N >= 3
+                                          texture2d_array<P, access::read> in2 [[texture(2)]],
+#endif // N >= 3
+#if N >= 4
+                                          texture2d_array<P, access::read> in3 [[texture(3)]],
+#endif // N >= 4
+#if N >= 5
+                                          texture2d_array<P, access::read> in4 [[texture(4)]],
+#endif // N >= 5
+#if N >= 6
+                                          texture2d_array<P, access::read> in5 [[texture(5)]],
+#endif // N >= 6
+                                          texture2d_array<P, access::write> out [[texture(N)]],
+                                          constant ConcatParam & pm [[buffer(0)]],
+                                          uint3 gid [[thread_position_in_grid]]) {
+  int x = gid.x - pm.offset;
+  if (x < 0) return;
+  if (x < pm.vdim[0]) {
+    VECTOR(P, 4) r = in0.read(gid.xy, gid.z);
+    out.write(r, gid.xy, gid.z);
+    return;
+  }
+  x -= pm.vdim[0];
+  if (x < pm.vdim[1]) {
+    VECTOR(P, 4) r = in1.read(uint2(x, gid.y), gid.z);
+    out.write(r, gid.xy, gid.z);
+    return;
+  }
+#if N >= 3
+  x -= pm.vdim[1];
+  if (x < pm.vdim[2]) {
+    VECTOR(P, 4) r = in2.read(uint2(x, gid.y), gid.z);
+    out.write(r, gid.xy, gid.z);
+    return;
+  }
+#endif // N >= 3
+#if N >= 4
+  x -= pm.vdim[2];
+  if (x < pm.vdim[3]) {
+    VECTOR(P, 4) r = in3.read(uint2(x, gid.y), gid.z);
+    out.write(r, gid.xy, gid.z);
+    return;
+  }
+#endif // N >= 4
+#if N >= 5
+  x -= pm.vdim[3];
+  if (x < pm.vdim[4]) {
+    VECTOR(P, 4) r = in4.read(uint2(x, gid.y), gid.z);
+    out.write(r, gid.xy, gid.z);
+    return;
+  }
+#endif // N >= 5
+#if N >= 6
+  x -= pm.vdim[4];
+  if (x < pm.vdim[5]) {
+    VECTOR(P, 4) r = in5.read(uint2(x, gid.y), gid.z);
+    out.write(r, gid.xy, gid.z);
+    return;
+  }
+#endif // N >= 6
+}
+#endif // V == VX
+
+#if V == VY
+kernel void FUNC(concat, R, N, VV, P)(texture2d_array<P, access::read> in0 [[texture(0)]],
+                                      texture2d_array<P, access::read> in1 [[texture(1)]],
+#if N >= 3
+                                      texture2d_array<P, access::read> in2 [[texture(2)]],
+#endif // N >= 3
+#if N >= 4
+                                      texture2d_array<P, access::read> in3 [[texture(3)]],
+#endif // N >= 4
+#if N >= 5
+                                      texture2d_array<P, access::read> in4 [[texture(4)]],
+#endif // N >= 5
+#if N >= 6
+                                      texture2d_array<P, access::read> in5 [[texture(5)]],
+#endif // N >= 6
+                                      texture2d_array<P, access::write> out [[texture(N)]],
+                                      constant ConcatParam & pm [[buffer(0)]],
+                                      uint3 gid [[thread_position_in_grid]]) {
+  int y = gid.y - pm.offset;
+  if (y < 0) return;
+  if (y < pm.vdim[0]) {
+    VECTOR(P, 4)  r = in0.read(gid.xy, gid.z);
+    out.write(r, gid.xy, gid.z);
+    return;
+  }
+  y -= pm.vdim[0];
+  if (y < pm.vdim[1]) {
+    VECTOR(P, 4)  r = in1.read(uint2(gid.x, y), gid.z);
+    out.write(r, gid.xy, gid.z);
+    return;
+  }
+#if N >= 3
+  y -= pm.vdim[1];
+  if (y < pm.vdim[2]) {
+    VECTOR(P, 4)  r = in2.read(uint2(gid.x, y), gid.z);
+    out.write(r, gid.xy, gid.z);
+    return;
+  }
+#endif // N >= 3
+#if N >= 4
+  y -= pm.vdim[2];
+  if (y < pm.vdim[3]) {
+    VECTOR(P, 4)  r = in3.read(uint2(gid.x, y), gid.z);
+    out.write(r, gid.xy, gid.z);
+    return;
+  }
+#endif // N >= 4
+#if N >= 5
+  y -= pm.vdim[3];
+  if (y < pm.vdim[4]) {
+    VECTOR(P, 4)  r = in4.read(uint2(gid.x, y), gid.z);
+    out.write(r, gid.xy, gid.z);
+    return;
+  }
+#endif // N >= 5
+#if N >= 6
+  y -= pm.vdim[4];
+  if (y < pm.vdim[5]) {
+    VECTOR(P, 4)  r = in5.read(uint2(gid.x, y), gid.z);
+    out.write(r, gid.xy, gid.z);
+    return;
+  }
+#endif // N >= 6
+}
+#endif // V == VY
+
+#if V == VZ
+kernel void FUNC(concat, R, N, VV, P)(texture2d_array<P, access::read> in0 [[texture(0)]],
+                                      texture2d_array<P, access::read> in1 [[texture(1)]],
+#if N >= 3
+                                      texture2d_array<P, access::read> in2 [[texture(2)]],
+#endif // N >= 3
+#if N >= 4
+                                      texture2d_array<P, access::read> in3 [[texture(3)]],
+#endif // N >= 4
+#if N >= 5
+                                      texture2d_array<P, access::read> in4 [[texture(4)]],
+#endif // N >= 5
+#if N >= 6
+                                      texture2d_array<P, access::read> in5 [[texture(5)]],
+#endif // N >= 6
+                                      texture2d_array<P, access::write> out [[texture(N)]],
+                                      constant ConcatParam & pm [[buffer(0)]],
+                                      uint3 gid [[thread_position_in_grid]]) {
+  int z = gid.z - pm.offset;
+  if (z < 0) return;
+  if (z < pm.vdim[0]) {
+    VECTOR(P, 4) r = in0.read(gid.xy, gid.z);
+    out.write(r, gid.xy, gid.z);
+    return;
+  }
+  z -= pm.vdim[0];
+  if (z < pm.vdim[1]) {
+    VECTOR(P, 4)  r = in1.read(gid.xy, z);
+    out.write(r, gid.xy, gid.z);
+    return;
+  }
+#if N >= 3
+  z -= pm.vdim[1];
+  if (z < pm.vdim[2]) {
+    VECTOR(P, 4)  r = in2.read(gid.xy, z);
+    out.write(r, gid.xy, gid.z);
+    return;
+  }
+#endif // N >= 3
+#if N >= 4
+  z -= pm.vdim[2];
+  if (z < pm.vdim[3]) {
+    VECTOR(P, 4)  r = in3.read(gid.xy, z);
+    out.write(r, gid.xy, gid.z);
+    return;
+  }
+#endif // N >= 4
+#if N >= 5
+  z -= pm.vdim[3];
+  if (z < pm.vdim[4]) {
+    VECTOR(P, 4)  r = in4.read(gid.xy, z);
+    out.write(r, gid.xy, gid.z);
+    return;
+  }
+#endif // N >= 5
+#if N >= 6
+  z -= pm.vdim[4];
+  if (z < pm.vdim[5]) {
+    VECTOR(P, 4)  r = in5.read(gid.xy, z);
+    out.write(r, gid.xy, gid.z);
+    return;
+  }
+#endif // N >= 6
+}
+#endif // V == VZ
+
+
+#undef VV
+#endif // #ifdef P

metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/metal/ConcatKernel.metal

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+ 
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+ 
+ http://www.apache.org/licenses/LICENSE-2.0
+ 
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
+
+#include <metal_stdlib>
+#include "Common.metal"
+
+using namespace metal;
+
+struct ConcatParam {
+  int32_t odim[4];
+  int32_t axis;
+  int32_t offset;
+  int32_t trans[4];
+  int32_t vdim[6];
+};
+
+#define VNORMAL 1
+#define VX 2
+#define VY 3
+#define VZ 4
+
+// >> fast mode
+// only support concat_{2,3,4}_{2,3,4,5,6}_y_{float,half}
+// only support concat_{3,4}_{2,3,4,5,6}_x_{float,half}
+// only support concat_{1,2,3,4}_{2,3,4,5,6}_z_{float,half}
+// >> normal mode (loop mode)
+// ssd-ar: (R=4, N=3, V=z), (R=3, N=2, V=y), (R=2, N=5, V=x), (R=3, N=5, V=x)
+// ssd: (R=2, N=6, V=y), (R=3, N=6, V=y)
+// genet: (R=4, N=2, V=normal)
+
+// ssd-ar: (R=3, N=5, V=x)
+#define V VX
+  #define R 3
+    #define N 5
+      #define P float
+        #include "ConcatKernel.inc.metal"
+      #undef P
+      #define P half
+        #include "ConcatKernel.inc.metal"
+      #undef P
+    #undef N
+  #undef R
+#undef V
+
+// ssd-ar: (R=2, N=5, V=x)
+#define V VX
+  #define R 2
+    #define N 5
+      #define P float
+        #include "ConcatKernel.inc.metal"
+      #undef P
+      #define P half
+        #include "ConcatKernel.inc.metal"
+      #undef P
+    #undef N
+  #undef R
+#undef V
+
+
+// ssd-ar: (R=3, N=2, V=y)
+#define V VY
+  #define R 3
+    #define N 2
+      #define P float
+        #include "ConcatKernel.inc.metal"
+      #undef P
+      #define P half
+        #include "ConcatKernel.inc.metal"
+      #undef P
+    #undef N
+  #undef R
+#undef V
+
+// ssd-ar: (R=4, N=3, V=z)
+#define V VZ
+  #define R 4
+    #define N 3
+      #define P float
+        #include "ConcatKernel.inc.metal"
+      #undef P
+      #define P half
+        #include "ConcatKernel.inc.metal"
+      #undef P
+    #undef N
+  #undef R
+#undef V
+
+
+// ssd: (R=2, N=6, V=y)
+#define V VY
+  #define R 2
+    #define N 6
+      #define P float
+        #include "ConcatKernel.inc.metal"
+      #undef P
+      #define P half
+        #include "ConcatKernel.inc.metal"
+      #undef P
+    #undef N
+  #undef R
+#undef V
+
+// ssd: (R=3, N=6, V=y)
+#define V VY
+  #define R 3
+    #define N 6
+      #define P float
+        #include "ConcatKernel.inc.metal"
+      #undef P
+      #define P half
+        #include "ConcatKernel.inc.metal"
+      #undef P
+    #undef N
+  #undef R
+#undef V
+
+#define V VNORMAL
+  #define R 4
+    #define N 2
+      #define P float
+        #include "ConcatKernel.inc.metal"
+      #undef P
+      #define P half
+        #include "ConcatKernel.inc.metal"
+      #undef P
+    #undef N
+  #undef R
+#undef V
+
+
+#define V VY
+  #define R 2
+    #define N 2
+      #define P float
+        #include "ConcatKernel.inc.metal"
+      #undef P
+      #define P half
+        #include "ConcatKernel.inc.metal"
+      #undef P
+    #undef N
+  #undef R
+#undef V
+
+
+#define V VY
+  #define R 2
+    #define N 5
+      #define P float
+        #include "ConcatKernel.inc.metal"
+      #undef P
+      #define P half
+        #include "ConcatKernel.inc.metal"
+      #undef P
+    #undef N
+  #undef R
+#undef V
+
+
+
+

metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/metal/ConvAddBNReluKernel.metal

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+ 
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+ 
+ http://www.apache.org/licenses/LICENSE-2.0
+ 
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
+
+#include <metal_stdlib>
+#include "Common.metal"
+using namespace metal;
+
+
+kernel void conv_add_batch_norm_relu_1x1_half(
+            texture2d_array<half, access::sample> inTexture [[texture(0)]],
+            texture2d_array<half, access::write> outTexture [[texture(1)]],
+            constant MetalConvParam &param [[buffer(0)]],
+            const device half4 *weights [[buffer(1)]],
+            const device half4 *biase [[buffer(2)]],
+            const device half4 *new_scale [[buffer(3)]],
+            const device half4 *new_biase [[buffer(4)]],
+            uint3 gid [[thread_position_in_grid]]) {
+  
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) {
+    return;
+  }
+  
+  ushort2 stride = ushort2(param.strideX, param.strideY);
+  ushort2 posInInput = ushort2(gid.xy) * stride + ushort2(param.offsetX, param.offsetY);
+  
+  constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
+  const uint kernelHXW = 1;
+  
+  uint input_arr_size = inTexture.get_array_size();
+  uint weithTo = gid.z * kernelHXW * input_arr_size * 4;
+  
+  float4 output = float4(0.0);
+  
+  half4 input;
+  for (uint i = 0; i < input_arr_size; ++i) {
+    input = inTexture.sample(sample, float2(posInInput.x, posInInput.y), i);
+    half4 weight_x = weights[weithTo + 0 * kernelHXW * input_arr_size  + i];
+    output.x += dot(input, weight_x);
+    
+    half4 weight_y = weights[weithTo + 1 * kernelHXW * input_arr_size  + i];
+    output.y += dot(input, weight_y);
+    
+    half4 weight_z = weights[weithTo + 2 * kernelHXW * input_arr_size  + i];
+    output.z += dot(input, weight_z);
+    
+    half4 weight_w = weights[weithTo + 3 * kernelHXW * input_arr_size + i];
+    output.w += dot(input, weight_w);
+  }
+  output = fmax((output + float4(biase[gid.z])) * float4(new_scale[gid.z]) + float4(new_biase[gid.z]), 0.0);
+  outTexture.write(half4(output), gid.xy, gid.z);
+}
+
+kernel void conv_add_batch_norm_relu_3x3_half(
+            texture2d_array<half, access::sample> inTexture [[texture(0)]],
+            texture2d_array<half, access::write> outTexture [[texture(1)]],
+            constant MetalConvParam &param [[buffer(0)]],
+            const device half4 *weights [[buffer(1)]],
+            const device half4 *biase [[buffer(2)]],
+            const device half4 *new_scale [[buffer(3)]],
+            const device half4 *new_biase [[buffer(4)]],
+            uint3 gid [[thread_position_in_grid]]) {
+  
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) {
+    return;
+  }
+  
+  ushort2 stride = ushort2(param.strideX, param.strideY);
+  const ushort2 posInInput = ushort2(gid.xy) * stride + ushort2(param.offsetX, param.offsetY);
+  
+  constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
+  const uint kernelHXW = 9;
+  uint input_arr_size = inTexture.get_array_size();
+  uint weithTo = gid.z * kernelHXW * input_arr_size * 4;
+  
+  float4 output = float4(0.0);
+  
+  half4 input[9];
+  for (uint i = 0; i < input_arr_size; ++i) {
+    input[0] = inTexture.sample(sample, float2(posInInput.x - 1,    posInInput.y - 1), i);
+    input[1] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y - 1), i);
+    input[2] = inTexture.sample(sample, float2(posInInput.x + 1,    posInInput.y - 1), i);
+    input[3] = inTexture.sample(sample, float2(posInInput.x - 1,    posInInput.y), i);
+    input[4] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y), i);
+    input[5] = inTexture.sample(sample, float2(posInInput.x + 1,    posInInput.y), i);
+    input[6] = inTexture.sample(sample, float2(posInInput.x - 1,    posInInput.y + 1), i);
+    input[7] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y + 1), i);
+    input[8] = inTexture.sample(sample, float2(posInInput.x + 1,    posInInput.y + 1), i);
+    for (int j = 0; j < 9; ++j) {
+      half4 weight_x = weights[weithTo + 0 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.x += dot(input[j], weight_x);
+      
+      half4 weight_y = weights[weithTo + 1 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.y += dot(input[j], weight_y);
+      
+      half4 weight_z = weights[weithTo + 2 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.z += dot(input[j], weight_z);
+      
+      half4 weight_w = weights[weithTo + 3 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.w += dot(input[j], weight_w);
+    }
+  }
+  output = fmax((output + float4(biase[gid.z])) * float4(new_scale[gid.z]) + float4(new_biase[gid.z]), 0.0);
+  outTexture.write(half4(output), gid.xy, gid.z);
+}
+
+kernel void depthwise_conv_add_batch_norm_relu_3x3_half(
+            texture2d_array<half, access::sample> inTexture [[texture(0)]],
+            texture2d_array<half, access::write> outTexture [[texture(1)]],
+            constant MetalConvParam &param [[buffer(0)]],
+            const device half *weights [[buffer(1)]],
+            const device half4 *biase [[buffer(2)]],
+            const device half4 *new_scale [[buffer(3)]],
+            const device half4 *new_biase [[buffer(4)]],
+            uint3 gid [[thread_position_in_grid]]) {
+  
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) {
+    return;
+  }
+  uint output_slice = gid.z;
+  ushort2 stride = ushort2(param.strideX, param.strideY);
+  ushort2 posInInput = ushort2(gid.xy) * stride + ushort2(param.offsetX, param.offsetY);
+  constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
+  const uint kernelHXW = 9;
+  uint weithTo = gid.z * kernelHXW * 4;
+  float4 output = float4(0.0);
+  half4 inputs[9];
+  inputs[0] = inTexture.sample(sample, float2(posInInput.x - 1,    posInInput.y - 1), output_slice);
+  inputs[1] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y - 1), output_slice);
+  inputs[2] = inTexture.sample(sample, float2(posInInput.x + 1,    posInInput.y - 1), output_slice);
+  inputs[3] = inTexture.sample(sample, float2(posInInput.x - 1,    posInInput.y), output_slice);
+  inputs[4] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y), output_slice);
+  inputs[5] = inTexture.sample(sample, float2(posInInput.x + 1,    posInInput.y), output_slice);
+  inputs[6] = inTexture.sample(sample, float2(posInInput.x - 1,    posInInput.y + 1), output_slice);
+  inputs[7] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y + 1), output_slice);
+  inputs[8] = inTexture.sample(sample, float2(posInInput.x + 1,    posInInput.y + 1), output_slice);
+  for (int j = 0; j < 9; ++j) {
+    half4 input = inputs[j];
+    output.x += input.x * weights[weithTo + 0 * kernelHXW + j];
+    output.y += input.y * weights[weithTo + 1 * kernelHXW + j];
+    output.z += input.z * weights[weithTo + 2 * kernelHXW + j];
+    output.w += input.w * weights[weithTo + 3 * kernelHXW + j];
+  }
+  output = fmax((output + float4(biase[gid.z])) * float4(new_scale[gid.z]) + float4(new_biase[gid.z]), 0.0);
+  outTexture.write(half4(output), gid.xy, gid.z);
+}
+
+
+
+/*---------------------------------------------*/
+
+
+
+kernel void conv_add_batch_norm_relu_1x1(texture2d_array<float, access::sample> inTexture [[texture(0)]],
+                                         texture2d_array<float, access::write> outTexture [[texture(1)]],
+                                         constant MetalConvParam &param [[buffer(0)]],
+                                         const device float4 *weights [[buffer(1)]],
+                                         const device float4 *biase [[buffer(2)]],
+                                         const device float4 *new_scale [[buffer(3)]],
+                                         const device float4 *new_biase [[buffer(4)]],
+                                         uint3 gid [[thread_position_in_grid]]) {
+  
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) {
+    return;
+  }
+  
+  ushort2 stride = ushort2(param.strideX, param.strideY);
+  ushort2 posInInput = ushort2(gid.xy) * stride + ushort2(param.offsetX, param.offsetY);
+  
+  constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
+  const uint kernelHXW = 1;
+  
+  uint input_arr_size = inTexture.get_array_size();
+  uint weithTo = gid.z * kernelHXW * input_arr_size * 4;
+  
+  float4 output = float4(0.0);
+  
+  float4 input;
+  for (uint i = 0; i < input_arr_size; ++i) {
+    input = inTexture.sample(sample, float2(posInInput.x, posInInput.y), i);
+    float4 weight_x = weights[weithTo + 0 * kernelHXW * input_arr_size  + i];
+    output.x += dot(input, weight_x);
+    
+    float4 weight_y = weights[weithTo + 1 * kernelHXW * input_arr_size  + i];
+    output.y += dot(input, weight_y);
+    
+    float4 weight_z = weights[weithTo + 2 * kernelHXW * input_arr_size  + i];
+    output.z += dot(input, weight_z);
+    
+    float4 weight_w = weights[weithTo + 3 * kernelHXW * input_arr_size + i];
+    output.w += dot(input, weight_w);
+  }
+  output = fmax((output + biase[gid.z]) * new_scale[gid.z] + new_biase[gid.z], 0.0);
+  outTexture.write(output, gid.xy, gid.z);
+}
+
+kernel void conv_add_batch_norm_relu_3x3(texture2d_array<float, access::sample> inTexture [[texture(0)]],
+                                         texture2d_array<float, access::write> outTexture [[texture(1)]],
+                                         constant MetalConvParam &param [[buffer(0)]],
+                                         const device float4 *weights [[buffer(1)]],
+                                         const device float4 *biase [[buffer(2)]],
+                                         const device float4 *new_scale [[buffer(3)]],
+                                         const device float4 *new_biase [[buffer(4)]],
+                                         uint3 gid [[thread_position_in_grid]]) {
+  
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) {
+    return;
+  }
+  
+  ushort2 stride = ushort2(param.strideX, param.strideY);
+  const ushort2 posInInput = ushort2(gid.xy) * stride + ushort2(param.offsetX, param.offsetY);
+  
+  constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
+  const uint kernelHXW = 9;
+  uint input_arr_size = inTexture.get_array_size();
+  uint weithTo = gid.z * kernelHXW * input_arr_size * 4;
+  
+  float4 output = float4(0.0);
+  
+  float4 input[9];
+  for (uint i = 0; i < input_arr_size; ++i) {
+    input[0] = inTexture.sample(sample, float2(posInInput.x - 1,    posInInput.y - 1), i);
+    input[1] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y - 1), i);
+    input[2] = inTexture.sample(sample, float2(posInInput.x + 1,    posInInput.y - 1), i);
+    input[3] = inTexture.sample(sample, float2(posInInput.x - 1,    posInInput.y), i);
+    input[4] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y), i);
+    input[5] = inTexture.sample(sample, float2(posInInput.x + 1,    posInInput.y), i);
+    input[6] = inTexture.sample(sample, float2(posInInput.x - 1,    posInInput.y + 1), i);
+    input[7] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y + 1), i);
+    input[8] = inTexture.sample(sample, float2(posInInput.x + 1,    posInInput.y + 1), i);
+    for (int j = 0; j < 9; ++j) {
+      float4 weight_x = weights[weithTo + 0 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.x += dot(input[j], weight_x);
+      
+      float4 weight_y = weights[weithTo + 1 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.y += dot(input[j], weight_y);
+      
+      float4 weight_z = weights[weithTo + 2 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.z += dot(input[j], weight_z);
+      
+      float4 weight_w = weights[weithTo + 3 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.w += dot(input[j], weight_w);
+    }
+  }
+  output = fmax((output + biase[gid.z]) * new_scale[gid.z] + new_biase[gid.z], 0.0);
+  outTexture.write(output, gid.xy, gid.z);
+}
+
+kernel void depthwise_conv_add_batch_norm_relu_3x3(texture2d_array<float, access::sample> inTexture [[texture(0)]],
+                                                   texture2d_array<float, access::write> outTexture [[texture(1)]],
+                                                   constant MetalConvParam &param [[buffer(0)]],
+                                                   const device float *weights [[buffer(1)]],
+                                                   const device float4 *biase [[buffer(2)]],
+                                                   const device float4 *new_scale [[buffer(3)]],
+                                                   const device float4 *new_biase [[buffer(4)]],
+                                                   uint3 gid [[thread_position_in_grid]]) {
+  
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) {
+    return;
+  }
+  uint output_slice = gid.z;
+  ushort2 stride = ushort2(param.strideX, param.strideY);
+  ushort2 posInInput = ushort2(gid.xy) * stride + ushort2(param.offsetX, param.offsetY);
+  constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
+  const uint kernelHXW = 9;
+  uint weithTo = gid.z * kernelHXW * 4;
+  float4 output = float4(0.0);
+  float4 inputs[9];
+  inputs[0] = inTexture.sample(sample, float2(posInInput.x - 1,    posInInput.y - 1), output_slice);
+  inputs[1] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y - 1), output_slice);
+  inputs[2] = inTexture.sample(sample, float2(posInInput.x + 1,    posInInput.y - 1), output_slice);
+  inputs[3] = inTexture.sample(sample, float2(posInInput.x - 1,    posInInput.y), output_slice);
+  inputs[4] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y), output_slice);
+  inputs[5] = inTexture.sample(sample, float2(posInInput.x + 1,    posInInput.y), output_slice);
+  inputs[6] = inTexture.sample(sample, float2(posInInput.x - 1,    posInInput.y + 1), output_slice);
+  inputs[7] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y + 1), output_slice);
+  inputs[8] = inTexture.sample(sample, float2(posInInput.x + 1,    posInInput.y + 1), output_slice);
+  for (int j = 0; j < 9; ++j) {
+    float4 input = inputs[j];
+    output.x += input.x * weights[weithTo + 0 * kernelHXW + j];
+    output.y += input.y * weights[weithTo + 1 * kernelHXW + j];
+    output.z += input.z * weights[weithTo + 2 * kernelHXW + j];
+    output.w += input.w * weights[weithTo + 3 * kernelHXW + j];
+  }
+  output = fmax((output + biase[gid.z]) * new_scale[gid.z] + new_biase[gid.z], 0.0);
+  outTexture.write(output, gid.xy, gid.z);
+}
+

metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/metal/ConvAddMetal.metal

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+ 
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+ 
+ http://www.apache.org/licenses/LICENSE-2.0
+ 
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
+
+#include <metal_stdlib>
+#include "Common.metal"
+
+using namespace metal;
+
+#pragma mark - convAdd
+kernel void conv_add_1x1(texture2d_array<float, access::sample> inTexture [[texture(0)]],
+                         texture2d_array<float, access::write> outTexture [[texture(1)]],
+                         constant MetalConvParam &param [[buffer(0)]],
+                         const device float4 *weights [[buffer(1)]],
+                         const device float4 *biase [[buffer(2)]],
+                         uint3 gid [[thread_position_in_grid]]) {
+  
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) {
+    return;
+  }
+  
+  ushort2 stride = ushort2(param.strideX, param.strideY);
+  ushort2 posInInput = ushort2(gid.xy) * stride + ushort2(param.offsetX, param.offsetY);
+  
+  constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
+  const uint kernelHXW = 1;
+  
+  uint input_arr_size = inTexture.get_array_size();
+  uint weithTo = gid.z * kernelHXW * input_arr_size * 4;
+  
+  float4 output = biase[gid.z];
+  
+  float4 input;
+  for (uint i = 0; i < input_arr_size; ++i) {
+    input = inTexture.sample(sample, float2(posInInput.x, posInInput.y), i);
+    float4 weight_x = weights[weithTo + 0 * kernelHXW * input_arr_size  + i];
+    output.x += dot(input, weight_x);
+    
+    float4 weight_y = weights[weithTo + 1 * kernelHXW * input_arr_size  + i];
+    output.y += dot(input, weight_y);
+    
+    float4 weight_z = weights[weithTo + 2 * kernelHXW * input_arr_size  + i];
+    output.z += dot(input, weight_z);
+    
+    float4 weight_w = weights[weithTo + 3 * kernelHXW * input_arr_size + i];
+    output.w += dot(input, weight_w);
+  }
+//  output = output + biase[gid.z];
+  outTexture.write(output, gid.xy, gid.z);
+}
+
+kernel void conv_add_3x3(texture2d_array<float, access::sample> inTexture [[texture(0)]],
+                         texture2d_array<float, access::write> outTexture [[texture(1)]],
+                         constant MetalConvParam &param [[buffer(0)]],
+                         const device float4 *weights [[buffer(1)]],
+                         const device float4 *biase [[buffer(2)]],
+                         uint3 gid [[thread_position_in_grid]]) {
+  
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) {
+    return;
+  }
+  
+  ushort2 stride = ushort2(param.strideX, param.strideY);
+  const ushort2 posInInput = ushort2(gid.xy) * stride + ushort2(param.offsetX, param.offsetY);
+  
+  constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
+  
+  const uint kernelHXW = 9;
+  
+  uint input_arr_size = inTexture.get_array_size();
+  
+  uint weithTo = gid.z * kernelHXW * input_arr_size * 4;
+  
+  float4 output = biase[gid.z];
+  
+  ushort dilation_x = param.dilationX;
+  ushort dilation_y = param.dilationY;
+  
+  float4 input[9];
+  
+  for (uint i = 0; i < input_arr_size; ++i) {
+    input[0] = inTexture.sample(sample, float2(posInInput.x - dilation_x, posInInput.y - dilation_y), i);
+    
+    input[1] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y - dilation_y), i);
+    
+    input[2] = inTexture.sample(sample, float2(posInInput.x + dilation_x, posInInput.y - dilation_y), i);
+    
+    input[3] = inTexture.sample(sample, float2(posInInput.x - dilation_x,    posInInput.y), i);
+    
+    input[4] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y), i);
+    
+    input[5] = inTexture.sample(sample, float2(posInInput.x + dilation_x,    posInInput.y), i);
+    
+    input[6] = inTexture.sample(sample, float2(posInInput.x - dilation_x,    posInInput.y + dilation_y), i);
+    
+    input[7] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y + dilation_y), i);
+    
+    input[8] = inTexture.sample(sample, float2(posInInput.x + dilation_x,    posInInput.y + dilation_y), i);
+    
+    for (int j = 0; j < 9; ++j) {
+      float4 weight_x = weights[weithTo + 0 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.x += dot(input[j], weight_x);
+      
+      float4 weight_y = weights[weithTo + 1 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.y += dot(input[j], weight_y);
+      
+      float4 weight_z = weights[weithTo + 2 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.z += dot(input[j], weight_z);
+      
+      float4 weight_w = weights[weithTo + 3 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.w += dot(input[j], weight_w);
+    }
+  }
+//  output = output + biase[gid.z];
+  outTexture.write(output, gid.xy, gid.z);
+}
+
+kernel void conv_add_5x1(texture2d_array<float, access::sample> inTexture [[texture(0)]],
+                         texture2d_array<float, access::write> outTexture [[texture(1)]],
+                         constant MetalConvParam &param [[buffer(0)]],
+                         const device float4 *weights [[buffer(1)]],
+                         const device float4 *biase [[buffer(2)]],
+                         uint3 gid [[thread_position_in_grid]]) {
+  
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) {
+    return;
+  }
+  
+  ushort2 stride = ushort2(param.strideX, param.strideY);
+  const ushort2 posInInput = ushort2(gid.xy) * stride + ushort2(param.offsetX, param.offsetY);
+  
+  constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
+  
+  const uint kernelHXW = 5;
+  
+  uint input_arr_size = inTexture.get_array_size();
+  
+  uint weithTo = gid.z * kernelHXW * input_arr_size * 4;
+  
+  float4 output = biase[gid.z];
+  
+  ushort dilation_y = param.dilationY;
+  float4 input[5];
+  
+  for (uint i = 0; i < input_arr_size; ++i) {
+    input[0] = inTexture.sample(sample, float2(posInInput.x, posInInput.y - 2 * dilation_y), i);
+    
+    input[1] = inTexture.sample(sample, float2(posInInput.x, posInInput.y - dilation_y), i);
+    
+    input[2] = inTexture.sample(sample, float2(posInInput.x, posInInput.y), i);
+    
+    input[3] = inTexture.sample(sample, float2(posInInput.x, posInInput.y + dilation_y), i);
+    
+    input[4] = inTexture.sample(sample, float2(posInInput.x, posInInput.y + 2 * dilation_y), i);
+    
+    for (int j = 0; j < 5; ++j) {
+      float4 weight_x = weights[weithTo + 0 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.x += dot(input[j], weight_x);
+      
+      float4 weight_y = weights[weithTo + 1 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.y += dot(input[j], weight_y);
+      
+      float4 weight_z = weights[weithTo + 2 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.z += dot(input[j], weight_z);
+      
+      float4 weight_w = weights[weithTo + 3 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.w += dot(input[j], weight_w);
+    }
+  }
+//  output = output + biase[gid.z];
+  outTexture.write(output, gid.xy, gid.z);
+}
+
+
+kernel void conv_add_1x5(texture2d_array<float, access::sample> inTexture [[texture(0)]],
+                         texture2d_array<float, access::write> outTexture [[texture(1)]],
+                         constant MetalConvParam &param [[buffer(0)]],
+                         const device float4 *weights [[buffer(1)]],
+                         const device float4 *biase [[buffer(2)]],
+                         uint3 gid [[thread_position_in_grid]]) {
+  
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) {
+    return;
+  }
+  
+  ushort2 stride = ushort2(param.strideX, param.strideY);
+  const ushort2 posInInput = ushort2(gid.xy) * stride + ushort2(param.offsetX, param.offsetY);
+  
+  constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
+  
+  const uint kernelHXW = 5;
+  
+  uint input_arr_size = inTexture.get_array_size();
+  
+  uint weithTo = gid.z * kernelHXW * input_arr_size * 4;
+  
+  float4 output = biase[gid.z];
+  
+  ushort dilation_x = param.dilationX;
+  float4 input[5];
+  
+  for (uint i = 0; i < input_arr_size; ++i) {
+    input[0] = inTexture.sample(sample, float2(posInInput.x - 2 * dilation_x, posInInput.y), i);
+    
+    input[1] = inTexture.sample(sample, float2(posInInput.x - dilation_x, posInInput.y), i);
+    
+    input[2] = inTexture.sample(sample, float2(posInInput.x, posInInput.y), i);
+    
+    input[3] = inTexture.sample(sample, float2(posInInput.x + dilation_x, posInInput.y), i);
+    
+    input[4] = inTexture.sample(sample, float2(posInInput.x + 2 * dilation_x, posInInput.y), i);
+    
+    for (int j = 0; j < 5; ++j) {
+      float4 weight_x = weights[weithTo + 0 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.x += dot(input[j], weight_x);
+      
+      float4 weight_y = weights[weithTo + 1 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.y += dot(input[j], weight_y);
+      
+      float4 weight_z = weights[weithTo + 2 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.z += dot(input[j], weight_z);
+      
+      float4 weight_w = weights[weithTo + 3 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.w += dot(input[j], weight_w);
+    }
+  }
+//  output = output + biase[gid.z];
+  outTexture.write(output, gid.xy, gid.z);
+}
+
+
+kernel void depthwise_conv_add_3x3(texture2d_array<float, access::sample> inTexture [[texture(0)]],
+                                   texture2d_array<float, access::write> outTexture [[texture(1)]],
+                                   constant MetalConvParam &param [[buffer(0)]],
+                                   const device float *weights [[buffer(1)]],
+                                   const device float4 *biase [[buffer(2)]],
+                                   uint3 gid [[thread_position_in_grid]]) {
+  
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) {
+    return;
+  }
+  uint output_slice = gid.z;
+  ushort2 stride = ushort2(param.strideX, param.strideY);
+  ushort2 posInInput = ushort2(gid.xy) * stride + ushort2(param.offsetX, param.offsetY);
+  constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
+  const uint kernelHXW = 9;
+  uint weithTo = gid.z * kernelHXW * 4;
+  float4 output = biase[gid.z];
+  float4 inputs[9];
+  inputs[0] = inTexture.sample(sample, float2(posInInput.x - 1,    posInInput.y - 1), output_slice);
+  inputs[1] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y - 1), output_slice);
+  inputs[2] = inTexture.sample(sample, float2(posInInput.x + 1,    posInInput.y - 1), output_slice);
+  inputs[3] = inTexture.sample(sample, float2(posInInput.x - 1,    posInInput.y), output_slice);
+  inputs[4] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y), output_slice);
+  inputs[5] = inTexture.sample(sample, float2(posInInput.x + 1,    posInInput.y), output_slice);
+  inputs[6] = inTexture.sample(sample, float2(posInInput.x - 1,    posInInput.y + 1), output_slice);
+  inputs[7] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y + 1), output_slice);
+  inputs[8] = inTexture.sample(sample, float2(posInInput.x + 1,    posInInput.y + 1), output_slice);
+  for (int j = 0; j < 9; ++j) {
+    float4 input = inputs[j];
+    output.x += input.x * weights[weithTo + 0 * kernelHXW + j];
+    output.y += input.y * weights[weithTo + 1 * kernelHXW + j];
+    output.z += input.z * weights[weithTo + 2 * kernelHXW + j];
+    output.w += input.w * weights[weithTo + 3 * kernelHXW + j];
+  }
+//  output = output + biase[gid.z];
+  outTexture.write(output, gid.xy, gid.z);
+}
+
+
+#pragma mark - half
+
+kernel void conv_add_1x1_half(texture2d_array<half, access::sample> inTexture [[texture(0)]],
+                         texture2d_array<half, access::write> outTexture [[texture(1)]],
+                         constant MetalConvParam &param [[buffer(0)]],
+                         const device half4 *weights [[buffer(1)]],
+                         const device half4 *biase [[buffer(2)]],
+                         uint3 gid [[thread_position_in_grid]]) {
+  
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) {
+    return;
+  }
+  
+  ushort2 stride = ushort2(param.strideX, param.strideY);
+  ushort2 posInInput = ushort2(gid.xy) * stride + ushort2(param.offsetX, param.offsetY);
+  
+  constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
+  const uint kernelHXW = 1;
+  
+  uint input_arr_size = inTexture.get_array_size();
+  uint weithTo = gid.z * kernelHXW * input_arr_size * 4;
+  
+  half4 output = biase[gid.z];
+  
+  half4 input;
+  for (uint i = 0; i < input_arr_size; ++i) {
+    input = inTexture.sample(sample, float2(posInInput.x, posInInput.y), i);
+    half4 weight_x = weights[weithTo + 0 * kernelHXW * input_arr_size  + i];
+    output.x += dot(input, weight_x);
+    
+    half4 weight_y = weights[weithTo + 1 * kernelHXW * input_arr_size  + i];
+    output.y += dot(input, weight_y);
+    
+    half4 weight_z = weights[weithTo + 2 * kernelHXW * input_arr_size  + i];
+    output.z += dot(input, weight_z);
+    
+    half4 weight_w = weights[weithTo + 3 * kernelHXW * input_arr_size + i];
+    output.w += dot(input, weight_w);
+  }
+//  output = output + float4(biase[gid.z]);
+  outTexture.write(output, gid.xy, gid.z);
+}
+
+kernel void conv_add_3x3_half(texture2d_array<half, access::sample> inTexture [[texture(0)]],
+                         texture2d_array<half, access::write> outTexture [[texture(1)]],
+                         constant MetalConvParam &param [[buffer(0)]],
+                         const device half4 *weights [[buffer(1)]],
+                         const device half4 *biase [[buffer(2)]],
+                         uint3 gid [[thread_position_in_grid]]) {
+  
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) {
+    return;
+  }
+  
+  ushort2 stride = ushort2(param.strideX, param.strideY);
+  const ushort2 posInInput = ushort2(gid.xy) * stride + ushort2(param.offsetX, param.offsetY);
+  
+  constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
+  const uint kernelHXW = 9;
+  uint input_arr_size = inTexture.get_array_size();
+  uint weithTo = gid.z * kernelHXW * input_arr_size * 4;
+  
+  half4 output = biase[gid.z];
+  
+  ushort dilation_x = param.dilationX;
+  ushort dilation_y = param.dilationY;
+  
+  half4 input[9];
+  for (uint i = 0; i < input_arr_size; ++i) {
+    input[0] = inTexture.sample(sample, float2(posInInput.x - dilation_x,    posInInput.y - dilation_y), i);
+    input[1] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y - dilation_y), i);
+    input[2] = inTexture.sample(sample, float2(posInInput.x + dilation_x,    posInInput.y - dilation_y), i);
+    input[3] = inTexture.sample(sample, float2(posInInput.x - dilation_x,    posInInput.y), i);
+    input[4] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y), i);
+    input[5] = inTexture.sample(sample, float2(posInInput.x + dilation_x,    posInInput.y), i);
+    input[6] = inTexture.sample(sample, float2(posInInput.x - dilation_x,    posInInput.y + dilation_y), i);
+    input[7] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y + dilation_y), i);
+    input[8] = inTexture.sample(sample, float2(posInInput.x + dilation_x,    posInInput.y + dilation_y), i);
+    for (int j = 0; j < 9; ++j) {
+      half4 weight_x = weights[weithTo + 0 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.x += dot(float4(input[j]), float4(weight_x));
+      
+      half4 weight_y = weights[weithTo + 1 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.y += dot(float4(input[j]), float4(weight_y));
+      
+      half4 weight_z = weights[weithTo + 2 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.z += dot(float4(input[j]), float4(weight_z));
+      
+      half4 weight_w = weights[weithTo + 3 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.w += dot(float4(input[j]), float4(weight_w));
+    }
+  }
+//  output = output + float4(biase[gid.z]);
+  outTexture.write(output, gid.xy, gid.z);
+}
+
+kernel void depthwise_conv_add_3x3_half(texture2d_array<half, access::sample> inTexture [[texture(0)]],
+                                   texture2d_array<half, access::write> outTexture [[texture(1)]],
+                                   constant MetalConvParam &param [[buffer(0)]],
+                                   const device half *weights [[buffer(1)]],
+                                   const device half4 *biase [[buffer(2)]],
+                                   uint3 gid [[thread_position_in_grid]]) {
+  
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) {
+    return;
+  }
+  uint output_slice = gid.z;
+  ushort2 stride = ushort2(param.strideX, param.strideY);
+  ushort2 posInInput = ushort2(gid.xy) * stride + ushort2(param.offsetX, param.offsetY);
+  constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
+  const uint kernelHXW = 9;
+  uint weithTo = gid.z * kernelHXW * 4;
+  half4 output = biase[gid.z];
+  half4 inputs[9];
+  inputs[0] = inTexture.sample(sample, float2(posInInput.x - 1,    posInInput.y - 1), output_slice);
+  inputs[1] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y - 1), output_slice);
+  inputs[2] = inTexture.sample(sample, float2(posInInput.x + 1,    posInInput.y - 1), output_slice);
+  inputs[3] = inTexture.sample(sample, float2(posInInput.x - 1,    posInInput.y), output_slice);
+  inputs[4] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y), output_slice);
+  inputs[5] = inTexture.sample(sample, float2(posInInput.x + 1,    posInInput.y), output_slice);
+  inputs[6] = inTexture.sample(sample, float2(posInInput.x - 1,    posInInput.y + 1), output_slice);
+  inputs[7] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y + 1), output_slice);
+  inputs[8] = inTexture.sample(sample, float2(posInInput.x + 1,    posInInput.y + 1), output_slice);
+  for (int j = 0; j < 9; ++j) {
+    half4 input = inputs[j];
+    output.x += input.x * weights[weithTo + 0 * kernelHXW + j];
+    output.y += input.y * weights[weithTo + 1 * kernelHXW + j];
+    output.z += input.z * weights[weithTo + 2 * kernelHXW + j];
+    output.w += input.w * weights[weithTo + 3 * kernelHXW + j];
+  }
+//  output = output + float4(biase[gid.z]);
+  outTexture.write(output, gid.xy, gid.z);
+}
+
+
+kernel void conv_add_5x1_half(texture2d_array<half, access::sample> inTexture [[texture(0)]],
+                         texture2d_array<half, access::write> outTexture [[texture(1)]],
+                         constant MetalConvParam &param [[buffer(0)]],
+                         const device half4 *weights [[buffer(1)]],
+                         const device half4 *biase [[buffer(2)]],
+                         uint3 gid [[thread_position_in_grid]]) {
+  
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) {
+    return;
+  }
+  
+  ushort2 stride = ushort2(param.strideX, param.strideY);
+  const ushort2 posInInput = ushort2(gid.xy) * stride + ushort2(param.offsetX, param.offsetY);
+  
+  constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
+  
+  const uint kernelHXW = 5;
+  
+  uint input_arr_size = inTexture.get_array_size();
+  
+  uint weithTo = gid.z * kernelHXW * input_arr_size * 4;
+  
+  half4 output = biase[gid.z];
+  
+  ushort dilation_y = param.dilationY;
+  half4 input[5];
+  
+  for (uint i = 0; i < input_arr_size; ++i) {
+    input[0] = inTexture.sample(sample, float2(posInInput.x, posInInput.y - 2 * dilation_y), i);
+    
+    input[1] = inTexture.sample(sample, float2(posInInput.x, posInInput.y - dilation_y), i);
+    
+    input[2] = inTexture.sample(sample, float2(posInInput.x, posInInput.y), i);
+    
+    input[3] = inTexture.sample(sample, float2(posInInput.x, posInInput.y + dilation_y), i);
+    
+    input[4] = inTexture.sample(sample, float2(posInInput.x, posInInput.y + 2 * dilation_y), i);
+    
+    for (int j = 0; j < 5; ++j) {
+      half4 weight_x = weights[weithTo + 0 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.x += dot(input[j], weight_x);
+      
+      half4 weight_y = weights[weithTo + 1 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.y += dot(input[j], weight_y);
+      
+      half4 weight_z = weights[weithTo + 2 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.z += dot(input[j], weight_z);
+      
+      half4 weight_w = weights[weithTo + 3 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.w += dot(input[j], weight_w);
+    }
+  }
+//  output = output + float4(biase[gid.z]);
+  outTexture.write(output, gid.xy, gid.z);
+}
+
+
+kernel void conv_add_1x5_half(texture2d_array<half, access::sample> inTexture [[texture(0)]],
+                         texture2d_array<half, access::write> outTexture [[texture(1)]],
+                         constant MetalConvParam &param [[buffer(0)]],
+                         const device half4 *weights [[buffer(1)]],
+                         const device half4 *biase [[buffer(2)]],
+                         uint3 gid [[thread_position_in_grid]]) {
+  
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) {
+    return;
+  }
+  
+  ushort2 stride = ushort2(param.strideX, param.strideY);
+  const ushort2 posInInput = ushort2(gid.xy) * stride + ushort2(param.offsetX, param.offsetY);
+  
+  constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
+  
+  const uint kernelHXW = 5;
+  
+  uint input_arr_size = inTexture.get_array_size();
+  
+  uint weithTo = gid.z * kernelHXW * input_arr_size * 4;
+  
+  half4 output = biase[gid.z];
+  
+  ushort dilation_x = param.dilationX;
+  half4 input[5];
+  
+  for (uint i = 0; i < input_arr_size; ++i) {
+    input[0] = inTexture.sample(sample, float2(posInInput.x - 2 * dilation_x, posInInput.y), i);
+    
+    input[1] = inTexture.sample(sample, float2(posInInput.x - dilation_x, posInInput.y), i);
+    
+    input[2] = inTexture.sample(sample, float2(posInInput.x, posInInput.y), i);
+    
+    input[3] = inTexture.sample(sample, float2(posInInput.x + dilation_x, posInInput.y), i);
+    
+    input[4] = inTexture.sample(sample, float2(posInInput.x + 2 * dilation_x, posInInput.y), i);
+    
+    for (int j = 0; j < 5; ++j) {
+      half4 weight_x = weights[weithTo + 0 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.x += dot(input[j], weight_x);
+      
+      half4 weight_y = weights[weithTo + 1 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.y += dot(input[j], weight_y);
+      
+      half4 weight_z = weights[weithTo + 2 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.z += dot(input[j], weight_z);
+      
+      half4 weight_w = weights[weithTo + 3 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.w += dot(input[j], weight_w);
+    }
+  }
+//  output = output + float4(biase[gid.z]);
+  outTexture.write(output, gid.xy, gid.z);
+}
+
+
+kernel void test_conv_add_3x3(texture2d_array<float, access::sample> inTexture [[texture(0)]],
+                              texture2d_array<float, access::write> outTexture [[texture(1)]],
+                              constant MetalConvParam &param [[buffer(0)]],
+                              const device float4 *weights [[buffer(1)]],
+                              const device float4 *biase [[buffer(2)]],
+                              uint3 gid [[thread_position_in_grid]]) {
+  
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) {
+    return;
+  }
+  
+  if (gid.x > 0 || gid.y > 0 || gid.z > 0) { return; }
+  
+  ushort2 stride = ushort2(param.strideX, param.strideY);
+  const ushort2 posInInput = ushort2(gid.xy) * stride + ushort2(param.offsetX, param.offsetY);
+  
+  constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
+  
+  const uint kernelHXW = 9;
+  
+  uint input_arr_size = inTexture.get_array_size();
+  
+  uint weithTo = gid.z * kernelHXW * input_arr_size * 4;
+  
+  float4 output = float4(0.0);
+  
+  ushort dilation_x = param.dilationX;
+  ushort dilation_y = param.dilationY;
+  
+  float4 input[9];
+  
+  for (uint i = 0; i < input_arr_size; ++i) {
+    
+    input[0] = inTexture.sample(sample, float2(posInInput.x - dilation_x, posInInput.y - dilation_y), i);
+    
+    input[1] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y - dilation_y), i);
+    
+    input[2] = inTexture.sample(sample, float2(posInInput.x + dilation_x, posInInput.y - dilation_y), i);
+    
+    input[3] = inTexture.sample(sample, float2(posInInput.x - dilation_x,    posInInput.y), i);
+    
+    input[4] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y), i);
+    
+    input[5] = inTexture.sample(sample, float2(posInInput.x + dilation_x,    posInInput.y), i);
+    
+    input[6] = inTexture.sample(sample, float2(posInInput.x - dilation_x,    posInInput.y + dilation_y), i);
+    
+    input[7] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y + dilation_y), i);
+    
+    input[8] = inTexture.sample(sample, float2(posInInput.x + dilation_x,    posInInput.y + dilation_y), i);
+    
+    for (int j = 0; j < 9; ++j) {
+      float4 weight_x = weights[weithTo + 0 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.x += dot(input[j], weight_x);
+      
+      float4 weight_y = weights[weithTo + 1 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.y += dot(input[j], weight_y);
+      
+      float4 weight_z = weights[weithTo + 2 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.z += dot(input[j], weight_z);
+      
+      float4 weight_w = weights[weithTo + 3 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.w += dot(input[j], weight_w);
+    }
+  }
+  //  output = output + biase[gid.z];
+  outTexture.write(output, gid.xy, gid.z);
+}
+
+
+

metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/metal/ConvAddPrelu.inc.metal

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+ 
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+ 
+ http://www.apache.org/licenses/LICENSE-2.0
+ 
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
+
+#ifdef P
+
+#include "Macro.metal"
+
+
+#pragma mark - convAdd
+kernel void FUNC3_(conv_add_1x1, PRELU_TYPE, P)(texture2d_array<P, access::sample> inTexture [[texture(0)]],
+                         texture2d_array<P, access::write> outTexture [[texture(1)]],
+                         constant MetalConvParam &param [[buffer(0)]],
+                         const device VECTOR(P, 4) *weights [[buffer(1)]],
+                         const device VECTOR(P, 4) *biase [[buffer(2)]],
+#ifdef PRELU_CHANNEL
+                         const device VECTOR(P, 4) *alpha [[buffer(3)]],
+#endif
+#ifdef PRELU_ELEMENT
+                         const device VECTOR(P, 4) *alpha [[buffer(3)]],
+#endif
+#ifdef PRELU_OTHER
+                         const device P *alpha [[buffer(3)]],
+#endif
+                         uint3 gid [[thread_position_in_grid]]) {
+  
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) {
+    return;
+  }
+  
+  ushort2 stride = ushort2(param.strideX, param.strideY);
+  ushort2 posInInput = ushort2(gid.xy) * stride + ushort2(param.offsetX, param.offsetY);
+  
+  constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
+  const uint kernelHXW = 1;
+  
+  uint input_arr_size = inTexture.get_array_size();
+  uint weithTo = gid.z * kernelHXW * input_arr_size * 4;
+  
+  VECTOR(P, 4) output = biase[gid.z];
+  
+  VECTOR(P, 4) input;
+  for (uint i = 0; i < input_arr_size; ++i) {
+    input = inTexture.sample(sample,float2(posInInput.x, posInInput.y), i);
+    VECTOR(P, 4) weight_x = weights[weithTo + 0 * kernelHXW * input_arr_size  + i];
+    output.x += dot(input, weight_x);
+    
+    VECTOR(P, 4) weight_y = weights[weithTo + 1 * kernelHXW * input_arr_size  + i];
+    output.y += dot(input, weight_y);
+    
+    VECTOR(P, 4) weight_z = weights[weithTo + 2 * kernelHXW * input_arr_size  + i];
+    output.z += dot(input, weight_z);
+    
+    VECTOR(P, 4) weight_w = weights[weithTo + 3 * kernelHXW * input_arr_size + i];
+    output.w += dot(input, weight_w);
+  }
+  
+//  output = output + float4(biase[gid.z]);
+  
+#ifdef PRELU_CHANNEL
+  VECTOR(P, 4) alpha_value = alpha[gid.z];
+  output.x = output.x > 0 ? output.x : (alpha_value.x * output.x);
+  output.y = output.y > 0 ? output.y : (alpha_value.y * output.y);
+  output.z = output.z > 0 ? output.z : (alpha_value.z * output.z);
+  output.w = output.w > 0 ? output.w : (alpha_value.w * output.w);
+#endif
+#ifdef PRELU_ELEMENT
+  int alpha_to = (gid.y * outTexture.get_width() + gid.x) * outTexture.get_array_size();
+  VECTOR(P, 4) alpha_value = alpha[alpha_to + gid.z];
+  output.x = output.x > 0 ? output.x : (alpha_value.x * output.x);
+  output.y = output.y > 0 ? output.y : (alpha_value.y * output.y);
+  output.z = output.z > 0 ? output.z : (alpha_value.z * output.z);
+  output.w = output.w > 0 ? output.w : (alpha_value.w * output.w);
+#endif
+#ifdef PRELU_OTHER
+  P alpha_value = alpha[0];
+  output.x = output.x > 0 ? output.x : (alpha_value * output.x);
+  output.y = output.y > 0 ? output.y : (alpha_value * output.y);
+  output.z = output.z > 0 ? output.z : (alpha_value * output.z);
+  output.w = output.w > 0 ? output.w : (alpha_value * output.w);
+#endif
+  outTexture.write(VECTOR(P, 4)(output), gid.xy, gid.z);
+}
+
+kernel void FUNC3_(conv_add_3x3, PRELU_TYPE, P)(texture2d_array<P, access::sample> inTexture [[texture(0)]],
+    texture2d_array<P, access::write> outTexture [[texture(1)]],
+    constant MetalConvParam &param [[buffer(0)]],
+    const device VECTOR(P, 4) *weights [[buffer(1)]],
+    const device VECTOR(P, 4) *biase [[buffer(2)]],
+#ifdef PRELU_CHANNEL
+     const device VECTOR(P, 4) *alpha [[buffer(3)]],
+#endif
+#ifdef PRELU_ELEMENT
+     const device VECTOR(P, 4) *alpha [[buffer(3)]],
+#endif
+#ifdef PRELU_OTHER
+     const device P *alpha [[buffer(3)]],
+#endif
+     uint3 gid [[thread_position_in_grid]]) {
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) {
+    return;
+  }
+
+  ushort2 stride = ushort2(param.strideX, param.strideY);
+  const ushort2 posInInput = ushort2(gid.xy) * stride + ushort2(param.offsetX, param.offsetY);
+
+  constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
+
+  const uint kernelHXW = 9;
+
+  uint input_arr_size = inTexture.get_array_size();
+
+  uint weithTo = gid.z * kernelHXW * input_arr_size * 4;
+
+  VECTOR(P, 4) output = biase[gid.z];
+
+  ushort dilation_x = param.dilationX;
+  ushort dilation_y = param.dilationY;
+
+  VECTOR(P, 4) input[9];
+
+  for (uint i = 0; i < input_arr_size; ++i) {
+    input[0] = inTexture.sample(sample, float2(posInInput.x - dilation_x, posInInput.y - dilation_y), i);
+
+    input[1] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y - dilation_y), i);
+
+    input[2] = inTexture.sample(sample, float2(posInInput.x + dilation_x, posInInput.y - dilation_y), i);
+
+    input[3] = inTexture.sample(sample, float2(posInInput.x - dilation_x,    posInInput.y), i);
+
+    input[4] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y), i);
+
+    input[5] = inTexture.sample(sample, float2(posInInput.x + dilation_x,    posInInput.y), i);
+
+    input[6] = inTexture.sample(sample, float2(posInInput.x - dilation_x,    posInInput.y + dilation_y), i);
+
+    input[7] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y + dilation_y), i);
+
+    input[8] = inTexture.sample(sample, float2(posInInput.x + dilation_x,    posInInput.y + dilation_y), i);
+
+    for (int j = 0; j < 9; ++j) {
+      VECTOR(P, 4) weight_x = weights[weithTo + 0 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.x += dot(input[j], weight_x);
+
+      VECTOR(P, 4) weight_y = weights[weithTo + 1 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.y += dot(input[j], weight_y);
+
+      VECTOR(P, 4) weight_z = weights[weithTo + 2 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.z += dot(input[j], weight_z);
+
+      VECTOR(P, 4) weight_w = weights[weithTo + 3 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.w += dot(input[j], weight_w);
+    }
+  }
+//  output = output + float4(biase[gid.z]);
+  
+#ifdef PRELU_CHANNEL
+  VECTOR(P, 4) alpha_value = alpha[gid.z];
+  output.x = output.x > 0 ? output.x : (alpha_value.x * output.x);
+  output.y = output.y > 0 ? output.y : (alpha_value.y * output.y);
+  output.z = output.z > 0 ? output.z : (alpha_value.z * output.z);
+  output.w = output.w > 0 ? output.w : (alpha_value.w * output.w);
+#endif
+#ifdef PRELU_ELEMENT
+  int alpha_to = (gid.y * outTexture.get_width() + gid.x) * outTexture.get_array_size();
+  VECTOR(P, 4) alpha_value = alpha[alpha_to + gid.z];
+  output.x = output.x > 0 ? output.x : (alpha_value.x * output.x);
+  output.y = output.y > 0 ? output.y : (alpha_value.y * output.y);
+  output.z = output.z > 0 ? output.z : (alpha_value.z * output.z);
+  output.w = output.w > 0 ? output.w : (alpha_value.w * output.w);
+#endif
+#ifdef PRELU_OTHER
+  P alpha_value = alpha[0];
+  output.x = output.x > 0 ? output.x : (alpha_value * output.x);
+  output.y = output.y > 0 ? output.y : (alpha_value * output.y);
+  output.z = output.z > 0 ? output.z : (alpha_value * output.z);
+  output.w = output.w > 0 ? output.w : (alpha_value * output.w);
+#endif
+  outTexture.write(VECTOR(P, 4)(output), gid.xy, gid.z);
+}
+
+kernel void FUNC3_(conv_add_5x1, PRELU_TYPE, P)(texture2d_array<P, access::sample> inTexture [[texture(0)]],
+                         texture2d_array<P, access::write> outTexture [[texture(1)]],
+                         constant MetalConvParam &param [[buffer(0)]],
+                         const device VECTOR(P, 4) *weights [[buffer(1)]],
+                         const device VECTOR(P, 4) *biase [[buffer(2)]],
+#ifdef PRELU_CHANNEL
+                        const device VECTOR(P, 4) *alpha [[buffer(3)]],
+#endif
+#ifdef PRELU_ELEMENT
+                        const device VECTOR(P, 4) *alpha [[buffer(3)]],
+#endif
+#ifdef PRELU_OTHER
+                        const device P *alpha [[buffer(3)]],
+#endif
+                         uint3 gid [[thread_position_in_grid]]) {
+
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) {
+    return;
+  }
+
+  ushort2 stride = ushort2(param.strideX, param.strideY);
+  const ushort2 posInInput = ushort2(gid.xy) * stride + ushort2(param.offsetX, param.offsetY);
+
+  constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
+
+  const uint kernelHXW = 5;
+
+  uint input_arr_size = inTexture.get_array_size();
+
+  uint weithTo = gid.z * kernelHXW * input_arr_size * 4;
+
+  VECTOR(P, 4) output = biase[gid.z];;
+
+  ushort dilation_y = param.dilationY;
+  VECTOR(P, 4) input[5];
+
+  for (uint i = 0; i < input_arr_size; ++i) {
+    input[0] = inTexture.sample(sample, float2(posInInput.x, posInInput.y - 2 * dilation_y), i);
+
+    input[1] = inTexture.sample(sample, float2(posInInput.x, posInInput.y - dilation_y), i);
+
+    input[2] = inTexture.sample(sample, float2(posInInput.x, posInInput.y), i);
+
+    input[3] = inTexture.sample(sample, float2(posInInput.x, posInInput.y + dilation_y), i);
+
+    input[4] = inTexture.sample(sample, float2(posInInput.x, posInInput.y + 2 * dilation_y), i);
+
+    for (int j = 0; j < 5; ++j) {
+      VECTOR(P, 4) weight_x = weights[weithTo + 0 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.x += dot(input[j], weight_x);
+
+      VECTOR(P, 4) weight_y = weights[weithTo + 1 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.y += dot(input[j], weight_y);
+
+      VECTOR(P, 4) weight_z = weights[weithTo + 2 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.z += dot(input[j], weight_z);
+
+      VECTOR(P, 4) weight_w = weights[weithTo + 3 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.w += dot(input[j], weight_w);
+    }
+  }
+  
+#ifdef PRELU_CHANNEL
+  VECTOR(P, 4) alpha_value = alpha[gid.z];
+  output.x = output.x > 0 ? output.x : (alpha_value.x * output.x);
+  output.y = output.y > 0 ? output.y : (alpha_value.y * output.y);
+  output.z = output.z > 0 ? output.z : (alpha_value.z * output.z);
+  output.w = output.w > 0 ? output.w : (alpha_value.w * output.w);
+#endif
+#ifdef PRELU_ELEMENT
+  int alpha_to = (gid.y * outTexture.get_width() + gid.x) * outTexture.get_array_size();
+  VECTOR(P, 4) alpha_value = alpha[alpha_to + gid.z];
+  output.x = output.x > 0 ? output.x : (alpha_value.x * output.x);
+  output.y = output.y > 0 ? output.y : (alpha_value.y * output.y);
+  output.z = output.z > 0 ? output.z : (alpha_value.z * output.z);
+  output.w = output.w > 0 ? output.w : (alpha_value.w * output.w);
+#endif
+#ifdef PRELU_OTHER
+  P alpha_value = alpha[0];
+  output.x = output.x > 0 ? output.x : (alpha_value * output.x);
+  output.y = output.y > 0 ? output.y : (alpha_value * output.y);
+  output.z = output.z > 0 ? output.z : (alpha_value * output.z);
+  output.w = output.w > 0 ? output.w : (alpha_value * output.w);
+#endif
+  outTexture.write(VECTOR(P, 4)(output), gid.xy, gid.z);
+}
+
+
+kernel void FUNC3_(conv_add_1x5, PRELU_TYPE, P)(texture2d_array<P, access::sample> inTexture [[texture(0)]],
+                         texture2d_array<P, access::write> outTexture [[texture(1)]],
+                         constant MetalConvParam &param [[buffer(0)]],
+                         const device VECTOR(P, 4) *weights [[buffer(1)]],
+                         const device VECTOR(P, 4) *biase [[buffer(2)]],
+#ifdef PRELU_CHANNEL
+                         const device VECTOR(P, 4) *alpha [[buffer(3)]],
+#endif
+#ifdef PRELU_ELEMENT
+                         const device VECTOR(P, 4) *alpha [[buffer(3)]],
+#endif
+#ifdef PRELU_OTHER
+                         const device P *alpha [[buffer(3)]],
+#endif
+                         uint3 gid [[thread_position_in_grid]]) {
+
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) {
+    return;
+  }
+
+  ushort2 stride = ushort2(param.strideX, param.strideY);
+  const ushort2 posInInput = ushort2(gid.xy) * stride + ushort2(param.offsetX, param.offsetY);
+
+  constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
+
+  const uint kernelHXW = 5;
+
+  uint input_arr_size = inTexture.get_array_size();
+
+  uint weithTo = gid.z * kernelHXW * input_arr_size * 4;
+
+  VECTOR(P, 4) output = biase[gid.z];
+
+  ushort dilation_x = param.dilationX;
+  VECTOR(P, 4) input[5];
+
+  for (uint i = 0; i < input_arr_size; ++i) {
+    input[0] = inTexture.sample(sample, float2(posInInput.x - 2 * dilation_x, posInInput.y), i);
+
+    input[1] = inTexture.sample(sample, float2(posInInput.x - dilation_x, posInInput.y), i);
+
+    input[2] = inTexture.sample(sample, float2(posInInput.x, posInInput.y), i);
+
+    input[3] = inTexture.sample(sample, float2(posInInput.x + dilation_x, posInInput.y), i);
+
+    input[4] = inTexture.sample(sample, float2(posInInput.x + 2 * dilation_x, posInInput.y), i);
+
+    for (int j = 0; j < 5; ++j) {
+      VECTOR(P, 4) weight_x = weights[weithTo + 0 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.x += dot(input[j], weight_x);
+
+      VECTOR(P, 4) weight_y = weights[weithTo + 1 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.y += dot(input[j], weight_y);
+
+      VECTOR(P, 4) weight_z = weights[weithTo + 2 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.z += dot(input[j], weight_z);
+
+      VECTOR(P, 4) weight_w = weights[weithTo + 3 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.w += dot(input[j], weight_w);
+    }
+  }
+  
+#ifdef PRELU_CHANNEL
+  VECTOR(P, 4) alpha_value = alpha[gid.z];
+  output.x = output.x > 0 ? output.x : (alpha_value.x * output.x);
+  output.y = output.y > 0 ? output.y : (alpha_value.y * output.y);
+  output.z = output.z > 0 ? output.z : (alpha_value.z * output.z);
+  output.w = output.w > 0 ? output.w : (alpha_value.w * output.w);
+#endif
+#ifdef PRELU_ELEMENT
+  int alpha_to = (gid.y * outTexture.get_width() + gid.x) * outTexture.get_array_size();
+  VECTOR(P, 4) alpha_value = alpha[alpha_to + gid.z];
+  output.x = output.x > 0 ? output.x : (alpha_value.x * output.x);
+  output.y = output.y > 0 ? output.y : (alpha_value.y * output.y);
+  output.z = output.z > 0 ? output.z : (alpha_value.z * output.z);
+  output.w = output.w > 0 ? output.w : (alpha_value.w * output.w);
+#endif
+#ifdef PRELU_OTHER
+  P alpha_value = alpha[0];
+  output.x = output.x > 0 ? output.x : (alpha_value * output.x);
+  output.y = output.y > 0 ? output.y : (alpha_value * output.y);
+  output.z = output.z > 0 ? output.z : (alpha_value * output.z);
+  output.w = output.w > 0 ? output.w : (alpha_value * output.w);
+#endif
+  outTexture.write(VECTOR(P, 4)(output), gid.xy, gid.z);
+}
+
+kernel void FUNC3_(depthwise_conv_add_3x3, PRELU_TYPE, P)(texture2d_array<P, access::sample> inTexture [[texture(0)]],
+    texture2d_array<P, access::write> outTexture [[texture(1)]],
+    constant MetalConvParam &param [[buffer(0)]],
+    const device P *weights [[buffer(1)]],
+    const device VECTOR(P, 4) *biase [[buffer(2)]],
+#ifdef PRELU_CHANNEL
+    const device VECTOR(P, 4) *alpha [[buffer(3)]],
+#endif
+#ifdef PRELU_ELEMENT
+    const device VECTOR(P, 4) *alpha [[buffer(3)]],
+#endif
+#ifdef PRELU_OTHER
+    const device P *alpha [[buffer(3)]],
+#endif
+    uint3 gid [[thread_position_in_grid]]) {
+
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) {
+    return;
+  }
+  uint output_slice = gid.z;
+  ushort2 stride = ushort2(param.strideX, param.strideY);
+  ushort2 posInInput = ushort2(gid.xy) * stride + ushort2(param.offsetX, param.offsetY);
+  constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
+  const uint kernelHXW = 9;
+  uint weithTo = gid.z * kernelHXW * 4;
+  VECTOR(P, 4) output = biase[gid.z];
+  VECTOR(P, 4) inputs[9];
+  inputs[0] = inTexture.sample(sample, float2(posInInput.x - 1,    posInInput.y - 1), output_slice);
+  inputs[1] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y - 1), output_slice);
+  inputs[2] = inTexture.sample(sample, float2(posInInput.x + 1,    posInInput.y - 1), output_slice);
+  inputs[3] = inTexture.sample(sample, float2(posInInput.x - 1,    posInInput.y), output_slice);
+  inputs[4] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y), output_slice);
+  inputs[5] = inTexture.sample(sample, float2(posInInput.x + 1,    posInInput.y), output_slice);
+  inputs[6] = inTexture.sample(sample, float2(posInInput.x - 1,    posInInput.y + 1), output_slice);
+  inputs[7] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y + 1), output_slice);
+  inputs[8] = inTexture.sample(sample, float2(posInInput.x + 1,    posInInput.y + 1), output_slice);
+  for (int j = 0; j < 9; ++j) {
+    VECTOR(P, 4) input = inputs[j];
+    output.x += input.x * weights[weithTo + 0 * kernelHXW + j];
+    output.y += input.y * weights[weithTo + 1 * kernelHXW + j];
+    output.z += input.z * weights[weithTo + 2 * kernelHXW + j];
+    output.w += input.w * weights[weithTo + 3 * kernelHXW + j];
+  }
+  
+#ifdef PRELU_CHANNEL
+  VECTOR(P, 4) alpha_value = alpha[gid.z];
+  output.x = output.x > 0 ? output.x : (alpha_value.x * output.x);
+  output.y = output.y > 0 ? output.y : (alpha_value.y * output.y);
+  output.z = output.z > 0 ? output.z : (alpha_value.z * output.z);
+  output.w = output.w > 0 ? output.w : (alpha_value.w * output.w);
+#endif
+#ifdef PRELU_ELEMENT
+  int alpha_to = (gid.y * outTexture.get_width() + gid.x) * outTexture.get_array_size();
+  VECTOR(P, 4) alpha_value = alpha[alpha_to + gid.z];
+  output.x = output.x > 0 ? output.x : (alpha_value.x * output.x);
+  output.y = output.y > 0 ? output.y : (alpha_value.y * output.y);
+  output.z = output.z > 0 ? output.z : (alpha_value.z * output.z);
+  output.w = output.w > 0 ? output.w : (alpha_value.w * output.w);
+#endif
+#ifdef PRELU_OTHER
+  P alpha_value = alpha[0];
+  output.x = output.x > 0 ? output.x : (alpha_value * output.x);
+  output.y = output.y > 0 ? output.y : (alpha_value * output.y);
+  output.z = output.z > 0 ? output.z : (alpha_value * output.z);
+  output.w = output.w > 0 ? output.w : (alpha_value * output.w);
+#endif
+  outTexture.write(VECTOR(P, 4)(output), gid.xy, gid.z);
+}
+
+#endif
+

metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/metal/ConvAddPreluKernel.metal

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+ 
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+ 
+ http://www.apache.org/licenses/LICENSE-2.0
+ 
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
+
+#include <metal_stdlib>
+#include "Common.metal"
+using namespace metal;
+
+#define P float
+
+  #define PRELU_CHANNEL prelu_channel
+  #define PRELU_TYPE prelu_channel
+    #include "ConvAddPrelu.inc.metal"
+  #undef  PRELU_TYPE
+  #undef  PRELU_CHANNEL
+
+  #define PRELU_ELEMENT prelu_element
+  #define PRELU_TYPE prelu_element
+    #include "ConvAddPrelu.inc.metal"
+  #undef  PRELU_TYPE
+  #undef  PRELU_ELEMENT
+
+  #define PRELU_OTHER   prelu_other
+  #define PRELU_TYPE prelu_other
+    #include "ConvAddPrelu.inc.metal"
+  #undef  PRELU_TYPE
+  #undef  PRELU_OTHER
+
+#undef P
+
+#define P half
+
+  #define PRELU_CHANNEL prelu_channel
+  #define PRELU_TYPE prelu_channel
+    #include "ConvAddPrelu.inc.metal"
+  #undef  PRELU_TYPE
+  #undef  PRELU_CHANNEL
+
+  #define PRELU_ELEMENT prelu_element
+  #define PRELU_TYPE prelu_element
+    #include "ConvAddPrelu.inc.metal"
+  #undef  PRELU_TYPE
+  #undef  PRELU_ELEMENT
+
+  #define PRELU_OTHER   prelu_other
+  #define PRELU_TYPE prelu_other
+    #include "ConvAddPrelu.inc.metal"
+  #undef  PRELU_TYPE
+  #undef  PRELU_OTHER
+
+#undef P
+
+
+
+

metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/metal/ConvBNReluKernel.metal

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+ 
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+ 
+ http://www.apache.org/licenses/LICENSE-2.0
+ 
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
+
+#include <metal_stdlib>
+#include "Common.metal"
+
+using namespace metal;
+
+#pragma mark - conv bn relu
+kernel void conv_batch_norm_relu_1x1(texture2d_array<float, access::sample> inTexture [[texture(0)]],
+                                     texture2d_array<float, access::write> outTexture [[texture(1)]],
+                                     constant MetalConvParam &param [[buffer(0)]],
+                                     const device float4 *weights [[buffer(1)]],
+                                     const device float4 *new_scale [[buffer(2)]],
+                                     const device float4 *new_biase [[buffer(3)]],
+                                     uint3 gid [[thread_position_in_grid]]) {
+  
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) {
+    return;
+  }
+  
+  ushort2 stride = ushort2(param.strideX, param.strideY);
+  ushort2 posInInput = ushort2(gid.xy) * stride + ushort2(param.offsetX, param.offsetY);
+  
+  constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
+  const uint kernelHXW = 1;
+  
+  uint input_arr_size = inTexture.get_array_size();
+  uint weithTo = gid.z * kernelHXW * input_arr_size * 4;
+  
+  float4 output = float4(0.0);
+  
+  float4 input;
+  for (uint i = 0; i < input_arr_size; ++i) {
+    input = inTexture.sample(sample, float2(posInInput.x, posInInput.y), i);
+    float4 weight_x = weights[weithTo + 0 * kernelHXW * input_arr_size  + i];
+    output.x += dot(input, weight_x);
+    
+    float4 weight_y = weights[weithTo + 1 * kernelHXW * input_arr_size  + i];
+    output.y += dot(input, weight_y);
+    
+    float4 weight_z = weights[weithTo + 2 * kernelHXW * input_arr_size  + i];
+    output.z += dot(input, weight_z);
+    
+    float4 weight_w = weights[weithTo + 3 * kernelHXW * input_arr_size + i];
+    output.w += dot(input, weight_w);
+  }
+  output = fmax(output * new_scale[gid.z] + new_biase[gid.z], 0.0);
+  outTexture.write(output, gid.xy, gid.z);
+}
+
+kernel void conv_batch_norm_relu_3x3(texture2d_array<float, access::sample> inTexture [[texture(0)]],
+                                     texture2d_array<float, access::write> outTexture [[texture(1)]],
+                                     constant MetalConvParam &param [[buffer(0)]],
+                                     const device float4 *weights [[buffer(1)]],
+                                     const device float4 *new_scale [[buffer(2)]],
+                                     const device float4 *new_biase [[buffer(3)]],
+                                     uint3 gid [[thread_position_in_grid]]) {
+  
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) {
+    return;
+  }
+  
+  ushort2 stride = ushort2(param.strideX, param.strideY);
+  const ushort2 posInInput = ushort2(gid.xy) * stride + ushort2(param.offsetX, param.offsetY);
+  
+  constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
+  const uint kernelHXW = 9;
+  uint input_arr_size = inTexture.get_array_size();
+  uint weithTo = gid.z * kernelHXW * input_arr_size * 4;
+  
+  float4 output = float4(0.0);
+  
+  float4 input[9];
+  for (uint i = 0; i < input_arr_size; ++i) {
+    input[0] = inTexture.sample(sample, float2(posInInput.x - 1,    posInInput.y - 1), i);
+    input[1] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y - 1), i);
+    input[2] = inTexture.sample(sample, float2(posInInput.x + 1,    posInInput.y - 1), i);
+    input[3] = inTexture.sample(sample, float2(posInInput.x - 1,    posInInput.y), i);
+    input[4] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y), i);
+    input[5] = inTexture.sample(sample, float2(posInInput.x + 1,    posInInput.y), i);
+    input[6] = inTexture.sample(sample, float2(posInInput.x - 1,    posInInput.y + 1), i);
+    input[7] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y + 1), i);
+    input[8] = inTexture.sample(sample, float2(posInInput.x + 1,    posInInput.y + 1), i);
+    for (int j = 0; j < 9; ++j) {
+      float4 weight_x = weights[weithTo + 0 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.x += dot(input[j], weight_x);
+      
+      float4 weight_y = weights[weithTo + 1 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.y += dot(input[j], weight_y);
+      
+      float4 weight_z = weights[weithTo + 2 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.z += dot(input[j], weight_z);
+      
+      float4 weight_w = weights[weithTo + 3 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.w += dot(input[j], weight_w);
+    }
+  }
+  output = fmax(output * new_scale[gid.z] + new_biase[gid.z], 0.0);
+  outTexture.write(output, gid.xy, gid.z);
+}
+
+kernel void depthwise_conv_batch_norm_relu_3x3(texture2d_array<float, access::sample> inTexture [[texture(0)]],
+                                               texture2d_array<float, access::write> outTexture [[texture(1)]],
+                                               constant MetalConvParam &param [[buffer(0)]],
+                                               const device float *weights [[buffer(1)]],
+                                               const device float4 *new_scale [[buffer(2)]],
+                                               const device float4 *new_biase [[buffer(3)]],
+                                               uint3 gid [[thread_position_in_grid]]) {
+  
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) {
+    return;
+  }
+  uint output_slice = gid.z;
+  ushort2 stride = ushort2(param.strideX, param.strideY);
+  ushort2 posInInput = ushort2(gid.xy) * stride + ushort2(param.offsetX, param.offsetY);
+  constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
+  const uint kernelHXW = 9;
+  uint weithTo = gid.z * kernelHXW * 4;
+  float4 output = float4(0.0);
+  float4 inputs[9];
+  inputs[0] = inTexture.sample(sample, float2(posInInput.x - 1,    posInInput.y - 1), output_slice);
+  inputs[1] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y - 1), output_slice);
+  inputs[2] = inTexture.sample(sample, float2(posInInput.x + 1,    posInInput.y - 1), output_slice);
+  inputs[3] = inTexture.sample(sample, float2(posInInput.x - 1,    posInInput.y), output_slice);
+  inputs[4] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y), output_slice);
+  inputs[5] = inTexture.sample(sample, float2(posInInput.x + 1,    posInInput.y), output_slice);
+  inputs[6] = inTexture.sample(sample, float2(posInInput.x - 1,    posInInput.y + 1), output_slice);
+  inputs[7] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y + 1), output_slice);
+  inputs[8] = inTexture.sample(sample, float2(posInInput.x + 1,    posInInput.y + 1), output_slice);
+  for (int j = 0; j < 9; ++j) {
+    float4 input = inputs[j];
+    output.x += input.x * weights[weithTo + 0 * kernelHXW + j];
+    output.y += input.y * weights[weithTo + 1 * kernelHXW + j];
+    output.z += input.z * weights[weithTo + 2 * kernelHXW + j];
+    output.w += input.w * weights[weithTo + 3 * kernelHXW + j];
+  }
+  output = fmax(output * new_scale[gid.z] + new_biase[gid.z], 0.0);
+  outTexture.write(output, gid.xy, gid.z);
+}
+
+#pragma mark - half
+kernel void conv_batch_norm_relu_1x1_half(texture2d_array<half, access::sample> inTexture [[texture(0)]],
+                                     texture2d_array<half, access::write> outTexture [[texture(1)]],
+                                     constant MetalConvParam &param [[buffer(0)]],
+                                     const device half4 *weights [[buffer(1)]],
+                                     const device half4 *new_scale [[buffer(2)]],
+                                     const device half4 *new_biase [[buffer(3)]],
+                                     uint3 gid [[thread_position_in_grid]]) {
+  
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) {
+    return;
+  }
+  
+  ushort2 stride = ushort2(param.strideX, param.strideY);
+  ushort2 posInInput = ushort2(gid.xy) * stride + ushort2(param.offsetX, param.offsetY);
+  
+  constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
+  const uint kernelHXW = 1;
+  
+  uint input_arr_size = inTexture.get_array_size();
+  uint weithTo = gid.z * kernelHXW * input_arr_size * 4;
+  
+  float4 output = float4(0.0);
+  
+  half4 input;
+  for (uint i = 0; i < input_arr_size; ++i) {
+    input = inTexture.sample(sample, float2(posInInput.x, posInInput.y), i);
+    half4 weight_x = weights[weithTo + 0 * kernelHXW * input_arr_size  + i];
+    output.x += dot(float4(input), float4(weight_x));
+    
+    half4 weight_y = weights[weithTo + 1 * kernelHXW * input_arr_size  + i];
+    output.y += dot(float4(input), float4(weight_y));
+    
+    half4 weight_z = weights[weithTo + 2 * kernelHXW * input_arr_size  + i];
+    output.z += dot(float4(input), float4(weight_z));
+    
+    half4 weight_w = weights[weithTo + 3 * kernelHXW * input_arr_size + i];
+    output.w += dot(float4(input), float4(weight_w));
+  }
+  output = fmax(output * float4(new_scale[gid.z]) + float4(new_biase[gid.z]), 0.0);
+  outTexture.write(half4(output), gid.xy, gid.z);
+}
+
+kernel void conv_batch_norm_relu_3x3_half(texture2d_array<half, access::sample> inTexture [[texture(0)]],
+                                     texture2d_array<half, access::write> outTexture [[texture(1)]],
+                                     constant MetalConvParam &param [[buffer(0)]],
+                                     const device half4 *weights [[buffer(1)]],
+                                     const device half4 *new_scale [[buffer(2)]],
+                                     const device half4 *new_biase [[buffer(3)]],
+                                     uint3 gid [[thread_position_in_grid]]) {
+  
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) {
+    return;
+  }
+  
+  ushort2 stride = ushort2(param.strideX, param.strideY);
+  const ushort2 posInInput = ushort2(gid.xy) * stride + ushort2(param.offsetX, param.offsetY);
+  
+  constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
+  const uint kernelHXW = 9;
+  uint input_arr_size = inTexture.get_array_size();
+  uint weithTo = gid.z * kernelHXW * input_arr_size * 4;
+  
+  float4 output = float4(0.0);
+  
+  half4 input[9];
+  for (uint i = 0; i < input_arr_size; ++i) {
+    input[0] = inTexture.sample(sample, float2(posInInput.x - 1,    posInInput.y - 1), i);
+    input[1] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y - 1), i);
+    input[2] = inTexture.sample(sample, float2(posInInput.x + 1,    posInInput.y - 1), i);
+    input[3] = inTexture.sample(sample, float2(posInInput.x - 1,    posInInput.y), i);
+    input[4] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y), i);
+    input[5] = inTexture.sample(sample, float2(posInInput.x + 1,    posInInput.y), i);
+    input[6] = inTexture.sample(sample, float2(posInInput.x - 1,    posInInput.y + 1), i);
+    input[7] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y + 1), i);
+    input[8] = inTexture.sample(sample, float2(posInInput.x + 1,    posInInput.y + 1), i);
+    for (int j = 0; j < 9; ++j) {
+      half4 weight_x = weights[weithTo + 0 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.x += dot(float4(input[j]), float4(weight_x));
+      
+      half4 weight_y = weights[weithTo + 1 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.y += dot(float4(input[j]), float4(weight_y));
+      
+      half4 weight_z = weights[weithTo + 2 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.z += dot(float4(input[j]), float4(weight_z));
+      
+      half4 weight_w = weights[weithTo + 3 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.w += dot(float4(input[j]), float4(weight_w));
+    }
+  }
+  output = fmax(output * float4(new_scale[gid.z]) + float4(new_biase[gid.z]), 0.0);
+  outTexture.write(half4(output), gid.xy, gid.z);
+}
+
+kernel void depthwise_conv_batch_norm_relu_3x3_half(texture2d_array<half, access::sample> inTexture [[texture(0)]],
+                                               texture2d_array<half, access::write> outTexture [[texture(1)]],
+                                               constant MetalConvParam &param [[buffer(0)]],
+                                               const device half *weights [[buffer(1)]],
+                                               const device half4 *new_scale [[buffer(2)]],
+                                               const device half4 *new_biase [[buffer(3)]],
+                                               uint3 gid [[thread_position_in_grid]]) {
+  
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) {
+    return;
+  }
+  uint output_slice = gid.z;
+  ushort2 stride = ushort2(param.strideX, param.strideY);
+  ushort2 posInInput = ushort2(gid.xy) * stride + ushort2(param.offsetX, param.offsetY);
+  constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
+  const uint kernelHXW = 9;
+  uint weithTo = gid.z * kernelHXW * 4;
+  float4 output = float4(0.0);
+  half4 inputs[9];
+  inputs[0] = inTexture.sample(sample, float2(posInInput.x - 1,    posInInput.y - 1), output_slice);
+  inputs[1] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y - 1), output_slice);
+  inputs[2] = inTexture.sample(sample, float2(posInInput.x + 1,    posInInput.y - 1), output_slice);
+  inputs[3] = inTexture.sample(sample, float2(posInInput.x - 1,    posInInput.y), output_slice);
+  inputs[4] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y), output_slice);
+  inputs[5] = inTexture.sample(sample, float2(posInInput.x + 1,    posInInput.y), output_slice);
+  inputs[6] = inTexture.sample(sample, float2(posInInput.x - 1,    posInInput.y + 1), output_slice);
+  inputs[7] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y + 1), output_slice);
+  inputs[8] = inTexture.sample(sample, float2(posInInput.x + 1,    posInInput.y + 1), output_slice);
+  for (int j = 0; j < 9; ++j) {
+    half4 input = inputs[j];
+    output.x += input.x * weights[weithTo + 0 * kernelHXW + j];
+    output.y += input.y * weights[weithTo + 1 * kernelHXW + j];
+    output.z += input.z * weights[weithTo + 2 * kernelHXW + j];
+    output.w += input.w * weights[weithTo + 3 * kernelHXW + j];
+  }
+  output = fmax(output * float4(new_scale[gid.z]) + float4(new_biase[gid.z]), 0.0);
+  outTexture.write(half4(output), gid.xy, gid.z);
+}
+

metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/metal/ConvKernel.metal

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+ 
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+ 
+ http://www.apache.org/licenses/LICENSE-2.0
+ 
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
+
+#include <metal_stdlib>
+#include "Common.metal"
+using namespace metal;
+
+// conv
+#pragma mark -- conv
+kernel void conv_3x3(texture2d_array<float, access::sample> inTexture [[texture(0)]],
+                     texture2d_array<float, access::write> outTexture [[texture(1)]],
+                     constant MetalConvParam &param [[buffer(0)]],
+                     const device float4 *weights [[buffer(1)]],
+                     uint3 gid [[thread_position_in_grid]]) {
+  
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) {
+    return;
+  }
+  
+  ushort2 stride = ushort2(param.strideX, param.strideY);
+  const ushort2 posInInput = ushort2(gid.xy) * stride + ushort2(param.offsetX, param.offsetY);
+  
+  constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
+  const uint kernelHXW = 9;
+  uint input_arr_size = inTexture.get_array_size();
+  uint weithTo = gid.z * kernelHXW * input_arr_size * 4;
+  
+  float4 output = float4(0.0);
+  
+  float4 input[9];
+  for (uint i = 0; i < input_arr_size; ++i) {
+    input[0] = inTexture.sample(sample, float2(posInInput.x - 1,    posInInput.y - 1), i);
+    input[1] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y - 1), i);
+    input[2] = inTexture.sample(sample, float2(posInInput.x + 1,    posInInput.y - 1), i);
+    input[3] = inTexture.sample(sample, float2(posInInput.x - 1,    posInInput.y), i);
+    input[4] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y), i);
+    input[5] = inTexture.sample(sample, float2(posInInput.x + 1,    posInInput.y), i);
+    input[6] = inTexture.sample(sample, float2(posInInput.x - 1,    posInInput.y + 1), i);
+    input[7] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y + 1), i);
+    input[8] = inTexture.sample(sample, float2(posInInput.x + 1,    posInInput.y + 1), i);
+    for (int j = 0; j < 9; ++j) {
+      float4 weight_x = weights[weithTo + 0 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.x += dot(input[j], weight_x);
+      
+      float4 weight_y = weights[weithTo + 1 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.y += dot(input[j], weight_y);
+      
+      float4 weight_z = weights[weithTo + 2 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.z += dot(input[j], weight_z);
+      
+      float4 weight_w = weights[weithTo + 3 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.w += dot(input[j], weight_w);
+    }
+  }
+  outTexture.write(output, gid.xy, gid.z);
+}
+
+kernel void depthwise_conv_3x3(texture2d_array<float, access::sample> inTexture [[texture(0)]],
+                               texture2d_array<float, access::write> outTexture [[texture(1)]],
+                               constant MetalConvParam &param [[buffer(0)]],
+                               const device float *weights [[buffer(1)]],
+                               uint3 gid [[thread_position_in_grid]]) {
+  
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) {
+    return;
+  }
+  uint output_slice = gid.z;
+  ushort2 stride = ushort2(param.strideX, param.strideY);
+  ushort2 posInInput = ushort2(gid.xy) * stride + ushort2(param.offsetX, param.offsetY);
+  constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
+  const uint kernelHXW = 9;
+  uint weithTo = gid.z * kernelHXW * 4;
+  float4 output = float4(0.0);
+  float4 inputs[9];
+  inputs[0] = inTexture.sample(sample, float2(posInInput.x - 1,    posInInput.y - 1), output_slice);
+  inputs[1] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y - 1), output_slice);
+  inputs[2] = inTexture.sample(sample, float2(posInInput.x + 1,    posInInput.y - 1), output_slice);
+  inputs[3] = inTexture.sample(sample, float2(posInInput.x - 1,    posInInput.y), output_slice);
+  inputs[4] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y), output_slice);
+  inputs[5] = inTexture.sample(sample, float2(posInInput.x + 1,    posInInput.y), output_slice);
+  inputs[6] = inTexture.sample(sample, float2(posInInput.x - 1,    posInInput.y + 1), output_slice);
+  inputs[7] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y + 1), output_slice);
+  inputs[8] = inTexture.sample(sample, float2(posInInput.x + 1,    posInInput.y + 1), output_slice);
+  for (int j = 0; j < 9; ++j) {
+    float4 input = inputs[j];
+    output.x += input.x * weights[weithTo + 0 * kernelHXW + j];
+    output.y += input.y * weights[weithTo + 1 * kernelHXW + j];
+    output.z += input.z * weights[weithTo + 2 * kernelHXW + j];
+    output.w += input.w * weights[weithTo + 3 * kernelHXW + j];
+  }
+  outTexture.write(output, gid.xy, gid.z);
+}
+
+kernel void conv_1x1(texture2d_array<float, access::sample> inTexture [[texture(0)]],
+                     texture2d_array<float, access::write> outTexture [[texture(1)]],
+                     constant MetalConvParam &param [[buffer(0)]],
+                     const device float4 *weights [[buffer(1)]],
+                     uint3 gid [[thread_position_in_grid]]) {
+  
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) {
+    return;
+  }
+  
+  ushort2 stride = ushort2(param.strideX, param.strideY);
+  ushort2 posInInput = ushort2(gid.xy) * stride + ushort2(param.offsetX, param.offsetY);
+  
+  constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
+  const uint kernelHXW = 1;
+  
+  uint input_arr_size = inTexture.get_array_size();
+  uint weithTo = gid.z * kernelHXW * input_arr_size * 4;
+  
+  float4 output = float4(0.0);
+  
+  float4 input;
+  for (uint i = 0; i < input_arr_size; ++i) {
+    input = inTexture.sample(sample, float2(posInInput.x, posInInput.y), i);
+    float4 weight_x = weights[weithTo + 0 * kernelHXW * input_arr_size  + i];
+    output.x += dot(input, weight_x);
+    
+    float4 weight_y = weights[weithTo + 1 * kernelHXW * input_arr_size  + i];
+    output.y += dot(input, weight_y);
+    
+    float4 weight_z = weights[weithTo + 2 * kernelHXW * input_arr_size  + i];
+    output.z += dot(input, weight_z);
+    
+    float4 weight_w = weights[weithTo + 3 * kernelHXW * input_arr_size + i];
+    output.w += dot(input, weight_w);
+  }
+  outTexture.write(output, gid.xy, gid.z);
+}
+
+
+kernel void conv_3x3_half(texture2d_array<half, access::sample> inTexture [[texture(0)]],
+                     texture2d_array<half, access::write> outTexture [[texture(1)]],
+                     constant MetalConvParam &param [[buffer(0)]],
+                     const device half4 *weights [[buffer(1)]],
+                     uint3 gid [[thread_position_in_grid]]) {
+  
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) {
+    return;
+  }
+  
+  ushort2 stride = ushort2(param.strideX, param.strideY);
+  const ushort2 posInInput = ushort2(gid.xy) * stride + ushort2(param.offsetX, param.offsetY);
+  
+  constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
+  const uint kernelHXW = 9;
+  uint input_arr_size = inTexture.get_array_size();
+  uint weithTo = gid.z * kernelHXW * input_arr_size * 4;
+  
+  float4 output = float4(0.0);
+  
+  half4 input[9];
+  for (uint i = 0; i < input_arr_size; ++i) {
+    input[0] = inTexture.sample(sample, float2(posInInput.x - 1,    posInInput.y - 1), i);
+    input[1] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y - 1), i);
+    input[2] = inTexture.sample(sample, float2(posInInput.x + 1,    posInInput.y - 1), i);
+    input[3] = inTexture.sample(sample, float2(posInInput.x - 1,    posInInput.y), i);
+    input[4] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y), i);
+    input[5] = inTexture.sample(sample, float2(posInInput.x + 1,    posInInput.y), i);
+    input[6] = inTexture.sample(sample, float2(posInInput.x - 1,    posInInput.y + 1), i);
+    input[7] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y + 1), i);
+    input[8] = inTexture.sample(sample, float2(posInInput.x + 1,    posInInput.y + 1), i);
+    for (int j = 0; j < 9; ++j) {
+      half4 weight_x = weights[weithTo + 0 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.x += dot(float4(input[j]), float4(weight_x));
+      
+      half4 weight_y = weights[weithTo + 1 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.y += dot(float4(input[j]), float4(weight_y));
+      
+      half4 weight_z = weights[weithTo + 2 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.z += dot(float4(input[j]), float4(weight_z));
+      
+      half4 weight_w = weights[weithTo + 3 * kernelHXW * input_arr_size + j * input_arr_size + i];
+      output.w += dot(float4(input[j]), float4(weight_w));
+    }
+  }
+  outTexture.write(half4(output), gid.xy, gid.z);
+}
+
+kernel void depthwise_conv_3x3_half(texture2d_array<half, access::sample> inTexture [[texture(0)]],
+                               texture2d_array<half, access::write> outTexture [[texture(1)]],
+                               constant MetalConvParam &param [[buffer(0)]],
+                               const device half *weights [[buffer(1)]],
+                               uint3 gid [[thread_position_in_grid]]) {
+  
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) {
+    return;
+  }
+  uint output_slice = gid.z;
+  ushort2 stride = ushort2(param.strideX, param.strideY);
+  ushort2 posInInput = ushort2(gid.xy) * stride + ushort2(param.offsetX, param.offsetY);
+  constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
+  const uint kernelHXW = 9;
+  uint weithTo = gid.z * kernelHXW * 4;
+  float4 output = float4(0.0);
+  half4 inputs[9];
+  inputs[0] = inTexture.sample(sample, float2(posInInput.x - 1,    posInInput.y - 1), output_slice);
+  inputs[1] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y - 1), output_slice);
+  inputs[2] = inTexture.sample(sample, float2(posInInput.x + 1,    posInInput.y - 1), output_slice);
+  inputs[3] = inTexture.sample(sample, float2(posInInput.x - 1,    posInInput.y), output_slice);
+  inputs[4] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y), output_slice);
+  inputs[5] = inTexture.sample(sample, float2(posInInput.x + 1,    posInInput.y), output_slice);
+  inputs[6] = inTexture.sample(sample, float2(posInInput.x - 1,    posInInput.y + 1), output_slice);
+  inputs[7] = inTexture.sample(sample, float2(posInInput.x,        posInInput.y + 1), output_slice);
+  inputs[8] = inTexture.sample(sample, float2(posInInput.x + 1,    posInInput.y + 1), output_slice);
+  for (int j = 0; j < 9; ++j) {
+    half4 input = inputs[j];
+    output.x += float(input.x) * float(weights[weithTo + 0 * kernelHXW + j]);
+    output.y += float(input.y) * float(weights[weithTo + 1 * kernelHXW + j]);
+    output.z += float(input.z) * float(weights[weithTo + 2 * kernelHXW + j]);
+    output.w += float(input.w) * float(weights[weithTo + 3 * kernelHXW + j]);
+  }
+  outTexture.write(half4(output), gid.xy, gid.z);
+}
+
+kernel void conv_1x1_half(texture2d_array<half, access::sample> inTexture [[texture(0)]],
+                     texture2d_array<half, access::write> outTexture [[texture(1)]],
+                     constant MetalConvParam &param [[buffer(0)]],
+                     const device half4 *weights [[buffer(1)]],
+                     uint3 gid [[thread_position_in_grid]]) {
+  
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) {
+    return;
+  }
+  
+  ushort2 stride = ushort2(param.strideX, param.strideY);
+  ushort2 posInInput = ushort2(gid.xy) * stride + ushort2(param.offsetX, param.offsetY);
+  
+  constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
+  const uint kernelHXW = 1;
+  
+  uint input_arr_size = inTexture.get_array_size();
+  uint weithTo = gid.z * kernelHXW * input_arr_size * 4;
+  
+  float4 output = float4(0.0);
+  
+  half4 input;
+  for (uint i = 0; i < input_arr_size; ++i) {
+    input = inTexture.sample(sample, float2(posInInput.x, posInInput.y), i);
+    half4 weight_x = weights[weithTo + 0 * kernelHXW * input_arr_size  + i];
+    output.x += dot(float4(input), float4(weight_x));
+    
+    half4 weight_y = weights[weithTo + 1 * kernelHXW * input_arr_size  + i];
+    output.y += dot(float4(input), float4(weight_y));
+    
+    half4 weight_z = weights[weithTo + 2 * kernelHXW * input_arr_size  + i];
+    output.z += dot(float4(input), float4(weight_z));
+    
+    half4 weight_w = weights[weithTo + 3 * kernelHXW * input_arr_size + i];
+    output.w += dot(float4(input), float4(weight_w));
+  }
+  outTexture.write(half4(output), gid.xy, gid.z);
+}
+
+

metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/metal/ConvTransposeKernel.metal

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+ 
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+ 
+ http://www.apache.org/licenses/LICENSE-2.0
+ 
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
+
+#include <metal_stdlib>
+using namespace metal;
+
+struct MetalConvTransposeParam{
+  ushort kernelW;
+  ushort kernelH;
+  
+  ushort strideX;
+  ushort strideY;
+  
+  ushort paddingX;
+  ushort paddingY;
+  
+  ushort dilationX;
+  ushort dilationY;
+};
+
+kernel void conv_transpose2x2_stride2(texture2d_array<float, access::sample> inTexture [[texture(0)]],
+                                      texture2d_array<float, access::write> outTexture [[texture(1)]],
+                                      constant MetalConvTransposeParam &param [[buffer(0)]],
+                                      const device float4 *weights [[buffer(1)]],
+                                      uint3 gid [[thread_position_in_grid]]) {
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) {
+    return;
+  }
+  
+  int input_array_size = inTexture.get_array_size();
+  int kernel_index_x = gid.x % 2;
+  int kernel_index_y = gid.y % 2;
+  int kernel_index = kernel_index_y * 2 + kernel_index_x;
+  int kernel_to = gid.z * input_array_size * 4 * 4 + (kernel_index * input_array_size);
+  int input_x = gid.x / 2;
+  int input_y = gid.y / 2;
+  
+  constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
+  float4 output = float4(0.0);
+  for (int i = 0; i < input_array_size; ++i) {
+    
+    float4 input = inTexture.sample(sample, float2(input_x, input_y), i);
+    
+    float4 kernel_slice0 = weights[kernel_to + input_array_size * 4 * 0 + i];
+    float4 kernel_slice1 = weights[kernel_to + input_array_size * 4 * 1 + i];
+    float4 kernel_slice2 = weights[kernel_to + input_array_size * 4 * 2 + i];
+    float4 kernel_slice3 = weights[kernel_to + input_array_size * 4 * 3 + i];
+    
+    output.x += dot(input, kernel_slice0);
+    
+    output.y += dot(input, kernel_slice1);
+    
+    output.z += dot(input, kernel_slice2);
+    
+    output.w += dot(input, kernel_slice3);
+  }
+  
+  outTexture.write(output, gid.xy, gid.z);
+}
+
+kernel void conv_transpose2x2_stride2_half(texture2d_array<half, access::sample> inTexture [[texture(0)]],
+                                      texture2d_array<half, access::write> outTexture [[texture(1)]],
+                                      constant MetalConvTransposeParam &param [[buffer(0)]],
+                                      const device half4 *weights [[buffer(1)]],
+                                      uint3 gid [[thread_position_in_grid]]) {
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) {
+    return;
+  }
+  
+  int input_array_size = inTexture.get_array_size();
+  int kernel_index_x = gid.x % 2;
+  int kernel_index_y = gid.y % 2;
+  int kernel_index = kernel_index_y * 2 + kernel_index_x;
+  int kernel_to = gid.z * input_array_size * 4 * 4 + (kernel_index * input_array_size);
+  int input_x = gid.x / 2;
+  int input_y = gid.y / 2;
+  
+  constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
+  float4 output = float4(0.0);
+  for (int i = 0; i < input_array_size; ++i) {
+    
+    half4 input = inTexture.sample(sample, float2(input_x, input_y), i);
+    
+    half4 kernel_slice0 = weights[kernel_to + input_array_size * 4 * 0 + i];
+    half4 kernel_slice1 = weights[kernel_to + input_array_size * 4 * 1 + i];
+    half4 kernel_slice2 = weights[kernel_to + input_array_size * 4 * 2 + i];
+    half4 kernel_slice3 = weights[kernel_to + input_array_size * 4 * 3 + i];
+    
+    output.x += dot(float4(input), float4(kernel_slice0));
+    
+    output.y += dot(float4(input), float4(kernel_slice1));
+    
+    output.z += dot(float4(input), float4(kernel_slice2));
+    
+    output.w += dot(float4(input), float4(kernel_slice3));
+  }
+  
+  outTexture.write(half4(output), gid.xy, gid.z);
+}
+
+//kernel void conv_transpose(texture2d_array<float, access::sample> inTexture [[texture(0)]],
+//                           texture2d_array<float, access::write> outTexture [[texture(1)]],
+//                           constant MetalConvTransposeParam &param [[buffer(0)]],
+//                           const device float4 *weights [[buffer(1)]],
+//                           uint3 gid [[thread_position_in_grid]]){
+//  if (gid.x >= outTexture.get_width() ||
+//      gid.y >= outTexture.get_height() ||
+//      gid.z >= outTexture.get_array_size()) {
+//    return;
+//  }
+//
+//  int input_array_size = inTexture.get_array_size();
+//
+//  uint kernel_one_output_slice = input_array_size * param.kernelW * param.kernelH;
+//
+//  uint kernel_stride_z = gid.z * 4 * (kernel_one_output_slice);
+//
+//  constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
+//
+//  float4 output;
+//
+//  for (int w = 0; w < param.kernelW; ++w) {
+//    int top = gid.x - w * param.dilationX + param.paddingX;
+//    int input_x = top / param.strideX;
+//    if (top < 0 || input_x >= int(inTexture.get_width())) {
+//      continue;
+//    }
+//
+//    for (int h = 0; h < param.kernelH; ++h) {
+//      int top_y = gid.y - h * param.dilationY + param.paddingY;
+//      int input_y = top_y / param.strideY;
+//      if (top_y < 0 || input_y >= int(inTexture.get_height())) {
+//        continue;
+//      }
+//
+//      uint kernel_index = (w * param.kernelH + h) * inTexture.get_array_size();
+//
+//      for (int slice = 0; slice < input_array_size; ++slice) {
+//
+//        float4 input;
+//        float4 kernel_slice = weights[kernel_stride_z + 0 * kernel_one_output_slice + kernel_index + slice];
+//        float4 kernel_slice1 = weights[kernel_stride_z + 1 * kernel_one_output_slice + kernel_index + slice];
+//
+//        float4 kernel_slice2 = weights[kernel_stride_z + 2 * kernel_one_output_slice + kernel_index + slice];
+//
+//        float4 kernel_slice3 = weights[kernel_stride_z + 3 * kernel_one_output_slice + kernel_index + slice];
+//
+//        input = inTexture.sample(sample, float2(input_x,    input_y), slice);
+//        output.x += dot(input, kernel_slice);
+//        output.y += dot(input, kernel_slice1);
+//        output.z += dot(input, kernel_slice2);
+//        output.w += dot(input, kernel_slice3);
+//      }
+//    }
+//  }
+//
+//  outTexture.write(output, gid.xy, gid.z);
+//}
+//

metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/metal/Elementwise.metal

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+ 
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+ 
+ http://www.apache.org/licenses/LICENSE-2.0
+ 
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
+
+#include <metal_stdlib>
+#include "Common.metal"
+
+using namespace metal;
+
+struct ElementwiseAddParam {
+  int32_t fast;
+  int32_t axis;
+  int32_t ylen;
+  int32_t xdim[4];
+  int32_t xtrans[4];
+  int32_t ydim[4];
+  int32_t ytrans[4];
+};
+
+kernel void elementwise_add(texture2d_array<float, access::read> inputX [[texture(0)]],
+                            texture2d_array<float, access::read> inputY [[texture(1)]],
+                            texture2d_array<float, access::write> outTexture [[texture(2)]],
+                            constant ElementwiseAddParam &pm [[buffer(0)]],
+                            uint3 gid [[thread_position_in_grid]]) {
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) return;
+  float4 rx, ry;
+
+  if (pm.fast == 1) {
+    rx = inputX.read(gid.xy, gid.z);
+    ry = inputY.read(gid.xy, gid.z);
+  } else {
+    rx = inputX.read(gid.xy, gid.z);
+    int32_t x_xyzn[4] = {int32_t(gid.x), int32_t(gid.y), int32_t(gid.z), 0}, x_abcd[4], t_abcd[4];
+    int32_t y_abcd[4] = {0, 0, 0, 0}, y_xyzn[4];
+    int32_t xtrans[4] = {pm.xtrans[0], pm.xtrans[1], pm.xtrans[2], pm.xtrans[3]};
+    int32_t ytrans[4] = {pm.ytrans[0], pm.ytrans[1], pm.ytrans[2], pm.ytrans[3]};
+    int32_t yshift = 4 - pm.ylen - pm.axis;
+    for (int n = 0; n < 4; n++) {
+      x_xyzn[3] = n;
+      xyzn2abcd(pm.xdim[3], x_xyzn, x_abcd);
+      invtrans(xtrans, x_abcd, t_abcd);
+      for (int k = pm.axis; k < (pm.axis + pm.ylen); k++) {
+        y_abcd[yshift+k] = t_abcd[k];
+      }
+      trans(ytrans, y_abcd, t_abcd);
+      abcd2xyzn(pm.ydim[3], t_abcd, y_xyzn);
+      ry[n] = inputY.read(uint2(y_xyzn[0], y_xyzn[1]), y_xyzn[2])[y_xyzn[3]];
+    }
+  }
+  float4 r = rx + ry;
+  outTexture.write(r, gid.xy, gid.z);
+}
+
+kernel void elementwise_add_half(texture2d_array<half, access::read> inputX [[texture(0)]],
+                            texture2d_array<half, access::read> inputY [[texture(1)]],
+                            texture2d_array<half, access::write> outTexture [[texture(2)]],
+                            constant ElementwiseAddParam &pm [[buffer(0)]],
+                            uint3 gid [[thread_position_in_grid]]) {
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) return;
+  half4 rx, ry;
+
+  if (pm.fast == 1) {
+    rx = inputX.read(gid.xy, gid.z);
+    ry = inputY.read(gid.xy, gid.z);
+  } else {
+    rx = inputX.read(gid.xy, gid.z);
+    int32_t x_xyzn[4] = {int32_t(gid.x), int32_t(gid.y), int32_t(gid.z), 0}, x_abcd[4], t_abcd[4];
+    int32_t y_abcd[4] = {0, 0, 0, 0}, y_xyzn[4];
+    int32_t xtrans[4] = {pm.xtrans[0], pm.xtrans[1], pm.xtrans[2], pm.xtrans[3]};
+    int32_t ytrans[4] = {pm.ytrans[0], pm.ytrans[1], pm.ytrans[2], pm.ytrans[3]};
+    int32_t yshift = 4 - pm.ylen - pm.axis;
+    for (int n = 0; n < 4; n++) {
+      x_xyzn[3] = n;
+      xyzn2abcd(pm.xdim[3], x_xyzn, x_abcd);
+      invtrans(xtrans, x_abcd, t_abcd);
+      for (int k = pm.axis; k < (pm.axis + pm.ylen); k++) {
+        y_abcd[yshift+k] = t_abcd[k];
+      }
+      trans(ytrans, y_abcd, t_abcd);
+      abcd2xyzn(pm.ydim[3], t_abcd, y_xyzn);
+      ry[n] = inputY.read(uint2(y_xyzn[0], y_xyzn[1]), y_xyzn[2])[y_xyzn[3]];
+    }
+  }
+  half4 r = rx + ry;
+  outTexture.write(r, gid.xy, gid.z);
+}

metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/metal/ElementwiseAddPreluKernel.inc.metal

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+ 
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+ 
+ http://www.apache.org/licenses/LICENSE-2.0
+ 
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
+
+#ifdef P
+
+#include <metal_stdlib>
+#include "Macro.metal"
+
+using namespace metal;
+
+kernel void FUNC3_(elementwise_add, PRELU_TYPE, P)(texture2d_array<P, access::read> inputX [[texture(0)]],
+                                 texture2d_array<P, access::read> inputY [[texture(1)]],
+                                 texture2d_array<P, access::write> outTexture [[texture(2)]],
+                                 constant ElementwiseAddParam &pm [[buffer(0)]],
+#ifdef PRELU_CHANNEL
+                                 const device VECTOR(P, 4) *alpha [[buffer(1)]],
+#endif
+#ifdef PRELU_ELEMENT
+                                 const device VECTOR(P, 4) *alpha [[buffer(1)]],
+#endif
+#ifdef PRELU_OTHER
+                                 const device P *alpha [[buffer(1)]],
+#endif
+                                 uint3 gid [[thread_position_in_grid]]) {
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) return;
+  VECTOR(P, 4) rx, ry;
+  
+  if (pm.fast == 1) {
+    rx = inputX.read(gid.xy, gid.z);
+    ry = inputY.read(gid.xy, gid.z);
+    } else {
+      rx = inputX.read(gid.xy, gid.z);
+      int32_t x_xyzn[4] = {int32_t(gid.x), int32_t(gid.y), int32_t(gid.z), 0}, x_abcd[4], t_abcd[4];
+      int32_t y_abcd[4] = {0, 0, 0, 0}, y_xyzn[4];
+      int32_t xtrans[4] = {pm.xtrans[0], pm.xtrans[1], pm.xtrans[2], pm.xtrans[3]};
+      int32_t ytrans[4] = {pm.ytrans[0], pm.ytrans[1], pm.ytrans[2], pm.ytrans[3]};
+      int32_t yshift = 4 - pm.ylen - pm.axis;
+      for (int n = 0; n < 4; n++) {
+        x_xyzn[3] = n;
+        xyzn2abcd(pm.xdim[3], x_xyzn, x_abcd);
+        invtrans(xtrans, x_abcd, t_abcd);
+        for (int k = pm.axis; k < (pm.axis + pm.ylen); k++) {
+          y_abcd[yshift+k] = t_abcd[k];
+        }
+        trans(ytrans, y_abcd, t_abcd);
+        abcd2xyzn(pm.ydim[3], t_abcd, y_xyzn);
+        ry[n] = inputY.read(uint2(y_xyzn[0], y_xyzn[1]), y_xyzn[2])[y_xyzn[3]];
+      }
+  }
+  VECTOR(P, 4) output = rx + ry;
+  
+#ifdef PRELU_CHANNEL
+  VECTOR(P, 4) alpha_value = alpha[gid.z];
+  output.x = output.x > 0 ? output.x : (alpha_value.x * output.x);
+  output.y = output.y > 0 ? output.y : (alpha_value.y * output.y);
+  output.z = output.z > 0 ? output.z : (alpha_value.z * output.z);
+  output.w = output.w > 0 ? output.w : (alpha_value.w * output.w);
+#endif
+#ifdef PRELU_ELEMENT
+  int alpha_to = (gid.y * outTexture.get_width() + gid.x) * outTexture.get_array_size();
+  VECTOR(P, 4) alpha_value = alpha[alpha_to + gid.z];
+  output.x = output.x > 0 ? output.x : (alpha_value.x * output.x);
+  output.y = output.y > 0 ? output.y : (alpha_value.y * output.y);
+  output.z = output.z > 0 ? output.z : (alpha_value.z * output.z);
+  output.w = output.w > 0 ? output.w : (alpha_value.w * output.w);
+#endif
+#ifdef PRELU_OTHER
+  P alpha_value = alpha[0];
+  output.x = output.x > 0 ? output.x : (alpha_value * output.x);
+  output.y = output.y > 0 ? output.y : (alpha_value * output.y);
+  output.z = output.z > 0 ? output.z : (alpha_value * output.z);
+  output.w = output.w > 0 ? output.w : (alpha_value * output.w);
+#endif
+  
+  outTexture.write(output, gid.xy, gid.z);
+}
+
+#endif

metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/metal/ElementwiseAddPreluKernel.metal

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+ 
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+ 
+ http://www.apache.org/licenses/LICENSE-2.0
+ 
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
+
+#include <metal_stdlib>
+#include "Common.metal"
+using namespace metal;
+
+struct ElementwiseAddParam {
+  int32_t fast;
+  int32_t axis;
+  int32_t ylen;
+  int32_t xdim[4];
+  int32_t xtrans[4];
+  int32_t ydim[4];
+  int32_t ytrans[4];
+};
+
+#define P float
+
+#define PRELU_CHANNEL prelu_channel
+#define PRELU_TYPE channel
+#include "ElementwiseAddPreluKernel.inc.metal"
+#undef  PRELU_TYPE
+#undef  PRELU_CHANNEL
+
+#define PRELU_ELEMENT element
+#define PRELU_TYPE prelu_element
+#include "ElementwiseAddPreluKernel.inc.metal"
+#undef  PRELU_TYPE
+#undef  PRELU_ELEMENT
+
+#define PRELU_OTHER   other
+#define PRELU_TYPE prelu_other
+#include "ElementwiseAddPreluKernel.inc.metal"
+#undef  PRELU_TYPE
+#undef  PRELU_OTHER
+
+#undef P
+
+#define P half
+
+#define PRELU_CHANNEL channel
+#define PRELU_TYPE channel
+#include "ElementwiseAddPreluKernel.inc.metal"
+#undef  PRELU_TYPE
+#undef  PRELU_CHANNEL
+
+#define PRELU_ELEMENT element
+#define PRELU_TYPE prelu_element
+#include "ElementwiseAddPreluKernel.inc.metal"
+#undef  PRELU_TYPE
+#undef  PRELU_ELEMENT
+
+#define PRELU_OTHER   other
+#define PRELU_TYPE prelu_other
+#include "ElementwiseAddPreluKernel.inc.metal"
+#undef  PRELU_TYPE
+#undef  PRELU_OTHER
+
+#undef P
+
+
+
+

metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/metal/FetchKernel.inc.metal

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+ 
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+ 
+ http://www.apache.org/licenses/LICENSE-2.0
+ 
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
+
+#ifdef P
+
+#define CONCAT3_(a, b, c) a ## _ ## b ## _ ## c
+#define CONCAT2_(a, b) a ## _ ## b
+#define CONCAT2(a, b) a ## b
+#define FUNC(m, n, q) CONCAT3_(m, n, q)
+#define FUNC_T(m, n) CONCAT2_(m, n)
+
+#define VECTOR(p, n) CONCAT2(p, n)
+
+kernel void FUNC_T(fetch, P)(texture2d_array<P, access::read> inTexture [[texture(0)]],
+                  device float *output [[buffer(0)]],
+                  uint3 gid [[thread_position_in_grid]]) {
+  if (gid.x >= inTexture.get_width() ||
+      gid.y >= inTexture.get_height() ||
+      gid.z >= inTexture.get_array_size()) {
+    return;
+  }
+
+  int input_width = inTexture.get_width();
+  int input_height = inTexture.get_height();
+  const VECTOR(P, 4) input = inTexture.read(gid.xy, gid.z);
+  int output_to = 4 * input_width * input_height;
+  
+  output[gid.z * output_to + 0 * input_width * input_height + gid.y * input_width + gid.x] = input.x;
+  
+  output[gid.z * output_to + 1 * input_width * input_height + gid.y * input_width + gid.x] = input.y;
+  output[gid.z * output_to + 2 * input_width * input_height + gid.y * input_width + gid.x] = input.z;
+  output[gid.z * output_to + 3 * input_width * input_height + gid.y * input_width + gid.x] = input.w;
+}
+
+#endif

metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/metal/FetchKernel.metal

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+ 
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+ 
+ http://www.apache.org/licenses/LICENSE-2.0
+ 
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
+
+#include <metal_stdlib>
+using namespace metal;
+
+#define P float
+
+#include "FetchKernel.inc.metal"
+
+#undef P
+
+#define P half
+
+#include "FetchKernel.inc.metal"
+
+#undef P
+
+
+kernel void fetch_placeholder(texture2d_array<float, access::read> inTexture [[texture(0)]],
+                              device float *output [[buffer(0)]],
+                              uint3 gid [[thread_position_in_grid]]) {
+  
+}
+
+kernel void fetch_placeholder_half(texture2d_array<half, access::read> inTexture [[texture(0)]],
+                                   device float *output [[buffer(0)]],
+                                   uint3 gid [[thread_position_in_grid]]) {
+}

metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/metal/Kernels.metal

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+ 
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+ 
+ http://www.apache.org/licenses/LICENSE-2.0
+ 
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
+
+#include <metal_stdlib>
+#include "Common.metal"
+using namespace metal;
+
+// 占位函数, 啥也没干
+kernel void place_holder(texture2d<half, access::read> inTexture [[texture(0)]],
+                         texture2d_array<half, access::write> outTexture [[texture(1)]],
+                         uint3 gid [[thread_position_in_grid]]) {
+}
+
+struct OutputDim {
+  ushort width;
+  ushort height;
+  ushort strideX;
+  ushort strideY;
+};
+
+kernel void resize(texture2d<half, access::read> inTexture [[texture(0)]],
+                   texture2d_array<half, access::write> outTexture [[texture(1)]],
+                   constant OutputDim &params [[buffer(0)]],
+                   uint3 gid [[thread_position_in_grid]]) {
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) return;
+  
+  constexpr sampler s(coord::pixel, filter::nearest, address::clamp_to_zero);
+  const uint2 pos = gid.xy * uint2(params.strideX, params.strideY);
+  const half4 input = inTexture.read(pos);
+  outTexture.write(half4(input.x, input.y, input.z, input.w), gid.xy, gid.z);
+}
+
+
+kernel void texture2d_to_2d_array(texture2d<float, access::read> inTexture [[texture(0)]],
+                                  texture2d_array<float, access::write> outTexture [[texture(1)]],
+                                  uint3 gid [[thread_position_in_grid]]) {
+  if (gid.x >= inTexture.get_width() ||
+      gid.y >= inTexture.get_height()){
+    return;
+  }
+  const float4 input = inTexture.read(gid.xy);
+  outTexture.write(input, gid.xy, 0);
+}
+
+kernel void texture2d_to_2d_array_half(texture2d<half, access::read> inTexture [[texture(0)]],
+                                      texture2d_array<half, access::write> outTexture [[texture(1)]],
+                                      uint3 gid [[thread_position_in_grid]]) {
+  if (gid.x >= inTexture.get_width() ||
+      gid.y >= inTexture.get_height()){
+    return;
+  }
+  const half4 input = inTexture.read(gid.xy);
+  outTexture.write(input, gid.xy, 0);
+}
+
+

metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/metal/Macro.metal

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+ 
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+ 
+ http://www.apache.org/licenses/LICENSE-2.0
+ 
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
+
+#include <metal_stdlib>
+using namespace metal;
+
+
+#define CONCAT2(a, b) a ## b
+#define CONCAT2_(a, b) a ## _ ## b
+#define CONCAT3_(a, b, c) a ## _ ## b ## _ ## c
+#define CONCAT4_(a, b, c, d) a ## _ ## b ## _ ## c ## _ ## d
+#define CONCAT5_(a, b, c, d, e) a ## _ ## b ## _ ## c ## _ ## d ## _ ## e
+
+#define FUNC(f, r, n, v, p) CONCAT5_(f, r, n, v, p)
+#define VECTOR(p, n) CONCAT2(p, n)
+#define FUNC2_(a, b) CONCAT2_(a, b)
+#define FUNC3_(a, b, c) CONCAT3_(a, b, c)
+

metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/metal/NMSFetchResultKernel.metal

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+ 
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+ 
+ http://www.apache.org/licenses/LICENSE-2.0
+ 
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
+
+#include <metal_stdlib>
+using namespace metal;
+
+kernel void nms_fetch_result(texture2d_array<float, access::read> inTexture [[texture(0)]],
+    device float *output [[buffer(0)]],
+    uint3 gid [[thread_position_in_grid]]) {
+  
+  if (gid.x >= inTexture.get_width() ||
+      gid.y >= inTexture.get_height() ||
+      gid.z >= inTexture.get_array_size()) {
+    return;
+  }
+  
+  int input_width = inTexture.get_width();
+  const float4 input = inTexture.read(gid.xy, gid.z);
+  output[gid.y * input_width + gid.x] = input.x;
+  
+}
+
+
+kernel void nms_fetch_result_half(texture2d_array<half, access::read> inTexture [[texture(0)]],
+                             device float *output [[buffer(0)]],
+                             uint3 gid [[thread_position_in_grid]]) {
+  
+  if (gid.x >= inTexture.get_width() ||
+      gid.y >= inTexture.get_height() ||
+      gid.z >= inTexture.get_array_size()) {
+    return;
+  }
+  
+  int input_width = inTexture.get_width();
+  const half4 input = inTexture.read(gid.xy, gid.z);
+  output[gid.y * input_width + gid.x] = input.x;
+}
+
+kernel void nms_fetch_bbox(texture2d_array<float, access::read> inTexture [[texture(0)]],
+    device float4 *output [[buffer(0)]],
+    uint3 gid [[thread_position_in_grid]]) {
+  
+  if (gid.x >= inTexture.get_width() ||
+      gid.y >= inTexture.get_height() ||
+      gid.z >= inTexture.get_array_size()) {
+    return;
+  }
+  
+  int input_width = inTexture.get_width();
+//  int input_height = inTexture.get_height();
+  const float4 input = inTexture.read(gid.xy, gid.z);
+  output[gid.y * input_width + gid.x] = input;
+}
+
+kernel void nms_fetch_bbox_half(texture2d_array<half, access::read> inTexture [[texture(0)]],
+                           device float4 *output [[buffer(0)]],
+                           uint3 gid [[thread_position_in_grid]]) {
+  if (gid.x >= inTexture.get_width() ||
+      gid.y >= inTexture.get_height() ||
+      gid.z >= inTexture.get_array_size()) {
+    return;
+  }
+  
+  int input_width = inTexture.get_width();
+//  int input_height = inTexture.get_height();
+  const half4 input = inTexture.read(gid.xy, gid.z);
+  output[gid.y * input_width + gid.x] = float4(input);
+}
+

metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/metal/PoolKernel.inc.metal

+//
+//  PoolKernel.inc.metal
+//  paddle-mobile
+//
+//  Created by liuRuiLong on 2018/12/29.
+//  Copyright © 2018 orange. All rights reserved.
+//
+
+#ifdef P
+
+kernel void FUNC2_(pool, P)(texture2d_array<P, access::read> inTexture [[texture(0)]],
+                 texture2d_array<P, access::write> outTexture [[texture(1)]],
+                 constant PoolParam &pm [[buffer(0)]],
+                 uint3 gid [[thread_position_in_grid]]) {
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) return;
+  int xmin = gid.x * pm.strideX - pm.paddingX;
+  int xmax = min(xmin + pm.ksizeX, int(inTexture.get_width()));
+  xmin = max(xmin, 0);
+  int ymin = gid.y * pm.strideX - pm.paddingX;
+  int ymax = min(ymin + pm.ksizeX, int(inTexture.get_height()));
+  ymin = max(ymin, 0);
+  
+  VECTOR(P, 4) r = 0;
+  if (pm.poolType == 0) {
+    r = inTexture.read(uint2(xmin, ymin), gid.z);
+    for (int x = xmin; x < xmax; x++) {
+      for (int y = ymin; y < ymax; y++) {
+        r = fmax(r, inTexture.read(uint2(x, y), gid.z));
+      }
+    }
+  } else if (pm.poolType == 1) {
+    for (int x = xmin; x < xmax; x++) {
+      for (int y = ymin; y < ymax; y++) {
+        r += inTexture.read(uint2(x, y), gid.z);
+      }
+    }
+    r /= (xmax - xmin) * (ymax - ymin);
+  }
+  outTexture.write(r, gid.xy, gid.z);
+}
+
+#endif

metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/metal/PoolKernel.metal

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+ 
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+ 
+ http://www.apache.org/licenses/LICENSE-2.0
+ 
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
+
+#include <metal_stdlib>
+#include "Macro.metal"
+
+using namespace metal;
+
+struct PoolParam {
+  int ksizeX;
+  int ksizeY;
+  int strideX;
+  int strideY;
+  int paddingX;
+  int paddingY;
+  int poolType;
+};
+
+#define P float
+#import "PoolKernel.inc.metal"
+#undef P
+
+#define P half
+#import "PoolKernel.inc.metal"
+#undef P

metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/metal/PreluKernel.metal

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+ 
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+ 
+ http://www.apache.org/licenses/LICENSE-2.0
+ 
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
+
+#include <metal_stdlib>
+using namespace metal;
+
+kernel void prelu_channel(texture2d_array<float, access::sample> inTexture [[texture(0)]],
+                           texture2d_array<float, access::write> outTexture [[texture(1)]],
+                           const device float4 *alpha [[buffer(0)]],
+                           uint3 gid [[thread_position_in_grid]]){
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) {
+    return;
+  }
+  
+  constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
+  float4 input = inTexture.sample(sample, float2(gid.x, gid.y), gid.z);
+  float4 alpha_value = alpha[gid.z];
+  float4 output;
+  output.x = input.x > 0 ? input.x : (alpha_value.x * input.x);
+  output.y = input.y > 0 ? input.y : (alpha_value.y * input.y);
+  output.z = input.z > 0 ? input.z : (alpha_value.z * input.z);
+  output.w = input.w > 0 ? input.w : (alpha_value.w * input.w);
+  outTexture.write(output, gid.xy, gid.z);
+}
+
+kernel void prelu_element(texture2d_array<float, access::sample> inTexture [[texture(0)]],
+                          texture2d_array<float, access::write> outTexture [[texture(1)]],
+                          const device float4 *alpha [[buffer(0)]],
+                          uint3 gid [[thread_position_in_grid]]){
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) {
+    return;
+  }
+  
+  constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
+  float4 input = inTexture.sample(sample, float2(gid.x, gid.y), gid.z);
+
+  int alpha_to = (gid.y * inTexture.get_width() + gid.x) * inTexture.get_array_size();
+  float4 alpha_value = alpha[alpha_to + gid.z];
+
+  float4 output;
+  output.x = input.x > 0 ? input.x : (alpha_value.x * input.x);
+  output.y = input.y > 0 ? input.y : (alpha_value.y * input.y);
+  output.z = input.z > 0 ? input.z : (alpha_value.z * input.z);
+  output.w = input.w > 0 ? input.w : (alpha_value.w * input.w);
+  outTexture.write(output, gid.xy, gid.z);
+}
+
+kernel void prelu_other(texture2d_array<float, access::sample> inTexture [[texture(0)]],
+                          texture2d_array<float, access::write> outTexture [[texture(1)]],
+                          const device float *alpha [[buffer(0)]],
+                          uint3 gid [[thread_position_in_grid]]){
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) {
+    return;
+  }
+  
+  constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
+  float4 input = inTexture.sample(sample, float2(gid.x, gid.y), gid.z);
+  float alpha_value = alpha[0];
+  float4 output;
+  output.x = input.x > 0 ? input.x : (alpha_value * input.x);
+  output.y = input.y > 0 ? input.y : (alpha_value * input.y);
+  output.z = input.z > 0 ? input.z : (alpha_value * input.z);
+  output.w = input.w > 0 ? input.w : (alpha_value * input.w);
+  outTexture.write(output, gid.xy, gid.z);
+}
+
+
+kernel void prelu_channel_half(texture2d_array<half, access::sample> inTexture [[texture(0)]],
+                          texture2d_array<half, access::write> outTexture [[texture(1)]],
+                          const device half4 *alpha [[buffer(0)]],
+                          uint3 gid [[thread_position_in_grid]]){
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) {
+    return;
+  }
+  
+  constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
+  half4 input = inTexture.sample(sample, float2(gid.x, gid.y), gid.z);
+  half4 alpha_value = alpha[gid.z];
+  half4 output;
+  output.x = input.x > 0 ? input.x : (alpha_value.x * input.x);
+  output.y = input.y > 0 ? input.y : (alpha_value.y * input.y);
+  output.z = input.z > 0 ? input.z : (alpha_value.z * input.z);
+  output.w = input.w > 0 ? input.w : (alpha_value.w * input.w);
+  outTexture.write(output, gid.xy, gid.z);
+}
+
+kernel void prelu_element_half(texture2d_array<half, access::sample> inTexture [[texture(0)]],
+                          texture2d_array<half, access::write> outTexture [[texture(1)]],
+                          const device half4 *alpha [[buffer(0)]],
+                          uint3 gid [[thread_position_in_grid]]){
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) {
+    return;
+  }
+  
+  constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
+  half4 input = inTexture.sample(sample, float2(gid.x, gid.y), gid.z);
+  
+  int alpha_to = (gid.y * inTexture.get_width() + gid.x) * inTexture.get_array_size();
+  half4 alpha_value = alpha[alpha_to + gid.z];
+  
+  half4 output;
+  output.x = input.x > 0 ? input.x : (alpha_value.x * input.x);
+  output.y = input.y > 0 ? input.y : (alpha_value.y * input.y);
+  output.z = input.z > 0 ? input.z : (alpha_value.z * input.z);
+  output.w = input.w > 0 ? input.w : (alpha_value.w * input.w);
+  outTexture.write(output, gid.xy, gid.z);
+}
+
+kernel void prelu_other_half(texture2d_array<half, access::sample> inTexture [[texture(0)]],
+                        texture2d_array<half, access::write> outTexture [[texture(1)]],
+                        const device half *alpha [[buffer(0)]],
+                        uint3 gid [[thread_position_in_grid]]){
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) {
+    return;
+  }
+  
+  constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
+  half4 input = inTexture.sample(sample, float2(gid.x, gid.y), gid.z);
+  half alpha_value = alpha[0];
+  half4 output;
+  output.x = input.x > 0 ? input.x : (alpha_value * input.x);
+  output.y = input.y > 0 ? input.y : (alpha_value * input.y);
+  output.z = input.z > 0 ? input.z : (alpha_value * input.z);
+  output.w = input.w > 0 ? input.w : (alpha_value * input.w);
+  outTexture.write(output, gid.xy, gid.z);
+}
+
+

metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/metal/PriorBoxKernel.metal

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+ 
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+ 
+ http://www.apache.org/licenses/LICENSE-2.0
+ 
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
+
+#include <metal_stdlib>
+using namespace metal;
+
+struct PriorBoxMetalParam {
+  float offset;
+  float stepWidth;
+  float stepHeight;
+  float minSize;
+  float maxSize;
+  float imageWidth;
+  float imageHeight;
+  
+  bool clip;
+  
+  uint numPriors;
+  uint aspecRatiosSize;
+  uint minSizeSize;
+  uint maxSizeSize;
+};
+
+kernel void prior_box(texture2d_array<float, access::read> inTexture [[texture(0)]],
+                      texture2d_array<float, access::write> outBoxTexture [[texture(1)]],
+                      texture2d_array<float, access::write> varianceTexture [[texture(2)]],
+                      const device float *aspect_ratios [[buffer(0)]],
+                      constant PriorBoxMetalParam &param [[buffer(1)]],
+                      const device float4 *variances [[buffer(2)]],
+                      uint3 gid [[thread_position_in_grid]]) {
+  if (gid.x >= outBoxTexture.get_width() ||
+      gid.y >= outBoxTexture.get_height() ||
+      gid.z >= outBoxTexture.get_array_size()) return;
+  
+  float center_x = (gid.x + param.offset) * param.stepWidth;
+  float center_y = (gid.y + param.offset) * param.stepHeight;
+  
+  float box_width, box_height;
+  
+  if (gid.z < param.aspecRatiosSize) {
+    float ar = aspect_ratios[gid.z];
+    box_width = param.minSize * sqrt(ar) / 2;
+    box_height = param.minSize / sqrt(ar) / 2;
+    float4 box;
+    box.x = (center_x - box_width) / param.imageWidth;
+    box.y = (center_y - box_height) / param.imageHeight;
+    box.z = (center_x + box_width) / param.imageWidth;
+    box.w = (center_y + box_height) / param.imageHeight;
+    
+    float4 res;
+    if (param.clip) {
+      res = fmin(fmax(box, 0.0), 1.0);
+    } else {
+      res = box;
+    }
+    
+    outBoxTexture.write(res, gid.xy, gid.z);
+  } else if (gid.z >= param.aspecRatiosSize) {
+    if (param.maxSizeSize > 0) {
+      box_width = box_height = sqrt(param.minSize * param.maxSize) / 2;
+      float4 max_box;
+      max_box.x = (center_x - box_width) / param.imageWidth;
+      max_box.y = (center_y - box_height) / param.imageHeight;
+      max_box.z = (center_x + box_width) / param.imageWidth;
+      max_box.w = (center_y + box_height) / param.imageHeight;
+
+      float4 res;
+      if (param.clip) {
+        res = min(max(max_box, 0.0), 1.0);
+      } else {
+        res = max_box;
+      }
+      outBoxTexture.write(max_box, gid.xy, gid.z);
+    }
+  }
+  
+  float4 variance = variances[0];
+  if (gid.z < param.numPriors) {
+    float4 variances_output;
+    variances_output.x = variance.x;
+    variances_output.y = variance.y;
+    variances_output.z = variance.z;
+    variances_output.w = variance.w;
+    varianceTexture.write(variances_output, gid.xy, gid.z);
+  }
+}
+
+
+kernel void prior_box_half(texture2d_array<half, access::read> inTexture [[texture(0)]],
+                      texture2d_array<half, access::write> outBoxTexture [[texture(1)]],
+                      texture2d_array<half, access::write> varianceTexture [[texture(2)]],
+                      const device half *aspect_ratios [[buffer(0)]],
+                      constant PriorBoxMetalParam &param [[buffer(1)]],
+                      const device float4 *variances [[buffer(2)]],
+                      uint3 gid [[thread_position_in_grid]]) {
+  if (gid.x >= outBoxTexture.get_width() ||
+      gid.y >= outBoxTexture.get_height() ||
+      gid.z >= outBoxTexture.get_array_size()) return;
+  
+  float center_x = (gid.x + param.offset) * param.stepWidth;
+  float center_y = (gid.y + param.offset) * param.stepHeight;
+  
+  float box_width, box_height;
+  
+  if (gid.z < param.aspecRatiosSize) {
+    half ar = aspect_ratios[gid.z];
+    box_width = param.minSize * sqrt(ar) / 2;
+    box_height = param.minSize / sqrt(ar) / 2;
+    float4 box;
+    box.x = (center_x - box_width) / param.imageWidth;
+    box.y = (center_y - box_height) / param.imageHeight;
+    box.z = (center_x + box_width) / param.imageWidth;
+    box.w = (center_y + box_height) / param.imageHeight;
+    
+    float4 res;
+    if (param.clip) {
+      res = fmin(fmax(box, 0.0), 1.0);
+    } else {
+      res = box;
+    }
+    
+    outBoxTexture.write(half4(res), gid.xy, gid.z);
+  } else if (gid.z >= param.aspecRatiosSize) {
+    if (param.maxSizeSize > 0) {
+      box_width = box_height = sqrt(param.minSize * param.maxSize) / 2;
+      float4 max_box;
+      max_box.x = (center_x - box_width) / param.imageWidth;
+      max_box.y = (center_y - box_height) / param.imageHeight;
+      max_box.z = (center_x + box_width) / param.imageWidth;
+      max_box.w = (center_y + box_height) / param.imageHeight;
+      
+      float4 res;
+      if (param.clip) {
+        res = min(max(max_box, 0.0), 1.0);
+      } else {
+        res = max_box;
+      }
+      outBoxTexture.write(half4(max_box), gid.xy, gid.z);
+    }
+  }
+  
+  float4 variance = variances[0];
+  if (gid.z < param.numPriors) {
+    float4 variances_output;
+    variances_output.x = variance.x;
+    variances_output.y = variance.y;
+    variances_output.z = variance.z;
+    variances_output.w = variance.w;
+    varianceTexture.write(half4(variances_output), gid.xy, gid.z);
+  }
+}
+
+
+
+kernel void prior_box_MinMaxAspectRatiosOrder(texture2d_array<float, access::read> inTexture [[texture(0)]],
+                      texture2d_array<float, access::write> outBoxTexture [[texture(1)]],
+                      texture2d_array<float, access::write> varianceTexture [[texture(2)]],
+                      const device float *aspect_ratios [[buffer(0)]],
+                      constant PriorBoxMetalParam &param [[buffer(1)]],
+                      const device float4 *variances [[buffer(2)]],
+                      uint3 gid [[thread_position_in_grid]]) {
+  if (gid.x >= outBoxTexture.get_width() ||
+      gid.y >= outBoxTexture.get_height() ||
+      gid.z >= outBoxTexture.get_array_size()) return;
+  
+  float center_x = (gid.x + param.offset) * param.stepWidth;
+  float center_y = (gid.y + param.offset) * param.stepHeight;
+  
+  float box_width, box_height;
+  
+  
+  
+  if (gid.z == 0) {
+    box_width = box_height = param.minSize / 2;
+    
+    float4 box;
+    box.x = (center_x - box_width) / param.imageWidth;
+    box.y = (center_y - box_height) / param.imageHeight;
+    box.z = (center_x + box_width) / param.imageWidth;
+    box.w = (center_y + box_height) / param.imageHeight;
+    
+    float4 res;
+    if (param.clip) {
+      res = fmin(fmax(box, 0.0), 1.0);
+    } else {
+      res = box;
+    }
+
+    outBoxTexture.write(res, gid.xy, gid.z);
+  }
+  
+  if (gid.z == 1 && param.maxSizeSize > 0) {
+    
+    box_width = box_height = sqrt(param.minSize * param.maxSize) / 2;
+    float4 max_box;
+    max_box.x = (center_x - box_width) / param.imageWidth;
+    max_box.y = (center_y - box_height) / param.imageHeight;
+    max_box.z = (center_x + box_width) / param.imageWidth;
+    max_box.w = (center_y + box_height) / param.imageHeight;
+    
+    float4 res;
+    if (param.clip) {
+      res = min(max(max_box, 0.0), 1.0);
+    } else {
+      res = max_box;
+    }
+    outBoxTexture.write(res, gid.xy, gid.z);
+  }
+  
+  int aspect_to = 0;
+  if (param.maxSizeSize > 0) {
+    aspect_to = gid.z - 2;
+  } else {
+    aspect_to = gid.z - 1;
+  }
+  
+
+  
+  
+  if (aspect_to >= 0 && aspect_to < int(param.aspecRatiosSize)) {
+    
+    int skip = 0;
+    for (int i = 0; i < aspect_to + 1; ++i) {
+      if (fabs(aspect_ratios[i] - 1.) < 1e-6) {
+        skip += 1;
+      }
+    }
+    aspect_to += skip;
+    
+    float ar = aspect_ratios[aspect_to];
+    
+    box_width = param.minSize * sqrt(ar) / 2;
+    box_height = param.minSize / sqrt(ar) / 2;
+    float4 box;
+    box.x = (center_x - box_width) / param.imageWidth;
+    box.y = (center_y - box_height) / param.imageHeight;
+    box.z = (center_x + box_width) / param.imageWidth;
+    box.w = (center_y + box_height) / param.imageHeight;
+    
+    float4 res;
+    if (param.clip) {
+      res = fmin(fmax(box, 0.0), 1.0);
+    } else {
+      res = box;
+    }
+    
+    outBoxTexture.write(res, gid.xy, gid.z);
+  }
+  
+  float4 variance = variances[0];
+  if (gid.z < param.numPriors) {
+    float4 variances_output;
+    variances_output.x = variance.x;
+    variances_output.y = variance.y;
+    variances_output.z = variance.z;
+    variances_output.w = variance.w;
+    varianceTexture.write(variances_output, gid.xy, gid.z);
+  }
+}
+
+
+kernel void prior_box_MinMaxAspectRatiosOrder_half(texture2d_array<half, access::read> inTexture [[texture(0)]],
+                           texture2d_array<half, access::write> outBoxTexture [[texture(1)]],
+                           texture2d_array<half, access::write> varianceTexture [[texture(2)]],
+                           const device half *aspect_ratios [[buffer(0)]],
+                           constant PriorBoxMetalParam &param [[buffer(1)]],
+                           const device float4 *variances [[buffer(2)]],
+                           uint3 gid [[thread_position_in_grid]]) {
+  if (gid.x >= outBoxTexture.get_width() ||
+      gid.y >= outBoxTexture.get_height() ||
+      gid.z >= outBoxTexture.get_array_size()) return;
+  
+  float center_x = (gid.x + param.offset) * param.stepWidth;
+  float center_y = (gid.y + param.offset) * param.stepHeight;
+  
+  float box_width, box_height;
+  
+  
+  
+  if (gid.z == 0) {
+    box_width = box_height = param.minSize / 2;
+    
+    float4 box;
+    box.x = (center_x - box_width) / param.imageWidth;
+    box.y = (center_y - box_height) / param.imageHeight;
+    box.z = (center_x + box_width) / param.imageWidth;
+    box.w = (center_y + box_height) / param.imageHeight;
+    
+    float4 res;
+    if (param.clip) {
+      res = fmin(fmax(box, 0.0), 1.0);
+    } else {
+      res = box;
+    }
+    
+    outBoxTexture.write(half4(res), gid.xy, gid.z);
+  }
+  
+  if (gid.z == 1 && param.maxSizeSize > 0) {
+    
+    box_width = box_height = sqrt(param.minSize * param.maxSize) / 2;
+    float4 max_box;
+    max_box.x = (center_x - box_width) / param.imageWidth;
+    max_box.y = (center_y - box_height) / param.imageHeight;
+    max_box.z = (center_x + box_width) / param.imageWidth;
+    max_box.w = (center_y + box_height) / param.imageHeight;
+    
+    float4 res;
+    if (param.clip) {
+      res = min(max(max_box, 0.0), 1.0);
+    } else {
+      res = max_box;
+    }
+    outBoxTexture.write(half4(res), gid.xy, gid.z);
+  }
+  
+  int aspect_to = 0;
+  if (param.maxSizeSize > 0) {
+    aspect_to = gid.z - 2;
+  } else {
+    aspect_to = gid.z - 1;
+  }
+  
+  if (aspect_to > 0 && aspect_to < int(param.aspecRatiosSize) && fabs(aspect_ratios[aspect_to] - 1.) > 1e-6) {
+    float ar = aspect_ratios[aspect_to];
+    
+    box_width = param.minSize * sqrt(ar) / 2;
+    box_height = param.minSize / sqrt(ar) / 2;
+    float4 box;
+    box.x = (center_x - box_width) / param.imageWidth;
+    box.y = (center_y - box_height) / param.imageHeight;
+    box.z = (center_x + box_width) / param.imageWidth;
+    box.w = (center_y + box_height) / param.imageHeight;
+    
+    float4 res;
+    if (param.clip) {
+      res = fmin(fmax(box, 0.0), 1.0);
+    } else {
+      res = box;
+    }
+    
+    outBoxTexture.write(half4(res), gid.xy, gid.z);
+  }
+  
+  float4 variance = variances[0];
+  if (gid.z < param.numPriors) {
+    float4 variances_output;
+    variances_output.x = variance.x;
+    variances_output.y = variance.y;
+    variances_output.z = variance.z;
+    variances_output.w = variance.w;
+    varianceTexture.write(half4(variances_output), gid.xy, gid.z);
+  }
+}
+
+

metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/metal/ReluKernel.metal

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+ 
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+ 
+ http://www.apache.org/licenses/LICENSE-2.0
+ 
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
+
+#include <metal_stdlib>
+using namespace metal;
+
+
+kernel void relu_half(texture2d_array<half, access::sample> inTexture [[texture(0)]],
+                 texture2d_array<half, access::write> outTexture [[texture(1)]],
+                 uint3 gid [[thread_position_in_grid]]) {
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) return;
+  constexpr sampler s(coord::pixel, filter::nearest, address::clamp_to_zero);
+  const half4 input = inTexture.read(gid.xy, gid.z);
+  const float4 relu = fmax((float4)input, 0.0);
+  outTexture.write(half4(relu), gid.xy, gid.z);
+}
+
+kernel void relu(texture2d_array<float, access::sample> inTexture [[texture(0)]],
+                      texture2d_array<float, access::write> outTexture [[texture(1)]],
+                      uint3 gid [[thread_position_in_grid]]) {
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) return;
+  constexpr sampler s(coord::pixel, filter::nearest, address::clamp_to_zero);
+  const float4 input = inTexture.read(gid.xy, gid.z);
+  const float4 relu = fmax((float4)input, 0.0);
+  outTexture.write(float4(relu), gid.xy, gid.z);
+}

metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/metal/ReshapeKernel.inc.metal

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+ 
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+ 
+ http://www.apache.org/licenses/LICENSE-2.0
+ 
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
+
+#ifdef P
+
+#define CONCAT2(a, b) a ## b
+#define CONCAT2_(a, b) a ## _ ## b
+#define CONCAT3_(a, b, c) a ## _ ## b ## _ ## c
+#define CONCAT4_(a, b, c, d) a ## _ ## b ## _ ## c ## _ ## d
+
+#define FUNC(f, r1, r2, p) CONCAT4_(f, r1, r2, p)
+#define VECTOR(p, n) CONCAT2(p, n)
+#define FUNC_R(f, r) CONCAT2_(f, r)
+
+kernel void FUNC(reshape, RIN, ROUT, P)(texture2d_array<P, access::read> inTexture [[texture(0)]],
+                    texture2d_array<P, access::write> outTexture [[texture(1)]],
+                    constant ReshapeParam &rp [[buffer(0)]],
+                    uint3 gid [[thread_position_in_grid]]) {
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) return;
+
+  int oxyzn[4] = {int(gid.x), int(gid.y), int(gid.z), 0}, oabcd[4], ixyzn[4], iabcd[4];
+  ReshapeParam lrp = rp;
+  int oC = lrp.odim[lrp.otrans[3]];
+  int iC = lrp.idim[lrp.itrans[3]];
+  int count = lrp.odim[0] * lrp.odim[1] * lrp.odim[2] * lrp.odim[3];
+  VECTOR(P, 4) r;
+  for (int n = 0; n < 4; n++) {
+    oxyzn[3] = n;
+#if ROUT == 4
+    xyzn2abcd_4(oC, oxyzn, oabcd);
+#else
+    FUNC_R(xyzn2abcd, ROUT)(oxyzn, oabcd);
+#endif
+    int tabcd[4];
+    invtrans(lrp.otrans, oabcd, tabcd);
+    int index = abcd2index(lrp.odim, tabcd);
+    if (index < count) {
+      index2abcd(lrp.idim, index, tabcd);
+      trans(lrp.itrans, tabcd, iabcd);
+#if RIN == 4
+      abcd2xyzn_4(iC, iabcd, ixyzn);
+#else
+      FUNC_R(abcd2xyzn, RIN)(iabcd, ixyzn);
+#endif
+      r[n] = inTexture.read(uint2(ixyzn[0], ixyzn[1]), ixyzn[2])[ixyzn[3]];
+    } else {
+      r[n] = 0;
+    }
+  }
+  outTexture.write(r, gid.xy, gid.z);
+}
+
+#endif

metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/metal/ReshapeKernel.metal

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+ 
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+ 
+ http://www.apache.org/licenses/LICENSE-2.0
+ 
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONRITIONS OF ANY KINR, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
+
+#include <metal_stdlib>
+#include "Common.metal"
+
+using namespace metal;
+
+struct ReshapeParam {
+  int32_t idim[4];
+  int32_t itrans[4];
+  int32_t odim[4];
+  int32_t otrans[4];
+};
+
+#define P float
+#define RIN 4
+#define ROUT 4
+#include "ReshapeKernel.inc.metal"
+#undef ROUT
+#define ROUT 3
+#include "ReshapeKernel.inc.metal"
+#undef ROUT
+#define ROUT 2
+#include "ReshapeKernel.inc.metal"
+#undef ROUT
+#define ROUT 1
+#include "ReshapeKernel.inc.metal"
+#undef ROUT
+#undef RIN
+
+#define RIN 3
+#define ROUT 4
+#include "ReshapeKernel.inc.metal"
+#undef ROUT
+#define ROUT 3
+#include "ReshapeKernel.inc.metal"
+#undef ROUT
+#define ROUT 2
+#include "ReshapeKernel.inc.metal"
+#undef ROUT
+#define ROUT 1
+#include "ReshapeKernel.inc.metal"
+#undef ROUT
+#undef RIN
+
+#define RIN 2
+#define ROUT 4
+#include "ReshapeKernel.inc.metal"
+#undef ROUT
+#define ROUT 3
+#include "ReshapeKernel.inc.metal"
+#undef ROUT
+#define ROUT 2
+#include "ReshapeKernel.inc.metal"
+#undef ROUT
+#define ROUT 1
+#include "ReshapeKernel.inc.metal"
+#undef ROUT
+#undef RIN
+
+#define RIN 1
+#define ROUT 4
+#include "ReshapeKernel.inc.metal"
+#undef ROUT
+#define ROUT 3
+#include "ReshapeKernel.inc.metal"
+#undef ROUT
+#define ROUT 2
+#include "ReshapeKernel.inc.metal"
+#undef ROUT
+#define ROUT 1
+#include "ReshapeKernel.inc.metal"
+#undef ROUT
+#undef RIN
+
+#undef P
+
+#define P half
+#define RIN 4
+#define ROUT 4
+#include "ReshapeKernel.inc.metal"
+#undef ROUT
+#define ROUT 3
+#include "ReshapeKernel.inc.metal"
+#undef ROUT
+#define ROUT 2
+#include "ReshapeKernel.inc.metal"
+#undef ROUT
+#define ROUT 1
+#include "ReshapeKernel.inc.metal"
+#undef ROUT
+#undef RIN
+
+#define RIN 3
+#define ROUT 4
+#include "ReshapeKernel.inc.metal"
+#undef ROUT
+#define ROUT 3
+#include "ReshapeKernel.inc.metal"
+#undef ROUT
+#define ROUT 2
+#include "ReshapeKernel.inc.metal"
+#undef ROUT
+#define ROUT 1
+#include "ReshapeKernel.inc.metal"
+#undef ROUT
+#undef RIN
+
+#define RIN 2
+#define ROUT 4
+#include "ReshapeKernel.inc.metal"
+#undef ROUT
+#define ROUT 3
+#include "ReshapeKernel.inc.metal"
+#undef ROUT
+#define ROUT 2
+#include "ReshapeKernel.inc.metal"
+#undef ROUT
+#define ROUT 1
+#include "ReshapeKernel.inc.metal"
+#undef ROUT
+#undef RIN
+
+#define RIN 1
+#define ROUT 4
+#include "ReshapeKernel.inc.metal"
+#undef ROUT
+#define ROUT 3
+#include "ReshapeKernel.inc.metal"
+#undef ROUT
+#define ROUT 2
+#include "ReshapeKernel.inc.metal"
+#undef ROUT
+#define ROUT 1
+#include "ReshapeKernel.inc.metal"
+#undef ROUT
+#undef RIN
+#undef P

metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/metal/ResizeBilinear.metal

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+ 
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+ 
+ http://www.apache.org/licenses/LICENSE-2.0
+ 
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
+
+#include <metal_stdlib>
+using namespace metal;
+
+struct resize_bilinear_param {
+//  int32_t out_h;
+//  int32_t out_w;
+  float ratio_h;
+  float ratio_w;
+};
+
+kernel void resize_bilinear(texture2d_array<float, access::read> input [[texture(0)]],
+                     texture2d_array<float, access::write> output [[texture(2)]],
+                     constant resize_bilinear_param & pm [[buffer(0)]],
+                     uint3 gid [[thread_position_in_grid]]) {
+  float4 r;
+  if ((input.get_width() == output.get_width()) && (input.get_height() == output.get_height())) {
+    r = input.read(gid.xy, gid.z);
+  } else {
+    float w = gid.x * pm.ratio_w;
+    float h = gid.y * pm.ratio_h;
+    uint w0 = w, h0 = h;
+    uint w1 = w0 + 1, h1 = h0 + 1;
+    float w1lambda = w - w0, h1lambda = h - h0;
+    float w2lambda = 1.0 - w1lambda, h2lambda = 1.0 - h1lambda;
+    if (w1 >= input.get_width()) w1 = w0;
+    if (h1 >= input.get_height()) h1 = h0;
+    float4 r0 = input.read(uint2(w0, h0), gid.z);
+    float4 r1 = input.read(uint2(w1, h0), gid.z);
+    float4 r2 = input.read(uint2(w0, h1), gid.z);
+    float4 r3 = input.read(uint2(w1, h1), gid.z);
+    r = h2lambda * (w2lambda * r0 + w1lambda * r1) + h1lambda * (w2lambda * r2 + w1lambda * r3);
+  }
+  output.write(r, gid.xy, gid.z);
+}
+
+kernel void resize_bilinear_half(texture2d_array<half, access::read> input [[texture(0)]],
+                            texture2d_array<half, access::write> output [[texture(2)]],
+                            constant resize_bilinear_param & pm [[buffer(0)]],
+                            uint3 gid [[thread_position_in_grid]]) {
+  
+  half4 r;
+  if ((input.get_width() == output.get_width()) && (input.get_height() == output.get_height())) {
+    r = input.read(gid.xy, gid.z);
+  } else {
+    half w = gid.x * pm.ratio_w;
+    half h = gid.y * pm.ratio_h;
+    uint w0 = w, h0 = h;
+    uint w1 = w0 + 1, h1 = h0 + 1;
+    half w1lambda = w - w0, h1lambda = h - h0;
+    half w2lambda = 1.0 - w1lambda, h2lambda = 1.0 - h1lambda;
+    if (w1 >= input.get_width()) w1 = w0;
+    if (h1 >= input.get_height()) h1 = h0;
+    half4 r0 = input.read(uint2(w0, h0), gid.z);
+    half4 r1 = input.read(uint2(w1, h0), gid.z);
+    half4 r2 = input.read(uint2(w0, h1), gid.z);
+    half4 r3 = input.read(uint2(w1, h1), gid.z);
+    r = h2lambda * (w2lambda * r0 + w1lambda * r1) + h1lambda * (w2lambda * r2 + w1lambda * r3);
+  }
+  output.write(r, gid.xy, gid.z);
+  output.write(r, gid.xy, gid.z);
+}

metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/metal/Scale.metal

+//
+//  Scale.metal
+//  paddle-mobile
+//
+//  Created by liuRuiLong on 2019/1/4.
+//  Copyright © 2019 orange. All rights reserved.
+//
+
+#include <metal_stdlib>
+using namespace metal;
+
+kernel void scale(texture2d<float, access::sample> inTexture [[texture(0)]], texture2d<float, access::write> outTexture [[texture(1)]], uint2 gid [[thread_position_in_grid]]) {
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height()) return;
+  float w_stride = inTexture.get_width() / outTexture.get_width();
+  float h_stride = inTexture.get_height() / outTexture.get_height();
+  constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
+  float4 input = inTexture.sample(sample, float2(gid.x * w_stride,    gid.y * h_stride), 0);
+  outTexture.write(input, gid);
+}
+
+kernel void scale_half(texture2d<float, access::sample> inTexture [[texture(0)]], texture2d<half, access::write> outTexture [[texture(1)]], uint2 gid [[thread_position_in_grid]]) {
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height()) return;
+  float w_stride = inTexture.get_width() / outTexture.get_width();
+  float h_stride = inTexture.get_height() / outTexture.get_height();
+  constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
+  float4 input = inTexture.sample(sample, float2(gid.x * w_stride,    gid.y * h_stride), 0);
+  outTexture.write(half4(input), gid);
+}

metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/metal/Shape.metal

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+ 
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+ 
+ http://www.apache.org/licenses/LICENSE-2.0
+ 
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
+
+#include <metal_stdlib>
+using namespace metal;
+
+kernel void shape() {
+}
+kernel void shape_half() {
+}

metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/metal/Softmax.inc.metal

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+ 
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+ 
+ http://www.apache.org/licenses/LICENSE-2.0
+ 
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
+
+#ifdef P
+
+#define CONCAT2(a, b) a ## b
+#define CONCAT2_(a, b) a ## _ ## b
+
+#define FUNC(f, p) CONCAT2_(f, p)
+#define VECTOR(p, n) CONCAT2(p, n)
+
+kernel void FUNC(softmax, P)(texture2d_array<P, access::read> inTexture [[texture(0)]],
+                    texture2d_array<P, access::write> outTexture [[texture(1)]],
+                    constant SoftmaxParam &sp [[buffer(0)]],
+                    uint3 gid [[thread_position_in_grid]]) {
+  if (gid.x >= outTexture.get_width() ||
+      gid.y >= outTexture.get_height() ||
+      gid.z >= outTexture.get_array_size()) return;
+//  int zsize = inTexture.get_array_size();
+  P maxv = inTexture.read(uint2(0, gid.y), 0)[0];
+  int group = sp.K / 4;
+  int remain = sp.K % 4;
+  for (int x = 0; x < group; x++) {
+    VECTOR(P, 4) r = inTexture.read(uint2(x, gid.y), 0);
+    maxv = max(maxv, max(r[0], max(r[1], max(r[2], r[3]))));
+  }
+  if (remain > 0) {
+    VECTOR(P, 4) r = inTexture.read(uint2(group, gid.y), 0);
+    for (int i = 0; i < remain; i++) {
+      maxv = max(maxv, r[i]);
+    }
+  }
+  VECTOR(P, 4) rsum = {0, 0, 0, 0};
+  for (int x = 0; x < group; x++) {
+    VECTOR(P, 4) r = inTexture.read(uint2(x, gid.y), 0);
+    rsum += exp(r - maxv);
+  }
+  P sum = rsum[0] + rsum[1] + rsum[2] + rsum[3];
+  if (remain > 0) {
+    VECTOR(P, 4) r = inTexture.read(uint2(group, gid.y), 0);
+    for (int i = 0; i < remain; i++) {
+      sum += exp(r[i] - maxv);
+    }
+  }
+  VECTOR(P, 4) rr = inTexture.read(gid.xy, gid.z);
+  rr = exp(rr - maxv) / sum;
+  outTexture.write(rr, gid.xy, gid.z);
+}
+
+#endif

metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/metal/Softmax.metal

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+ 
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+ 
+ http://www.apache.org/licenses/LICENSE-2.0
+ 
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
+
+#include <metal_stdlib>
+using namespace metal;
+
+struct SoftmaxParam {
+  int N;
+  int K;
+};
+
+#define P float
+#include "Softmax.inc.metal"
+#undef P
+
+#define P half
+#include "Softmax.inc.metal"
+#undef P

metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/metal/Split.inc.metal

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+ 
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+ 
+ http://www.apache.org/licenses/LICENSE-2.0
+ 
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
+
+#ifdef P
+
+#define CONCAT2(a, b) a ## b
+#define CONCAT2_(a, b) a ## _ ## b
+#define CONCAT3_(a, b, c) a ## _ ## b ## _ ## c
+#define CONCAT4_(a, b, c, d) a ## _ ## b ## _ ## c ## _ ## d
+#define CONCAT5_(a, b, c, d, e) a ## _ ## b ## _ ## c ## _ ## d ## _ ## e
+
+#define FUNC(f, r, n, v, p) CONCAT5_(f, r, n, v, p)
+#define VECTOR(p, n) CONCAT2(p, n)
+#define FUNC_R(f, r) CONCAT2_(f, r)
+
+#if V == VX
+#define VV x
+#elif V == VY
+#define VV y
+#elif V == VZ
+#define VV z
+#else
+#define VV normal
+#endif
+
+#if V == VY
+kernel void FUNC(split, R, N, VV, P)(texture2d_array<P, access::read> input [[texture(0)]],
+                                 texture2d_array<P, access::write> out1 [[texture(1)]],
+                                 texture2d_array<P, access::write> out2 [[texture(2)]],
+#if N >= 3
+                                 texture2d_array<P, access::write> out3 [[texture(3)]],
+#endif // N >= 3
+#if N >= 4
+                                 texture2d_array<P, access::write> out4 [[texture(4)]],
+#endif // N >= 4
+                                 constant SplitParam &sp [[buffer(0)]],
+                                 uint3 gid [[thread_position_in_grid]]) {
+
+  VECTOR(P, 4) r = input.read(gid.xy, gid.z);
+  int y = gid.y - sp.offset;
+  if (y < sp.vdim[0]) {
+    out1.write(r, gid.xy, gid.z);
+    return;
+  }
+  y -= sp.vdim[0];
+  if (y < sp.vdim[1]) {
+    out2.write(r, uint2(gid.x, y), gid.z);
+    return;
+  }
+#if N >= 3
+  y -= sp.vdim[1];
+  if (y < sp.vdim[2]) {
+    out3.write(r, uint2(gid.x, y), gid.z);
+    return;
+  }
+#endif // N >= 3
+#if N >= 4
+  y -= sp.vdim[2];
+  if (y < sp.vdim[3]) {
+    out4.write(r, uint2(gid.x, y), gid.z);
+    return;
+  }
+#endif // N >= 4
+}
+#endif // V == VY
+
+
+#if V == VX
+kernel void FUNC(split, R, N, VV, P)(texture2d_array<P, access::read> input [[texture(0)]],
+                                     texture2d_array<P, access::write> out1 [[texture(1)]],
+                                     texture2d_array<P, access::write> out2 [[texture(2)]],
+#if N >= 3
+                                     texture2d_array<P, access::write> out3 [[texture(3)]],
+#endif // N >= 3
+#if N >= 4
+                                     texture2d_array<P, access::write> out4 [[texture(4)]],
+#endif // N >= 4
+                                     constant SplitParam &sp [[buffer(0)]],
+                                     uint3 gid [[thread_position_in_grid]]) {
+  VECTOR(P, 4) r = input.read(gid.xy, gid.z);
+  int x = gid.x;
+  if (x < sp.vdim[0]) {
+    out1.write(r, gid.xy, gid.z);
+    return;
+  }
+  x -= sp.vdim[0];
+  if (x < sp.vdim[1]) {
+    out2.write(r, uint2(x, gid.y), gid.z);
+    return;
+  }
+#if N >= 3
+  x -= sp.vdim[1];
+  if (x < sp.vdim[2]) {
+    out3.write(r, uint2(x, gid.y), gid.z);
+    return;
+  }
+#endif // N >= 3
+#if N >= 4
+  x -= sp.vdim[2];
+  if (x < sp.vdim[3]) {
+    out4.write(r, uint2(x, gid.y), gid.z);
+    return;
+  }
+#endif // N >= 4
+}
+#endif // V == VX
+
+
+
+#undef VV
+#endif

metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/metal/Split.metal

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+ 
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+ 
+ http://www.apache.org/licenses/LICENSE-2.0
+ 
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
+
+#include <metal_stdlib>
+#include "Common.metal"
+
+using namespace metal;
+
+struct SplitParam {
+  int32_t idim[4];
+  int32_t axis;
+  int32_t offset;
+  int32_t trans[4];
+  int32_t vdim[4];
+};
+
+#define VNORMAL 1
+#define VX 2
+#define VY 3
+#define VZ 4
+
+// only support split_{2, 3, 4}_{2, 3, 4}_y_{float, half}
+// only support split_{3, 4}_{2, 3, 4}_x_{float, half}
+
+
+//// ssd-ar: (R=3, N=2, V=y)
+#define V VY
+  #define R 3
+    #define N 2
+      #define P float
+        #include "Split.inc.metal"
+      #undef P
+      #define P half
+        #include "Split.inc.metal"
+      #undef P
+    #undef N
+  #undef R
+#undef V
+
+
+//// ssd-ar: (R=2, N=2, V=y)
+#define V VY
+  #define R 2
+    #define N 2
+      #define P float
+        #include "Split.inc.metal"
+      #undef P
+      #define P half
+        #include "Split.inc.metal"
+      #undef P
+    #undef N
+  #undef R
+#undef V

metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/metal/TransposeKernel.inc.metal

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+ 
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+ 
+ http://www.apache.org/licenses/LICENSE-2.0
+ 
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
+
+#ifdef P
+
+#define CONCAT2(a, b) a ## b
+#define CONCAT2_(a, b) a ## _ ## b
+#define CONCAT3_(a, b, c) a ## _ ## b ## _ ## c
+
+#define FUNC(f, r, p) CONCAT3_(f, r, p)
+#define VECTOR(p, n) CONCAT2(p, n)
+
+kernel void FUNC(transpose, R, P)(texture2d_array<P, access::read> inTexture [[texture(0)]],
+                      texture2d_array<P, access::write> outTexture [[texture(1)]],
+                      constant TransposeParam &pm [[buffer(0)]],
+                      uint3 gid [[thread_position_in_grid]]) {
+  VECTOR(P, 4) r;
+  int oxyzn[4] = {int(gid.x), int(gid.y), int(gid.z), 0};
+  int iabcd[4], oabcd[4], ixyzn[4];
+  for (int n = 0; n < 4; n++) {
+    oxyzn[3] = n;
+#if R == 4
+    xyzn2abcd_4(pm.oC, oxyzn, iabcd);
+#endif // R == 4
+#if R == 3
+    xyzn2abcd_3(oxyzn, oabcd);
+#endif // R == 3
+#if R == 2
+    xyzn2abcd_2(oxyzn, oabcd);
+#endif // R == 2
+    iabcd[pm.axis[0]] = oabcd[0];
+    iabcd[pm.axis[1]] = oabcd[1];
+    iabcd[pm.axis[2]] = oabcd[2];
+    iabcd[pm.axis[3]] = oabcd[3];
+#if R == 4
+    abcd2xyzn_4(pm.iC, iabcd, ixyzn);
+#endif // R == 4
+#if R == 3
+    abcd2xyzn_3(iabcd, ixyzn);
+#endif // R == 3
+#if R == 2
+    abcd2xyzn_2(iabcd, ixyzn);
+#endif // R == 2
+    r[n] = inTexture.read(uint2(ixyzn[0], ixyzn[1]), ixyzn[2])[ixyzn[3]];
+  }
+  outTexture.write(r, gid.xy, gid.z);
+}
+
+#endif

metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/metal/TransposeKernel.metal

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+ 
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+ 
+ http://www.apache.org/licenses/LICENSE-2.0
+ 
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
+
+#include <metal_stdlib>
+#include "Common.metal"
+using namespace metal;
+
+struct TransposeParam {
+  int iC;
+  int oC;
+  int axis[4];
+};
+
+kernel void transpose_copy_float(texture2d_array<float, access::read> inTexture [[texture(0)]],
+                           texture2d_array<float, access::write> outTexture [[texture(1)]],
+                           constant TransposeParam &pm [[buffer(0)]],
+                           uint3 gid [[thread_position_in_grid]]) {
+  outTexture.write(inTexture.read(gid.xy, gid.z), gid.xy, gid.z);
+}
+kernel void transpose_copy_half(texture2d_array<half, access::read> inTexture [[texture(0)]],
+                           texture2d_array<half, access::write> outTexture [[texture(1)]],
+                           constant TransposeParam &pm [[buffer(0)]],
+                           uint3 gid [[thread_position_in_grid]]) {
+  outTexture.write(inTexture.read(gid.xy, gid.z), gid.xy, gid.z);
+}
+
+#define R 4
+  #define P float
+    #include "TransposeKernel.inc.metal"
+  #undef P
+  #define P half
+    #include "TransposeKernel.inc.metal"
+  #undef P
+#undef R
+
+#define R 3
+  #define P float
+    #include "TransposeKernel.inc.metal"
+  #undef P
+  #define P half
+    #include "TransposeKernel.inc.metal"
+  #undef P
+#undef R
+
+#define R 2
+  #define P float
+    #include "TransposeKernel.inc.metal"
+  #undef P
+  #define P half
+    #include "TransposeKernel.inc.metal"
+  #undef P
+#undef R

metal/paddle-mobile/paddle-mobile/Operators/MulticlassNMSOp.swift → metal/paddle-mobile/paddle-mobile/Src/Operators/MulticlassNMSOp.swift

@@ -38,8 +38,11 @@ class MulticlassNMSParam<P: PrecisionType>: OpParam {
 
 class MulticlassNMSOp<P: PrecisionType>: Operator<MulticlassNMSKernel<P>, MulticlassNMSParam<P>>, Runable, Creator, InferShaperable{
 
-  func inputVariant() -> [String : [Variant]] {
-    return ["Scores" : [para.middleOutput], "BBoxes" : [para.bboxOutput]]
+  func inputVariant() -> [String : [MTLBuffer]] {
+    guard let scoreBuffer = para.middleOutput.resultBuffer, let bboxBuffer = para.middleOutput.resultBuffer else {
+      fatalError()
+    }
+    return ["Scores" : [scoreBuffer], "BBoxes" : [bboxBuffer]]
   }
   
   func computeMiddleResult(device: MTLDevice, buffer: MTLCommandBuffer) {

metal/paddle-mobile/paddle-mobile/Operators/ReluOp.swift → metal/paddle-mobile/paddle-mobile/Src/Operators/ReluOp.swift

@@ -47,6 +47,7 @@ class ReluOp<P: PrecisionType>: Operator<ReluKernel<P>, ReluParam<P>>, Runable,
   
   func delogOutput() {
     print(" \(type) output: ")
+    print(para.output.metalTexture)
     print(para.output.metalTexture.toTensor(dim: (n: para.output.tensorDim[0], c: para.output.tensorDim[1], h: para.output.tensorDim[2], w: para.output.tensorDim[3])).strideArray())
 //    let device = para.output.metalTexture!.device
 //    let outputArray: [Float32] = device.texture2tensor(texture: para.output.metalTexture, dim: para.output.tensorDim.dims, transpose: para.output.transpose)

metal/paddle-mobile/paddle-mobile/Program/BlockDesc.swift → metal/paddle-mobile/paddle-mobile/Src/Program/BlockDesc.swift

@@ -14,10 +14,10 @@
 
 import Foundation
 
-class BlockDesc {
+public class BlockDesc {
     let index: Int
     let parentIndex: Int
-    let vars: [VarDesc]
+    public let vars: [VarDesc]
     let ops: [OpDesc]
     init(block: PaddleMobile_Framework_Proto_BlockDesc) {
         index = Int(block.idx)
@@ -45,7 +45,7 @@ class BlockDesc {
 }
 
 extension BlockDesc: CustomStringConvertible, CustomDebugStringConvertible {
-    var description: String {
+  public var description: String {
         var str = ""
         
         for i in 0..<ops.count {
@@ -61,9 +61,7 @@ extension BlockDesc: CustomStringConvertible, CustomDebugStringConvertible {
         return str
     }
     
-    var debugDescription: String {
+  public var debugDescription: String {
         return description
     }
-    
-    
 }

metal/paddle-mobile/paddle-mobile/Program/Program.swift → metal/paddle-mobile/paddle-mobile/Src/Program/Program.swift

@@ -14,10 +14,10 @@
 
 import Foundation
 
-public class Program {
-    let paramPath: String
-    let programDesc: ProgramDesc
-    let scope: Scope
+@objc public class Program: NSObject {
+    public let paramPath: String
+    public let programDesc: ProgramDesc
+    public let scope: Scope
     init(inProgramDesc: ProgramDesc, inParamPath: String, inScope: Scope) {
         programDesc = inProgramDesc
         paramPath = inParamPath

metal/paddle-mobile/paddle-mobile/Program/ProgramDesc.swift → metal/paddle-mobile/paddle-mobile/Src/Program/ProgramDesc.swift

@@ -15,7 +15,7 @@
 import Foundation
 
 public class ProgramDesc {
-    var blocks: [BlockDesc] = []
+    public var blocks: [BlockDesc] = []
     init(protoProgram: PaddleMobile_Framework_Proto_ProgramDesc) {
         for block in protoProgram.blocks {
             self.blocks.append(BlockDesc.init(block: block))

metal/paddle-mobile/paddle-mobile/Program/Scope.swift → metal/paddle-mobile/paddle-mobile/Src/Program/Scope.swift

@@ -14,7 +14,7 @@
 
 import Foundation
 
-class Scope {
+public class Scope {
     let feedKey: String
     let fetchKey: String
     func setInput(input: Variant) {
@@ -29,7 +29,7 @@ class Scope {
         return vars[feedKey];
     }
     
-    func output() -> Variant? {
+    public func output() -> Variant? {
         return vars[fetchKey];
     }
     
@@ -38,7 +38,7 @@ class Scope {
         fetchKey = inFetchKey
     }
     
-    var vars: [String : Variant] = [:]
+    public var vars: [String : Variant] = [:]
     subscript(key: String) -> Variant?{
         get {
             return vars[key]

metal/paddle-mobile/paddle-mobile/Program/VarDesc.swift → metal/paddle-mobile/paddle-mobile/Src/Program/VarDesc.swift

@@ -14,7 +14,7 @@
 
 import Foundation
 
-enum VarTypeType: Int {
+public enum VarTypeType: Int {
     case ErrorType = -1,
     Bool = 0,
     Int16 = 1,
@@ -56,10 +56,10 @@ enum VarTypeType: Int {
     }
 }
 
-class VarDesc {
-    let name: String
-    let persistable: Bool
-    let type: VarTypeType
+public class VarDesc {
+    public let name: String
+    public let persistable: Bool
+    public let type: VarTypeType
     let tensorDesc: TensorDesc?
     init(protoVarDesc: PaddleMobile_Framework_Proto_VarDesc) {
         type = VarTypeType.init(rawValue: protoVarDesc.type.type.rawValue) ?? .ErrorType
@@ -79,7 +79,7 @@ class VarDesc {
 }
 
 extension VarDesc: CustomStringConvertible, CustomDebugStringConvertible {
-    var description: String {
+  public var description: String {
         var str = ""
         str += "var name \(name): \n"
         if let inTensorDesc = tensorDesc {
@@ -93,7 +93,7 @@ extension VarDesc: CustomStringConvertible, CustomDebugStringConvertible {
         return str
     }
     
-    var debugDescription: String {
+  public var debugDescription: String {
         return description
     }
 }

metal/paddle-mobile/paddle-mobile/framework/Dim.swift → metal/paddle-mobile/paddle-mobile/Src/framework/Dim.swift

@@ -14,47 +14,42 @@
 
 import Foundation
 
-public struct Dim {
-    public init(inDim: [Int]) {
-        dims = inDim
-    }
-  
-  public init(inDim: (n: Int, h: Int, w: Int, c: Int)) {
-    dims = [inDim.n, inDim.h, inDim.w, inDim.c]
-  }
-  
-    mutating func swapeDimAt(index1: Int, index2: Int) {
-        dims.swapAt(index1, index2)
-    }
-    
-    func cout() -> Int {
-        return dims.count
-    }
-    
-    func numel() -> Int {
-        return dims.reduce(1) { $0 * $1 }
-    }
-    
-    public static func ==(left: Dim, right: Dim) -> Bool {
-        return left.dims == right.dims;
-    }
+@objc public class Dim: NSObject {
+  private(set) var dims: [Int]
+  
+  @objc public init(inDim: [Int]) {
+    dims = inDim
+  }
+  
+  public func cout() -> Int {
+    return dims.count
+  }
+  
+  public func numel() -> Int {
+    return dims.reduce(1) { $0 * $1 }
+  }
+  
+  public static func ==(left: Dim, right: Dim) -> Bool {
+    return left.dims == right.dims;
+  }
   
   public static func !=(left: Dim, right: Dim) -> Bool {
     return left.dims != right.dims;
   }
-    
-    public subscript(index: Int) -> Int {
-        return dims[index];
-    }
-    
-    private(set) var dims: [Int]
-    private init(){
-        fatalError()
-    }
-}
-
-extension Dim: CustomStringConvertible {
-    public var description: String {
-        return "\(dims)"
-    }
+  
+  public subscript(index: Int) -> Int {
+    return dims[index];
+  }
+  
+  public override var description: String {
+    return "\(dims)"
+  }
+  
+  func swapeDimAt(index1: Int, index2: Int) {
+    dims.swapAt(index1, index2)
+  }
+  
+  private override init(){
+    fatalError()
+  }
 }

metal/paddle-mobile/paddle-mobile/framework/Executor.swift → metal/paddle-mobile/paddle-mobile/Src/framework/Executor.swift

@@ -19,13 +19,12 @@ let testTo = 5
 
 var isTest = false
 
-let computePrecision: ComputePrecision = .Float32
-public class GPUResultHolder {
-  public let dim: [Int]
-  public let capacity: Int
-  public var resultPointer: UnsafeMutablePointer<Float32>?
-  public var intermediateResults: [String : [Variant]]?
-  public init(inDim: [Int], inPointer: UnsafeMutablePointer<Float32>?, inCapacity: Int, inIntermediateResults: [String : [Variant]]? = nil) {
+@objc public class GPUResultHolder: NSObject{
+  @objc public let dim: [Int]
+  @objc public let capacity: Int
+  @objc public var resultPointer: UnsafeMutablePointer<Float32>?
+  @objc public var intermediateResults: [String : [MTLBuffer]]?
+  public init(inDim: [Int], inPointer: UnsafeMutablePointer<Float32>?, inCapacity: Int, inIntermediateResults: [String : [MTLBuffer]]? = nil) {
     dim = inDim
     capacity = inCapacity
     
@@ -37,29 +36,10 @@ public class GPUResultHolder {
     intermediateResults = inIntermediateResults
   }
   
-}
-
-extension GPUResultHolder: CustomDebugStringConvertible, CustomStringConvertible {
-  public var debugDescription: String {
-    //    var str = ""
-    //    str += "Dim: \(dim) \n value:[ "
-    //    if resultArr.count < 20 {
-    //      for d in resultArr {
-    //        str += " \(d) "
-    //      }
-    //    } else {
-    //      for d in stride(from: 0, to: resultArr.count, by: resultArr.count/20) {
-    //        str += " \(resultArr[d]) "
-    //      }
-    //    }
-    //    str += " ]"
-    //    return str
+  public override var description: String {
     fatalError()
   }
   
-  public var description: String {
-    return debugDescription
-  }
 }
 
 public class Executor<P: PrecisionType> {
@@ -69,32 +49,18 @@ public class Executor<P: PrecisionType> {
   let device: MTLDevice
   let inflightSemaphore: DispatchSemaphore
   let queue: MTLCommandQueue
-  public init(inDevice:MTLDevice, inQueue: MTLCommandQueue, inProgram: Program) throws {
+  init(inDevice:MTLDevice, inQueue: MTLCommandQueue, inProgram: Program, initContext: InitContext) throws {
     self.inflightSemaphore = DispatchSemaphore(value: 1)
     program = inProgram
     device = inDevice
     queue = inQueue
     
-    //    print("before for ")
-    //print(program.scope.vars["fea_pyramid1_mbox_conf_flat.Flatten.output.1.tmp_0"])
-    
-    
     for block in inProgram.programDesc.blocks {
       //block.ops.count
       for i in 0..<block.ops.count {
         let opDesc = block.ops[i]
         do {
-          
-          
-          //          print("in for i \(i): ")
-          //      print(program.scope.vars["fea_pyramid1_mbox_conf_flat.Flatten.output.1.tmp_0"])
-          //
-          //          if i == 56 {
-          //          print(program.scope.vars["fea_pyramid1_mbox_conf_flat.Flatten.output.1.tmp_0"])
-          //
-          //          }
-          
-          let op = try OpCreator<P>.shared.creat(device: inDevice, opDesc: opDesc, scope: inProgram.scope)
+          let op = try OpCreator<P>.shared.creat(device: inDevice, opDesc: opDesc, scope: inProgram.scope, initContext: initContext)
           ops.append(op)
         } catch let error {
           throw error
@@ -134,7 +100,7 @@ public class Executor<P: PrecisionType> {
       }
     }
     
-    var outputTextures: [String : [Variant]]?
+    var outputTextures: [String : [MTLBuffer]]?
     if except > 0 {
       ops[ops.count - except].computeMiddleResult(device: device, buffer: buffer)
       outputTextures = ops[ops.count - except].inputVariant()
@@ -159,7 +125,7 @@ public class Executor<P: PrecisionType> {
        op.delogOutput()
        }
        */
-    
+      
       var resultHolder: GPUResultHolder
       if except > 0 {
         resultHolder = GPUResultHolder.init(inDim: [], inPointer: nil, inCapacity: 0,  inIntermediateResults: outputTextures)

metal/paddle-mobile/paddle-mobile/framework/Tensor.swift → metal/paddle-mobile/paddle-mobile/Src/framework/Tensor.swift

@@ -28,9 +28,7 @@ extension Tensorial {
   }
 }
 
-public enum ComputePrecision {
-  case Float32, Float16
-}
+
 
 class Tensor<P: PrecisionType>: Tensorial {
   

metal/paddle-mobile/paddle-mobile/framework/Texture.swift → metal/paddle-mobile/paddle-mobile/Src/framework/Texture.swift

@@ -71,7 +71,7 @@ extension InputTexture {
 
 
 public class Texture: Tensorial {
-  var dim: Dim
+  public var dim: Dim
   public var tensorDim: Dim
   public var padToFourDim: Dim
   private var textureDesc: MTLTextureDescriptor!
@@ -96,7 +96,7 @@ public class Texture: Tensorial {
     return metalTexture.realNHWC(dim: (n: padToFourDim[0], h: padToFourDim[1], w: padToFourDim[2], c: padToFourDim[3]))
   }
   
-  func initTexture(device: MTLDevice, inTranspose: [Int] = [0, 1, 2, 3], computePrecision: ComputePrecision = .Float16) {
+  public func initTexture(device: MTLDevice, inTranspose: [Int] = [0, 1, 2, 3], computePrecision: ComputePrecision = .Float16) {
     transpose = inTranspose
     for i in 0..<(4 - tensorDim.cout()) {
       if i != inTranspose[i] {
@@ -143,7 +143,7 @@ public class Texture: Tensorial {
     metalTexture = device.makeTexture(descriptor: tmpTextureDes) ?! " texture nil "
   }
   
-  func updateDims(inTensorDim: Dim, inDim: Dim) {
+  public func updateDims(inTensorDim: Dim, inDim: Dim) {
     var fourDim: Dim
     if inDim.cout() == 4 {
       fourDim = inDim

metal/paddle-mobile/paddle-mobile/paddle_mobile.h

@@ -14,8 +14,6 @@
 
 #pragma once
 
-#import "CPUCompute.h"
-#import "PaddleMobileGPU.h"
 #import <UIKit/UIKit.h>
 
 //! Project version number for paddle_mobile.