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Paddle-Lite
未验证 提交 b602b048 编写于 作者: R Ruilong Liu 提交者： GitHub
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Merge pull request #837 from codeWorm2015/metal 

align result
上级 9540e39b 7315defa
展开全部 隐藏空白更改
内联 并排
Showing with 2517 addition and 2130 deletion
metal/paddle-mobile-demo/paddle-mobile-demo.xcodeproj/project.pbxproj
浏览文件 @ b602b048
...@@ -16,6 +16,7 @@ ...@@ -16,6 +16,7 @@
FC039B8C20E11C560081E9F8 /* LaunchScreen.storyboard in Resources */ = {isa = PBXBuildFile; fileRef = FC039B8A20E11C560081E9F8 /* LaunchScreen.storyboard */; }; FC039B8C20E11C560081E9F8 /* LaunchScreen.storyboard in Resources */ = {isa = PBXBuildFile; fileRef = FC039B8A20E11C560081E9F8 /* LaunchScreen.storyboard */; };
FC918191211DBC3500B6F354 /* paddle-mobile.png in Resources */ = {isa = PBXBuildFile; fileRef = FC918190211DBC3500B6F354 /* paddle-mobile.png */; }; FC918191211DBC3500B6F354 /* paddle-mobile.png in Resources */ = {isa = PBXBuildFile; fileRef = FC918190211DBC3500B6F354 /* paddle-mobile.png */; };
FC918193211DC70500B6F354 /* iphone.JPG in Resources */ = {isa = PBXBuildFile; fileRef = FC918192211DC70500B6F354 /* iphone.JPG */; }; FC918193211DC70500B6F354 /* iphone.JPG in Resources */ = {isa = PBXBuildFile; fileRef = FC918192211DC70500B6F354 /* iphone.JPG */; };
FCA3A16121313E1F00084FE5 /* hand.jpg in Resources */ = {isa = PBXBuildFile; fileRef = FCA3A16021313E1F00084FE5 /* hand.jpg */; };
FCBCCC522122EEDC00D94F7E /* ssd_hand_params in Resources */ = {isa = PBXBuildFile; fileRef = FCBCCC502122EEDC00D94F7E /* ssd_hand_params */; }; FCBCCC522122EEDC00D94F7E /* ssd_hand_params in Resources */ = {isa = PBXBuildFile; fileRef = FCBCCC502122EEDC00D94F7E /* ssd_hand_params */; };
FCBCCC532122EEDC00D94F7E /* ssd_hand_model in Resources */ = {isa = PBXBuildFile; fileRef = FCBCCC512122EEDC00D94F7E /* ssd_hand_model */; }; FCBCCC532122EEDC00D94F7E /* ssd_hand_model in Resources */ = {isa = PBXBuildFile; fileRef = FCBCCC512122EEDC00D94F7E /* ssd_hand_model */; };
FCBCCC552122EF5500D94F7E /* MetalHelper.swift in Sources */ = {isa = PBXBuildFile; fileRef = FCBCCC542122EF5400D94F7E /* MetalHelper.swift */; }; FCBCCC552122EF5500D94F7E /* MetalHelper.swift in Sources */ = {isa = PBXBuildFile; fileRef = FCBCCC542122EF5400D94F7E /* MetalHelper.swift */; };
...@@ -56,6 +57,7 @@ ...@@ -56,6 +57,7 @@
FC039B8D20E11C560081E9F8 /* Info.plist */ = {isa = PBXFileReference; lastKnownFileType = text.plist.xml; path = Info.plist; sourceTree = "<group>"; }; FC039B8D20E11C560081E9F8 /* Info.plist */ = {isa = PBXFileReference; lastKnownFileType = text.plist.xml; path = Info.plist; sourceTree = "<group>"; };
FC918190211DBC3500B6F354 /* paddle-mobile.png */ = {isa = PBXFileReference; lastKnownFileType = image.png; path = "paddle-mobile.png"; sourceTree = "<group>"; }; FC918190211DBC3500B6F354 /* paddle-mobile.png */ = {isa = PBXFileReference; lastKnownFileType = image.png; path = "paddle-mobile.png"; sourceTree = "<group>"; };
FC918192211DC70500B6F354 /* iphone.JPG */ = {isa = PBXFileReference; lastKnownFileType = image.jpeg; path = iphone.JPG; sourceTree = "<group>"; }; FC918192211DC70500B6F354 /* iphone.JPG */ = {isa = PBXFileReference; lastKnownFileType = image.jpeg; path = iphone.JPG; sourceTree = "<group>"; };
FCA3A16021313E1F00084FE5 /* hand.jpg */ = {isa = PBXFileReference; lastKnownFileType = image.jpeg; path = hand.jpg; sourceTree = "<group>"; };
FCBCCC502122EEDC00D94F7E /* ssd_hand_params */ = {isa = PBXFileReference; lastKnownFileType = file; path = ssd_hand_params; sourceTree = "<group>"; }; FCBCCC502122EEDC00D94F7E /* ssd_hand_params */ = {isa = PBXFileReference; lastKnownFileType = file; path = ssd_hand_params; sourceTree = "<group>"; };
FCBCCC512122EEDC00D94F7E /* ssd_hand_model */ = {isa = PBXFileReference; lastKnownFileType = file; path = ssd_hand_model; sourceTree = "<group>"; }; FCBCCC512122EEDC00D94F7E /* ssd_hand_model */ = {isa = PBXFileReference; lastKnownFileType = file; path = ssd_hand_model; sourceTree = "<group>"; };
FCBCCC542122EF5400D94F7E /* MetalHelper.swift */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.swift; path = MetalHelper.swift; sourceTree = "<group>"; }; FCBCCC542122EF5400D94F7E /* MetalHelper.swift */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.swift; path = MetalHelper.swift; sourceTree = "<group>"; };
...@@ -137,6 +139,7 @@ ...@@ -137,6 +139,7 @@
FC0E2C1D20EDC030009C1FAC /* images */ = { FC0E2C1D20EDC030009C1FAC /* images */ = {
isa = PBXGroup; isa = PBXGroup;
children = ( children = (
FCA3A16021313E1F00084FE5 /* hand.jpg */,
FC918192211DC70500B6F354 /* iphone.JPG */, FC918192211DC70500B6F354 /* iphone.JPG */,
FC918190211DBC3500B6F354 /* paddle-mobile.png */, FC918190211DBC3500B6F354 /* paddle-mobile.png */,
FCDFD41A211D91C7005AB38B /* synset.txt */, FCDFD41A211D91C7005AB38B /* synset.txt */,
...@@ -245,6 +248,7 @@ ...@@ -245,6 +248,7 @@
FCDFD41B211D91C7005AB38B /* synset.txt in Resources */, FCDFD41B211D91C7005AB38B /* synset.txt in Resources */,
FCD04E6420F3146B0007374F /* model in Resources */, FCD04E6420F3146B0007374F /* model in Resources */,
FC039B8720E11C550081E9F8 /* Main.storyboard in Resources */, FC039B8720E11C550081E9F8 /* Main.storyboard in Resources */,
FCA3A16121313E1F00084FE5 /* hand.jpg in Resources */,
FCBCCC532122EEDC00D94F7E /* ssd_hand_model in Resources */, FCBCCC532122EEDC00D94F7E /* ssd_hand_model in Resources */,
); );
runOnlyForDeploymentPostprocessing = 0; runOnlyForDeploymentPostprocessing = 0;
......
metal/paddle-mobile-demo/paddle-mobile-demo/Base.lproj/Main.storyboard
浏览文件 @ b602b048
...@@ -19,10 +19,10 @@ ...@@ -19,10 +19,10 @@
<rect key="frame" x="0.0" y="0.0" width="375" height="667"/> <rect key="frame" x="0.0" y="0.0" width="375" height="667"/>
<autoresizingMask key="autoresizingMask" widthSizable="YES" heightSizable="YES"/> <autoresizingMask key="autoresizingMask" widthSizable="YES" heightSizable="YES"/>
<subviews> <subviews>
<imageView userInteractionEnabled="NO" contentMode="scaleAspectFit" horizontalHuggingPriority="251" verticalHuggingPriority="251" translatesAutoresizingMaskIntoConstraints="NO" id="ZZh-fw-LwK"> <imageView userInteractionEnabled="NO" contentMode="scaleAspectFit" horizontalHuggingPriority="251" verticalHuggingPriority="251" ambiguous="YES" image="hand.jpg" translatesAutoresizingMaskIntoConstraints="NO" id="ZZh-fw-LwK">
<rect key="frame" x="0.0" y="20" width="375" height="247"/> <rect key="frame" x="0.0" y="20" width="375" height="247"/>
</imageView> </imageView>
<label opaque="NO" userInteractionEnabled="NO" contentMode="left" horizontalHuggingPriority="251" verticalHuggingPriority="251" text="Thread:" textAlignment="natural" lineBreakMode="tailTruncation" baselineAdjustment="alignBaselines" adjustsFontSizeToFit="NO" translatesAutoresizingMaskIntoConstraints="NO" id="2EB-m2-a3L"> <label opaque="NO" userInteractionEnabled="NO" contentMode="left" horizontalHuggingPriority="251" verticalHuggingPriority="251" ambiguous="YES" text="Thread:" textAlignment="natural" lineBreakMode="tailTruncation" baselineAdjustment="alignBaselines" adjustsFontSizeToFit="NO" translatesAutoresizingMaskIntoConstraints="NO" id="2EB-m2-a3L">
<rect key="frame" x="10" y="538" width="68" height="24"/> <rect key="frame" x="10" y="538" width="68" height="24"/>
<constraints> <constraints>
<constraint firstAttribute="width" constant="68" id="Q5J-tq-JSX"/> <constraint firstAttribute="width" constant="68" id="Q5J-tq-JSX"/>
...@@ -32,19 +32,19 @@ ...@@ -32,19 +32,19 @@
<nil key="textColor"/> <nil key="textColor"/>
<nil key="highlightedColor"/> <nil key="highlightedColor"/>
</label> </label>
<pickerView contentMode="scaleToFill" translatesAutoresizingMaskIntoConstraints="NO" id="DlO-dk-RMr"> <pickerView contentMode="scaleToFill" ambiguous="YES" translatesAutoresizingMaskIntoConstraints="NO" id="DlO-dk-RMr">
<rect key="frame" x="88" y="510.5" width="287" height="80"/> <rect key="frame" x="88" y="510.5" width="287" height="80"/>
<constraints> <constraints>
<constraint firstAttribute="height" constant="80" id="Sbi-05-Mwd"/> <constraint firstAttribute="height" constant="80" id="Sbi-05-Mwd"/>
</constraints> </constraints>
</pickerView> </pickerView>
<pickerView contentMode="scaleToFill" translatesAutoresizingMaskIntoConstraints="NO" id="6MG-gv-hD5"> <pickerView contentMode="scaleToFill" ambiguous="YES" translatesAutoresizingMaskIntoConstraints="NO" id="6MG-gv-hD5">
<rect key="frame" x="85" y="401" width="290" height="80"/> <rect key="frame" x="85" y="401" width="290" height="80"/>
<constraints> <constraints>
<constraint firstAttribute="height" constant="80" id="yAL-JY-G6b"/> <constraint firstAttribute="height" constant="80" id="yAL-JY-G6b"/>
</constraints> </constraints>
</pickerView> </pickerView>
<label opaque="NO" userInteractionEnabled="NO" contentMode="left" horizontalHuggingPriority="251" verticalHuggingPriority="251" text="Models" textAlignment="natural" lineBreakMode="tailTruncation" baselineAdjustment="alignBaselines" adjustsFontSizeToFit="NO" translatesAutoresizingMaskIntoConstraints="NO" id="avL-VK-Kha"> <label opaque="NO" userInteractionEnabled="NO" contentMode="left" horizontalHuggingPriority="251" verticalHuggingPriority="251" ambiguous="YES" text="Models" textAlignment="natural" lineBreakMode="tailTruncation" baselineAdjustment="alignBaselines" adjustsFontSizeToFit="NO" translatesAutoresizingMaskIntoConstraints="NO" id="avL-VK-Kha">
<rect key="frame" x="10" y="429" width="65" height="24"/> <rect key="frame" x="10" y="429" width="65" height="24"/>
<constraints> <constraints>
<constraint firstAttribute="width" constant="65" id="6oA-g2-Xq4"/> <constraint firstAttribute="width" constant="65" id="6oA-g2-Xq4"/>
...@@ -54,7 +54,7 @@ ...@@ -54,7 +54,7 @@
<nil key="textColor"/> <nil key="textColor"/>
<nil key="highlightedColor"/> <nil key="highlightedColor"/>
</label> </label>
<button opaque="NO" contentMode="scaleToFill" contentHorizontalAlignment="center" contentVerticalAlignment="center" buttonType="roundedRect" showsTouchWhenHighlighted="YES" lineBreakMode="middleTruncation" translatesAutoresizingMaskIntoConstraints="NO" id="wUL-9N-u1V"> <button opaque="NO" contentMode="scaleToFill" ambiguous="YES" 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"/> <rect key="frame" x="16" y="597" width="63.5" height="30"/>
<color key="backgroundColor" white="0.0" alpha="1" colorSpace="custom" customColorSpace="genericGamma22GrayColorSpace"/> <color key="backgroundColor" white="0.0" alpha="1" colorSpace="custom" customColorSpace="genericGamma22GrayColorSpace"/>
<state key="normal" title="Image"> <state key="normal" title="Image">
...@@ -64,7 +64,7 @@ ...@@ -64,7 +64,7 @@
<action selector="selectImageAct:" destination="BYZ-38-t0r" eventType="touchUpInside" id="5uR-SM-fKO"/> <action selector="selectImageAct:" destination="BYZ-38-t0r" eventType="touchUpInside" id="5uR-SM-fKO"/>
</connections> </connections>
</button> </button>
<button opaque="NO" contentMode="scaleToFill" contentHorizontalAlignment="center" contentVerticalAlignment="center" buttonType="roundedRect" showsTouchWhenHighlighted="YES" lineBreakMode="middleTruncation" translatesAutoresizingMaskIntoConstraints="NO" id="XpL-9M-UOp"> <button opaque="NO" contentMode="scaleToFill" ambiguous="YES" contentHorizontalAlignment="center" contentVerticalAlignment="center" buttonType="roundedRect" showsTouchWhenHighlighted="YES" lineBreakMode="middleTruncation" translatesAutoresizingMaskIntoConstraints="NO" id="XpL-9M-UOp">
<rect key="frame" x="109.5" y="597" width="63" height="30"/> <rect key="frame" x="109.5" y="597" width="63" height="30"/>
<color key="backgroundColor" white="0.0" alpha="1" colorSpace="custom" customColorSpace="genericGamma22GrayColorSpace"/> <color key="backgroundColor" white="0.0" alpha="1" colorSpace="custom" customColorSpace="genericGamma22GrayColorSpace"/>
<state key="normal" title="Load"> <state key="normal" title="Load">
...@@ -74,7 +74,7 @@ ...@@ -74,7 +74,7 @@
<action selector="loadAct:" destination="BYZ-38-t0r" eventType="touchUpInside" id="fZ5-CQ-jCY"/> <action selector="loadAct:" destination="BYZ-38-t0r" eventType="touchUpInside" id="fZ5-CQ-jCY"/>
</connections> </connections>
</button> </button>
<button opaque="NO" contentMode="scaleToFill" contentHorizontalAlignment="center" contentVerticalAlignment="center" buttonType="roundedRect" showsTouchWhenHighlighted="YES" lineBreakMode="middleTruncation" translatesAutoresizingMaskIntoConstraints="NO" id="R90-Yf-S6g"> <button opaque="NO" contentMode="scaleToFill" ambiguous="YES" contentHorizontalAlignment="center" contentVerticalAlignment="center" buttonType="roundedRect" showsTouchWhenHighlighted="YES" lineBreakMode="middleTruncation" translatesAutoresizingMaskIntoConstraints="NO" id="R90-Yf-S6g">
<rect key="frame" x="202.5" y="597" width="63.5" height="30"/> <rect key="frame" x="202.5" y="597" width="63.5" height="30"/>
<color key="backgroundColor" white="0.0" alpha="1" colorSpace="custom" customColorSpace="genericGamma22GrayColorSpace"/> <color key="backgroundColor" white="0.0" alpha="1" colorSpace="custom" customColorSpace="genericGamma22GrayColorSpace"/>
<state key="normal" title="Predict"> <state key="normal" title="Predict">
...@@ -84,7 +84,7 @@ ...@@ -84,7 +84,7 @@
<action selector="predictAct:" destination="BYZ-38-t0r" eventType="touchUpInside" id="Iyy-sY-gt4"/> <action selector="predictAct:" destination="BYZ-38-t0r" eventType="touchUpInside" id="Iyy-sY-gt4"/>
</connections> </connections>
</button> </button>
<button opaque="NO" contentMode="scaleToFill" contentHorizontalAlignment="center" contentVerticalAlignment="center" buttonType="roundedRect" showsTouchWhenHighlighted="YES" lineBreakMode="middleTruncation" translatesAutoresizingMaskIntoConstraints="NO" id="a3K-ri-NVs"> <button opaque="NO" contentMode="scaleToFill" ambiguous="YES" contentHorizontalAlignment="center" contentVerticalAlignment="center" buttonType="roundedRect" showsTouchWhenHighlighted="YES" lineBreakMode="middleTruncation" translatesAutoresizingMaskIntoConstraints="NO" id="a3K-ri-NVs">
<rect key="frame" x="296" y="597" width="63" height="30"/> <rect key="frame" x="296" y="597" width="63" height="30"/>
<color key="backgroundColor" white="0.0" alpha="1" colorSpace="custom" customColorSpace="genericGamma22GrayColorSpace"/> <color key="backgroundColor" white="0.0" alpha="1" colorSpace="custom" customColorSpace="genericGamma22GrayColorSpace"/>
<state key="normal" title="Clear"> <state key="normal" title="Clear">
...@@ -94,7 +94,7 @@ ...@@ -94,7 +94,7 @@
<action selector="clearAct:" destination="BYZ-38-t0r" eventType="touchUpInside" id="JYf-UX-rCR"/> <action selector="clearAct:" destination="BYZ-38-t0r" eventType="touchUpInside" id="JYf-UX-rCR"/>
</connections> </connections>
</button> </button>
<view contentMode="scaleToFill" translatesAutoresizingMaskIntoConstraints="NO" id="w7H-Sk-Rai"> <view contentMode="scaleToFill" ambiguous="YES" translatesAutoresizingMaskIntoConstraints="NO" id="w7H-Sk-Rai">
<rect key="frame" x="79.5" y="597" width="30" height="30"/> <rect key="frame" x="79.5" y="597" width="30" height="30"/>
<color key="backgroundColor" white="1" alpha="1" colorSpace="custom" customColorSpace="genericGamma22GrayColorSpace"/> <color key="backgroundColor" white="1" alpha="1" colorSpace="custom" customColorSpace="genericGamma22GrayColorSpace"/>
<constraints> <constraints>
...@@ -102,7 +102,7 @@ ...@@ -102,7 +102,7 @@
<constraint firstAttribute="width" constant="30" id="vYd-Fc-KAj"/> <constraint firstAttribute="width" constant="30" id="vYd-Fc-KAj"/>
</constraints> </constraints>
</view> </view>
<view contentMode="scaleToFill" translatesAutoresizingMaskIntoConstraints="NO" id="T4O-nx-ciH"> <view contentMode="scaleToFill" ambiguous="YES" translatesAutoresizingMaskIntoConstraints="NO" id="T4O-nx-ciH">
<rect key="frame" x="266" y="597" width="30" height="30"/> <rect key="frame" x="266" y="597" width="30" height="30"/>
<color key="backgroundColor" white="1" alpha="1" colorSpace="custom" customColorSpace="genericGamma22GrayColorSpace"/> <color key="backgroundColor" white="1" alpha="1" colorSpace="custom" customColorSpace="genericGamma22GrayColorSpace"/>
<constraints> <constraints>
...@@ -110,7 +110,7 @@ ...@@ -110,7 +110,7 @@
<constraint firstAttribute="width" constant="30" id="fXE-S7-ZXL"/> <constraint firstAttribute="width" constant="30" id="fXE-S7-ZXL"/>
</constraints> </constraints>
</view> </view>
<view contentMode="scaleToFill" translatesAutoresizingMaskIntoConstraints="NO" id="976-fk-Kx2"> <view contentMode="scaleToFill" ambiguous="YES" translatesAutoresizingMaskIntoConstraints="NO" id="976-fk-Kx2">
<rect key="frame" x="172.5" y="597" width="30" height="30"/> <rect key="frame" x="172.5" y="597" width="30" height="30"/>
<color key="backgroundColor" white="1" alpha="1" colorSpace="custom" customColorSpace="genericGamma22GrayColorSpace"/> <color key="backgroundColor" white="1" alpha="1" colorSpace="custom" customColorSpace="genericGamma22GrayColorSpace"/>
<constraints> <constraints>
...@@ -118,7 +118,7 @@ ...@@ -118,7 +118,7 @@
<constraint firstAttribute="width" constant="30" id="L4p-hP-s5C"/> <constraint firstAttribute="width" constant="30" id="L4p-hP-s5C"/>
</constraints> </constraints>
</view> </view>
<label opaque="NO" userInteractionEnabled="NO" contentMode="left" horizontalHuggingPriority="251" verticalHuggingPriority="251" text="耗时:" lineBreakMode="tailTruncation" numberOfLines="0" baselineAdjustment="alignBaselines" adjustsFontSizeToFit="NO" translatesAutoresizingMaskIntoConstraints="NO" id="m5L-O7-P31"> <label opaque="NO" userInteractionEnabled="NO" contentMode="left" horizontalHuggingPriority="251" verticalHuggingPriority="251" ambiguous="YES" text="耗时:" lineBreakMode="tailTruncation" numberOfLines="0" baselineAdjustment="alignBaselines" adjustsFontSizeToFit="NO" translatesAutoresizingMaskIntoConstraints="NO" id="m5L-O7-P31">
<rect key="frame" x="15" y="277" width="350" height="38"/> <rect key="frame" x="15" y="277" width="350" height="38"/>
<constraints> <constraints>
<constraint firstAttribute="height" constant="38" id="6SS-sb-7I2"/> <constraint firstAttribute="height" constant="38" id="6SS-sb-7I2"/>
...@@ -133,7 +133,7 @@ ...@@ -133,7 +133,7 @@
<constraint firstAttribute="width" secondItem="4ey-Xr-U4e" secondAttribute="height" multiplier="6.5:1" id="8c5-FF-lB9"/> <constraint firstAttribute="width" secondItem="4ey-Xr-U4e" secondAttribute="height" multiplier="6.5:1" id="8c5-FF-lB9"/>
</constraints> </constraints>
</imageView> </imageView>
<textView clipsSubviews="YES" multipleTouchEnabled="YES" contentMode="scaleToFill" editable="NO" text="结果:" textAlignment="natural" translatesAutoresizingMaskIntoConstraints="NO" id="VQn-bS-fWp"> <textView clipsSubviews="YES" multipleTouchEnabled="YES" contentMode="scaleToFill" ambiguous="YES" editable="NO" text="结果:" textAlignment="natural" translatesAutoresizingMaskIntoConstraints="NO" id="VQn-bS-fWp">
<rect key="frame" x="10" y="323" width="355" height="70"/> <rect key="frame" x="10" y="323" width="355" height="70"/>
<color key="backgroundColor" white="1" alpha="1" colorSpace="custom" customColorSpace="genericGamma22GrayColorSpace"/> <color key="backgroundColor" white="1" alpha="1" colorSpace="custom" customColorSpace="genericGamma22GrayColorSpace"/>
<constraints> <constraints>
...@@ -203,6 +203,7 @@ ...@@ -203,6 +203,7 @@
</scene> </scene>
</scenes> </scenes>
<resources> <resources>
<image name="hand.jpg" width="564" height="664"/>
<image name="paddle-mobile.png" width="402" height="62"/> <image name="paddle-mobile.png" width="402" height="62"/>
</resources> </resources>
</document> </document>
metal/paddle-mobile-demo/paddle-mobile-demo/ModelHelper.swift
浏览文件 @ b602b048
...@@ -30,6 +30,7 @@ protocol Net { ...@@ -30,6 +30,7 @@ protocol Net {
var preprocessKernel: CusomKernel { get } var preprocessKernel: CusomKernel { get }
func getTexture(image: CGImage, getTexture: @escaping (MTLTexture) -> Void) func getTexture(image: CGImage, getTexture: @escaping (MTLTexture) -> Void)
func resultStr(res: [Float]) -> String func resultStr(res: [Float]) -> String
func fetchResult(paddleMobileRes: ResultHolder<Float32>) -> [Float32]
} }
extension Net { extension Net {
...@@ -39,10 +40,13 @@ extension Net { ...@@ -39,10 +40,13 @@ extension Net {
getTexture(resTexture) getTexture(resTexture)
} }
} }
func fetchResult(paddleMobileRes: ResultHolder<Float32>) -> [Float32] {
return paddleMobileRes.resultArr
}
} }
struct MobileNet: Net{ struct MobileNet: Net{
class MobilenetPreProccess: CusomKernel { class MobilenetPreProccess: CusomKernel {
init(device: MTLDevice) { init(device: MTLDevice) {
let s = CusomKernel.Shape.init(inWidth: 224, inHeight: 224, inChannel: 3) let s = CusomKernel.Shape.init(inWidth: 224, inHeight: 224, inChannel: 3)
...@@ -100,7 +104,8 @@ struct MobileNet_ssd_hand: Net{ ...@@ -100,7 +104,8 @@ struct MobileNet_ssd_hand: Net{
} }
func resultStr(res: [Float]) -> String { func resultStr(res: [Float]) -> String {
fatalError() return "哈哈哈, 还没好"
// fatalError()
} }
func bboxArea(box: [Float32], normalized: Bool) -> Float32 { func bboxArea(box: [Float32], normalized: Bool) -> Float32 {
...@@ -117,7 +122,6 @@ struct MobileNet_ssd_hand: Net{ ...@@ -117,7 +122,6 @@ struct MobileNet_ssd_hand: Net{
} }
} }
func jaccardOverLap(box1: [Float32], box2: [Float32], normalized: Bool) -> Float32 { func jaccardOverLap(box1: [Float32], box2: [Float32], normalized: Bool) -> Float32 {
if box2[0] > box1[2] || box2[2] < box1[0] || box2[1] > box1[3] || if box2[0] > box1[2] || box2[2] < box1[0] || box2[1] > box1[3] ||
box2[3] < box1[1] { box2[3] < box1[1] {
...@@ -136,9 +140,11 @@ struct MobileNet_ssd_hand: Net{ ...@@ -136,9 +140,11 @@ struct MobileNet_ssd_hand: Net{
} }
} }
func fetchResult(paddleMobileRes: [String : Texture<Float32>]) -> [Float32]{ func fetchResult(paddleMobileRes: ResultHolder<Float32>) -> [Float32]{
let bbox = paddleMobileRes["box_coder_0.tmp_0"] ?! " no bbox " let scores = paddleMobileRes.intermediateResults![0] as! Texture<Float32>
let scores = paddleMobileRes["transpose_12.tmp_0"] ?! " no scores " let bbox = paddleMobileRes.intermediateResults![1] as! Texture<Float32>
// let bbox = paddleMobileRes["box_coder_0.tmp_0"] ?! " no bbox "
// let scores = paddleMobileRes["transpose_12.tmp_0"] ?! " no scores "
let score_thredshold: Float32 = 0.01 let score_thredshold: Float32 = 0.01
let nms_top_k = 400 let nms_top_k = 400
let keep_top_k = 200 let keep_top_k = 200
...@@ -156,20 +162,29 @@ struct MobileNet_ssd_hand: Net{ ...@@ -156,20 +162,29 @@ struct MobileNet_ssd_hand: Net{
var scoreFormatArr: [Float32] = [] var scoreFormatArr: [Float32] = []
var outputArr: [Float32] = [] var outputArr: [Float32] = []
let numOfOneC = (scores.originDim[2] + 3) / 4 // 480 let numOfOneC = (scores.tensorDim[2] + 3) / 4 // 480
let cNumOfOneClass = numOfOneC * 4 // 1920
let boxSize = bbox.originDim[2] // 4 let cNumOfOneClass = scores.tensorDim[2] // 1917
let classNum = scores.originDim[1] // 7
let cPaddedNumOfOneClass = numOfOneC * 4 // 1920
let boxSize = bbox.tensorDim[2] // 4
let classNum = scores.tensorDim[1] // 7
let classNumOneTexture = classNum * 4 // 28 let classNumOneTexture = classNum * 4 // 28
for c in 0..<classNum { for c in 0..<classNum {
for n in 0..<numOfOneC { for n in 0..<numOfOneC {
let to = n * classNumOneTexture + c * 4 let to = n * classNumOneTexture + c * 4
scoreFormatArr.append(scoresArr[to]) if n == numOfOneC - 1 {
scoreFormatArr.append(scoresArr[to + 1]) for i in 0..<(4 - (cPaddedNumOfOneClass - cNumOfOneClass)) {
scoreFormatArr.append(scoresArr[to + 2]) scoreFormatArr.append(scoresArr[to + i])
scoreFormatArr.append(scoresArr[to + 3]) }
} else {
scoreFormatArr.append(scoresArr[to])
scoreFormatArr.append(scoresArr[to + 1])
scoreFormatArr.append(scoresArr[to + 2])
scoreFormatArr.append(scoresArr[to + 3])
}
} }
} }
...@@ -178,13 +193,13 @@ struct MobileNet_ssd_hand: Net{ ...@@ -178,13 +193,13 @@ struct MobileNet_ssd_hand: Net{
var numDet: Int = 0 var numDet: Int = 0
for i in 0..<classNum { for i in 0..<classNum {
var sliceScore = scoreFormatArr[(i * cNumOfOneClass)..<((i + 1) * cNumOfOneClass)] var sliceScore = Array<Float32>(scoreFormatArr[(i * cNumOfOneClass)..<((i + 1) * cNumOfOneClass)])
var scoreThresholdArr: [(Float32, Int)] = [] var scoreThresholdArr: [(Float32, Int)] = []
for i in 0..<cNumOfOneClass { for j in 0..<cNumOfOneClass {
if sliceScore[i] > score_thredshold { if sliceScore[j] > score_thredshold {
scoreThresholdArr.append((sliceScore[i], i)) scoreThresholdArr.append((sliceScore[j], j))
} }
} }
...@@ -204,7 +219,7 @@ struct MobileNet_ssd_hand: Net{ ...@@ -204,7 +219,7 @@ struct MobileNet_ssd_hand: Net{
if keep { if keep {
let keptIdx = selectedIndex[j].0 let keptIdx = selectedIndex[j].0
let box1 = Array<Float32>(bboxArr[(idx * boxSize)..<(idx * boxSize + 4)]) let box1 = Array<Float32>(bboxArr[(idx * boxSize)..<(idx * boxSize + 4)])
let box2 = Array<Float32>(bboxArr[(idx * boxSize)..<(keptIdx * boxSize + 4)]) let box2 = Array<Float32>(bboxArr[(keptIdx * boxSize)..<(keptIdx * boxSize + 4)])
let overlap = jaccardOverLap(box1: box1, box2: box2, normalized: true) let overlap = jaccardOverLap(box1: box1, box2: box2, normalized: true)
keep = (overlap <= nms_threshold) keep = (overlap <= nms_threshold)
...@@ -259,7 +274,8 @@ struct MobileNet_ssd_hand: Net{ ...@@ -259,7 +274,8 @@ struct MobileNet_ssd_hand: Net{
outputArr.append(contentsOf: subBox) outputArr.append(contentsOf: subBox)
} }
} }
print(" fuck success !")
print(outputArr)
return outputArr return outputArr
} }
......
metal/paddle-mobile-demo/paddle-mobile-demo/ViewController.swift
浏览文件 @ b602b048
...@@ -75,7 +75,7 @@ class ViewController: UIViewController { ...@@ -75,7 +75,7 @@ class ViewController: UIViewController {
} }
do { do {
let max = 10 let max = 1
var startDate = Date.init() var startDate = Date.init()
for i in 0..<max { for i in 0..<max {
try inExecutor.predict(input: inTexture, expect: modelHelper.dim, completionHandle: { [weak self] (result) in try inExecutor.predict(input: inTexture, expect: modelHelper.dim, completionHandle: { [weak self] (result) in
...@@ -87,14 +87,16 @@ class ViewController: UIViewController { ...@@ -87,14 +87,16 @@ class ViewController: UIViewController {
startDate = Date.init() startDate = Date.init()
} }
let resultArr = sSelf.modelHelper.fetchResult(paddleMobileRes: result)
if i == max - 1 { if i == max - 1 {
let time = Date.init().timeIntervalSince(startDate) let time = Date.init().timeIntervalSince(startDate)
DispatchQueue.main.async { DispatchQueue.main.async {
sSelf.resultTextView.text = sSelf.modelHelper.resultStr(res: result.resultArr) sSelf.resultTextView.text = sSelf.modelHelper.resultStr(res: resultArr)
sSelf.elapsedTimeLabel.text = "平均耗时: \(time/Double(max/2) * 1000.0) ms" sSelf.elapsedTimeLabel.text = "平均耗时: \(time/Double(max/2) * 1000.0) ms"
} }
} }
}, preProcessKernle: self.modelHelper.preprocessKernel) }, preProcessKernle: self.modelHelper.preprocessKernel, except: 2)
} }
} catch let error { } catch let error {
print(error) print(error)
...@@ -108,7 +110,7 @@ class ViewController: UIViewController { ...@@ -108,7 +110,7 @@ class ViewController: UIViewController {
threadPickerView.delegate = self threadPickerView.delegate = self
threadPickerView.dataSource = self threadPickerView.dataSource = self
selectImage = UIImage.init(named: "banana.jpeg") selectImage = UIImage.init(named: "hand.jpg")
selectImageView.image = selectImage selectImageView.image = selectImage
modelHelper.getTexture(image: selectImage!.cgImage!) {[weak self] (texture) in modelHelper.getTexture(image: selectImage!.cgImage!) {[weak self] (texture) in
self?.toPredictTexture = texture self?.toPredictTexture = texture
......
metal/paddle-mobile/paddle-mobile.xcodeproj/project.pbxproj
浏览文件 @ b602b048
...@@ -46,6 +46,8 @@ ...@@ -46,6 +46,8 @@
FC9D038020E22FBB000F735A /* FeedOp.swift in Sources */ = {isa = PBXBuildFile; fileRef = FC9D037F20E22FBB000F735A /* FeedOp.swift */; }; FC9D038020E22FBB000F735A /* FeedOp.swift in Sources */ = {isa = PBXBuildFile; fileRef = FC9D037F20E22FBB000F735A /* FeedOp.swift */; };
FC9D038220E2312E000F735A /* FetchOp.swift in Sources */ = {isa = PBXBuildFile; fileRef = FC9D038120E2312E000F735A /* FetchOp.swift */; }; FC9D038220E2312E000F735A /* FetchOp.swift in Sources */ = {isa = PBXBuildFile; fileRef = FC9D038120E2312E000F735A /* FetchOp.swift */; };
FC9D038420E23B01000F735A /* Texture.swift in Sources */ = {isa = PBXBuildFile; fileRef = FC9D038320E23B01000F735A /* Texture.swift */; }; FC9D038420E23B01000F735A /* Texture.swift in Sources */ = {isa = PBXBuildFile; fileRef = FC9D038320E23B01000F735A /* Texture.swift */; };
FCA3A1632132A4AC00084FE5 /* ReshapeKernel.metal in Sources */ = {isa = PBXBuildFile; fileRef = FCA3A1622132A4AC00084FE5 /* ReshapeKernel.metal */; };
FCA3A1652132A5EB00084FE5 /* Common.metal in Sources */ = {isa = PBXBuildFile; fileRef = FCA3A1642132A5EB00084FE5 /* Common.metal */; };
FCBCCC572122F41300D94F7E /* DwConvBNReluOp.swift in Sources */ = {isa = PBXBuildFile; fileRef = FCBCCC562122F41300D94F7E /* DwConvBNReluOp.swift */; }; FCBCCC572122F41300D94F7E /* DwConvBNReluOp.swift in Sources */ = {isa = PBXBuildFile; fileRef = FCBCCC562122F41300D94F7E /* DwConvBNReluOp.swift */; };
FCBCCC592122F42700D94F7E /* ConvBNReluOp.swift in Sources */ = {isa = PBXBuildFile; fileRef = FCBCCC582122F42700D94F7E /* ConvBNReluOp.swift */; }; FCBCCC592122F42700D94F7E /* ConvBNReluOp.swift in Sources */ = {isa = PBXBuildFile; fileRef = FCBCCC582122F42700D94F7E /* ConvBNReluOp.swift */; };
FCBCCC5B2122F66F00D94F7E /* ConvBNReluKernel.swift in Sources */ = {isa = PBXBuildFile; fileRef = FCBCCC5A2122F66F00D94F7E /* ConvBNReluKernel.swift */; }; FCBCCC5B2122F66F00D94F7E /* ConvBNReluKernel.swift in Sources */ = {isa = PBXBuildFile; fileRef = FCBCCC5A2122F66F00D94F7E /* ConvBNReluKernel.swift */; };
...@@ -126,6 +128,8 @@ ...@@ -126,6 +128,8 @@
FC9D037F20E22FBB000F735A /* FeedOp.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = FeedOp.swift; sourceTree = "<group>"; }; FC9D037F20E22FBB000F735A /* FeedOp.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = FeedOp.swift; sourceTree = "<group>"; };
FC9D038120E2312E000F735A /* FetchOp.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = FetchOp.swift; sourceTree = "<group>"; }; FC9D038120E2312E000F735A /* FetchOp.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = FetchOp.swift; sourceTree = "<group>"; };
FC9D038320E23B01000F735A /* Texture.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = Texture.swift; sourceTree = "<group>"; }; FC9D038320E23B01000F735A /* Texture.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = Texture.swift; sourceTree = "<group>"; };
FCA3A1622132A4AC00084FE5 /* ReshapeKernel.metal */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.metal; path = ReshapeKernel.metal; sourceTree = "<group>"; };
FCA3A1642132A5EB00084FE5 /* Common.metal */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.metal; path = Common.metal; sourceTree = "<group>"; };
FCBCCC562122F41300D94F7E /* DwConvBNReluOp.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = DwConvBNReluOp.swift; sourceTree = "<group>"; }; FCBCCC562122F41300D94F7E /* DwConvBNReluOp.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = DwConvBNReluOp.swift; sourceTree = "<group>"; };
FCBCCC582122F42700D94F7E /* ConvBNReluOp.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = ConvBNReluOp.swift; sourceTree = "<group>"; }; FCBCCC582122F42700D94F7E /* ConvBNReluOp.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = ConvBNReluOp.swift; sourceTree = "<group>"; };
FCBCCC5A2122F66F00D94F7E /* ConvBNReluKernel.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = ConvBNReluKernel.swift; sourceTree = "<group>"; }; FCBCCC5A2122F66F00D94F7E /* ConvBNReluKernel.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = ConvBNReluKernel.swift; sourceTree = "<group>"; };
...@@ -349,6 +353,8 @@ ...@@ -349,6 +353,8 @@
FCDDC6C9212FDF6800E5EF74 /* BatchNormKernel.metal */, FCDDC6C9212FDF6800E5EF74 /* BatchNormKernel.metal */,
FCDDC6CB212FDFDB00E5EF74 /* ReluKernel.metal */, FCDDC6CB212FDFDB00E5EF74 /* ReluKernel.metal */,
FCDDC6CE212FE14700E5EF74 /* PriorBoxKernel.metal */, FCDDC6CE212FE14700E5EF74 /* PriorBoxKernel.metal */,
FCA3A1622132A4AC00084FE5 /* ReshapeKernel.metal */,
FCA3A1642132A5EB00084FE5 /* Common.metal */,
); );
path = metal; path = metal;
sourceTree = "<group>"; sourceTree = "<group>";
...@@ -482,6 +488,7 @@ ...@@ -482,6 +488,7 @@
FC039BB820E11CC20081E9F8 /* framework.pb.swift in Sources */, FC039BB820E11CC20081E9F8 /* framework.pb.swift in Sources */,
FC039B9920E11C9A0081E9F8 /* Types.swift in Sources */, FC039B9920E11C9A0081E9F8 /* Types.swift in Sources */,
FC4CB74920F0B954007C0C6D /* ConvKernel.metal in Sources */, FC4CB74920F0B954007C0C6D /* ConvKernel.metal in Sources */,
FCA3A1632132A4AC00084FE5 /* ReshapeKernel.metal in Sources */,
FCBCCC592122F42700D94F7E /* ConvBNReluOp.swift in Sources */, FCBCCC592122F42700D94F7E /* ConvBNReluOp.swift in Sources */,
FC039BA920E11CBC0081E9F8 /* ConvOp.swift in Sources */, FC039BA920E11CBC0081E9F8 /* ConvOp.swift in Sources */,
FC9D038420E23B01000F735A /* Texture.swift in Sources */, FC9D038420E23B01000F735A /* Texture.swift in Sources */,
...@@ -503,6 +510,7 @@ ...@@ -503,6 +510,7 @@
FCBCCC69212306D300D94F7E /* ConcatKernel.swift in Sources */, FCBCCC69212306D300D94F7E /* ConcatKernel.swift in Sources */,
FCDDC6C8212FA3CA00E5EF74 /* ConvTransposeKernel.swift in Sources */, FCDDC6C8212FA3CA00E5EF74 /* ConvTransposeKernel.swift in Sources */,
FC82735920E3C04200BE430A /* OpCreator.swift in Sources */, FC82735920E3C04200BE430A /* OpCreator.swift in Sources */,
FCA3A1652132A5EB00084FE5 /* Common.metal in Sources */,
FCBCCC5D2122F8A100D94F7E /* DepthwiseConvOp.swift in Sources */, FCBCCC5D2122F8A100D94F7E /* DepthwiseConvOp.swift in Sources */,
FC0E2DBE20EE460D009C1FAC /* BatchNormKernel.swift in Sources */, FC0E2DBE20EE460D009C1FAC /* BatchNormKernel.swift in Sources */,
FC039BAB20E11CBC0081E9F8 /* Operator.swift in Sources */, FC039BAB20E11CBC0081E9F8 /* Operator.swift in Sources */,
......
metal/paddle-mobile/paddle-mobile/Common/Extensions.swift
浏览文件 @ b602b048
...@@ -16,95 +16,110 @@ import Foundation ...@@ -16,95 +16,110 @@ import Foundation
// 自定义 ?! 如果 ?! 前的返回值为一个可选值, 则进行隐式解包, 如果有值则返回这个值, 如果为nil 则fatalError 传入的信息 // 自定义 ?! 如果 ?! 前的返回值为一个可选值, 则进行隐式解包, 如果有值则返回这个值, 如果为nil 则fatalError 传入的信息
precedencegroup ExecutedOrFatalError{ precedencegroup ExecutedOrFatalError{
associativity: left associativity: left
higherThan: AssignmentPrecedence higherThan: AssignmentPrecedence
} }
infix operator ?!: ExecutedOrFatalError infix operator ?!: ExecutedOrFatalError
public func ?!<T>(option: T?, excuteOrError: @autoclosure () -> String) -> T{ public func ?!<T>(option: T?, excuteOrError: @autoclosure () -> String) -> T{
if let inOpt = option { if let inOpt = option {
return inOpt return inOpt
}else{ }else{
print(excuteOrError()) print(excuteOrError())
fatalError(excuteOrError()) fatalError(excuteOrError())
} }
} }
//Lense //Lense
struct Lense<A, B> { struct Lense<A, B> {
let from: (A) -> B let from: (A) -> B
let to: (B, A) -> A let to: (B, A) -> A
} }
precedencegroup CombineLense{ precedencegroup CombineLense{
associativity: left associativity: left
higherThan: AssignmentPrecedence higherThan: AssignmentPrecedence
} }
infix operator >>>: CombineLense infix operator >>>: CombineLense
func >>><A, B, C>(left: Lense<B, C>, right: Lense<A, B>) -> Lense<A, C> { func >>><A, B, C>(left: Lense<B, C>, right: Lense<A, B>) -> Lense<A, C> {
return Lense<A, C>.init(from: { (a) -> C in return Lense<A, C>.init(from: { (a) -> C in
left.from(right.from(a)) left.from(right.from(a))
}, to: { (c, a) -> A in }, to: { (c, a) -> A in
right.to( left.to(c, right.from(a)),a) right.to( left.to(c, right.from(a)),a)
}) })
} }
protocol CIntIndex { protocol CIntIndex {
associatedtype T; associatedtype T;
subscript(index: CInt) -> T { get set}; subscript(index: CInt) -> T { get set};
} }
extension Array: CIntIndex{ extension Array: CIntIndex{
typealias T = Element typealias T = Element
subscript(index: CInt) -> T { subscript(index: CInt) -> T {
get{ get{
guard Int64(Int.max) >= Int64(index) else{ guard Int64(Int.max) >= Int64(index) else{
fatalError("cint index out of Int range") fatalError("cint index out of Int range")
} }
return self[Int(index)] return self[Int(index)]
} }
set{ set{
guard Int64(Int.max) >= Int64(index) else{ guard Int64(Int.max) >= Int64(index) else{
fatalError("cint index out of Int range") fatalError("cint index out of Int range")
} }
self[Int(index)] = newValue self[Int(index)] = newValue
}
} }
}
} }
extension Array where Element: AnyObject{ extension Array where Element: AnyObject{
mutating func remove(element: Element) { mutating func remove(element: Element) {
if let index = index(where: { (node) -> Bool in if let index = index(where: { (node) -> Bool in
return unsafeBitCast(element, to: Int.self) == unsafeBitCast(node, to: Int.self) return unsafeBitCast(element, to: Int.self) == unsafeBitCast(node, to: Int.self)
}) { }) {
remove(at: index) remove(at: index)
}
} }
}
} }
//MARK: Array extension //MARK: Array extension
extension Array where Element: Comparable{ extension Array where Element: Comparable{
/// 返回数组前 r 个元素, 并将元素处于原数组的位置作为元组的第一个元素返回 /// 返回数组前 r 个元素, 并将元素处于原数组的位置作为元组的第一个元素返回
/// ///
/// - Parameter r: 前 r 个元素 /// - Parameter r: 前 r 个元素
/// - Returns: [(原有位置, 排好位置的元素)] /// - Returns: [(原有位置, 排好位置的元素)]
public func top(r: Int) -> [(Int, Element)] { public func top(r: Int) -> [(Int, Element)] {
precondition(r <= self.count) precondition(r <= self.count)
return Array<(Int, Element)>(zip(0..<self.count, self).sorted{ $0.1 > $1.1 }.prefix(through: r - 1)) return Array<(Int, Element)>(zip(0..<self.count, self).sorted{ $0.1 > $1.1 }.prefix(through: r - 1))
}
}
extension Array {
func strideArray(inCount: Int = 20) -> Array<Element> {
if count < inCount {
return self
} else {
let stride = count / inCount
var newArray: [Element] = []
for i in 0..<inCount {
newArray.append(self[i * stride])
}
return newArray
} }
}
} }
extension String{ extension String{
func cStr() -> UnsafePointer<Int8>? { func cStr() -> UnsafePointer<Int8>? {
return (self as NSString).utf8String return (self as NSString).utf8String
} }
} }
func address<T: AnyObject>(o: T) -> String { func address<T: AnyObject>(o: T) -> String {
return String.init(format: "%018p", unsafeBitCast(o, to: Int.self)) return String.init(format: "%018p", unsafeBitCast(o, to: Int.self))
} }
......
metal/paddle-mobile/paddle-mobile/Common/Types.swift
浏览文件 @ b602b048
...@@ -15,207 +15,210 @@ ...@@ -15,207 +15,210 @@
import Foundation import Foundation
public protocol SummableMultipliable: Equatable { public protocol SummableMultipliable: Equatable {
static func +(lhs: Self, rhs: Self) -> Self static func +(lhs: Self, rhs: Self) -> Self
static func *(lhs: Self, rhs: Self) -> Self static func *(lhs: Self, rhs: Self) -> Self
static func -(lhs: Self, rhs: Self) -> Self static func -(lhs: Self, rhs: Self) -> Self
} }
public protocol PrecisionType: SummableMultipliable{ public protocol PrecisionType: SummableMultipliable{
init(inFloat: Float32) init(inFloat: Float32)
init(inFloat16: Float16) init(inFloat16: Float16)
init<P: PrecisionType>(_ inP: P) init<P: PrecisionType>(_ inP: P)
static var bitSize: UInt { get } static var bitSize: UInt { get }
} }
public typealias Float16 = Int16 public typealias Float16 = Int16
extension Float16: PrecisionType { extension Float16: PrecisionType {
public static func * (prefix: Float16, postfix: Float16) { public static func * (prefix: Float16, postfix: Float16) {
return prefix * postfix return prefix * postfix
} }
public init<P>(_ inP: P) where P : PrecisionType { public init<P>(_ inP: P) where P : PrecisionType {
if P.bitSize == Float32.bitSize { if P.bitSize == Float32.bitSize {
self = Float16(inFloat: inP as! Float32) self = Float16(inFloat: inP as! Float32)
} else if P.bitSize == Float16.bitSize { } else if P.bitSize == Float16.bitSize {
self = inP as! Float16 self = inP as! Float16
} else { } else {
fatalError() fatalError()
} }
} }
public static var bitSize: UInt { public static var bitSize: UInt {
return 16 return 16
} }
public init(inFloat16: Float16) { public init(inFloat16: Float16) {
self = inFloat16 self = inFloat16
} }
public init(inFloat: Float32) { public init(inFloat: Float32) {
self = Int16(inFloat) self = Int16(inFloat)
} }
} }
extension Float32: PrecisionType { extension Float32: PrecisionType {
public init<P>(_ inP: P) where P : PrecisionType { public init<P>(_ inP: P) where P : PrecisionType {
if P.bitSize == Float32.bitSize { if P.bitSize == Float32.bitSize {
self = inP as! Float32 self = inP as! Float32
} else if P.bitSize == Float16.bitSize { } else if P.bitSize == Float16.bitSize {
self = Float32.init(inP as! Float16) self = Float32.init(inP as! Float16)
} else { } else {
fatalError() fatalError()
} }
} }
public init(inFloat: Float32) { public init(inFloat: Float32) {
self = inFloat self = inFloat
} }
public init(inFloat16: Float16) { public init(inFloat16: Float16) {
self = Float32.init(inFloat16) self = Float32.init(inFloat16)
} }
public static var bitSize: UInt { public static var bitSize: UInt {
return 32 return 32
} }
} }
// N - 0 C - 1 H - 2 W - 3 // N - 0 C - 1 H - 2 W - 3
struct DataLayout { struct DataLayout {
static func NCHW(dim: Dim = Dim.init(inDim: [0, 0, 0, 0])) -> DataLayout { static func NCHW(dim: Dim = Dim.init(inDim: [0, 0, 0, 0])) -> DataLayout {
return DataLayout.init([(.N, dim[0]), (.C, dim[1]), (.H, dim[2]), (.W, dim[3])]) return DataLayout.init([(.N, dim[0]), (.C, dim[1]), (.H, dim[2]), (.W, dim[3])])
} }
static func NHWC(dim: Dim = Dim.init(inDim: [0, 0, 0, 0])) -> DataLayout { static func NHWC(dim: Dim = Dim.init(inDim: [0, 0, 0, 0])) -> DataLayout {
return DataLayout.init([(.N, dim[0]), (.H, dim[1]), (.W, dim[2]), (.C, dim[3])]) return DataLayout.init([(.N, dim[0]), (.H, dim[1]), (.W, dim[2]), (.C, dim[3])])
} }
func count() -> Int { func count() -> Int {
return layoutWithDim.count return layoutWithDim.count
} }
var N: Int? { var N: Int? {
get { get {
for layoutDim in layoutWithDim { for layoutDim in layoutWithDim {
if layoutDim.0 == .N { if layoutDim.0 == .N {
return layoutDim.1 return layoutDim.1
}
}
return nil
}
set {
var newN = (Layout.N, newValue)
if let index = layoutWithDim.index(where: { (layout: Layout, dim: Int) -> Bool in
return layout == .N
}) {
fatalError()
}
}
}
var C: Int? {
get {
for layoutDim in layoutWithDim {
if layoutDim.0 == .C {
return layoutDim.1
}
}
return nil
}
set {
var newN = (Layout.C, newValue)
if let index = layoutWithDim.index(where: { (layout: Layout, dim: Int) -> Bool in
return layout == .N
}) {
fatalError()
}
}
}
var H: Int? {
get {
for layoutDim in layoutWithDim {
if layoutDim.0 == .H {
return layoutDim.1
}
}
return nil
} }
set { }
var newN = (Layout.H, newValue) return nil
if let index = layoutWithDim.index(where: { (layout: Layout, dim: Int) -> Bool in }
return layout == .H set {
}) { var newN = (Layout.N, newValue)
fatalError() if let index = layoutWithDim.index(where: { (layout: Layout, dim: Int) -> Bool in
} return layout == .N
}) {
fatalError()
}
}
}
var C: Int? {
get {
for layoutDim in layoutWithDim {
if layoutDim.0 == .C {
return layoutDim.1
} }
} }
var W: Int? { return nil
get { }
for layoutDim in layoutWithDim { set {
if layoutDim.0 == .W { var newN = (Layout.C, newValue)
return layoutDim.1 if let index = layoutWithDim.index(where: { (layout: Layout, dim: Int) -> Bool in
} return layout == .N
} }) {
return nil fatalError()
}
}
}
var H: Int? {
get {
for layoutDim in layoutWithDim {
if layoutDim.0 == .H {
return layoutDim.1
} }
set { }
var newN = (Layout.W, newValue) return nil
if let index = layoutWithDim.index(where: { (layout: Layout, dim: Int) -> Bool in }
return layout == .W set {
}) { var newN = (Layout.H, newValue)
fatalError() if let index = layoutWithDim.index(where: { (layout: Layout, dim: Int) -> Bool in
} return layout == .H
}) {
fatalError()
}
}
}
var W: Int? {
get {
for layoutDim in layoutWithDim {
if layoutDim.0 == .W {
return layoutDim.1
} }
} }
return nil
}
init(_ inLayout: [(Layout, Int)]) { set {
layoutWithDim = inLayout var newN = (Layout.W, newValue)
} if let index = layoutWithDim.index(where: { (layout: Layout, dim: Int) -> Bool in
return layout == .W
func layout() -> [Layout] { }) {
return layoutWithDim.map({ (layout: Layout, dim: Int) -> Layout in fatalError()
return layout }
}) }
} }
var layoutWithDim: [(Layout, Int)] = [(.N, 0), (.C, 0), (.H, 0), (.W, 0)]
init(_ inLayout: [(Layout, Int)]) {
func convertTo(inLayout: [Layout]) { layoutWithDim = inLayout
}
}
func layout() -> [Layout] {
enum Layout: Int{ return layoutWithDim.map({ (layout: Layout, dim: Int) -> Layout in
case N = 0 return layout
case C = 1 })
case H = 2 }
case W = 3
static func defaultLayout() -> [Layout] { var layoutWithDim: [(Layout, Int)] = [(.N, 0), (.C, 0), (.H, 0), (.W, 0)]
return [N, C, H, W]
} func convertTo(inLayout: [Layout]) {
}
}
enum Layout: Int{
case N = 0
case C = 1
case H = 2
case W = 3
static func defaultLayout() -> [Layout] {
return [N, C, H, W]
}
}
} }
extension DataLayout: Equatable { extension DataLayout: Equatable {
public static func == (lhs: DataLayout, rhs: DataLayout) -> Bool { public static func == (lhs: DataLayout, rhs: DataLayout) -> Bool {
if lhs.layoutWithDim.count == rhs.layoutWithDim.count { if lhs.layoutWithDim.count == rhs.layoutWithDim.count {
var result = true var result = true
for i in 0..<lhs.layoutWithDim.count { for i in 0..<lhs.layoutWithDim.count {
result = (lhs.layoutWithDim[i] == rhs.layoutWithDim[i]) result = (lhs.layoutWithDim[i].0 == rhs.layoutWithDim[i].0)
} if !result {
return result break
} else {
return false
} }
}
return result
} else {
return false
} }
}
} }
protocol Variant: CustomStringConvertible, CustomDebugStringConvertible { public protocol Variant: CustomStringConvertible, CustomDebugStringConvertible {
} }
extension Tensor: Variant { extension Tensor: Variant {
...@@ -231,5 +234,5 @@ extension InputTexture: Variant { ...@@ -231,5 +234,5 @@ extension InputTexture: Variant {
} }
extension MTLTexture where Self: Variant { extension MTLTexture where Self: Variant {
} }
metal/paddle-mobile/paddle-mobile/Executor.swift
浏览文件 @ b602b048
...@@ -15,130 +15,150 @@ ...@@ -15,130 +15,150 @@
import Foundation import Foundation
public class ResultHolder<P: PrecisionType> { public class ResultHolder<P: PrecisionType> {
public let dim: [Int] public let dim: [Int]
public let resultArr: [P] public let resultArr: [P]
public var intermediateResults: [Texture<P>]? public var intermediateResults: [Variant]?
public let elapsedTime: Double public let elapsedTime: Double
public init(inDim: [Int], inResult: [P], inElapsedTime: Double, inIntermediateResults: [Texture<P>]? = nil) { public init(inDim: [Int], inResult: [P], inElapsedTime: Double, inIntermediateResults: [Variant]? = nil) {
dim = inDim dim = inDim
resultArr = inResult resultArr = inResult
elapsedTime = inElapsedTime elapsedTime = inElapsedTime
intermediateResults = inIntermediateResults intermediateResults = inIntermediateResults
} }
} }
extension ResultHolder: CustomDebugStringConvertible, CustomStringConvertible { extension ResultHolder: CustomDebugStringConvertible, CustomStringConvertible {
public var debugDescription: String { public var debugDescription: String {
var str = "" var str = ""
str += "Dim: \(dim) \n value:[ " str += "Dim: \(dim) \n value:[ "
if resultArr.count < 20 { if resultArr.count < 20 {
for d in resultArr { for d in resultArr {
str += " \(d) " str += " \(d) "
} }
} else { } else {
for d in stride(from: 0, to: resultArr.count, by: resultArr.count/20) { for d in stride(from: 0, to: resultArr.count, by: resultArr.count/20) {
str += " \(resultArr[d]) " str += " \(resultArr[d]) "
} }
}
str += " ]"
return str
}
public var description: String {
return debugDescription
} }
str += " ]"
return str
}
public var description: String {
return debugDescription
}
} }
public class Executor<P: PrecisionType> { public class Executor<P: PrecisionType> {
var ops: [Runable & InferShaperable] = [] var ops: [Runable & InferShaperable] = []
let program: Program let program: Program
let device: MTLDevice let device: MTLDevice
let queue: MTLCommandQueue let queue: MTLCommandQueue
public init(inDevice:MTLDevice, inQueue: MTLCommandQueue, inProgram: Program) throws { public init(inDevice:MTLDevice, inQueue: MTLCommandQueue, inProgram: Program) throws {
program = inProgram program = inProgram
device = inDevice device = inDevice
queue = inQueue queue = inQueue
for block in inProgram.programDesc.blocks { for block in inProgram.programDesc.blocks {
//block.ops.count //block.ops.count
for i in 0..<block.ops.count { for i in 0..<39 {
let op = block.ops[i] let op = block.ops[i]
do { do {
let op = try OpCreator<P>.shared.creat(device: inDevice, opDesc: op, scope: inProgram.scope) let op = try OpCreator<P>.shared.creat(device: inDevice, opDesc: op, scope: inProgram.scope)
op.inferShape() // op.inferShape()
ops.append(op) ops.append(op)
} catch let error { } catch let error {
throw error throw error
}
}
} }
} }
}
}
public func predict(input: MTLTexture, expect: [Int], completionHandle: @escaping (ResultHolder<P>) -> Void, preProcessKernle: CusomKernel? = nil, except: Int = 0) throws {
guard let buffer = queue.makeCommandBuffer() else {
throw PaddleMobileError.predictError(message: "CommandBuffer is nil")
}
let resInput: MTLTexture
if let inPre = preProcessKernle {
do {
try inPre.compute(inputTexuture: input, commandBuffer: buffer)
resInput = inPre.outputTexture
} catch let error {
throw error
}
} else {
resInput = input
}
public func predict(input: MTLTexture, expect: [Int], completionHandle: @escaping (ResultHolder<P>) -> Void, preProcessKernle: CusomKernel? = nil) throws { let beforeDate = Date.init()
guard let buffer = queue.makeCommandBuffer() else { let inputTexture = InputTexture.init(inMTLTexture: resInput, inExpectDim: Dim.init(inDim: expect))
throw PaddleMobileError.predictError(message: "CommandBuffer is nil") program.scope.setInput(input: inputTexture)
} //(ops.count - except)
let resInput: MTLTexture for i in 0..<ops.count {
if let inPre = preProcessKernle { let op = ops[i]
do { do {
try inPre.compute(inputTexuture: input, commandBuffer: buffer) try op.run(device: device, buffer: buffer)
resInput = inPre.outputTexture } catch let error {
} catch let error { throw error
throw error }
}
} else {
resInput = input
}
let beforeDate = Date.init()
let inputTexture = InputTexture.init(inMTLTexture: resInput, inExpectDim: Dim.init(inDim: expect))
program.scope.setInput(input: inputTexture)
for op in ops {
do {
try op.run(device: device, buffer: buffer)
} catch let error {
throw error
}
}
buffer.addCompletedHandler { (commandbuffer) in
// let inputArr = resInput.floatArray(res: { (p:P) -> P in
// return p
// })
// print(inputArr)
// let stridableInput: [(index: Int, value: Float)] = input.stridableFloatArray()
// print(stridableInput)
// let _: Flo? = input.logDesc(header: "input: ", stridable: true)
// for op in self.ops {
// op.delogOutput()
// }
// return
// self.ops[2].delogOutput()
let afterDate = Date.init()
guard let outputVar = self.program.scope.output() else {
fatalError("output nil")
}
guard let output = outputVar as? Texture<P> else {
fatalError("output var type error")
}
let resultHodlder = ResultHolder<P>.init(inDim: output.dim.dims, inResult: output.metalTexture.floatArray(res: { (p:P) -> P in
return p
}), inElapsedTime: afterDate.timeIntervalSince(beforeDate))
completionHandle(resultHodlder)
}
buffer.commit()
} }
public func clear() { var outputTextures: [Variant]?
program.scope.clear() if except > 0 {
outputTextures = ops[ops.count - except].inputs()
} }
buffer.addCompletedHandler { (commandbuffer) in
// return;
// let inputArr = resInput.floatArray(res: { (p:P) -> P in
// return p
// })
// writeToLibrary(fileName: "input_hand", array: inputArr)
// print("write to library done")
// return
// print(inputArr)
// let stridableInput: [(index: Int, value: Float)] = input.stridableFloatArray()
// print(stridableInput)
// let _: Flo? = input.logDesc(header: "input: ", stridable: true)
for op in self.ops {
// op.delogOutput()
}
// return
self.ops[38].delogOutput()
// self.ops[91].delogOutput()
// self.ops[92].delogOutput()
// self.ops[93].delogOutput()
return;
let afterDate = Date.init()
var resultHolder: ResultHolder<P>
if except > 0 {
resultHolder = ResultHolder<P>.init(inDim: [], inResult: [], inElapsedTime: afterDate.timeIntervalSince(beforeDate), inIntermediateResults: outputTextures)
} else {
let outputVar: Variant = self.program.scope.output()!
let output: Texture<P> = outputVar as! Texture<P>
resultHolder = ResultHolder<P>.init(inDim: output.dim.dims, inResult: output.metalTexture.floatArray(res: { (p:P) -> P in
return p
}), inElapsedTime: afterDate.timeIntervalSince(beforeDate))
}
completionHandle(resultHolder)
}
buffer.commit()
}
public func clear() {
program.scope.clear()
}
} }
//public let paddle_executor: Executor = Executor.init() //public let paddle_executor: Executor = Executor.init()
metal/paddle-mobile/paddle-mobile/Operators/Base/Operator.swift
浏览文件 @ b602b048
...@@ -16,100 +16,101 @@ import Metal ...@@ -16,100 +16,101 @@ import Metal
import Foundation import Foundation
protocol Fusion { protocol Fusion {
static func fusionNode() -> Node static func fusionNode() -> Node
static func change() -> [String : [(from: String, to: String)]] static func change() -> [String : [(from: String, to: String)]]
static func fusionType() -> String static func fusionType() -> String
} }
protocol Runable { protocol Runable {
func run(device: MTLDevice, buffer: MTLCommandBuffer) throws func run(device: MTLDevice, buffer: MTLCommandBuffer) throws
func runImpl(device: MTLDevice,buffer: MTLCommandBuffer) throws func runImpl(device: MTLDevice,buffer: MTLCommandBuffer) throws
func delogOutput() func delogOutput()
func inputs() -> [Variant]
} }
extension Runable where Self: OperatorProtocol{ extension Runable where Self: OperatorProtocol{
func run(device: MTLDevice, buffer: MTLCommandBuffer) throws { func run(device: MTLDevice, buffer: MTLCommandBuffer) throws {
do { do {
try runImpl(device: device, buffer: buffer) try runImpl(device: device, buffer: buffer)
} catch let error { } catch let error {
throw error throw error
}
// print(type + ": " + para.outputDesc())
}
func delogOutput() {
print(type + ": has no implementation" )
} }
// print(type + ": " + para.outputDesc())
}
func delogOutput() {
print(type + ": has no implementation" )
}
} }
protocol Creator where Self: OperatorProtocol{ protocol Creator where Self: OperatorProtocol{
associatedtype OpType: OperatorProtocol & Runable & InferShaperable 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) throws -> OpType
} }
extension Creator where Self: OperatorProtocol { 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) throws -> OpType {
do { do {
return try OpType.provide(device:device, opDesc: opDesc, inScope: inScope) return try OpType.provide(device:device, opDesc: opDesc, inScope: inScope)
} catch let error { } catch let error {
throw error throw error
}
} }
}
} }
protocol InferShaperable { protocol InferShaperable {
func inferShape() func inferShape()
} }
protocol OperatorProtocol { protocol OperatorProtocol {
associatedtype ParamType associatedtype ParamType
associatedtype KerType: Computable where Self.KerType.ParamType == ParamType associatedtype KerType: Computable where Self.KerType.ParamType == ParamType
var type: String { get } var type: String { get }
var scope: Scope { get } var scope: Scope { get }
var inputs: [String : [String]] { get } var inputs: [String : [String]] { get }
var paraInputs: [String : [String]] { get set } var paraInputs: [String : [String]] { get set }
var outpus: [String : [String]] { get } var outpus: [String : [String]] { get }
var attrs: [String : Attr] { get } var attrs: [String : Attr] { get }
var para: ParamType { get } var para: ParamType { get }
var kernel: KerType { get } var kernel: KerType { get }
init(device: MTLDevice, opDesc: OpDesc, inScope: Scope) throws init(device: MTLDevice, opDesc: OpDesc, inScope: Scope) throws
} }
extension OperatorProtocol { extension OperatorProtocol {
static func provide(device: MTLDevice, opDesc: OpDesc, inScope: Scope) throws -> Self { static func provide(device: MTLDevice, opDesc: OpDesc, inScope: Scope) throws -> Self {
do { do {
return try Self.init(device: device, opDesc: opDesc, inScope: inScope) return try Self.init(device: device, opDesc: opDesc, inScope: inScope)
} catch let error { } catch let error {
throw error throw error
}
} }
}
} }
class Operator <KernelType: Computable , ParameterType>: OperatorProtocol where KernelType.ParamType == ParameterType { class Operator <KernelType: Computable , ParameterType>: OperatorProtocol where KernelType.ParamType == ParameterType {
typealias ParamType = ParameterType typealias ParamType = ParameterType
typealias KerType = KernelType typealias KerType = KernelType
let type: String let type: String
let inputs: [String : [String]] let inputs: [String : [String]]
var paraInputs: [String : [String]] var paraInputs: [String : [String]]
let outpus: [String : [String]] let outpus: [String : [String]]
let attrs: [String : Attr] let attrs: [String : Attr]
let para: ParamType let para: ParamType
let scope: Scope let scope: Scope
var kernel: KerType var kernel: KerType
required init(device: MTLDevice, opDesc: OpDesc, inScope: Scope) throws { required init(device: MTLDevice, opDesc: OpDesc, inScope: Scope) throws {
type = opDesc.type type = opDesc.type
scope = inScope scope = inScope
inputs = opDesc.inputs inputs = opDesc.inputs
outpus = opDesc.outputs outpus = opDesc.outputs
attrs = opDesc.attrs attrs = opDesc.attrs
paraInputs = opDesc.paraInputs paraInputs = opDesc.paraInputs
do { do {
para = try ParamType.init(opDesc:opDesc, inScope: inScope) para = try ParamType.init(opDesc:opDesc, inScope: inScope)
} catch let error { } catch let error {
throw error throw error
}
kernel = KernelType.init(device: device, param: para)
} }
kernel = KernelType.init(device: device, param: para)
}
} }
// op infos // op infos
......
metal/paddle-mobile/paddle-mobile/Operators/BatchNormOp.swift
浏览文件 @ b602b048
...@@ -15,45 +15,50 @@ ...@@ -15,45 +15,50 @@
import Foundation import Foundation
class BatchNormParam<P: PrecisionType>: OpParam { class BatchNormParam<P: PrecisionType>: OpParam {
typealias ParamPrecisionType = P typealias ParamPrecisionType = P
required init(opDesc: OpDesc, inScope: Scope) throws { required init(opDesc: OpDesc, inScope: Scope) throws {
do { do {
input = try BatchNormParam.inputX(inputs: opDesc.inputs, from: inScope) input = try BatchNormParam.inputX(inputs: opDesc.inputs, from: inScope)
output = try BatchNormParam.outputY(outputs: opDesc.outputs, from: inScope) output = try BatchNormParam.outputY(outputs: opDesc.outputs, from: inScope)
inputBias = try BatchNormParam.inputBiase(inputs: opDesc.paraInputs, from: inScope) inputBias = try BatchNormParam.inputBiase(inputs: opDesc.paraInputs, from: inScope)
inputMean = try BatchNormParam.inputMean(inputs: opDesc.paraInputs, from: inScope) inputMean = try BatchNormParam.inputMean(inputs: opDesc.paraInputs, from: inScope)
inputScale = try BatchNormParam.inputScale(inputs: opDesc.paraInputs, from: inScope) inputScale = try BatchNormParam.inputScale(inputs: opDesc.paraInputs, from: inScope)
inputVariance = try BatchNormParam.inputVariance(inputs: opDesc.paraInputs, from: inScope) inputVariance = try BatchNormParam.inputVariance(inputs: opDesc.paraInputs, from: inScope)
epsilon = try BatchNormParam.getAttr(key: "epsilon", attrs: opDesc.attrs) epsilon = try BatchNormParam.getAttr(key: "epsilon", attrs: opDesc.attrs)
momentum = try BatchNormParam.getAttr(key: "momentum", attrs: opDesc.attrs) momentum = try BatchNormParam.getAttr(key: "momentum", attrs: opDesc.attrs)
is_test = try BatchNormParam.getAttr(key: "is_test", attrs: opDesc.attrs) is_test = try BatchNormParam.getAttr(key: "is_test", attrs: opDesc.attrs)
} catch let error { } catch let error {
throw error throw error
}
} }
let input: Texture<P> }
var output: Texture<P> let input: Texture<P>
let inputBias: Tensor<ParamPrecisionType> var output: Texture<P>
let inputMean: Tensor<ParamPrecisionType> let inputBias: Tensor<ParamPrecisionType>
let inputScale: Tensor<ParamPrecisionType> let inputMean: Tensor<ParamPrecisionType>
let inputVariance: Tensor<ParamPrecisionType> let inputScale: Tensor<ParamPrecisionType>
let epsilon: Float let inputVariance: Tensor<ParamPrecisionType>
let momentum: Float let epsilon: Float
let is_test: Bool let momentum: Float
let is_test: Bool
} }
class BatchNormOp<P: PrecisionType>: Operator<BatchNormKernel<P>, BatchNormParam<P>>, Runable, Creator, InferShaperable{ class BatchNormOp<P: PrecisionType>: Operator<BatchNormKernel<P>, BatchNormParam<P>>, Runable, Creator, InferShaperable{
func inferShape() {
para.output.dim = para.input.dim func inputs() -> [Variant] {
} return [para.input, para.inputBias, para.inputMean, para.inputScale, para.inputVariance]
typealias OpType = BatchNormOp<P> }
func runImpl(device: MTLDevice, buffer: MTLCommandBuffer) throws {
do { func inferShape() {
try kernel.compute(commandBuffer: buffer, param: para) para.output.dim = para.input.dim
} catch let error { }
throw error typealias OpType = BatchNormOp<P>
} func runImpl(device: MTLDevice, buffer: MTLCommandBuffer) throws {
do {
try kernel.compute(commandBuffer: buffer, param: para)
} catch let error {
throw error
} }
}
} }
......
metal/paddle-mobile/paddle-mobile/Operators/BoxcoderOp.swift
浏览文件 @ b602b048
///* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved. ///* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
// //
// Licensed under the Apache License, Version 2.0 (the "License"); // Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License. // you may not use this file except in compliance with the License.
// You may obtain a copy of the License at // You may obtain a copy of the License at
// //
// http://www.apache.org/licenses/LICENSE-2.0 // http://www.apache.org/licenses/LICENSE-2.0
// //
// Unless required by applicable law or agreed to in writing, software // Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS, // distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and // See the License for the specific language governing permissions and
// limitations under the License. */ // limitations under the License. */
import Foundation import Foundation
class BoxcoderParam<P: PrecisionType>: OpParam { class BoxcoderParam<P: PrecisionType>: OpParam {
typealias ParamPrecisionType = P typealias ParamPrecisionType = P
required init(opDesc: OpDesc, inScope: Scope) throws { required init(opDesc: OpDesc, inScope: Scope) throws {
do { do {
priorBox = try BoxcoderParam.getFirstTensor(key: "PriorBox", map: opDesc.inputs, from: inScope) priorBox = try BoxcoderParam.getFirstTensor(key: "PriorBox", map: opDesc.inputs, from: inScope)
priorBoxVar = try BoxcoderParam.getFirstTensor(key: "PriorBoxVar", map: opDesc.inputs, from: inScope) priorBoxVar = try BoxcoderParam.getFirstTensor(key: "PriorBoxVar", map: opDesc.inputs, from: inScope)
targetBox = try BoxcoderParam.getFirstTensor(key: "TargetBox", map: opDesc.inputs, from: inScope) targetBox = try BoxcoderParam.getFirstTensor(key: "TargetBox", map: opDesc.inputs, from: inScope)
output = try BoxcoderParam.getFirstTensor(key: "OutputBox", map: opDesc.outputs, from: inScope) output = try BoxcoderParam.getFirstTensor(key: "OutputBox", map: opDesc.outputs, from: inScope)
codeType = try BoxcoderParam.getAttr(key: "code_type", attrs: opDesc.attrs) codeType = try BoxcoderParam.getAttr(key: "code_type", attrs: opDesc.attrs)
boxNormalized = try BoxcoderParam.getAttr(key: "box_normalized", attrs: opDesc.attrs) boxNormalized = try BoxcoderParam.getAttr(key: "box_normalized", attrs: opDesc.attrs)
} catch let error { } catch let error {
throw error throw error
} }
assert(priorBox.transpose == [0, 1, 2, 3]) assert(priorBox.transpose == [0, 1, 2, 3])
assert(priorBoxVar.transpose == [0, 1, 2, 3]) assert(priorBoxVar.transpose == [0, 1, 2, 3])
assert(targetBox.transpose == [0, 1, 2, 3]) assert(targetBox.transpose == [0, 1, 2, 3])
assert(codeType == "decode_center_size") // encode_center_size is not implemented assert(codeType == "decode_center_size") // encode_center_size is not implemented
assert((targetBox.tensorDim.cout() == 3) && (targetBox.tensorDim[0] == 1)) // N must be 1 (only handle batch size = 1) assert((targetBox.tensorDim.cout() == 3) && (targetBox.tensorDim[0] == 1)) // N must be 1 (only handle batch size = 1)
} }
let priorBox: Texture<P> let priorBox: Texture<P>
let priorBoxVar: Texture<P> let priorBoxVar: Texture<P>
...@@ -39,23 +39,42 @@ class BoxcoderParam<P: PrecisionType>: OpParam { ...@@ -39,23 +39,42 @@ class BoxcoderParam<P: PrecisionType>: OpParam {
var output: Texture<P> var output: Texture<P>
let codeType: String let codeType: String
let boxNormalized: Bool let boxNormalized: Bool
} }
class BoxcoderOp<P: PrecisionType>: Operator<BoxcoderKernel<P>, BoxcoderParam<P>>, Runable, Creator, InferShaperable{ class BoxcoderOp<P: PrecisionType>: Operator<BoxcoderKernel<P>, BoxcoderParam<P>>, Runable, Creator, InferShaperable{
func inputs() -> [Variant] {
return [para.priorBox, para.priorBoxVar, para.targetBox]
}
func inferShape() { func inferShape() {
// para.output.dim = para.input.dim // para.output.dim = para.input.dim
} }
typealias OpType = BoxcoderOp<P> typealias OpType = BoxcoderOp<P>
func runImpl(device: MTLDevice, buffer: MTLCommandBuffer) throws { func runImpl(device: MTLDevice, buffer: MTLCommandBuffer) throws {
do { do {
try kernel.compute(commandBuffer: buffer, param: para) try kernel.compute(commandBuffer: buffer, param: para)
} catch let error { } catch let error {
throw error throw error
} }
} }
}
func delogOutput() {
let outputArray = para.output.metalTexture.floatArray { (o: Float32) -> Float32 in
return o
}
print(outputArray.strideArray())
//box_coder_0.tmp_0
// writeToLibrary(fileName: "boxcoder_output", array: outputArray)
print(para.output.metalTexture)
print(" write done ")
}
}
metal/paddle-mobile/paddle-mobile/Operators/ConcatOp.swift
浏览文件 @ b602b048
...@@ -15,44 +15,67 @@ ...@@ -15,44 +15,67 @@
import Foundation import Foundation
class ConcatParam<P: PrecisionType>: OpParam { class ConcatParam<P: PrecisionType>: OpParam {
typealias ParamPrecisionType = P typealias ParamPrecisionType = P
required init(opDesc: OpDesc, inScope: Scope) throws { required init(opDesc: OpDesc, inScope: Scope) throws {
do { do {
guard let xlist = opDesc.inputs["X"] else { guard let xlist = opDesc.inputs["X"] else {
fatalError() fatalError()
} }
for x in xlist { for x in xlist {
guard let variant = inScope[x], let v = variant as? Texture<P> else { guard let variant = inScope[x], let v = variant as? Texture<P> else {
fatalError() fatalError()
}
input.append(v)
}
axis = try ConcatParam.getAttr(key: "axis", attrs: opDesc.attrs)
output = try ConcatParam.outputOut(outputs: opDesc.outputs, from: inScope)
} catch let error {
throw error
} }
input.append(v)
}
axis = try ConcatParam.getAttr(key: "axis", attrs: opDesc.attrs)
output = try ConcatParam.outputOut(outputs: opDesc.outputs, from: inScope)
} catch let error {
throw error
} }
var input: [Texture<P>] = [] }
var output: Texture<P> var input: [Texture<P>] = []
let axis: Int var output: Texture<P>
let axis: Int
} }
class ConcatOp<P: PrecisionType>: Operator<ConcatKernel<P>, ConcatParam<P>>, Runable, Creator, InferShaperable{ class ConcatOp<P: PrecisionType>: Operator<ConcatKernel<P>, ConcatParam<P>>, Runable, Creator, InferShaperable{
func inferShape() { func inputs() -> [Variant] {
// let dim = para.input.reduce([0, 0]) {[$0[0] + $1.dim[0], $1.dim[1]]} return para.input
// para.output.dim = Dim.init(inDim: dim) }
func inferShape() {
// let dim = para.input.reduce([0, 0]) {[$0[0] + $1.dim[0], $1.dim[1]]}
// para.output.dim = Dim.init(inDim: dim)
}
typealias OpType = ConcatOp<P>
func runImpl(device: MTLDevice, buffer: MTLCommandBuffer) throws {
do {
try kernel.compute(commandBuffer: buffer, param: para)
} catch let error {
throw error
} }
}
typealias OpType = ConcatOp<P>
func runImpl(device: MTLDevice, buffer: MTLCommandBuffer) throws { func delogOutput() {
do { let outputArray = para.output.metalTexture.floatArray { (o: Float32) -> Float32 in
try kernel.compute(commandBuffer: buffer, param: para) return o
} catch let error {
throw error
}
} }
print(outputArray.strideArray())
let device: MTLDevice = MTLCreateSystemDefaultDevice()!
// let tensorArray: [P] = device.texture2tensor(texture: para.output.metalTexture, dim: [1917, 4])
// print(tensorArray.strideArray())
// print(para.output.metalTexture)
// writeToLibrary(fileName: "concat_out", array: outputArray)
// print(" write done ")
// print(outputArray.strideArray())
}
} }
......
metal/paddle-mobile/paddle-mobile/Operators/ConvAddBatchNormReluOp.swift
浏览文件 @ b602b048
...@@ -16,120 +16,125 @@ import Foundation ...@@ -16,120 +16,125 @@ import Foundation
class ConvAddBatchNormReluParam<P: PrecisionType>: OpParam { class ConvAddBatchNormReluParam<P: PrecisionType>: OpParam {
typealias ParamPrecisionType = P typealias ParamPrecisionType = P
required init(opDesc: OpDesc, inScope: Scope) throws { required init(opDesc: OpDesc, inScope: Scope) throws {
do { do {
filter = try ConvAddBatchNormReluParam.inputFilter(paraInputs: opDesc.paraInputs, from: inScope) filter = try ConvAddBatchNormReluParam.inputFilter(paraInputs: opDesc.paraInputs, from: inScope)
input = try ConvAddBatchNormReluParam.input(inputs: opDesc.inputs, from: inScope) input = try ConvAddBatchNormReluParam.input(inputs: opDesc.inputs, from: inScope)
output = try ConvAddBatchNormReluParam.outputOut(outputs: opDesc.outputs, from: inScope) output = try ConvAddBatchNormReluParam.outputOut(outputs: opDesc.outputs, from: inScope)
stride = try ConvAddBatchNormReluParam.getAttr(key: "strides", attrs: opDesc.attrs) stride = try ConvAddBatchNormReluParam.getAttr(key: "strides", attrs: opDesc.attrs)
paddings = try ConvAddBatchNormReluParam.getAttr(key: "paddings", attrs: opDesc.attrs) paddings = try ConvAddBatchNormReluParam.getAttr(key: "paddings", attrs: opDesc.attrs)
dilations = try ConvAddBatchNormReluParam.getAttr(key: "dilations", attrs: opDesc.attrs) dilations = try ConvAddBatchNormReluParam.getAttr(key: "dilations", attrs: opDesc.attrs)
epsilon = try ConvAddBatchNormReluParam.getAttr(key: "epsilon", attrs: opDesc.attrs) epsilon = try ConvAddBatchNormReluParam.getAttr(key: "epsilon", attrs: opDesc.attrs)
groups = try ConvAddBatchNormReluParam.getAttr(key: "groups", attrs: opDesc.attrs) groups = try ConvAddBatchNormReluParam.getAttr(key: "groups", attrs: opDesc.attrs)
variance = try ConvAddBatchNormReluParam.inputVariance(inputs: opDesc.paraInputs, from: inScope) variance = try ConvAddBatchNormReluParam.inputVariance(inputs: opDesc.paraInputs, from: inScope)
bias = try ConvAddBatchNormReluParam.inputBiase(inputs: opDesc.paraInputs, from: inScope) bias = try ConvAddBatchNormReluParam.inputBiase(inputs: opDesc.paraInputs, from: inScope)
scale = try ConvAddBatchNormReluParam.inputScale(inputs: opDesc.paraInputs, from: inScope) scale = try ConvAddBatchNormReluParam.inputScale(inputs: opDesc.paraInputs, from: inScope)
mean = try ConvAddBatchNormReluParam.inputMean(inputs: opDesc.paraInputs, from: inScope) mean = try ConvAddBatchNormReluParam.inputMean(inputs: opDesc.paraInputs, from: inScope)
y = try ConvAddBatchNormReluParam.inputY(inputs: opDesc.paraInputs, from: inScope) y = try ConvAddBatchNormReluParam.inputY(inputs: opDesc.paraInputs, from: inScope)
} catch let error { } catch let error {
throw error throw error
}
} }
}
let input: Texture<P>
let input: Texture<P>
let variance: Tensor<ParamPrecisionType>
let bias: Tensor<ParamPrecisionType> let variance: Tensor<ParamPrecisionType>
let mean: Tensor<ParamPrecisionType> let bias: Tensor<ParamPrecisionType>
let scale: Tensor<ParamPrecisionType> let mean: Tensor<ParamPrecisionType>
let y: Tensor<ParamPrecisionType> let scale: Tensor<ParamPrecisionType>
let filter: Tensor<ParamPrecisionType> let y: Tensor<ParamPrecisionType>
let epsilon: Float32 let filter: Tensor<ParamPrecisionType>
var newScale: MTLBuffer? let epsilon: Float32
var newBiase: MTLBuffer? var newScale: MTLBuffer?
var newBiase: MTLBuffer?
var output: Texture<P>
let stride: [Int32] var output: Texture<P>
let paddings: [Int32] let stride: [Int32]
let dilations: [Int32] let paddings: [Int32]
let groups: Int let dilations: [Int32]
let groups: Int
} }
class ConvAddBatchNormReluOp<P: PrecisionType>: Operator<ConvAddBatchNormReluKernel<P>, ConvAddBatchNormReluParam<P>>, Runable, Creator, InferShaperable, Fusion{ class ConvAddBatchNormReluOp<P: PrecisionType>: Operator<ConvAddBatchNormReluKernel<P>, ConvAddBatchNormReluParam<P>>, Runable, Creator, InferShaperable, Fusion{
typealias OpType = ConvAddBatchNormReluOp<P>
func inputs() -> [Variant] {
return [para.variance, para.bias, para.mean, para.scale, para.y, para.filter, para.input]
}
typealias OpType = ConvAddBatchNormReluOp<P>
func inferShape() {
let inDims = para.input.dim
let filterDim = para.filter.dim
let strides = para.stride
let paddings = para.paddings
let dilations = para.dilations
func inferShape() { var outDim = [inDims[0]]
let inDims = para.input.dim for i in 0..<strides.count {
let filterDim = para.filter.dim let dilation: Int = Int(dilations[i])
let strides = para.stride let filterSize: Int = filterDim[i + 1]
let paddings = para.paddings let inputSize: Int = inDims[i + 1]
let dilations = para.dilations let padding: Int = Int(paddings[i])
let stride: Int = Int(strides[i])
var outDim = [inDims[0]] let dKernel = dilation * (filterSize - 1) + 1
for i in 0..<strides.count { let outputSize = (inputSize + 2 * padding - dKernel) / stride + 1
let dilation: Int = Int(dilations[i]) outDim.append(outputSize)
let filterSize: Int = filterDim[i + 1]
let inputSize: Int = inDims[i + 1]
let padding: Int = Int(paddings[i])
let stride: Int = Int(strides[i])
let dKernel = dilation * (filterSize - 1) + 1
let outputSize = (inputSize + 2 * padding - dKernel) / stride + 1
outDim.append(outputSize)
}
outDim.append(filterDim[0])
para.output.dim = Dim.init(inDim: outDim)
} }
outDim.append(filterDim[0])
func runImpl(device: MTLDevice, buffer: MTLCommandBuffer) throws { para.output.dim = Dim.init(inDim: outDim)
do { }
try kernel.compute(commandBuffer: buffer, param: para)
} catch let error { func runImpl(device: MTLDevice, buffer: MTLCommandBuffer) throws {
throw error do {
} try kernel.compute(commandBuffer: buffer, param: para)
} catch let error {
throw error
} }
}
static func fusionNode() -> Node {
let beginNode = Node.init(inType: gConvType)
_ = beginNode
--> Node.init(inType: gElementwiseAddType)
--> Node.init(inType: gBatchNormType)
--> Node.init(inType: gReluType)
return beginNode
}
static func change() -> [String : [(from: String, to: String)]] {
return [:]
}
static func fusionType() -> String {
return gConvAddBatchNormReluType
}
func delogOutput() {
static func fusionNode() -> Node { // let _: P? = para.input.metalTexture.logDesc(header: "conv add batchnorm relu input: ", stridable: false)
let beginNode = Node.init(inType: gConvType) // para.filter.logDataPointer(header: "filter data pointer: ")
_ = beginNode // print("filter: \(para.filter)")
--> Node.init(inType: gElementwiseAddType)
--> Node.init(inType: gBatchNormType)
--> Node.init(inType: gReluType)
return beginNode
}
static func change() -> [String : [(from: String, to: String)]] { // print("biase: \(para.y)")
return [:] // print("padding: \(para.paddings)")
} // print("stride: \(para.stride)")
static func fusionType() -> String { // let _: P? = para.y.buffer?.logDesc(header: " biase: ", stridable: false)
return gConvAddBatchNormReluType // let _: P? = para.newBiase?.logDesc(header: "new biase: ", stridable: false)
} // let _: P? = para.newScale?.logDesc(header: "new scale: ", stridable: false)
func delogOutput() { let output = para.output.metalTexture.floatArray { (p: P) -> P in
return p
// let _: P? = para.input.metalTexture.logDesc(header: "conv add batchnorm relu input: ", stridable: false)
// para.filter.logDataPointer(header: "filter data pointer: ")
// print("filter: \(para.filter)")
// print("biase: \(para.y)")
// print("padding: \(para.paddings)")
// print("stride: \(para.stride)")
// let _: P? = para.y.buffer?.logDesc(header: " biase: ", stridable: false)
// let _: P? = para.newBiase?.logDesc(header: "new biase: ", stridable: false)
// let _: P? = para.newScale?.logDesc(header: "new scale: ", stridable: false)
let output = para.output.metalTexture.floatArray { (p: P) -> P in
return p
}
//
writeToLibrary(fileName: "output_112x112x32_2", array: output)
print(" write done")
// let _: P? = para.output.metalTexture.logDesc(header: "conv add batchnorm relu output: ", stridable: false)
} }
//
writeToLibrary(fileName: "output_112x112x32_2", array: output)
print(" write done")
// let _: P? = para.output.metalTexture.logDesc(header: "conv add batchnorm relu output: ", stridable: false)
}
} }
metal/paddle-mobile/paddle-mobile/Operators/ConvAddOp.swift
浏览文件 @ b602b048
...@@ -15,80 +15,108 @@ ...@@ -15,80 +15,108 @@
import Foundation import Foundation
class ConvAddParam<P: PrecisionType>: OpParam { class ConvAddParam<P: PrecisionType>: OpParam {
typealias ParamPrecisionType = P typealias ParamPrecisionType = P
required init(opDesc: OpDesc, inScope: Scope) throws { required init(opDesc: OpDesc, inScope: Scope) throws {
do { do {
filter = try ConvAddParam.inputFilter(paraInputs: opDesc.paraInputs, from: inScope) filter = try ConvAddParam.inputFilter(paraInputs: opDesc.paraInputs, from: inScope)
input = try ConvAddParam.input(inputs: opDesc.inputs, from: inScope) input = try ConvAddParam.input(inputs: opDesc.inputs, from: inScope)
output = try ConvAddParam.outputOut(outputs: opDesc.outputs, from: inScope) output = try ConvAddParam.outputOut(outputs: opDesc.outputs, from: inScope)
stride = try ConvAddParam.getAttr(key: "strides", attrs: opDesc.attrs) stride = try ConvAddParam.getAttr(key: "strides", attrs: opDesc.attrs)
paddings = try ConvAddParam.getAttr(key: "paddings", attrs: opDesc.attrs) paddings = try ConvAddParam.getAttr(key: "paddings", attrs: opDesc.attrs)
dilations = try ConvAddParam.getAttr(key: "dilations", attrs: opDesc.attrs) dilations = try ConvAddParam.getAttr(key: "dilations", attrs: opDesc.attrs)
groups = try ConvAddParam.getAttr(key: "groups", attrs: opDesc.attrs) groups = try ConvAddParam.getAttr(key: "groups", attrs: opDesc.attrs)
y = try ConvAddParam.inputY(inputs: opDesc.paraInputs, from: inScope) y = try ConvAddParam.inputY(inputs: opDesc.paraInputs, from: inScope)
} catch let error { } catch let error {
throw error throw error
}
} }
}
let input: Texture<P>
let y: Tensor<ParamPrecisionType> let input: Texture<P>
let filter: Tensor<ParamPrecisionType> let y: Tensor<ParamPrecisionType>
let filter: Tensor<ParamPrecisionType>
var output: Texture<P>
let stride: [Int32] var output: Texture<P>
let paddings: [Int32] let stride: [Int32]
let dilations: [Int32] let paddings: [Int32]
let groups: Int let dilations: [Int32]
let groups: Int
} }
class ConvAddOp<P: PrecisionType>: Operator<ConvAddKernel<P>, ConvAddParam<P>>, Runable, Creator, InferShaperable, Fusion{ class ConvAddOp<P: PrecisionType>: Operator<ConvAddKernel<P>, ConvAddParam<P>>, Runable, Creator, InferShaperable, Fusion{
static func fusionNode() -> Node {
let beginNode = Node.init(inType: gConvType) func delogOutput() {
_ = beginNode print(" conv add: ")
--> Node.init(inType: gElementwiseAddType)
return beginNode // print(para.input.metalTexture)
}
static func change() -> [String : [(from: String, to: String)]] { // print(" filter array: ")
return [:] // let filterArray: [P] = para.filter.buffer.array()
// print(filterArray)
let input = para.input.metalTexture.floatArray { (p: P) -> P in
return p
} }
// print(input)
static func fusionType() -> String { let output = para.output.metalTexture.floatArray { (p: P) -> P in
return gConvAddType return p
} }
// print(para.output.metalTexture)
print(output)
}
static func fusionNode() -> Node {
let beginNode = Node.init(inType: gConvType)
_ = beginNode
--> Node.init(inType: gElementwiseAddType)
return beginNode
}
static func change() -> [String : [(from: String, to: String)]] {
return [:]
}
func inputs() -> [Variant] {
return [para.input, para.y, para.filter]
}
static func fusionType() -> String {
return gConvAddType
}
typealias OpType = ConvAddOp<P>
func inferShape() {
typealias OpType = ConvAddOp<P> let inDims = para.input.dim
let filterDim = para.filter.dim
let strides = para.stride
let paddings = para.paddings
let dilations = para.dilations
func inferShape() { var outDim = [inDims[0]]
for i in 0..<strides.count {
let inDims = para.input.dim let dilation: Int = Int(dilations[i])
let filterDim = para.filter.dim let filterSize: Int = filterDim[i + 1]
let strides = para.stride let inputSize: Int = inDims[i + 1]
let paddings = para.paddings let padding: Int = Int(paddings[i])
let dilations = para.dilations let stride: Int = Int(strides[i])
let dKernel = dilation * (filterSize - 1) + 1
var outDim = [inDims[0]] let outputSize = (inputSize + 2 * padding - dKernel) / stride + 1
for i in 0..<strides.count { outDim.append(outputSize)
let dilation: Int = Int(dilations[i])
let filterSize: Int = filterDim[i + 1]
let inputSize: Int = inDims[i + 1]
let padding: Int = Int(paddings[i])
let stride: Int = Int(strides[i])
let dKernel = dilation * (filterSize - 1) + 1
let outputSize = (inputSize + 2 * padding - dKernel) / stride + 1
outDim.append(outputSize)
}
outDim.append(filterDim[0])
para.output.dim = Dim.init(inDim: outDim)
} }
outDim.append(filterDim[0])
func runImpl(device: MTLDevice, buffer: MTLCommandBuffer) throws { para.output.dim = Dim.init(inDim: outDim)
do { }
try kernel.compute(commandBuffer: buffer, param: para)
} catch let error { func runImpl(device: MTLDevice, buffer: MTLCommandBuffer) throws {
throw error do {
} try kernel.compute(commandBuffer: buffer, param: para)
} catch let error {
throw error
} }
}
} }
metal/paddle-mobile/paddle-mobile/Operators/ConvBNReluOp.swift
浏览文件 @ b602b048
...@@ -15,115 +15,164 @@ ...@@ -15,115 +15,164 @@
import Foundation import Foundation
class ConvBNReluParam<P: PrecisionType>: OpParam { class ConvBNReluParam<P: PrecisionType>: OpParam {
typealias ParamPrecisionType = P typealias ParamPrecisionType = P
required init(opDesc: OpDesc, inScope: Scope) throws { required init(opDesc: OpDesc, inScope: Scope) throws {
do { do {
filter = try ConvBNReluParam.inputFilter(paraInputs: opDesc.paraInputs, from: inScope) filter = try ConvBNReluParam.inputFilter(paraInputs: opDesc.paraInputs, from: inScope)
input = try ConvBNReluParam.input(inputs: opDesc.inputs, from: inScope) input = try ConvBNReluParam.input(inputs: opDesc.inputs, from: inScope)
output = try ConvBNReluParam.outputOut(outputs: opDesc.outputs, from: inScope) output = try ConvBNReluParam.outputOut(outputs: opDesc.outputs, from: inScope)
stride = try ConvBNReluParam.getAttr(key: "strides", attrs: opDesc.attrs) stride = try ConvBNReluParam.getAttr(key: "strides", attrs: opDesc.attrs)
paddings = try ConvBNReluParam.getAttr(key: "paddings", attrs: opDesc.attrs) paddings = try ConvBNReluParam.getAttr(key: "paddings", attrs: opDesc.attrs)
dilations = try ConvBNReluParam.getAttr(key: "dilations", attrs: opDesc.attrs) dilations = try ConvBNReluParam.getAttr(key: "dilations", attrs: opDesc.attrs)
epsilon = try ConvBNReluParam.getAttr(key: "epsilon", attrs: opDesc.attrs) epsilon = try ConvBNReluParam.getAttr(key: "epsilon", attrs: opDesc.attrs)
groups = try ConvBNReluParam.getAttr(key: "groups", attrs: opDesc.attrs) groups = try ConvBNReluParam.getAttr(key: "groups", attrs: opDesc.attrs)
variance = try ConvBNReluParam.inputVariance(inputs: opDesc.paraInputs, from: inScope) variance = try ConvBNReluParam.inputVariance(inputs: opDesc.paraInputs, from: inScope)
bias = try ConvBNReluParam.inputBiase(inputs: opDesc.paraInputs, from: inScope) bias = try ConvBNReluParam.inputBiase(inputs: opDesc.paraInputs, from: inScope)
scale = try ConvBNReluParam.inputScale(inputs: opDesc.paraInputs, from: inScope) scale = try ConvBNReluParam.inputScale(inputs: opDesc.paraInputs, from: inScope)
mean = try ConvBNReluParam.inputMean(inputs: opDesc.paraInputs, from: inScope) mean = try ConvBNReluParam.inputMean(inputs: opDesc.paraInputs, from: inScope)
} catch let error { } catch let error {
throw error throw error
}
} }
}
let input: Texture<P>
let input: Texture<P>
let variance: Tensor<ParamPrecisionType>
let bias: Tensor<ParamPrecisionType> let variance: Tensor<ParamPrecisionType>
let mean: Tensor<ParamPrecisionType> let bias: Tensor<ParamPrecisionType>
let scale: Tensor<ParamPrecisionType> let mean: Tensor<ParamPrecisionType>
let filter: Tensor<ParamPrecisionType> let scale: Tensor<ParamPrecisionType>
let epsilon: Float32 let filter: Tensor<ParamPrecisionType>
var newScale: MTLBuffer? let epsilon: Float32
var newBiase: MTLBuffer? var newScale: MTLBuffer?
var newBiase: MTLBuffer?
var output: Texture<P>
let stride: [Int32] var output: Texture<P>
let paddings: [Int32] let stride: [Int32]
let dilations: [Int32] let paddings: [Int32]
let groups: Int let dilations: [Int32]
let groups: Int
} }
class ConvBNReluOp<P: PrecisionType>: Operator<ConvBNReluKernel<P>, ConvBNReluParam<P>>, Runable, Creator, InferShaperable, Fusion{ class ConvBNReluOp<P: PrecisionType>: Operator<ConvBNReluKernel<P>, ConvBNReluParam<P>>, Runable, Creator, InferShaperable, Fusion{
typealias OpType = ConvBNReluOp<P> typealias OpType = ConvBNReluOp<P>
func inputs() -> [Variant] {
return [para.input, para.variance, para.bias, para.mean, para.scale, para.filter]
}
func inferShape() {
let inDims = para.input.dim
let filterDim = para.filter.dim
let strides = para.stride
let paddings = para.paddings
let dilations = para.dilations
func inferShape() { var outDim = [inDims[0]]
let inDims = para.input.dim for i in 0..<strides.count {
let filterDim = para.filter.dim let dilation: Int = Int(dilations[i])
let strides = para.stride let filterSize: Int = filterDim[i + 1]
let paddings = para.paddings let inputSize: Int = inDims[i + 1]
let dilations = para.dilations let padding: Int = Int(paddings[i])
let stride: Int = Int(strides[i])
var outDim = [inDims[0]] let dKernel = dilation * (filterSize - 1) + 1
for i in 0..<strides.count { let outputSize = (inputSize + 2 * padding - dKernel) / stride + 1
let dilation: Int = Int(dilations[i]) outDim.append(outputSize)
let filterSize: Int = filterDim[i + 1]
let inputSize: Int = inDims[i + 1]
let padding: Int = Int(paddings[i])
let stride: Int = Int(strides[i])
let dKernel = dilation * (filterSize - 1) + 1
let outputSize = (inputSize + 2 * padding - dKernel) / stride + 1
outDim.append(outputSize)
}
outDim.append(filterDim[0])
para.output.dim = Dim.init(inDim: outDim)
} }
outDim.append(filterDim[0])
func runImpl(device: MTLDevice, buffer: MTLCommandBuffer) throws { para.output.dim = Dim.init(inDim: outDim)
do { }
try kernel.compute(commandBuffer: buffer, param: para)
} catch let error { func runImpl(device: MTLDevice, buffer: MTLCommandBuffer) throws {
throw error do {
} try kernel.compute(commandBuffer: buffer, param: para)
} catch let error {
throw error
} }
}
static func fusionNode() -> Node {
let beginNode = Node.init(inType: gConvType)
_ = beginNode
--> Node.init(inType: gBatchNormType)
--> Node.init(inType: gReluType)
return beginNode
}
static func change() -> [String : [(from: String, to: String)]] {
return [:]
}
static func fusionType() -> String {
return gConvBnReluType
}
func delogOutput() {
static func fusionNode() -> Node { // let _: P? = para.input.metalTexture.logDesc(header: "conv add batchnorm relu input: ", stridable: false)
let beginNode = Node.init(inType: gConvType) // para.filter.logDataPointer(header: "filter data pointer: ")
_ = beginNode // print("filter: \(para.filter)")
--> Node.init(inType: gBatchNormType)
--> Node.init(inType: gReluType)
return beginNode
}
static func change() -> [String : [(from: String, to: String)]] { // print("biase: \(para.y)")
return [:] // print("padding: \(para.paddings)")
} // print("stride: \(para.stride)")
// let _: P? = para.y.buffer?.logDesc(header: " biase: ", stridable: false)
// let _: P? = para.newBiase?.logDesc(header: "new biase: ", stridable: false)
// let _: P? = para.newScale?.logDesc(header: "new scale: ", stridable: false)
static func fusionType() -> String {
return gConvBnReluType
}
func delogOutput() { // print("input: ")
// print(para.input.metalTexture)
// let _: P? = para.input.metalTexture.logDesc(header: "conv add batchnorm relu input: ", stridable: false) //
// para.filter.logDataPointer(header: "filter data pointer: ") // let input = para.input.metalTexture.floatArray { (p: P) -> P in
// print("filter: \(para.filter)") // return p
// }
// print("biase: \(para.y)") // for i in 0..<input.count {
// print("padding: \(para.paddings)") // print(" index \(i) : \(input[i])")
// print("stride: \(para.stride)") // }
// print(input)
// let _: P? = para.y.buffer?.logDesc(header: " biase: ", stridable: false)
// let _: P? = para.newBiase?.logDesc(header: "new biase: ", stridable: false) // writeToLibrary(fileName: "input35", array: input)
// let _: P? = para.newScale?.logDesc(header: "new scale: ", stridable: false)
// print(input)
let output = para.output.metalTexture.floatArray { (p: P) -> P in
return p print(para.newBiase?.length)
} print(para.newScale?.length)
// // let newScale = para.newScale?.contents().bindMemory(to: P.self, capacity: para.newScale!.length)
writeToLibrary(fileName: "output_112x112x32_2", array: output) // let newBiase = para.newBiase?.contents().bindMemory(to: P.self, capacity: para.newBiase!.length)
print(" write done") //
// let filterArray: [Float32] = para.filter.buffer.array();
// let _: P? = para.output.metalTexture.logDesc(header: "conv add batchnorm relu output: ", stridable: false) //// writeToLibrary(fileName: "filter35", array: filterArray)
//
// print(filterArray)
//
// print("new scale: ")
// for i in 0..<(para.newScale!.length / MemoryLayout<P>.size) {
// print("index: \(i) \(newScale![i]) ")
// }
//
// print("new biase: ")
// for i in 0..<(para.newBiase!.length / MemoryLayout<P>.size) {
// print("index: \(i) \(newBiase![i]) ")
// }
print(para.output.metalTexture)
let output = para.output.metalTexture.floatArray { (p: P) -> P in
return p
} }
print(output)
//
writeToLibrary(fileName: "batch_norm_34.tmp_2", array: output)
print(" write done")
//
// let _: P? = para.output.metalTexture.logDesc(header: "conv add batchnorm relu output: ", stridable: true)
}
} }
metal/paddle-mobile/paddle-mobile/Operators/ConvOp.swift
浏览文件 @ b602b048
...@@ -15,74 +15,79 @@ ...@@ -15,74 +15,79 @@
import Foundation import Foundation
class ConvParam<P: PrecisionType>: OpParam { class ConvParam<P: PrecisionType>: OpParam {
typealias ParamPrecisionType = P typealias ParamPrecisionType = P
required init(opDesc: OpDesc, inScope: Scope) throws { required init(opDesc: OpDesc, inScope: Scope) throws {
do { do {
filter = try ConvParam.inputFilter(paraInputs: opDesc.paraInputs, from: inScope) filter = try ConvParam.inputFilter(paraInputs: opDesc.paraInputs, from: inScope)
input = try ConvParam.input(inputs: opDesc.inputs, from: inScope) input = try ConvParam.input(inputs: opDesc.inputs, from: inScope)
output = try ConvParam.output(outputs: opDesc.outputs, from: inScope) output = try ConvParam.output(outputs: opDesc.outputs, from: inScope)
stride = try ConvParam.getAttr(key: "strides", attrs: opDesc.attrs) stride = try ConvParam.getAttr(key: "strides", attrs: opDesc.attrs)
paddings = try ConvParam.getAttr(key: "paddings", attrs: opDesc.attrs) paddings = try ConvParam.getAttr(key: "paddings", attrs: opDesc.attrs)
dilations = try ConvParam.getAttr(key: "dilations", attrs: opDesc.attrs) dilations = try ConvParam.getAttr(key: "dilations", attrs: opDesc.attrs)
groups = try ConvParam.getAttr(key: "groups", attrs: opDesc.attrs) groups = try ConvParam.getAttr(key: "groups", attrs: opDesc.attrs)
} catch let error { } catch let error {
throw error throw error
}
} }
}
let input: Texture<P>
let filter: Tensor<ParamPrecisionType> let input: Texture<P>
var output: Texture<P> let filter: Tensor<ParamPrecisionType>
let stride: [Int32] var output: Texture<P>
let paddings: [Int32] let stride: [Int32]
let dilations: [Int32] let paddings: [Int32]
let groups: Int let dilations: [Int32]
let groups: Int
} }
class ConvOp<P: PrecisionType>: Operator<ConvKernel<P>, ConvParam<P>>, Runable, Creator, InferShaperable { class ConvOp<P: PrecisionType>: Operator<ConvKernel<P>, ConvParam<P>>, Runable, Creator, InferShaperable {
required init(device: MTLDevice, opDesc: OpDesc, inScope: Scope) throws {
do { func inputs() -> [Variant] {
try super.init(device: device, opDesc: opDesc, inScope: inScope) return [para.input, para.filter]
} catch let error { }
throw error
} required init(device: MTLDevice, opDesc: OpDesc, inScope: Scope) throws {
do {
} try super.init(device: device, opDesc: opDesc, inScope: inScope)
func inferShape() { } catch let error {
let inDims = para.input.dim throw error
let filterDim = para.filter.dim
let strides = para.stride
let paddings = para.paddings
let dilations = para.dilations
var outDim = [inDims[0]]
for i in 0..<strides.count {
let dilation: Int = Int(dilations[i])
let filterSize: Int = filterDim[i + 1]
let inputSize: Int = inDims[i + 1]
let padding: Int = Int(paddings[i])
let stride: Int = Int(strides[i])
let dKernel = dilation * (filterSize - 1) + 1
let outputSize = (inputSize + 2 * padding - dKernel) / stride + 1
outDim.append(outputSize)
}
outDim.append(filterDim[0])
para.output.dim = Dim.init(inDim: outDim)
} }
typealias OpType = ConvOp<P> }
func runImpl(device: MTLDevice, buffer: MTLCommandBuffer) throws { func inferShape() {
do { let inDims = para.input.dim
try kernel.compute(commandBuffer: buffer, param: para) let filterDim = para.filter.dim
} catch let error { let strides = para.stride
throw error let paddings = para.paddings
} let dilations = para.dilations
}
func delogOutput() { var outDim = [inDims[0]]
print("conv output : ") for i in 0..<strides.count {
print(para.output.metalTexture) let dilation: Int = Int(dilations[i])
// let _: Float16? = para.output.metalTexture.logDesc() let filterSize: Int = filterDim[i + 1]
let inputSize: Int = inDims[i + 1]
let padding: Int = Int(paddings[i])
let stride: Int = Int(strides[i])
let dKernel = dilation * (filterSize - 1) + 1
let outputSize = (inputSize + 2 * padding - dKernel) / stride + 1
outDim.append(outputSize)
}
outDim.append(filterDim[0])
para.output.dim = Dim.init(inDim: outDim)
}
typealias OpType = ConvOp<P>
func runImpl(device: MTLDevice, buffer: MTLCommandBuffer) throws {
do {
try kernel.compute(commandBuffer: buffer, param: para)
} catch let error {
throw error
} }
}
func delogOutput() {
print("conv output : ")
print(para.output.metalTexture)
// let _: Float16? = para.output.metalTexture.logDesc()
}
} }
metal/paddle-mobile/paddle-mobile/Operators/ConvTransposeOp.swift
浏览文件 @ b602b048
...@@ -28,6 +28,10 @@ class ConvTransposeParam<P: PrecisionType>: ConvParam<P> { ...@@ -28,6 +28,10 @@ class ConvTransposeParam<P: PrecisionType>: ConvParam<P> {
class ConvTransposeOp<P: PrecisionType>: Operator<ConvTransposeKernel<P>, ConvTransposeParam<P>>, Runable, Creator, InferShaperable{ class ConvTransposeOp<P: PrecisionType>: Operator<ConvTransposeKernel<P>, ConvTransposeParam<P>>, Runable, Creator, InferShaperable{
func inputs() -> [Variant] {
return [para.input, para.filter]
}
func inferShape() { func inferShape() {
// para.output.dim = para.input.dim // para.output.dim = para.input.dim
} }
......
metal/paddle-mobile/paddle-mobile/Operators/DepthwiseConvOp.swift
浏览文件 @ b602b048
...@@ -15,49 +15,54 @@ ...@@ -15,49 +15,54 @@
import Foundation import Foundation
class DepthConvOp<P: PrecisionType>: Operator<ConvKernel<P>, ConvParam<P>>, Runable, Creator, InferShaperable { class DepthConvOp<P: PrecisionType>: Operator<ConvKernel<P>, ConvParam<P>>, Runable, Creator, InferShaperable {
required init(device: MTLDevice, opDesc: OpDesc, inScope: Scope) throws {
do { func inputs() -> [Variant] {
try super.init(device: device, opDesc: opDesc, inScope: inScope) return [para.input, para.filter]
} catch let error { }
throw error
} 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
let filterDim = para.filter.dim
let strides = para.stride
let paddings = para.paddings
let dilations = para.dilations
func inferShape() { var outDim = [inDims[0]]
let inDims = para.input.dim for i in 0..<strides.count {
let filterDim = para.filter.dim let dilation: Int = Int(dilations[i])
let strides = para.stride let filterSize: Int = filterDim[i + 1]
let paddings = para.paddings let inputSize: Int = inDims[i + 1]
let dilations = para.dilations let padding: Int = Int(paddings[i])
let stride: Int = Int(strides[i])
var outDim = [inDims[0]] let dKernel = dilation * (filterSize - 1) + 1
for i in 0..<strides.count { let outputSize = (inputSize + 2 * padding - dKernel) / stride + 1
let dilation: Int = Int(dilations[i]) outDim.append(outputSize)
let filterSize: Int = filterDim[i + 1]
let inputSize: Int = inDims[i + 1]
let padding: Int = Int(paddings[i])
let stride: Int = Int(strides[i])
let dKernel = dilation * (filterSize - 1) + 1
let outputSize = (inputSize + 2 * padding - dKernel) / stride + 1
outDim.append(outputSize)
}
outDim.append(filterDim[0])
para.output.dim = Dim.init(inDim: outDim)
} }
outDim.append(filterDim[0])
typealias OpType = DepthConvOp<P> para.output.dim = Dim.init(inDim: outDim)
}
func runImpl(device: MTLDevice, buffer: MTLCommandBuffer) throws {
do { typealias OpType = DepthConvOp<P>
try kernel.compute(commandBuffer: buffer, param: para)
} catch let error { func runImpl(device: MTLDevice, buffer: MTLCommandBuffer) throws {
throw error do {
} try kernel.compute(commandBuffer: buffer, param: para)
} } catch let error {
throw error
func delogOutput() {
print("conv output : ")
print(para.output.metalTexture)
// let _: Float16? = para.output.metalTexture.logDesc()
} }
}
func delogOutput() {
print("conv output : ")
print(para.output.metalTexture)
// let _: Float16? = para.output.metalTexture.logDesc()
}
} }
metal/paddle-mobile/paddle-mobile/Operators/DwConvBNReluOp.swift
浏览文件 @ b602b048
...@@ -15,75 +15,79 @@ ...@@ -15,75 +15,79 @@
import Foundation import Foundation
class DwConvBNReluOp<P: PrecisionType>: Operator<ConvBNReluKernel<P>, ConvBNReluParam<P>>, Runable, Creator, InferShaperable, Fusion{ class DwConvBNReluOp<P: PrecisionType>: Operator<ConvBNReluKernel<P>, ConvBNReluParam<P>>, Runable, Creator, InferShaperable, Fusion{
typealias OpType = ConvBNReluOp<P> typealias OpType = ConvBNReluOp<P>
func inputs() -> [Variant] {
return [para.input, para.bias, para.mean, para.filter, para.variance, para.scale]
}
func inferShape() {
let inDims = para.input.dim
let filterDim = para.filter.dim
let strides = para.stride
let paddings = para.paddings
let dilations = para.dilations
func inferShape() { var outDim = [inDims[0]]
let inDims = para.input.dim for i in 0..<strides.count {
let filterDim = para.filter.dim let dilation: Int = Int(dilations[i])
let strides = para.stride let filterSize: Int = filterDim[i + 1]
let paddings = para.paddings let inputSize: Int = inDims[i + 1]
let dilations = para.dilations let padding: Int = Int(paddings[i])
let stride: Int = Int(strides[i])
var outDim = [inDims[0]] let dKernel = dilation * (filterSize - 1) + 1
for i in 0..<strides.count { let outputSize = (inputSize + 2 * padding - dKernel) / stride + 1
let dilation: Int = Int(dilations[i]) outDim.append(outputSize)
let filterSize: Int = filterDim[i + 1]
let inputSize: Int = inDims[i + 1]
let padding: Int = Int(paddings[i])
let stride: Int = Int(strides[i])
let dKernel = dilation * (filterSize - 1) + 1
let outputSize = (inputSize + 2 * padding - dKernel) / stride + 1
outDim.append(outputSize)
}
outDim.append(filterDim[0])
para.output.dim = Dim.init(inDim: outDim)
} }
outDim.append(filterDim[0])
func runImpl(device: MTLDevice, buffer: MTLCommandBuffer) throws { para.output.dim = Dim.init(inDim: outDim)
do { }
try kernel.compute(commandBuffer: buffer, param: para)
} catch let error { func runImpl(device: MTLDevice, buffer: MTLCommandBuffer) throws {
throw error do {
} try kernel.compute(commandBuffer: buffer, param: para)
} catch let error {
throw error
} }
}
static func fusionNode() -> Node {
let beginNode = Node.init(inType: gDepthConvType)
_ = beginNode
--> Node.init(inType: gBatchNormType)
--> Node.init(inType: gReluType)
return beginNode
}
static func change() -> [String : [(from: String, to: String)]] {
return [:]
}
static func fusionType() -> String {
return gDwConvBnReluType
}
func delogOutput() {
static func fusionNode() -> Node { // let _: P? = para.input.metalTexture.logDesc(header: "conv add batchnorm relu input: ", stridable: false)
let beginNode = Node.init(inType: gDepthConvType) // para.filter.logDataPointer(header: "filter data pointer: ")
_ = beginNode // print("filter: \(para.filter)")
--> Node.init(inType: gBatchNormType)
--> Node.init(inType: gReluType)
return beginNode
}
static func change() -> [String : [(from: String, to: String)]] { // print("biase: \(para.y)")
return [:] // print("padding: \(para.paddings)")
} // print("stride: \(para.stride)")
static func fusionType() -> String { // let _: P? = para.y.buffer?.logDesc(header: " biase: ", stridable: false)
return gDwConvBnReluType // let _: P? = para.newBiase?.logDesc(header: "new biase: ", stridable: false)
} // let _: P? = para.newScale?.logDesc(header: "new scale: ", stridable: false)
func delogOutput() { // let output = para.output.metalTexture.floatArray { (p: P) -> P in
// return p
// let _: P? = para.input.metalTexture.logDesc(header: "conv add batchnorm relu input: ", stridable: false) // }
// para.filter.logDataPointer(header: "filter data pointer: ") //
// print("filter: \(para.filter)") // writeToLibrary(fileName: "batch_norm_19.tmp_2", array: output)
// print(" write done")
// print("biase: \(para.y)")
// print("padding: \(para.paddings)") // let _: P? = para.output.metalTexture.logDesc(header: "conv add batchnorm relu output: ", stridable: false)
// print("stride: \(para.stride)") }
// let _: P? = para.y.buffer?.logDesc(header: " biase: ", stridable: false)
// let _: P? = para.newBiase?.logDesc(header: "new biase: ", stridable: false)
// let _: P? = para.newScale?.logDesc(header: "new scale: ", stridable: false)
let output = para.output.metalTexture.floatArray { (p: P) -> P in
return p
}
//
writeToLibrary(fileName: "output_112x112x32_2", array: output)
print(" write done")
// let _: P? = para.output.metalTexture.logDesc(header: "conv add batchnorm relu output: ", stridable: false)
}
} }
metal/paddle-mobile/paddle-mobile/Operators/ElementwiseAddOp.swift
浏览文件 @ b602b048
...@@ -15,33 +15,37 @@ ...@@ -15,33 +15,37 @@
import Foundation import Foundation
class ElementwiseAddParam<P: PrecisionType>: OpParam { class ElementwiseAddParam<P: PrecisionType>: OpParam {
typealias ParamPrecisionType = P typealias ParamPrecisionType = P
required init(opDesc: OpDesc, inScope: Scope) throws { required init(opDesc: OpDesc, inScope: Scope) throws {
do { do {
input = try ElementwiseAddParam.inputX(inputs: opDesc.inputs, from: inScope) input = try ElementwiseAddParam.inputX(inputs: opDesc.inputs, from: inScope)
inputY = try ElementwiseAddParam.inputY(inputs: opDesc.paraInputs, from: inScope) inputY = try ElementwiseAddParam.inputY(inputs: opDesc.paraInputs, from: inScope)
output = try ElementwiseAddParam.outputOut(outputs: opDesc.outputs, from: inScope) output = try ElementwiseAddParam.outputOut(outputs: opDesc.outputs, from: inScope)
axis = try ElementwiseAddParam.getAttr(key: "axis", attrs: opDesc.attrs) axis = try ElementwiseAddParam.getAttr(key: "axis", attrs: opDesc.attrs)
} catch let error { } catch let error {
throw error throw error
}
} }
let input: Texture<P> }
let inputY: Tensor<P> let input: Texture<P>
var output: Texture<P> let inputY: Tensor<P>
let axis: Int var output: Texture<P>
let axis: Int
} }
class ElementwiseAddOp<P: PrecisionType>: Operator<ElementwiseAddKernel<P>, ElementwiseAddParam<P>>, Runable, Creator, InferShaperable{ class ElementwiseAddOp<P: PrecisionType>: Operator<ElementwiseAddKernel<P>, ElementwiseAddParam<P>>, Runable, Creator, InferShaperable{
func inferShape() { func inputs() -> [Variant] {
para.output.dim = para.input.dim return [para.input, para.inputY]
} }
typealias OpType = ElementwiseAddOp<P> func inferShape() {
func runImpl(device: MTLDevice, buffer: MTLCommandBuffer) throws { para.output.dim = para.input.dim
} }
typealias OpType = ElementwiseAddOp<P>
func runImpl(device: MTLDevice, buffer: MTLCommandBuffer) throws {
}
} }
......
metal/paddle-mobile/paddle-mobile/Operators/FeedOp.swift
浏览文件 @ b602b048
...@@ -15,54 +15,58 @@ ...@@ -15,54 +15,58 @@
import Foundation import Foundation
class FeedParam<P: PrecisionType>: OpParam{ class FeedParam<P: PrecisionType>: OpParam{
var output: Texture<P> var output: Texture<P>
var input: InputTexture { var input: InputTexture {
return scope.input() as! InputTexture return scope.input() as! InputTexture
}
let scope: Scope
required init(opDesc: OpDesc, inScope: Scope) throws {
scope = inScope
do {
output = try FeedParam.outputOut(outputs: opDesc.outputs, from: inScope)
} catch let error {
throw error
} }
let scope: Scope }
required init(opDesc: OpDesc, inScope: Scope) throws { typealias ParamPrecisionType = P
scope = inScope
do {
output = try FeedParam.outputOut(outputs: opDesc.outputs, from: inScope)
} catch let error {
throw error
}
}
typealias ParamPrecisionType = P
} }
class FeedOp<P: PrecisionType>: Operator<Texture2DTo2DArrayKernel<P>, FeedParam<P>>, Runable, Creator, InferShaperable { class FeedOp<P: PrecisionType>: Operator<Texture2DTo2DArrayKernel<P>, FeedParam<P>>, Runable, Creator, InferShaperable {
typealias OpType = FeedOp<P> typealias OpType = FeedOp<P>
func inferShape() { func inputs() -> [Variant] {
// print("feed input: \(para.input.expectDim)") return [para.input]
print("feed output: \(para.output.dim)") }
// para.output.dim =
// para.output.dim = para.input.expectDim func inferShape() {
// print("feed input: \(para.input.expectDim)")
print("feed output: \(para.output.dim)")
// para.output.dim =
// para.output.dim = para.input.expectDim
}
func runImpl(device: MTLDevice, buffer: MTLCommandBuffer) throws {
do {
try kernel.compute(commandBuffer: buffer, param: para)
} catch let error {
throw error
} }
func runImpl(device: MTLDevice, buffer: MTLCommandBuffer) throws { // let resizeKernel = ResizeKernel<P>.init(device: device)
do { // let resizeParam = ResizeParam.init(input: para.input.mtlTexture, output: para.output.metalTexture, expectDim: para.input.expectDim)
try kernel.compute(commandBuffer: buffer, param: para) // do {
} catch let error { // try resizeKernel.compute(commandBuffer: buffer, param: resizeParam)
throw error // } catch let error {
} // throw error
// }
// let resizeKernel = ResizeKernel<P>.init(device: device) }
// let resizeParam = ResizeParam.init(input: para.input.mtlTexture, output: para.output.metalTexture, expectDim: para.input.expectDim)
// do { func delogOutput() {
// try resizeKernel.compute(commandBuffer: buffer, param: resizeParam) // para.input.mtlTexture.logDesc()
// } catch let error { // let _: P? = para.input.mtlTexture.logDesc(header: "feed input: ", stridable: true)
// throw error // let _: P? = para.output.metalTexture.logDesc(header: "feed output: ", stridable: false)
// } }
}
func delogOutput() {
// para.input.mtlTexture.logDesc()
// let _: P? = para.input.mtlTexture.logDesc(header: "feed input: ", stridable: true)
// let _: P? = para.output.metalTexture.logDesc(header: "feed output: ", stridable: false)
}
} }
metal/paddle-mobile/paddle-mobile/Operators/FetchOp.swift
浏览文件 @ b602b048
...@@ -15,40 +15,44 @@ ...@@ -15,40 +15,44 @@
import Foundation import Foundation
class FetchParam<P: PrecisionType>: OpParam{ class FetchParam<P: PrecisionType>: OpParam{
var output: Texture<P> var output: Texture<P>
let input: Texture<P> let input: Texture<P>
let scope: Scope let scope: Scope
required init(opDesc: OpDesc, inScope: Scope) throws { required init(opDesc: OpDesc, inScope: Scope) throws {
scope = inScope scope = inScope
do { do {
input = try FetchParam.inputX(inputs: opDesc.inputs, from: inScope) input = try FetchParam.inputX(inputs: opDesc.inputs, from: inScope)
output = input output = input
} catch let error { } catch let error {
throw error throw error
}
} }
}
typealias ParamPrecisionType = P
typealias ParamPrecisionType = P
} }
class FetchKernel<P: PrecisionType>: Kernel, Computable { class FetchKernel<P: PrecisionType>: Kernel, Computable {
func compute(commandBuffer: MTLCommandBuffer, param: FetchParam<P>) throws { func compute(commandBuffer: MTLCommandBuffer, param: FetchParam<P>) throws {
} }
required init(device: MTLDevice, param: FetchParam<P>) { required init(device: MTLDevice, param: FetchParam<P>) {
super.init(device: device, inFunctionName: "texture2d_to_2d_array") super.init(device: device, inFunctionName: "texture2d_to_2d_array")
} }
} }
class FetchOp<P: PrecisionType>: Operator< FetchKernel<P>, FetchParam<P>>, Runable, Creator, InferShaperable{ class FetchOp<P: PrecisionType>: Operator< FetchKernel<P>, FetchParam<P>>, Runable, Creator, InferShaperable{
func inferShape() { func inputs() -> [Variant] {
print(para.input.dim) return [para.input]
} }
typealias OpType = FetchOp<P> func inferShape() {
func runImpl(device: MTLDevice, buffer: MTLCommandBuffer) throws { print(para.input.dim)
scope.setOutput(output: para.output) }
}
typealias OpType = FetchOp<P>
func runImpl(device: MTLDevice, buffer: MTLCommandBuffer) throws {
scope.setOutput(output: para.output)
}
} }
metal/paddle-mobile/paddle-mobile/Operators/Kernels/ConvAddBatchNormReluKernel.swift
浏览文件 @ b602b048
...@@ -50,7 +50,7 @@ class ConvAddBatchNormReluKernel<P: PrecisionType>: Kernel, Computable, Testable ...@@ -50,7 +50,7 @@ class ConvAddBatchNormReluKernel<P: PrecisionType>: Kernel, Computable, Testable
required init(device: MTLDevice, param: ConvAddBatchNormReluParam<P>) { required init(device: MTLDevice, param: ConvAddBatchNormReluParam<P>) {
param.output.initTexture(device: device, transpose: [0, 2, 3, 1]) param.output.initTexture(device: device, inTranspose: [0, 2, 3, 1])
if param.filter.width == 1 && param.filter.height == 1 { 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")
......
metal/paddle-mobile/paddle-mobile/Operators/Kernels/ConvAddKernel.swift
浏览文件 @ b602b048
...@@ -25,7 +25,7 @@ class ConvAddKernel<P: PrecisionType>: Kernel, Computable { ...@@ -25,7 +25,7 @@ class ConvAddKernel<P: PrecisionType>: Kernel, Computable {
super.init(device: device, inFunctionName: "conv_add_3x3") super.init(device: device, inFunctionName: "conv_add_3x3")
} }
param.output.initTexture(device: device, transpose: [0, 3, 1, 2]) param.output.initTexture(device: device, inTranspose: [0, 3, 2, 1])
let offsetX = param.filter.width/2 - Int(param.paddings[0]) let offsetX = param.filter.width/2 - Int(param.paddings[0])
let offsetY = param.filter.height/2 - Int(param.paddings[1]) let offsetY = param.filter.height/2 - Int(param.paddings[1])
......
metal/paddle-mobile/paddle-mobile/Operators/Kernels/ConvBNReluKernel.swift
浏览文件 @ b602b048
...@@ -59,7 +59,7 @@ class ConvBNReluKernel<P: PrecisionType>: Kernel, Computable, Testable { ...@@ -59,7 +59,7 @@ class ConvBNReluKernel<P: PrecisionType>: Kernel, Computable, Testable {
} else { } else {
super.init(device: device, inFunctionName: "conv_batch_norm_relu_3x3") super.init(device: device, inFunctionName: "conv_batch_norm_relu_3x3")
} }
param.output.initTexture(device: device, transpose: [0, 2, 3, 1]) param.output.initTexture(device: device, inTranspose: [0, 2, 3, 1])
param.filter.initBuffer(device: device, precision: Tensor.BufferPrecision.Float32) param.filter.initBuffer(device: device, precision: Tensor.BufferPrecision.Float32)
param.variance.initBuffer(device: device) param.variance.initBuffer(device: device)
...@@ -70,8 +70,13 @@ class ConvBNReluKernel<P: PrecisionType>: Kernel, Computable, Testable { ...@@ -70,8 +70,13 @@ class ConvBNReluKernel<P: PrecisionType>: Kernel, Computable, Testable {
let offsetX = param.filter.width/2 - Int(param.paddings[0]) let offsetX = param.filter.width/2 - Int(param.paddings[0])
let offsetY = param.filter.height/2 - Int(param.paddings[1]) let offsetY = param.filter.height/2 - Int(param.paddings[1])
print("offset x: \(offsetX)") print(" param filter width: \(param.filter.width)")
print("offset y: \(offsetY)") print(" param filter height: \(param.filter.height)")
print(" param paddings: \(param.paddings)")
print("ConvBNReluKernel offset x: \(offsetX)")
print("ConvBNReluKernel offset y: \(offsetY)")
let offsetZ = 0.0 let offsetZ = 0.0
...@@ -116,8 +121,8 @@ class ConvBNReluKernel<P: PrecisionType>: Kernel, Computable, Testable { ...@@ -116,8 +121,8 @@ class ConvBNReluKernel<P: PrecisionType>: Kernel, Computable, Testable {
encoder.setTexture(param.output.metalTexture, index: 1) encoder.setTexture(param.output.metalTexture, index: 1)
encoder.setBytes(&metalParam, length: MemoryLayout<MetalConvParam>.size, index: 0) encoder.setBytes(&metalParam, length: MemoryLayout<MetalConvParam>.size, index: 0)
encoder.setBuffer(param.filter.buffer, offset: 0, index: 1) encoder.setBuffer(param.filter.buffer, offset: 0, index: 1)
encoder.setBuffer(param.newScale!, offset: 0, index: 3) encoder.setBuffer(param.newScale!, offset: 0, index: 2)
encoder.setBuffer(param.newBiase!, offset: 0, index: 4) encoder.setBuffer(param.newBiase!, offset: 0, index: 3)
encoder.dispatch(computePipline: pipline, outTexture: param.output.metalTexture) encoder.dispatch(computePipline: pipline, outTexture: param.output.metalTexture)
encoder.endEncoding() encoder.endEncoding()
} }
...@@ -132,9 +137,8 @@ class ConvBNReluKernel<P: PrecisionType>: Kernel, Computable, Testable { ...@@ -132,9 +137,8 @@ class ConvBNReluKernel<P: PrecisionType>: Kernel, Computable, Testable {
var inMetalParam = param.metalParam var inMetalParam = param.metalParam
encoder.setBytes(&inMetalParam, length: MemoryLayout<MetalConvParam>.size, index: 0) encoder.setBytes(&inMetalParam, length: MemoryLayout<MetalConvParam>.size, index: 0)
encoder.setBuffer(param.filterBuffer, offset: 0, index: 1) encoder.setBuffer(param.filterBuffer, offset: 0, index: 1)
encoder.setBuffer(param.biaseBuffer, offset: 0, index: 2) encoder.setBuffer(param.newScaleBuffer, offset: 0, index: 2)
encoder.setBuffer(param.newScaleBuffer, offset: 0, index: 3) encoder.setBuffer(param.newBiaseBuffer, offset: 0, index: 3)
encoder.setBuffer(param.newBiaseBuffer, offset: 0, index: 4)
encoder.dispatch(computePipline: pipline, outTexture: param.outputTexture) encoder.dispatch(computePipline: pipline, outTexture: param.outputTexture)
encoder.endEncoding() encoder.endEncoding()
} }
......
metal/paddle-mobile/paddle-mobile/Operators/Kernels/PriorBoxKernel.swift
浏览文件 @ b602b048
...@@ -15,88 +15,99 @@ ...@@ -15,88 +15,99 @@
import Foundation import Foundation
struct PriorBoxMetalParam { struct PriorBoxMetalParam {
let offset: Float32 let offset: Float32
let stepWidth: Float32 let stepWidth: Float32
let stepHeight: Float32 let stepHeight: Float32
let minSize: Float32 let minSize: Float32
let maxSize: Float32 let maxSize: Float32
let imageWidth: Float32 let imageWidth: Float32
let imageHeight: Float32 let imageHeight: Float32
let clip: Bool let clip: Bool
let numPriors: uint let numPriors: uint
let aspecRatiosSize: uint let aspecRatiosSize: uint
let minSizeSize: uint let minSizeSize: uint
let maxSizeSize: uint let maxSizeSize: uint
} }
class PriorBoxKernel<P: PrecisionType>: Kernel, Computable{ class PriorBoxKernel<P: PrecisionType>: Kernel, Computable{
var metalParam: PriorBoxMetalParam! var metalParam: PriorBoxMetalParam!
required init(device: MTLDevice, param: PriorBoxParam<P>) { required init(device: MTLDevice, param: PriorBoxParam<P>) {
super.init(device: device, inFunctionName: "prior_box") super.init(device: device, inFunctionName: "prior_box")
param.output.initTexture(device: device, transpose: [2, 0, 1, 3]) param.output.initTexture(device: device, inTranspose: [2, 0, 1, 3])
param.outputVariances.initTexture(device: device, transpose: [2, 0, 1, 3]) param.outputVariances.initTexture(device: device, inTranspose: [2, 0, 1, 3])
let imageWidth = Float32(param.inputImage.originDim[3]) let imageWidth = Float32(param.inputImage.originDim[3])
let imageHeight = Float32(param.inputImage.originDim[2]) let imageHeight = Float32(param.inputImage.originDim[2])
let featureWidth = param.inputImage.originDim[3] let featureWidth = param.input.originDim[3]
let featureHeight = param.inputImage.originDim[2] let featureHeight = param.input.originDim[2]
if param.stepW == 0 || param.stepH == 0 { if param.stepW == 0 || param.stepH == 0 {
param.stepW = Float32(imageWidth) / Float32(featureWidth) param.stepW = Float32(imageWidth) / Float32(featureWidth)
param.stepH = Float32(imageHeight) / Float32(featureHeight) param.stepH = Float32(imageHeight) / Float32(featureHeight)
}
var outputAspectRatior: [Float32] = []
outputAspectRatior.append(1.0)
let epsilon = 1e-6
for ar in param.aspectRatios {
var alreadyExist = false
for outputAr in outputAspectRatior {
if fabs(Double(ar) - Double(outputAr)) < Double(epsilon) {
alreadyExist = true
break
} }
}
var outputAspectRatior: [Float32] = [] if !alreadyExist {
outputAspectRatior.append(1.0) outputAspectRatior.append(ar)
}
let epsilon = 1e-6 if param.flip {
for ar in param.aspectRatios { outputAspectRatior.append(1.0 / ar)
var alreadyExist = false }
for outputAr in outputAspectRatior {
if fabs(Double(ar) - Double(outputAr)) < Double(epsilon) {
alreadyExist = true
break
}
}
if !alreadyExist {
outputAspectRatior.append(ar)
}
if param.flip {
outputAspectRatior.append(1.0 / ar)
}
}
param.newAspectRatios = outputAspectRatior
let aspectRatiosSize = uint(outputAspectRatior.count)
let maxSizeSize: uint = uint(param.maxSizes.count)
let minSizeSize: uint = uint(param.minSizes.count)
let numPriors = aspectRatiosSize * minSizeSize + maxSizeSize
let minSize = param.minSizes.last ?? 0.0
let maxSize = param.maxSizes.last ?? 0.0
metalParam = PriorBoxMetalParam.init(offset: param.offset, stepWidth: param.stepW, stepHeight: param.stepH, minSize: minSize, maxSize: maxSize, imageWidth: imageWidth, imageHeight: imageHeight, clip: param.clip, numPriors: numPriors, aspecRatiosSize: aspectRatiosSize, minSizeSize: minSizeSize, maxSizeSize: maxSizeSize)
} }
func compute(commandBuffer: MTLCommandBuffer, param: PriorBoxParam<P>) throws { param.newAspectRatios = outputAspectRatior
guard let encoder = commandBuffer.makeComputeCommandEncoder() else { let aspectRatiosSize = uint(outputAspectRatior.count)
throw PaddleMobileError.predictError(message: " encode is nil")
} let maxSizeSize: uint = uint(param.maxSizes.count)
encoder.setTexture(param.input.metalTexture, index: 0) let minSizeSize: uint = uint(param.minSizes.count)
encoder.setTexture(param.output.metalTexture, index: 1)
encoder.setTexture(param.outputVariances.metalTexture, index: 2) let numPriors = aspectRatiosSize * minSizeSize + maxSizeSize
encoder.setBytes(&metalParam, length: MemoryLayout<PriorBoxMetalParam>.size, index: 0)
encoder.setBytes(param.aspectRatios, length: MemoryLayout<Float32>.size * param.aspectRatios.count, index: 1) let minSize = param.minSizes.last ?? 0.0
encoder.setBytes(param.variances, length: MemoryLayout<Float32>.size * param.variances.count, index: 2) let maxSize = param.maxSizes.last ?? 0.0
encoder.dispatch(computePipline: pipline, outTexture: param.output.metalTexture)
encoder.endEncoding() metalParam = PriorBoxMetalParam.init(offset: param.offset, stepWidth: param.stepW, stepHeight: param.stepH, minSize: minSize, maxSize: maxSize, imageWidth: imageWidth, imageHeight: imageHeight, clip: param.clip, numPriors: numPriors, aspecRatiosSize: aspectRatiosSize, minSizeSize: minSizeSize, maxSizeSize: maxSizeSize)
}
func compute(commandBuffer: MTLCommandBuffer, param: PriorBoxParam<P>) throws {
guard let encoder = commandBuffer.makeComputeCommandEncoder() else {
throw PaddleMobileError.predictError(message: " encode is nil")
} }
print("metalParam: \(metalParam)")
print(" newAspectRatios ")
print(param.newAspectRatios!)
print(" clip: \(metalParam.clip)")
print(" metalParam.numPriors: \(metalParam.numPriors)")
print(" aspecRatiosSize: \(metalParam.aspecRatiosSize)")
encoder.setTexture(param.input.metalTexture, index: 0)
encoder.setTexture(param.output.metalTexture, index: 1)
encoder.setTexture(param.outputVariances.metalTexture, index: 2)
encoder.setBytes(&metalParam, length: MemoryLayout<PriorBoxMetalParam>.size, index: 0)
encoder.setBytes(param.newAspectRatios!, length: MemoryLayout<Float32>.size * param.newAspectRatios!.count, index: 1)
encoder.setBytes(param.variances, length: MemoryLayout<Float32>.size * param.variances.count, index: 2)
encoder.dispatch(computePipline: pipline, outTexture: param.output.metalTexture)
encoder.endEncoding()
}
} }
metal/paddle-mobile/paddle-mobile/Operators/Kernels/Texture2DTo2DArrayKernel.swift
浏览文件 @ b602b048
...@@ -32,7 +32,7 @@ class Texture2DTo2DArrayKernel<P: PrecisionType>: Kernel, Computable{ ...@@ -32,7 +32,7 @@ class Texture2DTo2DArrayKernel<P: PrecisionType>: Kernel, Computable{
} }
required init(device: MTLDevice, param: FeedParam<P>) { required init(device: MTLDevice, param: FeedParam<P>) {
param.output.initTexture(device: device, transpose: [0, 2, 3, 1]) param.output.initTexture(device: device, inTranspose: [0, 2, 3, 1])
super.init(device: device, inFunctionName: "texture2d_to_2d_array") super.init(device: device, inFunctionName: "texture2d_to_2d_array")
} }
} }
metal/paddle-mobile/paddle-mobile/Operators/Kernels/TransposeKernel.swift
浏览文件 @ b602b048
...@@ -15,80 +15,92 @@ ...@@ -15,80 +15,92 @@
import Foundation import Foundation
struct TransposeMetalParam { struct TransposeMetalParam {
var iC: Int32 = 0 var iC: Int32 = 0
var oC: Int32 = 0 var oC: Int32 = 0
var i0: Int32 var i0: Int32
var i1: Int32 var i1: Int32
var i2: Int32 var i2: Int32
var i3: Int32 var i3: Int32
init(_ i0: Int32, _ i1: Int32, _ i2: Int32, _ i3: Int32) { init(_ i0: Int32, _ i1: Int32, _ i2: Int32, _ i3: Int32) {
self.i0 = i0 self.i0 = i0
self.i1 = i1 self.i1 = i1
self.i2 = i2 self.i2 = i2
self.i3 = i3 self.i3 = i3
} }
init(_ axis: [Int]) { init(_ axis: [Int]) {
self.init(Int32(axis[0]), Int32(axis[1]), Int32(axis[2]), Int32(axis[3])) self.init(Int32(axis[0]), Int32(axis[1]), Int32(axis[2]), Int32(axis[3]))
} }
} }
struct TransposeTestParam: TestParam { struct TransposeTestParam: TestParam {
let inputTexture: MTLTexture let inputTexture: MTLTexture
let outputTexture: MTLTexture let outputTexture: MTLTexture
let iC: Int let iC: Int
let oC: Int let oC: Int
let axis: [Int] let axis: [Int]
} }
class TransposeKernel<P: PrecisionType>: Kernel, Computable, Testable { class TransposeKernel<P: PrecisionType>: Kernel, Computable, Testable {
func compute(commandBuffer: MTLCommandBuffer, param: TransposeParam<P>) throws { var metalParam: TransposeMetalParam!
guard let encoder = commandBuffer.makeComputeCommandEncoder() else { func compute(commandBuffer: MTLCommandBuffer, param: TransposeParam<P>) throws {
throw PaddleMobileError.predictError(message: " encode is nil") guard let encoder = commandBuffer.makeComputeCommandEncoder() else {
} throw PaddleMobileError.predictError(message: " encode is nil")
var invT: [Int] = [0, 1, 2, 3]
for (i, v) in param.input.transpose.enumerated() {
invT[v] = i
}
var axis: [Int] = [0, 1, 2, 3]
for i in 0..<param.axis.count {
axis[4-param.axis.count+i] = 4 - param.axis.count + Int(param.axis[i])
}
let realAxis = axis.map {invT[$0]}
var tmp = TransposeMetalParam.init(realAxis)
tmp.iC = Int32(param.input.dim[param.input.transpose[3]])
tmp.oC = Int32(param.output.dim[3])
if realAxis == [0, 1, 2, 3] {
print("====> transpose! FAST :)")
} else {
print("====> transpose! SLOW :(")
}
encoder.setTexture(param.input.metalTexture, index: 0)
encoder.setTexture(param.output.metalTexture, index: 1)
encoder.setBytes(&tmp, length: MemoryLayout<TransposeMetalParam>.size, index: 0)
encoder.dispatch(computePipline: pipline, outTexture: param.output.metalTexture)
encoder.endEncoding()
} }
encoder.setTexture(param.input.metalTexture, index: 0)
encoder.setTexture(param.output.metalTexture, index: 1)
encoder.setBytes(&metalParam, length: MemoryLayout<TransposeMetalParam>.size, index: 0)
encoder.dispatch(computePipline: pipline, outTexture: param.output.metalTexture)
encoder.endEncoding()
}
required init(device: MTLDevice, param: TransposeParam<P>) {
param.output.initTexture(device: device, inTranspose: [0, 1, 2, 3])
super.init(device: device, inFunctionName: "transpose")
required init(device: MTLDevice, param: TransposeParam<P>) { var invT: [Int] = [0, 1, 2, 3]
param.output.initTexture(device: device, transpose: [0, 1, 2, 3]) for (i, v) in param.input.transpose.enumerated() {
super.init(device: device, inFunctionName: "transpose") invT[v] = i
} }
required init(device: MTLDevice, testParam: TransposeTestParam) { var axis: [Int] = [0, 1, 2, 3]
super.init(device: device, inFunctionName: "transpose")
// var doNothing = false
// if param.axis.count == param.input.transpose.count {
// doNothing = param.axis == param.input.transpose.map { Int32($0) }
// }
for i in 0..<param.axis.count {
axis[4-param.axis.count+i] = 4 - param.axis.count + Int(param.axis[i])
}
let realAxis = axis.map {invT[$0]}
var tmp = TransposeMetalParam.init(realAxis)
tmp.iC = Int32(param.input.dim[param.input.transpose[3]])
tmp.oC = Int32(param.output.dim[3])
if realAxis == [0, 1, 2, 3] {
print("====> transpose! FAST :)")
} else {
print("====> transpose! SLOW :(")
}
metalParam = tmp
}
required init(device: MTLDevice, testParam: TransposeTestParam) {
super.init(device: device, inFunctionName: "transpose")
fatalError()
}
public func test(commandBuffer: MTLCommandBuffer, param: TransposeTestParam) {
guard let encoder = commandBuffer.makeComputeCommandEncoder() else {
fatalError()
} }
public func test(commandBuffer: MTLCommandBuffer, param: TransposeTestParam) { encoder.setTexture(param.inputTexture, index: 0)
guard let encoder = commandBuffer.makeComputeCommandEncoder() else { encoder.setTexture(param.outputTexture, index: 1)
fatalError() var tmp = TransposeMetalParam.init(param.axis)
} tmp.iC = Int32(param.iC)
tmp.oC = Int32(param.oC)
encoder.setTexture(param.inputTexture, index: 0)
encoder.setTexture(param.outputTexture, index: 1) encoder.setBytes(&tmp, length: MemoryLayout<TransposeMetalParam>.size, index: 0)
var tmp = TransposeMetalParam.init(param.axis) encoder.dispatch(computePipline: pipline, outTexture: param.outputTexture)
tmp.iC = Int32(param.iC) encoder.endEncoding()
tmp.oC = Int32(param.oC) }}
encoder.setBytes(&tmp, length: MemoryLayout<TransposeMetalParam>.size, index: 0)
encoder.dispatch(computePipline: pipline, outTexture: param.outputTexture)
encoder.endEncoding()
}}
metal/paddle-mobile/paddle-mobile/Operators/Kernels/metal/Common.metal 0 → 100644
浏览文件 @ b602b048
//
// common.metal
// paddle-mobile
//
// Created by liuRuiLong on 2018/8/26.
// Copyright © 2018年 orange. All rights reserved.
//
#include <metal_stdlib>
using namespace metal;
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];
}
}
metal/paddle-mobile/paddle-mobile/Operators/Kernels/metal/ConvKernel.metal
浏览文件 @ b602b048
...@@ -704,9 +704,8 @@ kernel void conv_batch_norm_relu_1x1(texture2d_array<float, access::sample> inTe ...@@ -704,9 +704,8 @@ kernel void conv_batch_norm_relu_1x1(texture2d_array<float, access::sample> inTe
texture2d_array<float, access::write> outTexture [[texture(1)]], texture2d_array<float, access::write> outTexture [[texture(1)]],
constant MetalConvParam &param [[buffer(0)]], constant MetalConvParam &param [[buffer(0)]],
const device float4 *weights [[buffer(1)]], const device float4 *weights [[buffer(1)]],
const device float4 *biase [[buffer(2)]], const device float4 *new_scale [[buffer(2)]],
const device float4 *new_scale [[buffer(3)]], const device float4 *new_biase [[buffer(3)]],
const device float4 *new_biase [[buffer(4)]],
uint3 gid [[thread_position_in_grid]]) { uint3 gid [[thread_position_in_grid]]) {
if (gid.x >= outTexture.get_width() || if (gid.x >= outTexture.get_width() ||
...@@ -749,9 +748,8 @@ kernel void conv_batch_norm_relu_3x3(texture2d_array<float, access::sample> inTe ...@@ -749,9 +748,8 @@ kernel void conv_batch_norm_relu_3x3(texture2d_array<float, access::sample> inTe
texture2d_array<float, access::write> outTexture [[texture(1)]], texture2d_array<float, access::write> outTexture [[texture(1)]],
constant MetalConvParam &param [[buffer(0)]], constant MetalConvParam &param [[buffer(0)]],
const device float4 *weights [[buffer(1)]], const device float4 *weights [[buffer(1)]],
const device float4 *biase [[buffer(2)]], const device float4 *new_scale [[buffer(2)]],
const device float4 *new_scale [[buffer(3)]], const device float4 *new_biase [[buffer(3)]],
const device float4 *new_biase [[buffer(4)]],
uint3 gid [[thread_position_in_grid]]) { uint3 gid [[thread_position_in_grid]]) {
if (gid.x >= outTexture.get_width() || if (gid.x >= outTexture.get_width() ||
...@@ -803,8 +801,8 @@ kernel void depthwise_conv_batch_norm_relu_3x3(texture2d_array<float, access::sa ...@@ -803,8 +801,8 @@ kernel void depthwise_conv_batch_norm_relu_3x3(texture2d_array<float, access::sa
texture2d_array<float, access::write> outTexture [[texture(1)]], texture2d_array<float, access::write> outTexture [[texture(1)]],
constant MetalConvParam &param [[buffer(0)]], constant MetalConvParam &param [[buffer(0)]],
const device float *weights [[buffer(1)]], const device float *weights [[buffer(1)]],
const device float4 *new_scale [[buffer(3)]], const device float4 *new_scale [[buffer(2)]],
const device float4 *new_biase [[buffer(4)]], const device float4 *new_biase [[buffer(3)]],
uint3 gid [[thread_position_in_grid]]) { uint3 gid [[thread_position_in_grid]]) {
if (gid.x >= outTexture.get_width() || if (gid.x >= outTexture.get_width() ||
......
metal/paddle-mobile/paddle-mobile/Operators/Kernels/metal/PriorBoxKernel.metal
浏览文件 @ b602b048
...@@ -60,7 +60,7 @@ kernel void prior_box(texture2d_array<float, access::read> inTexture [[texture(0 ...@@ -60,7 +60,7 @@ kernel void prior_box(texture2d_array<float, access::read> inTexture [[texture(0
float4 res; float4 res;
if (param.clip) { if (param.clip) {
res = min(max(box, 0.0), 1.0); res = fmin(fmax(box, 0.0), 1.0);
} else { } else {
res = box; res = box;
} }
...@@ -74,7 +74,7 @@ kernel void prior_box(texture2d_array<float, access::read> inTexture [[texture(0 ...@@ -74,7 +74,7 @@ kernel void prior_box(texture2d_array<float, access::read> inTexture [[texture(0
max_box.y = (center_y - box_height) / param.imageHeight; max_box.y = (center_y - box_height) / param.imageHeight;
max_box.z = (center_x + box_width) / param.imageWidth; max_box.z = (center_x + box_width) / param.imageWidth;
max_box.w = (center_y + box_height) / param.imageHeight; max_box.w = (center_y + box_height) / param.imageHeight;
float4 res; float4 res;
if (param.clip) { if (param.clip) {
res = min(max(max_box, 0.0), 1.0); res = min(max(max_box, 0.0), 1.0);
...@@ -92,6 +92,7 @@ kernel void prior_box(texture2d_array<float, access::read> inTexture [[texture(0 ...@@ -92,6 +92,7 @@ kernel void prior_box(texture2d_array<float, access::read> inTexture [[texture(0
variances_output.y = variance.y; variances_output.y = variance.y;
variances_output.z = variance.z; variances_output.z = variance.z;
variances_output.w = variance.w; variances_output.w = variance.w;
varianceTexture.write(variances_output, gid.xy, gid.z);
} }
} }
metal/paddle-mobile/paddle-mobile/Operators/Kernels/metal/ReshapeKernel.metal 0 → 100644
浏览文件 @ b602b048
/* 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 ReshapeParam {
int32_t idim[4];
int32_t itrans[4];
int32_t odim[4];
int32_t otrans[4];
};
kernel void reshape(texture2d_array<float, access::read> inTexture [[texture(0)]],
texture2d_array<float, 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];
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];
float4 r;
for (int n = 0; n < 4; n++) {
oxyzn[3] = n;
//4 (gid.x gid.y, gid.z, 0~4)
xyzn2abcd(oC, oxyzn, oabcd);
int tabcd[4];
invtrans(lrp.otrans, oabcd, tabcd);
int index = abcd2index(lrp.odim, tabcd);
if (index < count) {
int c = index % 4;
int temp0 = index % (inTexture.get_array_size() * 4);
int slice = temp0 / 4;
int temp1 = index % (inTexture.get_array_size() * 4 * lrp.idim[2]);
int w = temp1 / (inTexture.get_array_size() * 4);
int h = index / (inTexture.get_array_size() * 4 * lrp.idim[2]);
// index2abcd(lrp.idim, index, tabcd);
// abcd2xyzn(iC, tabcd, ixyzn);
r[n] = inTexture.read(uint2(w, h), slice)[c];
} else {
r[n] = 0;
}
}
outTexture.write(r, gid.xy, gid.z);
}
//
//kernel void reshape_half(texture2d_array<half, access::read> 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;
//
// half4 r = inTexture.read(uint2(0, 0), gid.x);
// outTexture.write(r, gid.xy, gid.z);
//}
metal/paddle-mobile/paddle-mobile/Operators/MulticlassNMSOp.swift
浏览文件 @ b602b048
...@@ -31,7 +31,11 @@ class MulticlassNMSParam<P: PrecisionType>: OpParam { ...@@ -31,7 +31,11 @@ class MulticlassNMSParam<P: PrecisionType>: OpParam {
} }
class MulticlassNMSOp<P: PrecisionType>: Operator<MulticlassNMSKernel<P>, MulticlassNMSParam<P>>, Runable, Creator, InferShaperable{ class MulticlassNMSOp<P: PrecisionType>: Operator<MulticlassNMSKernel<P>, MulticlassNMSParam<P>>, Runable, Creator, InferShaperable{
func inputs() -> [Variant] {
return [para.scores,para.bboxes]
}
func inferShape() { func inferShape() {
// para.output.dim = para.input.dim // para.output.dim = para.input.dim
} }
......
metal/paddle-mobile/paddle-mobile/Operators/PoolOp.swift
浏览文件 @ b602b048
...@@ -15,54 +15,58 @@ ...@@ -15,54 +15,58 @@
import Foundation import Foundation
class PoolParam<P: PrecisionType>: OpParam { class PoolParam<P: PrecisionType>: OpParam {
typealias ParamPrecisionType = P typealias ParamPrecisionType = P
required init(opDesc: OpDesc, inScope: Scope) throws { required init(opDesc: OpDesc, inScope: Scope) throws {
do { do {
input = try PoolParam.inputX(inputs: opDesc.inputs, from: inScope) input = try PoolParam.inputX(inputs: opDesc.inputs, from: inScope)
output = try PoolParam.outputOut(outputs: opDesc.outputs, from: inScope) output = try PoolParam.outputOut(outputs: opDesc.outputs, from: inScope)
poolType = try PoolParam.getAttr(key: "pooling_type", attrs: opDesc.attrs) poolType = try PoolParam.getAttr(key: "pooling_type", attrs: opDesc.attrs)
ksize = try PoolParam.getAttr(key: "ksize", attrs: opDesc.attrs) ksize = try PoolParam.getAttr(key: "ksize", attrs: opDesc.attrs)
stride = try PoolParam.getAttr(key: "strides", attrs: opDesc.attrs) stride = try PoolParam.getAttr(key: "strides", attrs: opDesc.attrs)
padding = try PoolParam.getAttr(key: "paddings", attrs: opDesc.attrs) padding = try PoolParam.getAttr(key: "paddings", attrs: opDesc.attrs)
ceilMode = try PoolParam.getAttr(key: "ceil_mode", attrs: opDesc.attrs) ceilMode = try PoolParam.getAttr(key: "ceil_mode", attrs: opDesc.attrs)
globalPooling = try PoolParam.getAttr(key: "global_pooling", attrs: opDesc.attrs) globalPooling = try PoolParam.getAttr(key: "global_pooling", attrs: opDesc.attrs)
} catch let error { } catch let error {
throw error throw error
}
// let buffer = input.metalTexture.buffer.contents().assumingMemoryBound(to: P.self)
} }
let input: Texture<P> // let buffer = input.metalTexture.buffer.contents().assumingMemoryBound(to: P.self)
var output: Texture<P> }
var ksize: [Int32] let input: Texture<P>
var stride: [Int32] var output: Texture<P>
var padding: [Int32] var ksize: [Int32]
var poolType: String var stride: [Int32]
var ceilMode: Bool var padding: [Int32]
var globalPooling: Bool var poolType: String
var ceilMode: Bool
var globalPooling: Bool
} }
class PoolOp<P: PrecisionType>: Operator<PoolKernel<P>, PoolParam<P>>, Runable, Creator, InferShaperable{ class PoolOp<P: PrecisionType>: Operator<PoolKernel<P>, PoolParam<P>>, Runable, Creator, InferShaperable{
func inferShape() { func inputs() -> [Variant] {
// para.output.dim = para.input.dim return [para.input]
} }
typealias OpType = PoolOp<P> func inferShape() {
func runImpl(device: MTLDevice, buffer: MTLCommandBuffer) throws { // para.output.dim = para.input.dim
do { }
try kernel.compute(commandBuffer: buffer, param: para)
} catch let error { typealias OpType = PoolOp<P>
throw error func runImpl(device: MTLDevice, buffer: MTLCommandBuffer) throws {
} do {
} try kernel.compute(commandBuffer: buffer, param: para)
} catch let error {
func delogOutput() { throw error
print("pool2d delog")
let _: P? = para.input.metalTexture.logDesc(header: "pool2d input: ", stridable: true)
print(para.ksize)
print(para.stride)
print(para.padding)
print(para.poolType)
let _: P? = para.output.metalTexture.logDesc(header: "pool2d output: ", stridable: true)
} }
}
func delogOutput() {
print("pool2d delog")
let _: P? = para.input.metalTexture.logDesc(header: "pool2d input: ", stridable: true)
print(para.ksize)
print(para.stride)
print(para.padding)
print(para.poolType)
let _: P? = para.output.metalTexture.logDesc(header: "pool2d output: ", stridable: true)
}
} }
metal/paddle-mobile/paddle-mobile/Operators/PreluOp.swift
浏览文件 @ b602b048
...@@ -35,6 +35,10 @@ class PreluParam<P: PrecisionType>: OpParam { ...@@ -35,6 +35,10 @@ class PreluParam<P: PrecisionType>: OpParam {
class PreluOp<P: PrecisionType>: Operator<PreluKernel<P>, PreluParam<P>>, Runable, Creator, InferShaperable{ class PreluOp<P: PrecisionType>: Operator<PreluKernel<P>, PreluParam<P>>, Runable, Creator, InferShaperable{
func inputs() -> [Variant] {
return [para.alpha, para.input]
}
func inferShape() { func inferShape() {
// para.output.dim = para.input.dim // para.output.dim = para.input.dim
} }
......
metal/paddle-mobile/paddle-mobile/Operators/ReluOp.swift
浏览文件 @ b602b048
...@@ -15,33 +15,37 @@ ...@@ -15,33 +15,37 @@
import Foundation import Foundation
class ReluParam<P: PrecisionType>: OpParam { class ReluParam<P: PrecisionType>: OpParam {
typealias ParamPrecisionType = P typealias ParamPrecisionType = P
required init(opDesc: OpDesc, inScope: Scope) throws { required init(opDesc: OpDesc, inScope: Scope) throws {
do { do {
input = try ReluParam.inputX(inputs: opDesc.inputs, from: inScope) input = try ReluParam.inputX(inputs: opDesc.inputs, from: inScope)
output = try ReluParam.outputOut(outputs: opDesc.outputs, from: inScope) output = try ReluParam.outputOut(outputs: opDesc.outputs, from: inScope)
} catch let error { } catch let error {
throw error throw error
}
} }
let input: Texture<P> }
var output: Texture<P> let input: Texture<P>
var output: Texture<P>
} }
class ReluOp<P: PrecisionType>: Operator<ReluKernel<P>, ReluParam<P>>, Runable, Creator, InferShaperable{ class ReluOp<P: PrecisionType>: Operator<ReluKernel<P>, ReluParam<P>>, Runable, Creator, InferShaperable{
func inferShape() { func inputs() -> [Variant] {
para.output.dim = para.input.dim return [para.input]
} }
typealias OpType = ReluOp<P> func inferShape() {
func runImpl(device: MTLDevice, buffer: MTLCommandBuffer) throws { para.output.dim = para.input.dim
do { }
try kernel.compute(commandBuffer: buffer, param: para)
} catch let error { typealias OpType = ReluOp<P>
throw error func runImpl(device: MTLDevice, buffer: MTLCommandBuffer) throws {
} do {
try kernel.compute(commandBuffer: buffer, param: para)
} catch let error {
throw error
} }
}
} }
......
metal/paddle-mobile/paddle-mobile/Program/TensorDesc.swift
浏览文件 @ b602b048
...@@ -17,7 +17,7 @@ import Foundation ...@@ -17,7 +17,7 @@ import Foundation
struct TensorDesc { struct TensorDesc {
let dims: [Int] let dims: [Int]
let dataType: VarTypeType let dataType: VarTypeType
let dataLayout: DataLayout = DataLayout.NHWC() let dataLayout: DataLayout = DataLayout.NCHW()
var NCHWDim: [Int] { var NCHWDim: [Int] {
get { get {
if dims.count != 4 { if dims.count != 4 {
...@@ -53,7 +53,7 @@ struct TensorDesc { ...@@ -53,7 +53,7 @@ struct TensorDesc {
} }
init(protoTensorDesc: PaddleMobile_Framework_Proto_VarType.TensorDesc) { init(protoTensorDesc: PaddleMobile_Framework_Proto_VarType.TensorDesc) {
dims = protoTensorDesc.dims.map{ Int($0) > 0 ? Int($0) : 1 } dims = protoTensorDesc.dims.map{ Int($0) > 0 ? Int($0) : abs(Int($0)) }
dataType = VarTypeType.init(rawValue: protoTensorDesc.dataType.rawValue) ?? .ErrorType dataType = VarTypeType.init(rawValue: protoTensorDesc.dataType.rawValue) ?? .ErrorType
} }
......
metal/paddle-mobile/paddle-mobile/framework/Tensor.swift
浏览文件 @ b602b048
...@@ -174,7 +174,7 @@ class Tensor<P: PrecisionType>: Tensorial { ...@@ -174,7 +174,7 @@ class Tensor<P: PrecisionType>: Tensorial {
fatalError(" not support !") fatalError(" not support !")
} }
//TODO: release //TODO: release
data.release() // data.release()
} }
var width: Int { var width: Int {
......
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