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Paddle-Lite
提交 6ff252ef 编写于 作者: qnqinan's avatar qnqinan
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Merge branch 'develop' of https://github.com/PaddlePaddle/paddle-mobile into develop

上级 9569b039 272191f1
隐藏空白更改
内联 并排
Showing with 263 addition and 82 deletion
metal/paddle-mobile-demo/paddle-mobile-demo.xcodeproj/project.pbxproj
浏览文件 @ 6ff252ef
......@@ -15,6 +15,7 @@
FC039B8720E11C550081E9F8 /* Main.storyboard in Resources */ = {isa = PBXBuildFile; fileRef = FC039B8520E11C550081E9F8 /* Main.storyboard */; };
FC039B8920E11C560081E9F8 /* Assets.xcassets in Resources */ = {isa = PBXBuildFile; fileRef = FC039B8820E11C560081E9F8 /* Assets.xcassets */; };
FC039B8C20E11C560081E9F8 /* LaunchScreen.storyboard in Resources */ = {isa = PBXBuildFile; fileRef = FC039B8A20E11C560081E9F8 /* LaunchScreen.storyboard */; };
FC1A1D552237EAC70047B7FD /* ImageTool.m in Sources */ = {isa = PBXBuildFile; fileRef = FC1A1D542237EAC70047B7FD /* ImageTool.m */; };
FC203FB221CBFDBA00B37166 /* test.jpg in Resources */ = {isa = PBXBuildFile; fileRef = FC203FA921CBFDBA00B37166 /* test.jpg */; };
FC2BFCBC21DF0A8600C262B2 /* 00001.jpg in Resources */ = {isa = PBXBuildFile; fileRef = FC2BFCBB21DF0A8600C262B2 /* 00001.jpg */; };
FC2BFCBE21DF15D900C262B2 /* 123.jpg in Resources */ = {isa = PBXBuildFile; fileRef = FC2BFCBD21DF15D900C262B2 /* 123.jpg */; };
......@@ -42,6 +43,8 @@
FC9797C321D608E000F2FD90 /* mobilenet_params in Resources */ = {isa = PBXBuildFile; fileRef = FC9797C121D608DF00F2FD90 /* mobilenet_params */; };
FC9797C721D609FB00F2FD90 /* synset.txt in Resources */ = {isa = PBXBuildFile; fileRef = FC9797C621D609FB00F2FD90 /* synset.txt */; };
FC9797CF21D6506F00F2FD90 /* mingren.jpg in Resources */ = {isa = PBXBuildFile; fileRef = FC9797CE21D6506F00F2FD90 /* mingren.jpg */; };
FC9B9F092236ABF300BB6DB0 /* combined_mobilenet_model_16 in Resources */ = {isa = PBXBuildFile; fileRef = FC9B9F072236ABD200BB6DB0 /* combined_mobilenet_model_16 */; };
FC9B9F0A2236ABF500BB6DB0 /* combined_mobilenet_params_16 in Resources */ = {isa = PBXBuildFile; fileRef = FC9B9F082236ABD300BB6DB0 /* combined_mobilenet_params_16 */; };
FCAFD84B2231614200496A36 /* yolo_16_param in Resources */ = {isa = PBXBuildFile; fileRef = FCAFD8492231614200496A36 /* yolo_16_param */; };
FCAFD84C2231614200496A36 /* yolo_16_model in Resources */ = {isa = PBXBuildFile; fileRef = FCAFD84A2231614200496A36 /* yolo_16_model */; };
FCBCCC552122EF5500D94F7E /* MetalHelper.swift in Sources */ = {isa = PBXBuildFile; fileRef = FCBCCC542122EF5400D94F7E /* MetalHelper.swift */; };
......@@ -83,6 +86,8 @@
FC039B8820E11C560081E9F8 /* Assets.xcassets */ = {isa = PBXFileReference; lastKnownFileType = folder.assetcatalog; path = Assets.xcassets; sourceTree = "<group>"; };
FC039B8B20E11C560081E9F8 /* Base */ = {isa = PBXFileReference; lastKnownFileType = file.storyboard; name = Base; path = Base.lproj/LaunchScreen.storyboard; sourceTree = "<group>"; };
FC039B8D20E11C560081E9F8 /* Info.plist */ = {isa = PBXFileReference; lastKnownFileType = text.plist.xml; path = Info.plist; sourceTree = "<group>"; };
FC1A1D532237EAC70047B7FD /* ImageTool.h */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.c.h; path = ImageTool.h; sourceTree = "<group>"; };
FC1A1D542237EAC70047B7FD /* ImageTool.m */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.c.objc; path = ImageTool.m; sourceTree = "<group>"; };
FC203FA921CBFDBA00B37166 /* test.jpg */ = {isa = PBXFileReference; lastKnownFileType = image.jpeg; path = test.jpg; sourceTree = "<group>"; };
FC27991121343A39000B6BAD /* paddle-mobile-demo-Bridging-Header.h */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.c.h; path = "paddle-mobile-demo-Bridging-Header.h"; sourceTree = "<group>"; };
FC2BFCBB21DF0A8600C262B2 /* 00001.jpg */ = {isa = PBXFileReference; lastKnownFileType = image.jpeg; path = 00001.jpg; sourceTree = "<group>"; };
......@@ -115,6 +120,8 @@
FC9797C121D608DF00F2FD90 /* mobilenet_params */ = {isa = PBXFileReference; lastKnownFileType = file; path = mobilenet_params; sourceTree = "<group>"; };
FC9797C621D609FB00F2FD90 /* synset.txt */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = text; path = synset.txt; sourceTree = "<group>"; };
FC9797CE21D6506F00F2FD90 /* mingren.jpg */ = {isa = PBXFileReference; lastKnownFileType = image.jpeg; path = mingren.jpg; sourceTree = "<group>"; };
FC9B9F072236ABD200BB6DB0 /* combined_mobilenet_model_16 */ = {isa = PBXFileReference; lastKnownFileType = file; path = combined_mobilenet_model_16; sourceTree = "<group>"; };
FC9B9F082236ABD300BB6DB0 /* combined_mobilenet_params_16 */ = {isa = PBXFileReference; lastKnownFileType = file; path = combined_mobilenet_params_16; sourceTree = "<group>"; };
FCAFD8492231614200496A36 /* yolo_16_param */ = {isa = PBXFileReference; lastKnownFileType = file; path = yolo_16_param; sourceTree = "<group>"; };
FCAFD84A2231614200496A36 /* yolo_16_model */ = {isa = PBXFileReference; lastKnownFileType = file; path = yolo_16_model; sourceTree = "<group>"; };
FCBCCC542122EF5400D94F7E /* MetalHelper.swift */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.swift; path = MetalHelper.swift; sourceTree = "<group>"; };
......@@ -183,6 +190,7 @@
FC039B8020E11C550081E9F8 /* paddle-mobile-demo */ = {
isa = PBXGroup;
children = (
FC1A1D522237EAA10047B7FD /* OC */,
FC2BFD4F21DF892500C262B2 /* Resources */,
FCBCCC542122EF5400D94F7E /* MetalHelper.swift */,
FC2BFD3F21DF5DDF00C262B2 /* OCInterface */,
......@@ -201,6 +209,15 @@
path = "paddle-mobile-demo";
sourceTree = "<group>";
};
FC1A1D522237EAA10047B7FD /* OC */ = {
isa = PBXGroup;
children = (
FC1A1D532237EAC70047B7FD /* ImageTool.h */,
FC1A1D542237EAC70047B7FD /* ImageTool.m */,
);
path = OC;
sourceTree = "<group>";
};
FC203FA821CBFDBA00B37166 /* images */ = {
isa = PBXGroup;
children = (
......@@ -269,6 +286,7 @@
FC704C1B21D237FC00F98BAB /* vision_model */ = {
isa = PBXGroup;
children = (
FC9B9F062236AB4800BB6DB0 /* mobilenet_16 */,
FCE834AB2232A4AE0057BF43 /* vision_mobilenet */,
FCAFD8482231614200496A36 /* yolo_16 */,
FC704C1F21D237FC00F98BAB /* yolo */,
......@@ -320,6 +338,15 @@
path = mobilenet;
sourceTree = "<group>";
};
FC9B9F062236AB4800BB6DB0 /* mobilenet_16 */ = {
isa = PBXGroup;
children = (
FC9B9F072236ABD200BB6DB0 /* combined_mobilenet_model_16 */,
FC9B9F082236ABD300BB6DB0 /* combined_mobilenet_params_16 */,
);
path = mobilenet_16;
sourceTree = "<group>";
};
FCAFD8482231614200496A36 /* yolo_16 */ = {
isa = PBXGroup;
children = (
......@@ -419,10 +446,12 @@
FCAFD84C2231614200496A36 /* yolo_16_model in Resources */,
FC2BFCC021DF279900C262B2 /* classify-img-output.png in Resources */,
FC203FB221CBFDBA00B37166 /* test.jpg in Resources */,
FC9B9F0A2236ABF500BB6DB0 /* combined_mobilenet_params_16 in Resources */,
FCC15E15221E716500DC3CB2 /* paddle-mobile-metallib.metallib in Resources */,
FC9797C321D608E000F2FD90 /* mobilenet_params in Resources */,
FC704C2421D237FC00F98BAB /* yolo_params in Resources */,
FCE834AE2232A4AE0057BF43 /* combined_mobilenet_params in Resources */,
FC9B9F092236ABF300BB6DB0 /* combined_mobilenet_model_16 in Resources */,
FC2BFCBC21DF0A8600C262B2 /* 00001.jpg in Resources */,
FC9797BE21D6045B00F2FD90 /* banana.jpeg in Resources */,
FC704C2521D237FC00F98BAB /* yolo_model in Resources */,
......@@ -490,6 +519,7 @@
C2E67E5E21524E460013F575 /* LoadPointerViewController.m in Sources */,
FC2BFD3121DF3FEA00C262B2 /* Genet.swift in Sources */,
FC039B8220E11C550081E9F8 /* AppDelegate.swift in Sources */,
FC1A1D552237EAC70047B7FD /* ImageTool.m in Sources */,
FC2BFD4421DF5E1E00C262B2 /* SuperResolutionNet.swift in Sources */,
FC2BFD3E21DF5CE800C262B2 /* PreProcessKernel.metal in Sources */,
FC2BFD3821DF46DE00C262B2 /* OCDemoViewController.m in Sources */,
......
metal/paddle-mobile-demo/paddle-mobile-demo/Net/MobileNetCombined.swift
浏览文件 @ 6ff252ef
......@@ -19,13 +19,14 @@ public class MobileNetCombined: Net {
@objc public override init(device: MTLDevice) {
super.init(device: device)
except = 0
modelPath = Bundle.main.path(forResource: "combined_mobilenet_model", ofType: nil) ?! "model null"
paramPath = Bundle.main.path(forResource: "combined_mobilenet_params", ofType: nil) ?! "para null"
modelPath = Bundle.main.path(forResource: "combined_mobilenet_model_16", ofType: nil) ?! "model null"
paramPath = Bundle.main.path(forResource: "combined_mobilenet_params_16", ofType: nil) ?! "para null"
inputDim = Dim.init(inDim: [1, 224, 224, 3])
metalLoadMode = .LoadMetalInCustomMetalLib
let paddleMobileMetallib = Bundle.main.path(forResource: "paddle-mobile-metallib", ofType: "metallib")
metalLibPath = paddleMobileMetallib
useMPS = true
paramPrecision = .Float16
preprocessKernel = ScaleKernel.init(device: device, shape: Shape.init(inWidth: 224, inHeight: 224, inChannel: 3), metalLoadMode: .LoadMetalInCustomMetalLib, metalLibPath: paddleMobileMetallib)
}
......
metal/paddle-mobile-demo/paddle-mobile-demo/OC/ImageTool.h 0 → 100644
浏览文件 @ 6ff252ef
//
// ImageTool.h
// paddle-mobile-demo
//
// Created by liuRuiLong on 2019/3/12.
// Copyright © 2019 orange. All rights reserved.
//
#import <UIKit/UIKit.h>
#import <CoreVideo/CoreVideo.h>
#import <Foundation/Foundation.h>
NS_ASSUME_NONNULL_BEGIN
@interface ImageTool : NSObject
+ (CVPixelBufferRef)imageToRGBPixelBuffer:(UIImage *)image;
@end
NS_ASSUME_NONNULL_END
metal/paddle-mobile-demo/paddle-mobile-demo/OC/ImageTool.m 0 → 100644
浏览文件 @ 6ff252ef
//
// ImageTool.m
// paddle-mobile-demo
//
// Created by liuRuiLong on 2019/3/12.
// Copyright © 2019 orange. All rights reserved.
//
#import "ImageTool.h"
@implementation ImageTool
+ (CVPixelBufferRef)imageToRGBPixelBuffer:(UIImage *)image {
CVPixelBufferRef pxbuffer = NULL;
#if defined(__arm__) || defined(__arm64__)
CGSize frameSize = CGSizeMake(CGImageGetWidth(image.CGImage),CGImageGetHeight(image.CGImage));
//Metal渲染纹理需要IOSurface属性
NSDictionary *options =
[NSDictionary dictionaryWithObjectsAndKeys:
[NSNumber numberWithBool:YES], kCVPixelBufferCGImageCompatibilityKey,
[NSNumber numberWithBool:YES], kCVPixelBufferCGBitmapContextCompatibilityKey,
[NSNumber numberWithBool:YES], kCVPixelBufferIOSurfaceOpenGLESTextureCompatibilityKey,
[NSNumber numberWithBool:YES], kCVPixelBufferIOSurfaceCoreAnimationCompatibilityKey,nil];
CVPixelBufferCreate(kCFAllocatorDefault, frameSize.width, frameSize.height,kCVPixelFormatType_32BGRA, (__bridge CFDictionaryRef)options, &pxbuffer);
CVPixelBufferLockBaseAddress(pxbuffer, 0);
void *pxdata = CVPixelBufferGetBaseAddress(pxbuffer);
CGColorSpaceRef rgbColorSpace = CGColorSpaceCreateDeviceRGB();
CGContextRef context = CGBitmapContextCreate(pxdata, frameSize.width, frameSize.height,8, CVPixelBufferGetBytesPerRow(pxbuffer),rgbColorSpace,(CGBitmapInfo)kCGBitmapByteOrder32Little | kCGImageAlphaPremultipliedFirst);
CGContextDrawImage(context, CGRectMake(0, 0, CGImageGetWidth(image.CGImage),CGImageGetHeight(image.CGImage)), image.CGImage);
CGColorSpaceRelease(rgbColorSpace);
CGContextRelease(context);
CVPixelBufferUnlockBaseAddress(pxbuffer, 0);
#endif
return pxbuffer;
}
@end
metal/paddle-mobile-demo/paddle-mobile-demo/ViewController.swift
浏览文件 @ 6ff252ef
......@@ -16,6 +16,7 @@ import UIKit
import MetalKit
import CoreMedia
import paddle_mobile
import paddle_mobile_demo
import MetalPerformanceShaders
class FileReader {
......@@ -75,8 +76,10 @@ class ViewController: UIViewController {
@IBOutlet weak var modelPickerView: UIPickerView!
@IBOutlet weak var threadPickerView: UIPickerView!
@IBOutlet weak var videoView: UIView!
var inputImageSize: CGSize = CGSize.init(width: 0, height: 0)
// var videoCapture: VideoCapture!
var textureCache: CVMetalTextureCache?
var selectImage: UIImage?
var inputPointer: UnsafeMutablePointer<Float32>?
var modelType: SupportModel = SupportModel.supportedModels()[0]
......@@ -102,7 +105,9 @@ class ViewController: UIViewController {
if self.toPredictTexture == nil {
let beforeDate = Date.init()
if modelType == .mobilenet_combined || modelType == .yolo {
self.toPredictTexture = try! MetalHelper.shared.textureLoader.newTexture(cgImage: selectImage!.cgImage!, options: nil)
let buffer = ImageTool.image(toRGBPixelBuffer: selectImage!)
let texture = convertToMTLTexture(imageBuffer: buffer.takeRetainedValue())
self.toPredictTexture = texture
} else {
runner.getTexture(image: selectImage!.cgImage!) { [weak self] (texture) in
let timeUse = Date.init().timeIntervalSince(beforeDate)
......@@ -150,6 +155,8 @@ class ViewController: UIViewController {
}
if success, let inResultHolderArr = resultHolder {
// writeToLibrary(fileName: "00001_result_32_new_new", buffer: UnsafeBufferPointer<Float32>.init(start: inResultHolderArr[0].result, count: inResultHolderArr[0].capacity))
let inResultHolder = inResultHolderArr[0]
if i == max - 1 {
let time = Date.init().timeIntervalSince(startDate)
......@@ -173,6 +180,8 @@ class ViewController: UIViewController {
override func viewDidLoad() {
super.viewDidLoad()
CVMetalTextureCacheCreate(kCFAllocatorDefault, nil, MetalHelper.shared.device, nil, &textureCache)
GlobalConfig.shared.computePrecision = .Float16
GlobalConfig.shared.debug = false
......@@ -259,5 +268,28 @@ extension ViewController: VideoCaptureDelegate{
}
extension ViewController {
private func convertToMTLTexture(imageBuffer: CVPixelBuffer?) -> MTLTexture? {
if let textureCache = textureCache, let imageBuffer = imageBuffer {
CVPixelBufferLockBaseAddress(imageBuffer, CVPixelBufferLockFlags(rawValue: 0))
let width = CVPixelBufferGetWidth(imageBuffer)
let height = CVPixelBufferGetHeight(imageBuffer)
inputImageSize = CGSize(width: width, height: height);
let pixelFormat: MTLPixelFormat = .bgra8Unorm
var texture: CVMetalTexture?
CVMetalTextureCacheCreateTextureFromImage(kCFAllocatorDefault, textureCache,
imageBuffer, nil, pixelFormat, width, height, 0, &texture)
CVPixelBufferUnlockBaseAddress(imageBuffer, CVPixelBufferLockFlags(rawValue: 0))
if let texture = texture {
return CVMetalTextureGetTexture(texture)
}
}
return nil
}
}
metal/paddle-mobile-demo/paddle-mobile-demo/paddle-mobile-demo-Bridging-Header.h
浏览文件 @ 6ff252ef
......@@ -3,3 +3,4 @@
//
#import <paddle_mobile/paddle_mobile.h>
#import "ImageTool.h"
metal/paddle-mobile/paddle-mobile/API/Net.swift
浏览文件 @ 6ff252ef
......@@ -56,10 +56,10 @@ import Foundation
/// 输入维度，按照 n h w c 方式传入
@objc public var inputDim: Dim = Dim.init(inDim: [])
/// 是否使用 MetalPerformanceShaders 进行运算
/// 是否使用 MetalPerformanceShaders 进行运算, 运算精度为 32 位时不支持开启 MPS
@objc public var useMPS: Bool = false
/// 模型精度 - 当使用模型精度为 Float 16 时 不要开启 useMPS, 暂不支持
/// 模型精度
@objc public var paramPrecision: Precision = .Float32
@objc public init(device: MTLDevice, inParamPointer: UnsafeMutableRawPointer, inParamSize:Int, inModelPointer: UnsafeMutableRawPointer, inModelSize: Int) {
......
metal/paddle-mobile/paddle-mobile/Src/Common/Tools.swift
浏览文件 @ 6ff252ef
......@@ -25,3 +25,22 @@ func writeToLibrary<P: PrecisionProtocol>(fileName: String, array: [P]) {
fileHandler.closeFile()
}
public func writeToLibrary<P: PrecisionProtocol>(fileName: String, buffer: UnsafeBufferPointer<P>) {
let libraryPath = NSSearchPathForDirectoriesInDomains(.libraryDirectory, .userDomainMask, true).last ?! " library path get error "
let filePath = libraryPath + "/" + fileName
let fileManager = FileManager.init()
fileManager.createFile(atPath: filePath, contents: nil, attributes: nil)
let fileHandler = FileHandle.init(forWritingAtPath: filePath) ?! " file handler nil "
let data = Data.init(buffer: buffer)
fileHandler.write(data)
fileHandler.closeFile()
}
func createFile(fileName: String) -> String {
let libraryPath = NSSearchPathForDirectoriesInDomains(.libraryDirectory, .userDomainMask, true).last ?! " library path get error "
let filePath = libraryPath + "/" + fileName
let fileManager = FileManager.init()
fileManager.createFile(atPath: filePath, contents: nil, attributes: nil)
return filePath
}
metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/Base/Kernel.swift
浏览文件 @ 6ff252ef
......@@ -38,11 +38,21 @@ protocol KernelProtocol {
}
@objc open class Kernel: NSObject{
let pipline: MTLComputePipelineState
let functionName: String
public init(device: MTLDevice, inFunctionName: String, usePaddleMobileLib: Bool = false, initContext: InitContext) {
pipline = device.pipeLine(funcName: inFunctionName, metalLoadMode: initContext.metalLoadMode, metalLibPath: initContext.metalLibPath)
private var _pipline: MTLComputePipelineState? = nil
var pipline: MTLComputePipelineState {
get {
return _pipline ?! " pipeline can't be nil "
}
}
let functionName: String?
public init(device: MTLDevice, inFunctionName: String?, usePaddleMobileLib: Bool = false, initContext: InitContext) {
functionName = inFunctionName
if let funcName = inFunctionName {
_pipline = device.pipeLine(funcName: funcName, metalLoadMode: initContext.metalLoadMode, metalLibPath: initContext.metalLibPath)
}
}
}
......@@ -104,7 +114,7 @@ open class BufferToTextureKernel: Kernel {
@objc open class CusomKernel: Kernel {
public let outputTexture: MTLTexture
public init(device: MTLDevice, inFunctionName: String, outputDim: Shape, metalLoadModel: MetalLoadMode, metalLibPath: String?) {
public init(device: MTLDevice, inFunctionName: String?, outputDim: Shape, metalLoadModel: MetalLoadMode, metalLibPath: String?) {
let textureDesc = MTLTextureDescriptor.init()
textureDesc.textureType = .type2D
textureDesc.width = outputDim.width
......
metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/ConvAddKernel.swift
浏览文件 @ 6ff252ef
......@@ -145,7 +145,7 @@ class ConvAddKernel<P: PrecisionProtocol>: Kernel, Computable {
convDic[key] = conv
imageDic[identifyingKey + "_input"] = MPSImage.init(texture: param.input.metalTexture, featureChannels: param.input.tensorDim[1])
imageDic[identifyingKey + "_output"] = MPSImage.init(texture: param.output.metalTexture, featureChannels: param.output.tensorDim[1])
super.init(device: device, inFunctionName: "place_holder", initContext: initContext)
super.init(device: device, inFunctionName: nil, initContext: initContext)
return
}
}
......
metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/Scale.swift
浏览文件 @ 6ff252ef
......@@ -13,16 +13,24 @@
limitations under the License. */
import Foundation
import MetalPerformanceShaders
public class ScaleKernel: CusomKernel {
var lanczos: MPSImageLanczosScale!
public init(device: MTLDevice, shape: Shape, metalLoadMode: MetalLoadMode, metalLibPath: String?) {
lanczos = MPSImageLanczosScale(device: device)
if GlobalConfig.shared.computePrecision == .Float32 {
super.init(device: device, inFunctionName: "scale", outputDim: shape, metalLoadModel: metalLoadMode, metalLibPath: metalLibPath)
super.init(device: device, inFunctionName: nil, outputDim: shape, metalLoadModel: metalLoadMode, metalLibPath: metalLibPath)
} else if GlobalConfig.shared.computePrecision == .Float16 {
super.init(device: device, inFunctionName: "scale_half", outputDim: shape, metalLoadModel: metalLoadMode, metalLibPath: metalLibPath)
super.init(device: device, inFunctionName: nil, outputDim: shape, metalLoadModel: metalLoadMode, metalLibPath: metalLibPath)
} else {
fatalError(" unsupport ")
}
}
public override func compute(inputTexuture: MTLTexture, commandBuffer: MTLCommandBuffer) throws {
lanczos.encode(commandBuffer: commandBuffer, sourceTexture: inputTexuture, destinationTexture: outputTexture)
}
}
metal/paddle-mobile/paddle-mobile/Src/Operators/Kernels/Texture2DTo2DArrayKernel.swift
浏览文件 @ 6ff252ef
......@@ -23,15 +23,6 @@ struct Texture2DTo2DArrayParam {
}
class Texture2DTo2DArrayKernel<P: PrecisionProtocol>: Kernel, Computable{
func compute(commandBuffer: MTLCommandBuffer, param: FeedParam<P>) throws {
guard let encoder = commandBuffer.makeComputeCommandEncoder() else {
throw PaddleMobileError.predictError(message: " encode is nil")
}
encoder.setTexture(param.input.mtlTexture, index: 0)
encoder.setTexture(param.output.metalTexture, index: 1)
encoder.dispatch(computePipline: pipline, outTexture: param.input.mtlTexture)
encoder.endEncoding()
}
required init(device: MTLDevice, param: FeedParam<P>, initContext: InitContext) {
param.output.initTexture(device: device, inTranspose: [0, 2, 3, 1], computePrecision: GlobalConfig.shared.computePrecision)
......@@ -42,6 +33,15 @@ class Texture2DTo2DArrayKernel<P: PrecisionProtocol>: Kernel, Computable{
} else {
fatalError()
}
}
func compute(commandBuffer: MTLCommandBuffer, param: FeedParam<P>) throws {
guard let encoder = commandBuffer.makeComputeCommandEncoder() else {
throw PaddleMobileError.predictError(message: " encode is nil")
}
encoder.setTexture(param.input.mtlTexture, index: 0)
encoder.setTexture(param.output.metalTexture, index: 1)
encoder.dispatch(computePipline: pipline, outTexture: param.input.mtlTexture)
encoder.endEncoding()
}
}
src/framework/executor.cpp
浏览文件 @ 6ff252ef
......@@ -465,11 +465,12 @@ void Executor<Device, T>::FeedData(const Tensor &t) {
template <typename Device, typename T>
void Executor<Device, T>::FeedData(const std::vector<void *> &v) {
auto input_size = v.size();
auto vars = program_.scope->VarContain("feed");
int index = 0;
auto vars = program_.scope->VarContain("feed", &index);
PADDLE_MOBILE_ENFORCE(input_size == vars.size(),
"input data number not correct");
for (int i = 0; i < input_size; i++) {
auto var = vars[i];
auto var = program_.scope->Var("feed", i + index);
auto feed_tensor = var->template GetMutable<LoDTensor>();
feed_tensor->external_data = v[i];
}
......@@ -478,11 +479,12 @@ void Executor<Device, T>::FeedData(const std::vector<void *> &v) {
template <typename Device, typename T>
void Executor<Device, T>::FeedTensorData(const vector<framework::Tensor> &v) {
auto input_size = v.size();
auto vars = program_.scope->VarContain("feed");
int index = 0;
auto vars = program_.scope->VarContain("feed", &index);
PADDLE_MOBILE_ENFORCE(input_size == vars.size(),
"input data number not correct");
for (int i = 0; i < input_size; i++) {
auto var = vars[i];
auto var = program_.scope->Var("feed", i + index);
auto feed_tensor = var->template GetMutable<LoDTensor>();
feed_tensor->ShareDataWith(v[i]);
}
......@@ -492,12 +494,13 @@ template <typename Device, typename T>
void Executor<Device, T>::GetResults(std::vector<void *> *v) {
auto output_size = v->size();
PADDLE_MOBILE_ENFORCE(output_size > 0, "Empty output");
auto vars = program_.scope->VarContain("fetch");
int index = 0;
auto vars = program_.scope->VarContain("fetch", &index);
PADDLE_MOBILE_ENFORCE(output_size == vars.size(),
"output data number not correct");
for (int i = 0; i < output_size; i++) {
auto var = vars[i];
auto var = program_.scope->Var("fetch", i + index);
auto fetch_tensor = var->template GetMutable<LoDTensor>();
(*v)[i] = fetch_tensor->template data<float>();
}
......@@ -506,11 +509,11 @@ void Executor<Device, T>::GetResults(std::vector<void *> *v) {
template <typename Device, typename T>
void Executor<Device, T>::GetTensorResults(
std::vector<framework::Tensor *> *v) {
auto vars = program_.scope->VarContain("fetch");
int index = 0;
auto vars = program_.scope->VarContain("fetch", &index);
auto output_size = vars.size();
for (int i = 0; i < output_size; i++) {
auto var = vars[i];
auto var = program_.scope->Var("fetch", i + index);
auto fetch_tensor = var->template GetMutable<LoDTensor>();
v->push_back(fetch_tensor);
}
......
src/framework/scope.cpp
浏览文件 @ 6ff252ef
......@@ -116,18 +116,26 @@ Variable *Scope::Var(const std::string &name, const int id) {
return Var(name + std::to_string(id));
}
std::vector<Variable *> Scope::VarContain(const std::string substring) {
std::vector<Variable *> Scope::VarContain(const std::string substring,
int *min) {
std::vector<Variable *> v;
int temp = 9999;
auto len0 = substring.length();
for (auto pair : vars_) {
if (pair.first.find(substring) == 0) {
v.push_back(pair.second);
auto len1 = pair.first.length();
int index = std::stoi(pair.first.substr(len0, len1));
if (index < temp) {
temp = index;
}
}
}
*min = temp;
return v;
}
void Scope::InsertVar(const std::string str, Variable *var) {}
void Scope::print_vars() {
DLOG << "====================start to print variables=================";
for (auto pair : vars_) {
......
src/framework/scope.h
浏览文件 @ 6ff252ef
......@@ -85,8 +85,7 @@ class Scope {
#ifdef PADDLE_MOBILE_FPGA
Variable *Var(const std::string &name, const int id);
std::vector<Variable *> VarContain(const std::string substring);
void InsertVar(const std::string str, Variable *var);
std::vector<Variable *> VarContain(const std::string substring, int *min);
void print_vars();
#endif
......
src/io/api_paddle_mobile.cc
浏览文件 @ 6ff252ef
......@@ -171,18 +171,6 @@ void PaddleMobilePredictor<Device, T>::GetPaddleTensor(const std::string &name,
ConvertTensors(*t, output);
};
template <typename Device, typename T>
void PaddleMobilePredictor<Device, T>::FeedData(
const std::vector<void *> &inputs) {
paddle_mobile_->FeedData(inputs);
}
template <typename Device, typename T>
void PaddleMobilePredictor<Device, T>::GetResults(
std::vector<void *> *outputs) {
paddle_mobile_->GetResults(outputs);
}
template <typename Device, typename T>
void PaddleMobilePredictor<Device, T>::Predict_From_To(int start, int end) {
paddle_mobile_->Predict_From_To(start, end);
......
src/io/api_paddle_mobile.h
浏览文件 @ 6ff252ef
......@@ -32,8 +32,6 @@ class PaddleMobilePredictor : public PaddlePredictor {
std::vector<PaddleTensor>* output_data,
int batch_size = -1) override;
#ifdef PADDLE_MOBILE_FPGA
void FeedData(const std::vector<void*>& inputs) override;
void GetResults(std::vector<void*>* outputs) override;
void Predict_From_To(int start, int end) override;
void FeedPaddleTensors(const std::vector<PaddleTensor>& inputs) override;
void FetchPaddleTensors(std::vector<PaddleTensor>* outputs) override;
......
src/io/paddle_inference_api.h
浏览文件 @ 6ff252ef
......@@ -113,6 +113,7 @@ class PaddlePredictor {
// `inputs`. `inputs` should be available until Run returns. Caller should be
// responsible for the output tensor's buffer, either allocated or passed from
// outside.
virtual bool Run(const std::vector<PaddleTensor>& inputs,
std::vector<PaddleTensor>* output_data,
int batch_size = -1) = 0;
......@@ -126,8 +127,6 @@ class PaddlePredictor {
std::string param_file;
};
#ifdef PADDLE_MOBILE_FPGA
virtual void FeedData(const std::vector<void*>& inputs) = 0;
virtual void GetResults(std::vector<void*>* outputs) = 0;
virtual void Predict_From_To(int start, int end) = 0;
virtual void FeedPaddleTensors(const std::vector<PaddleTensor>& inputs) = 0;
virtual void FetchPaddleTensors(std::vector<PaddleTensor>* outputs) = 0;
......
test/fpga/test_rfcn_api.cpp
浏览文件 @ 6ff252ef
......@@ -55,8 +55,21 @@ PaddleMobileConfig GetConfig() {
return config;
}
PaddleMobileConfig GetConfig1() {
PaddleMobileConfig config;
config.precision = PaddleMobileConfig::FP32;
config.device = PaddleMobileConfig::kFPGA;
config.model_dir = "../models/resnet50";
config.thread_num = 1;
config.batch_size = 1;
config.optimize = true;
config.quantification = false;
return config;
}
int main() {
open_device();
PaddleMobileConfig config = GetConfig();
auto predictor =
CreatePaddlePredictor<PaddleMobileConfig,
......@@ -64,46 +77,22 @@ int main() {
std::cout << "Finishing loading model" << std::endl;
float img_info[3] = {768, 1536, 768.0f / 960.0f};
int img_length = 768 * 1536 * 3;
float img_info[3] = {432, 1280, 1.0f};
int img_length = 432 * 1280 * 3;
auto img = reinterpret_cast<float *>(fpga_malloc(img_length * sizeof(float)));
readStream(g_image, reinterpret_cast<char *>(img));
std::cout << "Finishing initializing data" << std::endl;
/*
predictor->FeedData({img_info, img});
predictor->Predict_From_To(0, -1);
std::cout << " Finishing predicting " << std::endl;
std::vector<void *> v(3, nullptr);
predictor->GetResults(&v);
int post_nms = 300;
for (int num = 0; num < post_nms; num ++){
for (int i = 0; i < 8; i ++){
std:: cout << ((float*)(v[0]))[num * 8 + i] << std::endl;
}
}
for (int num = 0; num < post_nms; num ++){
for (int i = 0; i < 8; i ++){
std:: cout << ((float*)(v[1]))[num * 8 + i] << std::endl;
}
}
for (int num = 0; num < post_nms; num ++){
for (int i = 0; i < 4; i ++){
std:: cout << ((float*)(v[2]))[num * 4 + i] << std::endl;
}
}
*/
struct PaddleTensor t_img_info, t_img;
t_img_info.dtype = FLOAT32;
t_img.dtypeid = typeid(float);
t_img_info.layout = LAYOUT_HWC;
t_img_info.shape = std::vector<int>({1, 3});
t_img_info.name = "Image information";
t_img_info.data.Reset(img_info, 3 * sizeof(float));
t_img.dtype = FLOAT32;
t_img.dtypeid = typeid(float);
t_img.layout = LAYOUT_HWC;
t_img.shape = std::vector<int>({1, 768, 1536, 3});
t_img.shape = std::vector<int>({1, 432, 1280, 3});
t_img.name = "Image information";
t_img.data.Reset(img, img_length * sizeof(float));
predictor->FeedPaddleTensors({t_img_info, t_img});
......@@ -116,6 +105,9 @@ int main() {
std::vector<PaddleTensor> v; // No need to initialize v
predictor->FetchPaddleTensors(&v); // Old data in v will be cleared
std::cout << "Output number is " << v.size() << std::endl;
std::cout << "out[0] length " << v[0].data.length() << std::endl;
std::cout << "out[1] length " << v[1].data.length() << std::endl;
std::cout << "out[2] length " << v[2].data.length() << std::endl;
auto post_nms = v[0].data.length() / sizeof(float) / 8;
for (int num = 0; num < post_nms; num++) {
......@@ -138,6 +130,8 @@ int main() {
}
std::cout << "Finish getting vector values" << std::endl;
////////////////////////////////////////////////////
PaddleTensor tensor;
predictor->GetPaddleTensor("fetch2", &tensor);
for (int i = 0; i < post_nms; i++) {
......@@ -145,5 +139,36 @@ int main() {
std::cout << p[+i] << std::endl;
}
//////////////////////////////////////////////////////
PaddleMobileConfig config1 = GetConfig1();
auto predictor1 =
CreatePaddlePredictor<PaddleMobileConfig,
PaddleEngineKind::kPaddleMobile>(config1);
std::cout << "Finishing loading model" << std::endl;
int img_length1 = 224 * 224 * 3;
auto img1 =
reinterpret_cast<float *>(fpga_malloc(img_length1 * sizeof(float)));
std::cout << "Finishing initializing data" << std::endl;
struct PaddleTensor t_img1;
t_img1.dtypeid = typeid(float);
t_img1.layout = LAYOUT_HWC;
t_img1.shape = std::vector<int>({1, 224, 224, 3});
t_img1.name = "Image information";
t_img1.data.Reset(img1, img_length1 * sizeof(float));
predictor1->FeedPaddleTensors({t_img1});
predictor1->Predict_From_To(0, -1);
std::cout << "Finishing predicting " << std::endl;
std::vector<PaddleTensor> v1; // No need to initialize v
predictor1->FetchPaddleTensors(&v1); // Old data in v will be cleared
std::cout << "Output number is " << v1.size() << std::endl;
std::cout << "out[0] length " << v1[0].data.length() << std::endl;
return 0;
}
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