未验证 提交 1c263e04 编写于 作者: S smilejames 提交者: GitHub

Merge pull request #760 from codeWorm2015/develop

fix #759   merge metal version paddle mobile
......@@ -70,10 +70,17 @@ build
cmake-build-debug
cmake-build-release
#ios demo
demo/ios/PaddleMobileDemo/PaddleMobileDemo/googlenet_combine/
demo/ios/PaddleMobileDemo/PaddleMobileDemo/*.jpg
demo/ios/PaddleMobileDemo/PaddleMobileDemo/PaddleMobile/*.a
*.xcuserstate
/tools/quantification/quantify
# metal
Podfile.lock
metal/Pods/
SwiftProtobuf.framework
paddle-mobile.xcworkspace
metal/models/
metal/images/
platform :ios, 9.0
use_frameworks!
workspace 'paddle-mobile.xcworkspace'
target 'paddle-mobile-demo' do
project 'paddle-mobile-demo/paddle-mobile-demo.xcodeproj'
pod 'SwiftProtobuf', '~> 1.0'
end
target 'paddle-mobile' do
project 'paddle-mobile/paddle-mobile.xcodeproj'
pod 'SwiftProtobuf', '~> 1.0'
end
target 'paddle-mobile-unit-test' do
project 'paddle-mobile-unit-test/paddle-mobile-unit-test.xcodeproj'
pod 'SwiftProtobuf', '~> 1.0'
end
<?xml version="1.0" encoding="UTF-8"?>
<Workspace
version = "1.0">
<FileRef
location = "self:paddle-mobile-demo.xcodeproj">
</FileRef>
</Workspace>
<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
<plist version="1.0">
<dict>
<key>IDEDidComputeMac32BitWarning</key>
<true/>
</dict>
</plist>
<?xml version="1.0" encoding="UTF-8"?>
<Scheme
LastUpgradeVersion = "0940"
version = "1.3">
<BuildAction
parallelizeBuildables = "YES"
buildImplicitDependencies = "YES">
<BuildActionEntries>
<BuildActionEntry
buildForTesting = "YES"
buildForRunning = "YES"
buildForProfiling = "YES"
buildForArchiving = "YES"
buildForAnalyzing = "YES">
<BuildableReference
BuildableIdentifier = "primary"
BlueprintIdentifier = "FC039B7D20E11C550081E9F8"
BuildableName = "paddle-mobile-demo.app"
BlueprintName = "paddle-mobile-demo"
ReferencedContainer = "container:paddle-mobile-demo.xcodeproj">
</BuildableReference>
</BuildActionEntry>
</BuildActionEntries>
</BuildAction>
<TestAction
buildConfiguration = "Debug"
selectedDebuggerIdentifier = "Xcode.DebuggerFoundation.Debugger.LLDB"
selectedLauncherIdentifier = "Xcode.DebuggerFoundation.Launcher.LLDB"
shouldUseLaunchSchemeArgsEnv = "YES">
<Testables>
</Testables>
<MacroExpansion>
<BuildableReference
BuildableIdentifier = "primary"
BlueprintIdentifier = "FC039B7D20E11C550081E9F8"
BuildableName = "paddle-mobile-demo.app"
BlueprintName = "paddle-mobile-demo"
ReferencedContainer = "container:paddle-mobile-demo.xcodeproj">
</BuildableReference>
</MacroExpansion>
<AdditionalOptions>
</AdditionalOptions>
</TestAction>
<LaunchAction
buildConfiguration = "Debug"
selectedDebuggerIdentifier = "Xcode.DebuggerFoundation.Debugger.LLDB"
selectedLauncherIdentifier = "Xcode.DebuggerFoundation.Launcher.LLDB"
launchStyle = "0"
useCustomWorkingDirectory = "NO"
ignoresPersistentStateOnLaunch = "NO"
debugDocumentVersioning = "YES"
debugServiceExtension = "internal"
allowLocationSimulation = "YES">
<BuildableProductRunnable
runnableDebuggingMode = "0">
<BuildableReference
BuildableIdentifier = "primary"
BlueprintIdentifier = "FC039B7D20E11C550081E9F8"
BuildableName = "paddle-mobile-demo.app"
BlueprintName = "paddle-mobile-demo"
ReferencedContainer = "container:paddle-mobile-demo.xcodeproj">
</BuildableReference>
</BuildableProductRunnable>
<AdditionalOptions>
</AdditionalOptions>
</LaunchAction>
<ProfileAction
buildConfiguration = "Release"
shouldUseLaunchSchemeArgsEnv = "YES"
savedToolIdentifier = ""
useCustomWorkingDirectory = "NO"
debugDocumentVersioning = "YES">
<BuildableProductRunnable
runnableDebuggingMode = "0">
<BuildableReference
BuildableIdentifier = "primary"
BlueprintIdentifier = "FC039B7D20E11C550081E9F8"
BuildableName = "paddle-mobile-demo.app"
BlueprintName = "paddle-mobile-demo"
ReferencedContainer = "container:paddle-mobile-demo.xcodeproj">
</BuildableReference>
</BuildableProductRunnable>
</ProfileAction>
<AnalyzeAction
buildConfiguration = "Debug">
</AnalyzeAction>
<ArchiveAction
buildConfiguration = "Release"
revealArchiveInOrganizer = "YES">
</ArchiveAction>
</Scheme>
<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
<plist version="1.0">
<dict>
<key>SchemeUserState</key>
<dict>
<key>paddle-mobile-demo.xcscheme</key>
<dict>
<key>orderHint</key>
<integer>2</integer>
</dict>
</dict>
<key>SuppressBuildableAutocreation</key>
<dict>
<key>FC039B7D20E11C550081E9F8</key>
<dict>
<key>primary</key>
<true/>
</dict>
</dict>
</dict>
</plist>
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
import UIKit
@UIApplicationMain
class AppDelegate: UIResponder, UIApplicationDelegate {
var window: UIWindow?
func application(_ application: UIApplication, didFinishLaunchingWithOptions launchOptions: [UIApplicationLaunchOptionsKey: Any]?) -> Bool {
// Override point for customization after application launch.
return true
}
func applicationWillResignActive(_ application: UIApplication) {
// Sent when the application is about to move from active to inactive state. This can occur for certain types of temporary interruptions (such as an incoming phone call or SMS message) or when the user quits the application and it begins the transition to the background state.
// Use this method to pause ongoing tasks, disable timers, and invalidate graphics rendering callbacks. Games should use this method to pause the game.
}
func applicationDidEnterBackground(_ application: UIApplication) {
// Use this method to release shared resources, save user data, invalidate timers, and store enough application state information to restore your application to its current state in case it is terminated later.
// If your application supports background execution, this method is called instead of applicationWillTerminate: when the user quits.
}
func applicationWillEnterForeground(_ application: UIApplication) {
// Called as part of the transition from the background to the active state; here you can undo many of the changes made on entering the background.
}
func applicationDidBecomeActive(_ application: UIApplication) {
// Restart any tasks that were paused (or not yet started) while the application was inactive. If the application was previously in the background, optionally refresh the user interface.
}
func applicationWillTerminate(_ application: UIApplication) {
// Called when the application is about to terminate. Save data if appropriate. See also applicationDidEnterBackground:.
}
}
{
"images" : [
{
"idiom" : "iphone",
"size" : "20x20",
"scale" : "2x"
},
{
"idiom" : "iphone",
"size" : "20x20",
"scale" : "3x"
},
{
"idiom" : "iphone",
"size" : "29x29",
"scale" : "2x"
},
{
"idiom" : "iphone",
"size" : "29x29",
"scale" : "3x"
},
{
"idiom" : "iphone",
"size" : "40x40",
"scale" : "2x"
},
{
"idiom" : "iphone",
"size" : "40x40",
"scale" : "3x"
},
{
"idiom" : "iphone",
"size" : "60x60",
"scale" : "2x"
},
{
"idiom" : "iphone",
"size" : "60x60",
"scale" : "3x"
},
{
"idiom" : "ipad",
"size" : "20x20",
"scale" : "1x"
},
{
"idiom" : "ipad",
"size" : "20x20",
"scale" : "2x"
},
{
"idiom" : "ipad",
"size" : "29x29",
"scale" : "1x"
},
{
"idiom" : "ipad",
"size" : "29x29",
"scale" : "2x"
},
{
"idiom" : "ipad",
"size" : "40x40",
"scale" : "1x"
},
{
"idiom" : "ipad",
"size" : "40x40",
"scale" : "2x"
},
{
"idiom" : "ipad",
"size" : "76x76",
"scale" : "1x"
},
{
"idiom" : "ipad",
"size" : "76x76",
"scale" : "2x"
},
{
"idiom" : "ipad",
"size" : "83.5x83.5",
"scale" : "2x"
},
{
"idiom" : "ios-marketing",
"size" : "1024x1024",
"scale" : "1x"
}
],
"info" : {
"version" : 1,
"author" : "xcode"
}
}
\ No newline at end of file
{
"info" : {
"version" : 1,
"author" : "xcode"
}
}
\ No newline at end of file
<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<document type="com.apple.InterfaceBuilder3.CocoaTouch.Storyboard.XIB" version="3.0" toolsVersion="13122.16" systemVersion="17A277" targetRuntime="iOS.CocoaTouch" propertyAccessControl="none" useAutolayout="YES" launchScreen="YES" useTraitCollections="YES" useSafeAreas="YES" colorMatched="YES" initialViewController="01J-lp-oVM">
<dependencies>
<plugIn identifier="com.apple.InterfaceBuilder.IBCocoaTouchPlugin" version="13104.12"/>
<capability name="Safe area layout guides" minToolsVersion="9.0"/>
<capability name="documents saved in the Xcode 8 format" minToolsVersion="8.0"/>
</dependencies>
<scenes>
<!--View Controller-->
<scene sceneID="EHf-IW-A2E">
<objects>
<viewController id="01J-lp-oVM" sceneMemberID="viewController">
<view key="view" contentMode="scaleToFill" id="Ze5-6b-2t3">
<rect key="frame" x="0.0" y="0.0" width="375" height="667"/>
<autoresizingMask key="autoresizingMask" widthSizable="YES" heightSizable="YES"/>
<color key="backgroundColor" red="1" green="1" blue="1" alpha="1" colorSpace="custom" customColorSpace="sRGB"/>
<viewLayoutGuide key="safeArea" id="6Tk-OE-BBY"/>
</view>
</viewController>
<placeholder placeholderIdentifier="IBFirstResponder" id="iYj-Kq-Ea1" userLabel="First Responder" sceneMemberID="firstResponder"/>
</objects>
<point key="canvasLocation" x="53" y="375"/>
</scene>
</scenes>
</document>
<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
<plist version="1.0">
<dict>
<key>CFBundleDevelopmentRegion</key>
<string>$(DEVELOPMENT_LANGUAGE)</string>
<key>CFBundleExecutable</key>
<string>$(EXECUTABLE_NAME)</string>
<key>CFBundleIdentifier</key>
<string>$(PRODUCT_BUNDLE_IDENTIFIER)</string>
<key>CFBundleInfoDictionaryVersion</key>
<string>6.0</string>
<key>CFBundleName</key>
<string>$(PRODUCT_NAME)</string>
<key>CFBundlePackageType</key>
<string>APPL</string>
<key>CFBundleShortVersionString</key>
<string>1.0</string>
<key>CFBundleVersion</key>
<string>1</string>
<key>LSRequiresIPhoneOS</key>
<true/>
<key>NSCameraUsageDescription</key>
<string>use camera</string>
<key>NSPhotoLibraryUsageDescription</key>
<string>use album</string>
<key>UILaunchStoryboardName</key>
<string>LaunchScreen</string>
<key>UIMainStoryboardFile</key>
<string>Main</string>
<key>UIRequiredDeviceCapabilities</key>
<array>
<string>armv7</string>
</array>
<key>UISupportedInterfaceOrientations</key>
<array>
<string>UIInterfaceOrientationPortrait</string>
</array>
<key>UISupportedInterfaceOrientations~ipad</key>
<array>
<string>UIInterfaceOrientationPortrait</string>
<string>UIInterfaceOrientationPortraitUpsideDown</string>
<string>UIInterfaceOrientationLandscapeLeft</string>
<string>UIInterfaceOrientationLandscapeRight</string>
</array>
</dict>
</plist>
//
// MetalHelper.swift
// paddle-mobile-demo
//
// Created by liuRuiLong on 2018/7/25.
// Copyright © 2018年 orange. All rights reserved.
//
import Metal
import MetalKit
import Foundation
import paddle_mobile
import MetalPerformanceShaders
class MetalHelper {
let device: MTLDevice
let queue: MTLCommandQueue
let textureLoader: MTKTextureLoader
static let shared: MetalHelper = MetalHelper.init()
private init(){
device = MTLCreateSystemDefaultDevice()!
queue = device.makeCommandQueue()!
textureLoader = MTKTextureLoader.init(device: device)
}
static func scaleTexture(queue: MTLCommandQueue, input: MTLTexture, size:(width: Int, height: Int), complete: @escaping (MTLTexture) -> Void) {
let tmpTextureDes = MTLTextureDescriptor.init()
tmpTextureDes.width = size.width
tmpTextureDes.height = size.height
tmpTextureDes.depth = 1
tmpTextureDes.usage = [.shaderRead, .shaderWrite]
tmpTextureDes.pixelFormat = .rgba32Float
tmpTextureDes.textureType = .type2D
tmpTextureDes.storageMode = .shared
tmpTextureDes.cpuCacheMode = .defaultCache
let dest = MetalHelper.shared.device.makeTexture(descriptor: tmpTextureDes)
let scale = MPSImageLanczosScale.init(device: MetalHelper.shared.device)
let buffer = queue.makeCommandBuffer()
scale.encode(commandBuffer: buffer!, sourceTexture: input, destinationTexture: dest!)
buffer?.addCompletedHandler({ (buffer) in
complete(dest!)
})
buffer?.commit()
}
}
//
// ModelHelper.swift
// paddle-mobile-demo
//
// Created by liuRuiLong on 2018/8/10.
// Copyright © 2018年 orange. All rights reserved.
//
import UIKit
import MetalKit
import Foundation
import paddle_mobile
import MetalPerformanceShaders
class PreProccess: CusomKernel {
init(device: MTLDevice) {
let s = CusomKernel.Shape.init(inWidth: 224, inHeight: 224, inChannel: 3)
super.init(device: device, inFunctionName: "preprocess", outputDim: s, usePaddleMobileLib: false)
}
}
let modelHelperMap: [SupportModel : ModelHelper] = [.mobilenet : MobileNetHelper.init()]
enum SupportModel: String{
case mobilenet = "mobilenet"
static func supportedModels() -> [SupportModel] {
return [.mobilenet]
}
}
protocol ModelHelper {
var dim: [Int] { get }
var modelPath: String { get }
var paramPath: String { get }
var modelDir: String { get }
var preprocessKernel: CusomKernel { get }
func getTexture(image: CGImage, getTexture: @escaping (MTLTexture) -> Void)
func resultStr(res: [Float]) -> String
}
extension ModelHelper {
func getTexture(image: CGImage, getTexture: @escaping (MTLTexture) -> Void) {
let texture = try? MetalHelper.shared.textureLoader.newTexture(cgImage: image, options: [:]) ?! " texture loader error"
MetalHelper.scaleTexture(queue: MetalHelper.shared.queue, input: texture!, size: (224, 224)) { (resTexture) in
getTexture(resTexture)
}
}
}
struct MobileNetHelper: ModelHelper{
class PreWords {
var contents: [String] = []
init(fileName: String, type: String = "txt", inBundle: Bundle = Bundle.main) {
if let filePath = inBundle.path(forResource: fileName, ofType: type) {
let string = try! String.init(contentsOfFile: filePath)
contents = string.components(separatedBy: CharacterSet.newlines).filter{$0.count > 10}.map{
String($0[$0.index($0.startIndex, offsetBy: 10)...])
}
}else{
fatalError("no file call \(fileName)")
}
}
subscript(index: Int) -> String{
return contents[index]
}
}
let labels = PreWords.init(fileName: "synset")
func resultStr(res: [Float]) -> String {
var s: [String] = []
res.top(r: 5).enumerated().forEach{
s.append(String(format: "%d: %@ (%3.2f%%)", $0 + 1, labels[$1.0], $1.1 * 100))
}
return s.joined(separator: "\n")
}
var preprocessKernel: CusomKernel
let dim = [1, 224, 224, 3]
let modelPath: String
let paramPath: String
let modelDir: String
init() {
modelPath = Bundle.main.path(forResource: "model", ofType: nil) ?! "model null"
paramPath = Bundle.main.path(forResource: "params", ofType: nil) ?! "para null"
modelDir = ""
preprocessKernel = PreProccess.init(device: MetalHelper.shared.device)
}
}
//
// PreProcessKernel.metal
// paddle-mobile-demo
//
// Created by liuRuiLong on 2018/7/20.
// Copyright © 2018年 orange. All rights reserved.
//
#include <metal_stdlib>
using namespace metal;
kernel void preprocess(
texture2d<float, access::read> inTexture [[texture(0)]],
texture2d<float, access::write> outTexture [[texture(1)]],
uint2 gid [[thread_position_in_grid]])
{
if (gid.x >= outTexture.get_width() ||
gid.y >= outTexture.get_height()) {
return;
}
const auto means = float4(123.68f, 116.78f, 103.94f, 0.0f);
const float4 inColor = (inTexture.read(gid) * 255.0 - means) * 0.017;
outTexture.write(float4(inColor.z, inColor.y, inColor.x, 0.0f), gid);
}
kernel void preprocess_half(
texture2d<half, access::read> inTexture [[texture(0)]],
texture2d<half, access::write> outTexture [[texture(1)]],
uint2 gid [[thread_position_in_grid]])
{
if (gid.x >= outTexture.get_width() ||
gid.y >= outTexture.get_height()) {
return;
}
const auto means = half4(123.68f, 116.78f, 103.94f, 0.0f);
const half4 inColor = (inTexture.read(gid) * 255.0 - means) * 0.017;
outTexture.write(half4(inColor.z, inColor.y, inColor.x, 0.0f), gid);
}
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
import UIKit
import MetalKit
import paddle_mobile
import MetalPerformanceShaders
let threadSupport = [1]
class ViewController: UIViewController {
@IBOutlet weak var resultTextView: UITextView!
@IBOutlet weak var selectImageView: UIImageView!
@IBOutlet weak var elapsedTimeLabel: UILabel!
@IBOutlet weak var modelPickerView: UIPickerView!
@IBOutlet weak var threadPickerView: UIPickerView!
var selectImage: UIImage?
var program: Program?
var executor: Executor<Float32>?
var modelType: SupportModel = .mobilenet
var toPredictTexture: MTLTexture?
var modelHelper: ModelHelper {
return modelHelperMap[modelType] ?! " has no this type "
}
var threadNum = 1
@IBAction func loadAct(_ sender: Any) {
let inModelHelper = modelHelper
let queue = MetalHelper.shared.queue
let loader = Loader<Float32>.init()
do {
let modelPath = inModelHelper.modelPath
let paraPath = inModelHelper.paramPath
program = try loader.load(device: MetalHelper.shared.device, modelPath: modelPath, paraPath: paraPath)
executor = try Executor<Float32>.init(inDevice: MetalHelper.shared.device, inQueue: queue, inProgram: program!)
} catch let error {
print(error)
}
}
@IBAction func selectImageAct(_ sender: Any) {
let imagePicker = UIImagePickerController()
imagePicker.sourceType = .camera
imagePicker.delegate = self
self.present(imagePicker, animated: true, completion: nil)
}
@IBAction func clearAct(_ sender: Any) {
executor?.clear()
program = nil
executor = nil
}
@IBAction func predictAct(_ sender: Any) {
guard let inTexture = toPredictTexture else {
resultTextView.text = "请选择图片 ! "
return
}
guard let inExecutor = executor else {
resultTextView.text = "请先 load ! "
return
}
do {
let max = 100
var startDate = Date.init()
for i in 0..<max {
try inExecutor.predict(input: inTexture, expect: modelHelper.dim, completionHandle: { [weak self] (result) in
guard let sSelf = self else {
fatalError()
}
if i == (max / 2 - 1) {
startDate = Date.init()
}
if i == max - 1 {
let time = Date.init().timeIntervalSince(startDate)
DispatchQueue.main.async {
sSelf.resultTextView.text = sSelf.modelHelper.resultStr(res: result.resultArr)
sSelf.elapsedTimeLabel.text = "平均耗时: \(time/Double(max/2) * 1000.0) ms"
}
}
}, preProcessKernle: self.modelHelper.preprocessKernel)
}
} catch let error {
print(error)
}
}
override func viewDidLoad() {
super.viewDidLoad()
modelPickerView.delegate = self
modelPickerView.dataSource = self
threadPickerView.delegate = self
threadPickerView.dataSource = self
selectImage = UIImage.init(named: "banana.jpeg")
selectImageView.image = selectImage
modelHelper.getTexture(image: selectImage!.cgImage!) {[weak self] (texture) in
self?.toPredictTexture = texture
}
}
}
extension ViewController: UIPickerViewDataSource, UIPickerViewDelegate{
func numberOfComponents(in pickerView: UIPickerView) -> Int {
if pickerView == modelPickerView {
return 1
} else if pickerView == threadPickerView {
return 1
} else {
fatalError()
}
}
func pickerView(_ pickerView: UIPickerView, numberOfRowsInComponent component: Int) -> Int {
if pickerView == modelPickerView {
return SupportModel.supportedModels().count
} else if pickerView == threadPickerView {
return threadSupport.count
} else {
fatalError()
}
}
public func pickerView(_ pickerView: UIPickerView, titleForRow row: Int, forComponent component: Int) -> String? {
if pickerView == modelPickerView {
return SupportModel.supportedModels()[row].rawValue
} else if pickerView == threadPickerView {
return "\(threadSupport[row])"
} else {
fatalError()
}
}
public func pickerView(_ pickerView: UIPickerView, didSelectRow row: Int, inComponent component: Int) {
if pickerView == modelPickerView {
self.modelType = SupportModel.supportedModels()[row]
} else if pickerView == threadPickerView {
self.threadNum = threadSupport[row]
} else {
fatalError()
}
}
}
extension ViewController: UIImagePickerControllerDelegate, UINavigationControllerDelegate {
func imagePickerController(_ picker: UIImagePickerController, didFinishPickingMediaWithInfo info: [String : Any]) {
picker.dismiss(animated: true){[weak self] in
guard let sSelf = self, let image = info["UIImagePickerControllerOriginalImage"] as? UIImage else{
fatalError("no image")
}
sSelf.selectImage = image
sSelf.selectImageView.image = image
sSelf.modelHelper.getTexture(image: image.cgImage!, getTexture: { (texture) in
sSelf.toPredictTexture = texture
})
}
}
}
<?xml version="1.0" encoding="UTF-8"?>
<Workspace
version = "1.0">
<FileRef
location = "self:paddle-mobile-unit-test.xcodeproj">
</FileRef>
</Workspace>
<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
<plist version="1.0">
<dict>
<key>IDEDidComputeMac32BitWarning</key>
<true/>
</dict>
</plist>
<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
<plist version="1.0">
<dict>
<key>SchemeUserState</key>
<dict>
<key>paddle-mobile-unit-test.xcscheme</key>
<dict>
<key>orderHint</key>
<integer>6</integer>
</dict>
</dict>
</dict>
</plist>
//
// AppDelegate.swift
// paddle-mobile-unit-test
//
// Created by liuRuiLong on 2018/8/10.
// Copyright © 2018年 orange. All rights reserved.
//
import UIKit
@UIApplicationMain
class AppDelegate: UIResponder, UIApplicationDelegate {
var window: UIWindow?
func application(_ application: UIApplication, didFinishLaunchingWithOptions launchOptions: [UIApplicationLaunchOptionsKey: Any]?) -> Bool {
// Override point for customization after application launch.
return true
}
func applicationWillResignActive(_ application: UIApplication) {
// Sent when the application is about to move from active to inactive state. This can occur for certain types of temporary interruptions (such as an incoming phone call or SMS message) or when the user quits the application and it begins the transition to the background state.
// Use this method to pause ongoing tasks, disable timers, and invalidate graphics rendering callbacks. Games should use this method to pause the game.
}
func applicationDidEnterBackground(_ application: UIApplication) {
// Use this method to release shared resources, save user data, invalidate timers, and store enough application state information to restore your application to its current state in case it is terminated later.
// If your application supports background execution, this method is called instead of applicationWillTerminate: when the user quits.
}
func applicationWillEnterForeground(_ application: UIApplication) {
// Called as part of the transition from the background to the active state; here you can undo many of the changes made on entering the background.
}
func applicationDidBecomeActive(_ application: UIApplication) {
// Restart any tasks that were paused (or not yet started) while the application was inactive. If the application was previously in the background, optionally refresh the user interface.
}
func applicationWillTerminate(_ application: UIApplication) {
// Called when the application is about to terminate. Save data if appropriate. See also applicationDidEnterBackground:.
}
}
{
"images" : [
{
"idiom" : "iphone",
"size" : "20x20",
"scale" : "2x"
},
{
"idiom" : "iphone",
"size" : "20x20",
"scale" : "3x"
},
{
"idiom" : "iphone",
"size" : "29x29",
"scale" : "2x"
},
{
"idiom" : "iphone",
"size" : "29x29",
"scale" : "3x"
},
{
"idiom" : "iphone",
"size" : "40x40",
"scale" : "2x"
},
{
"idiom" : "iphone",
"size" : "40x40",
"scale" : "3x"
},
{
"idiom" : "iphone",
"size" : "60x60",
"scale" : "2x"
},
{
"idiom" : "iphone",
"size" : "60x60",
"scale" : "3x"
},
{
"idiom" : "ipad",
"size" : "20x20",
"scale" : "1x"
},
{
"idiom" : "ipad",
"size" : "20x20",
"scale" : "2x"
},
{
"idiom" : "ipad",
"size" : "29x29",
"scale" : "1x"
},
{
"idiom" : "ipad",
"size" : "29x29",
"scale" : "2x"
},
{
"idiom" : "ipad",
"size" : "40x40",
"scale" : "1x"
},
{
"idiom" : "ipad",
"size" : "40x40",
"scale" : "2x"
},
{
"idiom" : "ipad",
"size" : "76x76",
"scale" : "1x"
},
{
"idiom" : "ipad",
"size" : "76x76",
"scale" : "2x"
},
{
"idiom" : "ipad",
"size" : "83.5x83.5",
"scale" : "2x"
},
{
"idiom" : "ios-marketing",
"size" : "1024x1024",
"scale" : "1x"
}
],
"info" : {
"version" : 1,
"author" : "xcode"
}
}
\ No newline at end of file
{
"info" : {
"version" : 1,
"author" : "xcode"
}
}
\ No newline at end of file
<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<document type="com.apple.InterfaceBuilder3.CocoaTouch.Storyboard.XIB" version="3.0" toolsVersion="13122.16" systemVersion="17A277" targetRuntime="iOS.CocoaTouch" propertyAccessControl="none" useAutolayout="YES" launchScreen="YES" useTraitCollections="YES" useSafeAreas="YES" colorMatched="YES" initialViewController="01J-lp-oVM">
<dependencies>
<plugIn identifier="com.apple.InterfaceBuilder.IBCocoaTouchPlugin" version="13104.12"/>
<capability name="Safe area layout guides" minToolsVersion="9.0"/>
<capability name="documents saved in the Xcode 8 format" minToolsVersion="8.0"/>
</dependencies>
<scenes>
<!--View Controller-->
<scene sceneID="EHf-IW-A2E">
<objects>
<viewController id="01J-lp-oVM" sceneMemberID="viewController">
<view key="view" contentMode="scaleToFill" id="Ze5-6b-2t3">
<rect key="frame" x="0.0" y="0.0" width="375" height="667"/>
<autoresizingMask key="autoresizingMask" widthSizable="YES" heightSizable="YES"/>
<color key="backgroundColor" red="1" green="1" blue="1" alpha="1" colorSpace="custom" customColorSpace="sRGB"/>
<viewLayoutGuide key="safeArea" id="6Tk-OE-BBY"/>
</view>
</viewController>
<placeholder placeholderIdentifier="IBFirstResponder" id="iYj-Kq-Ea1" userLabel="First Responder" sceneMemberID="firstResponder"/>
</objects>
<point key="canvasLocation" x="53" y="375"/>
</scene>
</scenes>
</document>
<?xml version="1.0" encoding="UTF-8"?>
<document type="com.apple.InterfaceBuilder3.CocoaTouch.Storyboard.XIB" version="3.0" toolsVersion="13122.16" systemVersion="17A277" targetRuntime="iOS.CocoaTouch" propertyAccessControl="none" useAutolayout="YES" useTraitCollections="YES" useSafeAreas="YES" colorMatched="YES" initialViewController="BYZ-38-t0r">
<dependencies>
<plugIn identifier="com.apple.InterfaceBuilder.IBCocoaTouchPlugin" version="13104.12"/>
<capability name="Safe area layout guides" minToolsVersion="9.0"/>
<capability name="documents saved in the Xcode 8 format" minToolsVersion="8.0"/>
</dependencies>
<scenes>
<!--View Controller-->
<scene sceneID="tne-QT-ifu">
<objects>
<viewController id="BYZ-38-t0r" customClass="ViewController" customModuleProvider="target" sceneMemberID="viewController">
<view key="view" contentMode="scaleToFill" id="8bC-Xf-vdC">
<rect key="frame" x="0.0" y="0.0" width="375" height="667"/>
<autoresizingMask key="autoresizingMask" widthSizable="YES" heightSizable="YES"/>
<color key="backgroundColor" red="1" green="1" blue="1" alpha="1" colorSpace="custom" customColorSpace="sRGB"/>
<viewLayoutGuide key="safeArea" id="6Tk-OE-BBY"/>
</view>
</viewController>
<placeholder placeholderIdentifier="IBFirstResponder" id="dkx-z0-nzr" sceneMemberID="firstResponder"/>
</objects>
</scene>
</scenes>
</document>
<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
<plist version="1.0">
<dict>
<key>CFBundleDevelopmentRegion</key>
<string>$(DEVELOPMENT_LANGUAGE)</string>
<key>CFBundleExecutable</key>
<string>$(EXECUTABLE_NAME)</string>
<key>CFBundleIdentifier</key>
<string>$(PRODUCT_BUNDLE_IDENTIFIER)</string>
<key>CFBundleInfoDictionaryVersion</key>
<string>6.0</string>
<key>CFBundleName</key>
<string>$(PRODUCT_NAME)</string>
<key>CFBundlePackageType</key>
<string>APPL</string>
<key>CFBundleShortVersionString</key>
<string>1.0</string>
<key>CFBundleVersion</key>
<string>1</string>
<key>LSRequiresIPhoneOS</key>
<true/>
<key>UILaunchStoryboardName</key>
<string>LaunchScreen</string>
<key>UIMainStoryboardFile</key>
<string>Main</string>
<key>UIRequiredDeviceCapabilities</key>
<array>
<string>armv7</string>
</array>
<key>UISupportedInterfaceOrientations</key>
<array>
<string>UIInterfaceOrientationPortrait</string>
<string>UIInterfaceOrientationLandscapeLeft</string>
<string>UIInterfaceOrientationLandscapeRight</string>
</array>
<key>UISupportedInterfaceOrientations~ipad</key>
<array>
<string>UIInterfaceOrientationPortrait</string>
<string>UIInterfaceOrientationPortraitUpsideDown</string>
<string>UIInterfaceOrientationLandscapeLeft</string>
<string>UIInterfaceOrientationLandscapeRight</string>
</array>
</dict>
</plist>
//
// ViewController.swift
// paddle-mobile-unit-test
//
// Created by liuRuiLong on 2018/8/10.
// Copyright © 2018年 orange. All rights reserved.
//
import UIKit
import paddle_mobile
class ViewController: UIViewController {
override func viewDidLoad() {
super.viewDidLoad()
print(" done ")
}
}
<?xml version="1.0" encoding="UTF-8"?>
<Workspace
version = "1.0">
<FileRef
location = "self:paddle-mobile.xcodeproj">
</FileRef>
</Workspace>
<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
<plist version="1.0">
<dict>
<key>IDEDidComputeMac32BitWarning</key>
<true/>
</dict>
</plist>
<?xml version="1.0" encoding="UTF-8"?>
<Scheme
LastUpgradeVersion = "0940"
version = "1.3">
<BuildAction
parallelizeBuildables = "YES"
buildImplicitDependencies = "YES">
<BuildActionEntries>
<BuildActionEntry
buildForTesting = "YES"
buildForRunning = "YES"
buildForProfiling = "YES"
buildForArchiving = "YES"
buildForAnalyzing = "YES">
<BuildableReference
BuildableIdentifier = "primary"
BlueprintIdentifier = "FC039B6920E11C3C0081E9F8"
BuildableName = "paddle_mobile.framework"
BlueprintName = "paddle-mobile"
ReferencedContainer = "container:paddle-mobile.xcodeproj">
</BuildableReference>
</BuildActionEntry>
</BuildActionEntries>
</BuildAction>
<TestAction
buildConfiguration = "Debug"
selectedDebuggerIdentifier = "Xcode.DebuggerFoundation.Debugger.LLDB"
selectedLauncherIdentifier = "Xcode.DebuggerFoundation.Launcher.LLDB"
shouldUseLaunchSchemeArgsEnv = "YES">
<Testables>
</Testables>
<AdditionalOptions>
</AdditionalOptions>
</TestAction>
<LaunchAction
buildConfiguration = "Debug"
selectedDebuggerIdentifier = "Xcode.DebuggerFoundation.Debugger.LLDB"
selectedLauncherIdentifier = "Xcode.DebuggerFoundation.Launcher.LLDB"
launchStyle = "0"
useCustomWorkingDirectory = "NO"
ignoresPersistentStateOnLaunch = "NO"
debugDocumentVersioning = "YES"
debugServiceExtension = "internal"
allowLocationSimulation = "YES">
<MacroExpansion>
<BuildableReference
BuildableIdentifier = "primary"
BlueprintIdentifier = "FC039B6920E11C3C0081E9F8"
BuildableName = "paddle_mobile.framework"
BlueprintName = "paddle-mobile"
ReferencedContainer = "container:paddle-mobile.xcodeproj">
</BuildableReference>
</MacroExpansion>
<AdditionalOptions>
</AdditionalOptions>
</LaunchAction>
<ProfileAction
buildConfiguration = "Release"
shouldUseLaunchSchemeArgsEnv = "YES"
savedToolIdentifier = ""
useCustomWorkingDirectory = "NO"
debugDocumentVersioning = "YES">
<MacroExpansion>
<BuildableReference
BuildableIdentifier = "primary"
BlueprintIdentifier = "FC039B6920E11C3C0081E9F8"
BuildableName = "paddle_mobile.framework"
BlueprintName = "paddle-mobile"
ReferencedContainer = "container:paddle-mobile.xcodeproj">
</BuildableReference>
</MacroExpansion>
</ProfileAction>
<AnalyzeAction
buildConfiguration = "Debug">
</AnalyzeAction>
<ArchiveAction
buildConfiguration = "Release"
revealArchiveInOrganizer = "YES">
</ArchiveAction>
</Scheme>
<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
<plist version="1.0">
<dict>
<key>SchemeUserState</key>
<dict>
<key>paddle-mobile.xcscheme</key>
<dict>
<key>orderHint</key>
<integer>0</integer>
</dict>
</dict>
<key>SuppressBuildableAutocreation</key>
<dict>
<key>FC039B6920E11C3C0081E9F8</key>
<dict>
<key>primary</key>
<true/>
</dict>
</dict>
</dict>
</plist>
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
import Foundation
public enum PaddleMobileError: Error{
case loaderError(message: String)
case netError(message: String)
case memoryError(message: String)
case paramError(message: String)
case opError(message: String)
case predictError(message: String)
}
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
import Foundation
// 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{
associativity: left
higherThan: AssignmentPrecedence
}
infix operator ?!: ExecutedOrFatalError
public func ?!<T>(option: T?, excuteOrError: @autoclosure () -> String) -> T{
if let inOpt = option {
return inOpt
}else{
print(excuteOrError())
fatalError(excuteOrError())
}
}
//Lense
struct Lense<A, B> {
let from: (A) -> B
let to: (B, A) -> A
}
precedencegroup CombineLense{
associativity: left
higherThan: AssignmentPrecedence
}
infix operator >>>: CombineLense
func >>><A, B, C>(left: Lense<B, C>, right: Lense<A, B>) -> Lense<A, C> {
return Lense<A, C>.init(from: { (a) -> C in
left.from(right.from(a))
}, to: { (c, a) -> A in
right.to( left.to(c, right.from(a)),a)
})
}
protocol CIntIndex {
associatedtype T;
subscript(index: CInt) -> T { get set};
}
extension Array: CIntIndex{
typealias T = Element
subscript(index: CInt) -> T {
get{
guard Int64(Int.max) >= Int64(index) else{
fatalError("cint index out of Int range")
}
return self[Int(index)]
}
set{
guard Int64(Int.max) >= Int64(index) else{
fatalError("cint index out of Int range")
}
self[Int(index)] = newValue
}
}
}
extension Array where Element: AnyObject{
mutating func remove(element: Element) {
if let index = index(where: { (node) -> Bool in
return unsafeBitCast(element, to: Int.self) == unsafeBitCast(node, to: Int.self)
}) {
remove(at: index)
}
}
}
//MARK: Array extension
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
///
/// - Parameter r: 前 r 个元素
/// - Returns: [(原有位置, 排好位置的元素)]
public func top(r: Int) -> [(Int, Element)] {
precondition(r <= self.count)
return Array<(Int, Element)>(zip(0..<self.count, self).sorted{ $0.1 > $1.1 }.prefix(through: r - 1))
}
}
extension String{
func cStr() -> UnsafePointer<Int8>? {
return (self as NSString).utf8String
}
}
func address<T: AnyObject>(o: T) -> String {
return String.init(format: "%018p", unsafeBitCast(o, to: Int.self))
}
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
import Foundation
fileprivate var defaultMetalLibrary: MTLLibrary?
fileprivate var paddleMobileMetalLibrary: MTLLibrary?
extension MTLDevice {
func defaultLibrary() -> MTLLibrary {
if defaultMetalLibrary == nil {
defaultMetalLibrary = makeDefaultLibrary()
}
if let inDefaultLib = defaultMetalLibrary {
return inDefaultLib
} else {
fatalError(" default metal libary is nil")
}
}
func paddleMobileLibrary() -> MTLLibrary {
if paddleMobileMetalLibrary == nil {
guard let path = Bundle.init(for: Kernel.self).path(forResource: "default", ofType: "metallib") else {
fatalError("Counld't find paddle mobile library")
}
do {
paddleMobileMetalLibrary = try makeLibrary(filepath: path)
} catch _ {
fatalError("Counld't load paddle mobile library")
}
}
if let inPaddleMobileLib = paddleMobileMetalLibrary {
return inPaddleMobileLib
} else {
fatalError("PaddleMobile metal libary is nil")
}
}
func pipeLine(funcName: String, inPaddleMobileLib: Bool = true) -> MTLComputePipelineState {
let useLib = inPaddleMobileLib ? paddleMobileLibrary() : defaultLibrary()
guard let function = useLib.makeFunction(name: funcName) else {
fatalError(" function " + funcName + " not found")
}
do {
let pipLine = try makeComputePipelineState(function: function)
return pipLine
} catch _ {
fatalError("make pip line error occured")
}
}
func makeBuffer<P>(value: [P]) -> MTLBuffer {
let buffer = makeBuffer(length: value.count * MemoryLayout<P>.size, options: MTLResourceOptions.storageModeShared)
let contents = buffer?.contents().bindMemory(to: P.self, capacity: value.count * MemoryLayout<P>.size)
for i in 0..<value.count {
contents?[i] = value[i]
}
return buffer!
}
func makeFloatTexture<P>(value: [P], textureWidth: Int, textureHeight: Int, arrayLength: Int) -> MTLTexture{
let textureDesc = MTLTextureDescriptor.init()
textureDesc.width = textureWidth
textureDesc.height = textureHeight
textureDesc.depth = 1
textureDesc.usage = [.shaderRead, .shaderWrite]
textureDesc.pixelFormat = .rgba32Float
textureDesc.textureType = .type2DArray
textureDesc.storageMode = .shared
textureDesc.cpuCacheMode = .defaultCache
textureDesc.arrayLength = arrayLength
let texture = makeTexture(descriptor: textureDesc)!
if arrayLength == 1 && value.count >= 4{
let pointer: UnsafeMutablePointer<P> = UnsafeMutablePointer<P>.allocate(capacity: value.count * MemoryLayout<P>.size)
for i in 0..<value.count {
pointer[i] = value[i]
}
let bytesPerRow = texture.width * texture.depth * 4 * MemoryLayout<P>.size
let region = MTLRegion.init(origin: MTLOrigin.init(x: 0, y: 0, z: 0), size: MTLSize.init(width: texture.width, height: texture.height, depth: texture.depth))
texture.replace(region: region, mipmapLevel: 0, withBytes: pointer, bytesPerRow: bytesPerRow)
} else {
}
return texture
}
}
extension MTLComputeCommandEncoder {
func dispatch(computePipline: MTLComputePipelineState, outTexture: MTLTexture) {
let slices = (outTexture.arrayLength * 4 + 3)/4
let width = computePipline.threadExecutionWidth
let height = computePipline.maxTotalThreadsPerThreadgroup/width
let threadsPerGroup = MTLSize.init(width: width, height: height, depth: 1)
// print(" thread: threads per group: \(threadsPerGroup) ")
// print(" thread: out texture width: \(outTexture.width) , out texture height: \(outTexture.height)")
let groupWidth = (outTexture.width + width - 1)/width
let groupHeight = (outTexture.height + height - 1)/height
let groupDepth = slices
let groups = MTLSize.init(width: groupWidth, height: groupHeight, depth: groupDepth)
// print("groups: \(groups) ")
// print("threads per group: \(threadsPerGroup)")
setComputePipelineState(computePipline)
dispatchThreadgroups(groups, threadsPerThreadgroup: threadsPerGroup)
}
}
public extension MTLTexture {
func stridableFloatArray<P>(stridable: Bool = true) -> [(index: Int, value: P)] {
var arr: [P] = floatArray { (p: P) -> P in
return p;
}
var result: [(index: Int, value: P)] = []
if arr.count > 100 && stridable {
for j in stride(from: 0, to: arr.count , by: arr.count / 100){
result.append((j, arr[j]))
}
} else {
for j in 0..<arr.count {
result.append((j, arr[j]))
}
}
return result
}
func floatArray<P, T>(res: (P) -> T) -> [T] {
var fArr: [T] = []
if textureType == .type2DArray {
for i in 0..<arrayLength{
let bytes = UnsafeMutableRawPointer.allocate(byteCount: width * height * 4 * MemoryLayout<P>.size, alignment: MemoryLayout<P>.alignment)
let bytesPerRow = width * depth * 4 * MemoryLayout<P>.size
let bytesPerImage = width * height * depth * 4 * MemoryLayout<P>.size
let region = MTLRegion.init(origin: MTLOrigin.init(x: 0, y: 0, z: 0), size: MTLSize.init(width: width, height: height, depth: depth))
getBytes(bytes, bytesPerRow: bytesPerRow, bytesPerImage: bytesPerImage, from: region, mipmapLevel: 0, slice: i)
let p = bytes.assumingMemoryBound(to: P.self)
for j in 0..<width * height * depth * 4 {
fArr.append(res(p[j]))
}
bytes.deallocate()
}
} else if textureType == .type2D {
let bytes = UnsafeMutableRawPointer.allocate(byteCount: width * height * 4 * MemoryLayout<P>.size, alignment: MemoryLayout<P>.alignment)
let bytesPerRow = width * depth * 4 * MemoryLayout<P>.size
let region = MTLRegion.init(origin: MTLOrigin.init(x: 0, y: 0, z: 0), size: MTLSize.init(width: width, height: height, depth: depth))
getBytes(bytes, bytesPerRow: bytesPerRow, from: region, mipmapLevel: 0)
let p = bytes.assumingMemoryBound(to: P.self)
for j in 0..<width * height * 4 {
fArr.append(res(p[j]))
}
bytes.deallocate()
}
return fArr
}
func logDesc<T>(header: String = "", stridable: Bool = true) -> T? {
print(header)
print("texture: \(self)")
let res: [(index: Int, value: T)] = stridableFloatArray(stridable: stridable)
print(res)
// if textureType == .type2DArray {
// for i in 0..<arrayLength{
// var str: String = "slice: \(i): \n"
// let bytes = UnsafeMutableRawPointer.allocate(byteCount: width * height * 4 * MemoryLayout<T>.size, alignment: MemoryLayout<T>.alignment)
// let bytesPerRow = width * depth * 4 * MemoryLayout<T>.size
// let bytesPerImage = width * height * depth * 4 * MemoryLayout<T>.size
// let region = MTLRegion.init(origin: MTLOrigin.init(x: 0, y: 0, z: 0), size: MTLSize.init(width: width, height: height, depth: depth))
// getBytes(bytes, bytesPerRow: bytesPerRow, bytesPerImage: bytesPerImage, from: region, mipmapLevel: 0, slice: i)
// let p = bytes.assumingMemoryBound(to: T.self)
// str += "2d array count : \(width * height * depth * 4) \n"
// if stridable && width * height * depth * 4 > 100 {
// for j in stride(from: 0, to: width * height * depth * 4 , by: width * height * depth * 4 / 100){
// str += " index \(j): \(p[j])"
// }
// } else {
// for j in 0..<width * height * depth * 4 {
// str += " index \(j): \(p[j])"
// }
// }
//
// bytes.deallocate()
// print(str)
// }
// } else if textureType == .type2D {
// var str: String = "texture 2D: "
// let bytes = UnsafeMutableRawPointer.allocate(byteCount: width * height * 4 * MemoryLayout<T>.size, alignment: MemoryLayout<T>.alignment)
// let bytesPerRow = width * depth * 4 * MemoryLayout<T>.size
// let region = MTLRegion.init(origin: MTLOrigin.init(x: 0, y: 0, z: 0), size: MTLSize.init(width: width, height: height, depth: depth))
// getBytes(bytes, bytesPerRow: bytesPerRow, from: region, mipmapLevel: 0)
// let p = bytes.assumingMemoryBound(to: T.self)
// str += "2d count : \(width * width * 4) \n"
//
// if stridable {
// for j in stride(from: 0, to: width * height * 4, by: width * height * 4 / 100){
// str += "index \(j): \(p[j]) "
// }
// } else {
// for j in 0..<width * height * 4 {
// str += "index \(j): \(p[j]) "
// }
// }
//
// print(str)
// bytes.deallocate()
// }
return nil
}
}
public extension MTLBuffer {
func logDesc<T>(header: String = "", stridable: Bool = true) -> T? {
print(header)
print("MTLBuffer: \(self) ")
var str = ""
if stridable && length/MemoryLayout<T>.stride > 1000{
for j in stride(from: 0, to: length, by: length/MemoryLayout<T>.stride / 100){
str += " \(contents().assumingMemoryBound(to: T.self)[j])"
}
} else {
for i in 0..<length/MemoryLayout<T>.size {
str += " \(contents().assumingMemoryBound(to: T.self)[i])"
}
}
print(str)
return nil
}
func makeTexture(textureWidth: Int, textureHeight: Int, arrayLength: Int) -> MTLTexture {
let textureDesc = MTLTextureDescriptor.init()
textureDesc.width = textureWidth
textureDesc.height = textureHeight
textureDesc.depth = 1
textureDesc.usage = [.shaderRead, .shaderWrite]
textureDesc.pixelFormat = .rgba32Float
textureDesc.textureType = .type2DArray
textureDesc.storageMode = .shared
textureDesc.cpuCacheMode = .defaultCache
textureDesc.arrayLength = arrayLength
let texture = makeTexture(descriptor: textureDesc, offset: 0, bytesPerRow: textureWidth * 4 * 4)!
return texture
}
}
//
// TestConvAddBatchNormRelu.swift
// paddle-mobile-demo
//
// Created by liuRuiLong on 2018/7/25.
// Copyright © 2018年 orange. All rights reserved.
//
import Metal
import Foundation
public class PaddleMobileUnitTest {
let device: MTLDevice
let queue: MTLCommandQueue
public init(inDevice: MTLDevice, inQueue: MTLCommandQueue) {
device = inDevice
queue = inQueue
}
public func testConvAddBnRelu() {
let buffer = queue.makeCommandBuffer() ?! " buffer is nil "
let input: [Float32] = [
1.0, 2.0, 3.0, 4.0,
1.0, 2.0, 3.0, 4.0,
1.0, 2.0, 3.0, 4.0,
1.0, 2.0, 3.0, 4.0,
1.0, 2.0, 3.0, 4.0,
1.0, 2.0, 3.0, 4.0,
1.0, 2.0, 3.0, 4.0,
1.0, 2.0, 3.0, 4.0,
1.0, 2.0, 3.0, 4.0,
]
let filter: [Float32] = [
//1.0
1.0, 1.0, 1.0, 1.0,
1.0, 1.0, 1.0, 1.0,
1.0, 1.0, 1.0, 1.0,
1.0, 1.0, 1.0, 1.0,
1.0, 1.0, 1.0, 1.0,
1.0, 1.0, 1.0, 1.0,
1.0, 1.0, 1.0, 1.0,
1.0, 1.0, 1.0, 1.0,
1.0, 1.0, 1.0, 1.0,
//2.0
1.0, 1.0, 1.0, 1.0,
1.0, 1.0, 1.0, 1.0,
1.0, 1.0, 1.0, 1.0,
1.0, 1.0, 1.0, 1.0,
1.0, 1.0, 1.0, 1.0,
1.0, 1.0, 1.0, 1.0,
1.0, 1.0, 1.0, 1.0,
1.0, 1.0, 1.0, 1.0,
1.0, 1.0, 1.0, 1.0,
//3.0
1.0, 1.0, 1.0, 1.0,
1.0, 1.0, 1.0, 1.0,
1.0, 1.0, 1.0, 1.0,
1.0, 1.0, 1.0, 1.0,
1.0, 1.0, 1.0, 1.0,
1.0, 1.0, 1.0, 1.0,
1.0, 1.0, 1.0, 1.0,
1.0, 1.0, 1.0, 1.0,
1.0, 1.0, 1.0, 1.0,
//4.0
1.0, 1.0, 1.0, 1.0,
1.0, 1.0, 1.0, 1.0,
1.0, 1.0, 1.0, 1.0,
1.0, 1.0, 1.0, 1.0,
1.0, 1.0, 1.0, 1.0,
1.0, 1.0, 1.0, 1.0,
1.0, 1.0, 1.0, 1.0,
1.0, 1.0, 1.0, 1.0,
1.0, 1.0, 1.0, 1.0,
]
let biase: [Float32] = [1.0, 1.0, 1.0, 100.0]
let newScalue: [Float32] = [1.0, 1.0, 1.0, 1.0]
let newBiase: [Float32] = [1.0, 1.0, 1.0, 1.0]
let inputeTexture = device.makeFloatTexture(value: input, textureWidth: 3, textureHeight: 3, arrayLength: 1)
//filter
let filterBuffer = device.makeBuffer(value: filter)
// biase
let biaseBuffer = device.makeBuffer(value: biase)
// new scale
let newScalueBuffer = device.makeBuffer(value: newScalue)
// new biase
let newBiaseBuffer = device.makeBuffer(value: newBiase)
//output
let outputTexture = device.makeFloatTexture(value: [Float32](), textureWidth: 2, textureHeight: 2, arrayLength: 1)
let filterSize: (width: Int, height: Int, channel: Int) = (3, 3, 4)
let paddings: (Int, Int) = (1, 1)
let stride: (Int, Int) = (2, 2)
let offsetX = filterSize.width/2 - paddings.0
let offsetY = filterSize.height/2 - paddings.1
let metalParam = MetalConvParam.init(offsetX: Int16(offsetX), offsetY: Int16(offsetY), offsetZ: 0, strideX: UInt16(stride.0), strideY: UInt16(stride.1), paddedZ: UInt16(paddings.0))
let param = ConvAddBatchNormReluTestParam.init(inInputTexture: inputeTexture, inOutputTexture: outputTexture, inMetalParam: metalParam, inFilterBuffer: filterBuffer, inBiaseBuffer: biaseBuffer, inNewScaleBuffer: newScalueBuffer, inNewBiaseBuffer: newBiaseBuffer, inFilterSize: filterSize)
let convAddBnReluKernel = ConvAddBatchNormReluKernel<Float32>.init(device: device, testParam: param)
convAddBnReluKernel.test(commandBuffer: buffer, param: param)
buffer.addCompletedHandler { (buffer) in
let _: Float32? = inputeTexture.logDesc(header: "input texture", stridable: false)
let _: Float32? = outputTexture.logDesc(header: "output texture", stridable: false)
}
buffer.commit()
// let inputTexture = device.makeFloatTexture(value: <#T##[P]#>, textureWidth: <#T##Int#>, textureHeight: <#T##Int#>, arrayLength: <#T##Int#>)
// let param = ConvAddBatchNormReluTestParam.init(inInputTexture: <#T##MTLTexture#>, inOutputTexture: <#T##MTLTexture#>, inMetalParam: <#T##MetalConvParam#>, inFilterBuffer: <#T##MTLBuffer#>, inBiaseBuffer: <#T##MTLBuffer#>, inNewScaleBuffer: <#T##MTLBuffer#>, inNewBiaseBuffer: <#T##MTLBuffer#>, inFilterSize: <#T##(width: Int, height: Int, channel: Int)#>)
// ConvAddBatchNormReluKernel.init(device: <#T##MTLDevice#>, testParam: <#T##ConvAddBatchNormReluTestParam#>)
}
}
//
// Tools.swift
// paddle-mobile
//
// Created by liuRuiLong on 2018/7/26.
// Copyright © 2018年 orange. All rights reserved.
//
import Foundation
func writeToLibrary<P: PrecisionType>(fileName: String, array: [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: UnsafeBufferPointer.init(start: array, count: array.count))
fileHandler.write(data)
fileHandler.closeFile()
}
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
import Foundation
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
}
public protocol PrecisionType: SummableMultipliable{
init(inFloat: Float32)
init(inFloat16: Float16)
init<P: PrecisionType>(_ inP: P)
static var bitSize: UInt { get }
}
public typealias Float16 = Int16
extension Float16: PrecisionType {
public static func * (prefix: Float16, postfix: Float16) {
return prefix * postfix
}
public init<P>(_ inP: P) where P : PrecisionType {
if P.bitSize == Float32.bitSize {
self = Float16(inFloat: inP as! Float32)
} else if P.bitSize == Float16.bitSize {
self = inP as! Float16
} else {
fatalError()
}
}
public static var bitSize: UInt {
return 16
}
public init(inFloat16: Float16) {
self = inFloat16
}
public init(inFloat: Float32) {
self = Int16(inFloat)
}
}
extension Float32: PrecisionType {
public init<P>(_ inP: P) where P : PrecisionType {
if P.bitSize == Float32.bitSize {
self = inP as! Float32
} else if P.bitSize == Float16.bitSize {
self = Float32.init(inP as! Float16)
} else {
fatalError()
}
}
public init(inFloat: Float32) {
self = inFloat
}
public init(inFloat16: Float16) {
self = Float32.init(inFloat16)
}
public static var bitSize: UInt {
return 32
}
}
public enum DataLayout {
case NCHW
case NHWC
}
protocol Variant: CustomStringConvertible, CustomDebugStringConvertible {
}
extension Tensor: Variant {
}
extension Texture: Variant {
}
extension ResultHolder: Variant {
}
extension InputTexture: Variant {
}
extension MTLTexture where Self: Variant {
}
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
import Foundation
public class ResultHolder<P: PrecisionType> {
public let dim: [Int]
public let resultArr: [P]
public let elapsedTime: Double
public init(inDim: [Int], inResult: [P], inElapsedTime: Double) {
dim = inDim
resultArr = inResult
elapsedTime = inElapsedTime
}
}
extension ResultHolder: CustomDebugStringConvertible, CustomStringConvertible {
public var debugDescription: String {
var str = ""
str += "Dim: \(dim) \n value:[ "
if resultArr.count < 20 {
for d in resultArr {
str += " \(d) "
}
} else {
for d in stride(from: 0, to: resultArr.count, by: resultArr.count/20) {
str += " \(resultArr[d]) "
}
}
str += " ]"
return str
}
public var description: String {
return debugDescription
}
}
public class Executor<P: PrecisionType> {
var ops: [Runable & InferShaperable] = []
let program: Program
let device: MTLDevice
let queue: MTLCommandQueue
public init(inDevice:MTLDevice, inQueue: MTLCommandQueue, inProgram: Program) throws {
program = inProgram
device = inDevice
queue = inQueue
for block in inProgram.programDesc.blocks {
//block.ops.count
for i in 0..<block.ops.count {
let op = block.ops[i]
do {
let op = try OpCreator<P>.shared.creat(device: inDevice, opDesc: op, scope: inProgram.scope)
op.inferShape()
ops.append(op)
} catch let error {
throw error
}
}
// for op in block.ops {
// do {
// let op = try OpCreator<P>.shared.creat(device: inDevice, opDesc: op, scope: inProgram.scope)
// op.inferShape()
// ops.append(op)
// } catch let error {
// throw error
// }
// }
}
}
public func predict(input: MTLTexture, expect: [Int], completionHandle: @escaping (ResultHolder<P>) -> Void, preProcessKernle: CusomKernel? = nil) 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
}
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() {
program.scope.clear()
}
}
//public let paddle_executor: Executor = Executor.init()
<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
<plist version="1.0">
<dict>
<key>CFBundleDevelopmentRegion</key>
<string>$(DEVELOPMENT_LANGUAGE)</string>
<key>CFBundleExecutable</key>
<string>$(EXECUTABLE_NAME)</string>
<key>CFBundleIdentifier</key>
<string>$(PRODUCT_BUNDLE_IDENTIFIER)</string>
<key>CFBundleInfoDictionaryVersion</key>
<string>6.0</string>
<key>CFBundleName</key>
<string>$(PRODUCT_NAME)</string>
<key>CFBundlePackageType</key>
<string>FMWK</string>
<key>CFBundleShortVersionString</key>
<string>1.0</string>
<key>CFBundleVersion</key>
<string>$(CURRENT_PROJECT_VERSION)</string>
<key>NSPrincipalClass</key>
<string></string>
</dict>
</plist>
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
import Foundation
import SwiftProtobuf
public class Loader<P: PrecisionType> {
class ParaLoader {
let file: UnsafeMutablePointer<FILE>
let fileSize: Int
var nowIndex: Int
init(paramPath: String) throws {
guard let tmpFile = fopen(paramPath, "rb") else {
throw PaddleMobileError.loaderError(message: "open param file error" + paramPath)
}
file = tmpFile
fseek(file, 0, SEEK_END)
fileSize = ftell(file)
guard fileSize > 0 else {
throw PaddleMobileError.loaderError(message: "param file size is too small")
}
rewind(file)
nowIndex = 0
}
func read(tensor: Tensor<P>) throws {
guard nowIndex <= fileSize else {
throw PaddleMobileError.loaderError(message: "out of the file range")
}
func pointerReader<T>(type: T.Type) -> T {
let ptr = UnsafeMutablePointer<T>.allocate(capacity: MemoryLayout<T>.size)
fread(ptr, 1, MemoryLayout<T>.size, file)
nowIndex += MemoryLayout<T>.size
let pointee = ptr.pointee
ptr.deinitialize(count: MemoryLayout<UInt32>.size)
ptr.deallocate()
return pointee
}
let _ = pointerReader(type: UInt32.self)
let lodLevel = pointerReader(type: UInt64.self)
for _ in 0..<lodLevel {
let size = pointerReader(type: UInt64.self)
for _ in 0..<Int(size/UInt64(MemoryLayout<size_t>.size)){
_ = pointerReader(type: size_t.self)
}
}
let _ = pointerReader(type: UInt32.self)
let tensorDescSize = pointerReader(type: Int32.self)
fseek(file, Int(tensorDescSize), SEEK_CUR)
nowIndex += Int(tensorDescSize)
/*
这里没有根据 Data Type 去判断, 而是从外部泛型直接指定了精度
*/
//现在模型传入模型为 Float 类型, 这块应该根据模型来
// let tmpCapacity = MemoryLayout<Float>.size * tensor.numel()
// let tmpPointer = UnsafeMutablePointer<Float>.allocate(capacity: tmpCapacity);
let bytesRead = fread(tensor.data.pointer, 1, tensor.data.size, file)
guard bytesRead == tensor.data.size else {
throw PaddleMobileError.loaderError(message: "param read size error")
}
// TODO: use script to convert
// let bytesRead = fread(tmpPointer, 1, tmpCapacity, file)
// for i in 0..<tensor.numel() {
// tensor.data[i] = P.init(inFloat: tmpPointer[i])
// }
// tmpPointer.deinitialize(count: tmpCapacity)
// tmpPointer.deallocate()
nowIndex += bytesRead
}
deinit {
fclose(file)
}
}
public init(){}
public func load(device: MTLDevice, modelPath: String, paraPath: String) throws -> Program{
guard let modelData = try? Data.init(contentsOf: URL.init(fileURLWithPath: modelPath)) else {
throw PaddleMobileError.loaderError(message: "load " + modelPath + " failed !")
}
do {
let protoProgram = try PaddleMobile_Framework_Proto_ProgramDesc.init(
serializedData: modelData)
let originProgramDesc = ProgramDesc.init(protoProgram: protoProgram)
let programDesc = ProgramOptimize<P>.init().optimize(originProgramDesc: originProgramDesc)
print(programDesc)
guard let paraLoader = try? ParaLoader.init(paramPath: paraPath) else {
throw PaddleMobileError.loaderError(message: "load para error")
}
guard programDesc.blocks.count > 0 else {
throw PaddleMobileError.loaderError(message: "count of blocks must greater than 0")
}
// to get feed key and fetch key
let block = programDesc.blocks[0]
guard let firstOp = block.ops.first, let lastOp = block.ops.last else {
throw PaddleMobileError.loaderError(message: "at least two operator")
}
guard firstOp.type == gFeedType, lastOp.type == gFetchType else {
throw PaddleMobileError.loaderError(message: "the first op is not feed or the last op is not fetch")
}
guard let inputKey = opInfos[gFeedType]?.inputs.first, let outKey = opInfos[gFetchType]?.outputs.first else {
throw PaddleMobileError.loaderError(message: "the feed input key or fetch output key not found")
}
guard let feedKey = firstOp.inputs[inputKey]?.first, let fetchKey = lastOp.outputs[outKey]?.first else {
throw PaddleMobileError.loaderError(message: "feed key or fetch key not found")
}
let scope = Scope.init(inFeedKey: feedKey, inFetchKey: fetchKey)
// to load memory
for block in programDesc.blocks {
for varDesc in block.vars {
if (varDesc.type == .LodTensor) {
guard let tensorDesc = varDesc.tensorDesc else {
throw PaddleMobileError.loaderError(message: "get tensor desc failed")
}
// guard (try? tensorDesc.dataType.dataTypeSize()) == MemoryLayout<P>.size else {
// throw PaddleMobileError.memoryError(message: "PrecisionType not support")
// }
if (varDesc.persistable
&& varDesc.type != .FeedMiniBatch
&& varDesc.type != .FetchList) {
let dimArr = tensorDesc.dims
guard dimArr.count > 0 else {
throw PaddleMobileError.loaderError(message: "tensor desc dim size error")
}
let dim = Dim.init(inDim: dimArr)
let tensor = Tensor<P>.init(inDim: dim, inLayout: tensorDesc.dataLayout)
do {
try paraLoader.read(tensor: tensor)
} catch let error {
throw error
}
tensor.convert(to: .NHWC)
// tensor.initBuffer(device: device)
scope[varDesc.name] = tensor
} else {
let dim = Dim.init(inDim: tensorDesc.NHWCDim)
scope[varDesc.name] = Texture<P>.init(device: device, inDim: dim)
}
} else {
if varDesc.name == fetchKey {
scope[varDesc.name] = ResultHolder<P>.init(inDim: [], inResult: [], inElapsedTime: 0.0)
} else if varDesc.name == feedKey {
}
}
}
}
let program = Program.init(inProgramDesc: programDesc, inParamPath: paraPath, inScope: scope)
return program
} catch _ {
throw PaddleMobileError.loaderError(message: "protobuf decoder error")
}
}
}
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
import Foundation
fileprivate var singletons : [String : Any] = [:]
class OpCreator<P: PrecisionType> {
static var shared : OpCreator<P> {
let key = String(describing: P.self)
if let singleton = singletons[key] {
return singleton as! OpCreator<P>
} else {
let newSingleton = OpCreator<P>()
singletons[key] = newSingleton
return newSingleton
}
}
func creat(device: MTLDevice, opDesc: OpDesc, scope: Scope) throws -> Runable & InferShaperable {
guard let opCreator = opCreators[opDesc.type] else {
throw PaddleMobileError.opError(message: "there is no " + opDesc.type + " yet")
}
do {
return try opCreator(device, opDesc, scope)
} catch let error {
throw error
}
}
let opCreators: [String : (MTLDevice, OpDesc, Scope) throws -> Runable & InferShaperable] =
[gConvType : ConvOp<P>.creat,
gBatchNormType : BatchNormOp<P>.creat,
gReluType : ReluOp<P>.creat,
gElementwiseAdd : ElementwiseAddOp<P>.creat,
gFeedType : FeedOp<P>.creat,
gFetchType : FetchOp<P>.creat,
gConvAddBatchNormReluType : ConvAddBatchNormReluOp<P>.creat,
gPooType : PoolOp<P>.creat,
gSoftmaxType : SoftmaxOp<P>.creat,
gReshapeType : ReshapeOp<P>.creat,
gConvAddType : ConvAddOp<P>.creat]
private init(){}
}
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
import Foundation
/*
let opInputsOutputsKey = [gConvType : (inputs: ["Input"], outputs: ["Output"]),
gBatchNormType : (inputs: ["X"], outputs: ["Y"]),
gReluType : (inputs: ["X"], outputs: ["Out"]),
gElementwiseAdd : (inputs: ["X", "Y"], outputs: ["Out"])]
*/
protocol OpParam {
associatedtype OutputType: Variant
var output: OutputType { get set }
func outputDesc() -> String
associatedtype ParamPrecisionType: PrecisionType
init(opDesc: OpDesc, inScope: Scope) throws
static func getFirstTensor<VarType: Variant>(key: String, map: [String : [String]], from: Scope) throws -> VarType
static func inputX<VarType: Variant>(inputs: [String : [String]], from: Scope) throws -> VarType
static func inputBiase<VarType: Variant>(inputs: [String : [String]], from: Scope) throws -> VarType
static func inputMean<VarType: Variant>(inputs: [String : [String]], from: Scope) throws -> VarType
static func inputScale<VarType: Variant>(inputs: [String : [String]], from: Scope) throws -> VarType
static func inputVariance<VarType: Variant>(inputs: [String : [String]], from: Scope) throws -> VarType
static func inputFilter<VarType: Variant>(paraInputs: [String : [String]], from: Scope) throws -> VarType
static func input<VarType: Variant>(inputs: [String : [String]], from: Scope) throws -> VarType
static func output<VarType: Variant>(outputs: [String : [String]], from: Scope) throws -> VarType
static func outputY<VarType: Variant>(outputs: [String : [String]], from: Scope) throws -> VarType
static func inputY<VarType: Variant>(inputs: [String : [String]], from: Scope) throws -> VarType
static func outputOut<VarType: Variant>(outputs: [String : [String]], from: Scope) throws -> VarType
static func getAttr<T>(key: String, attrs: [String : Attr]) throws -> T
}
extension OpParam {
func outputDesc() -> String {
return output.debugDescription
}
static func getFirstTensor<VarType: Variant>(key: String, map: [String : [String]], from: Scope) throws -> VarType {
guard let mapKeys = map[key], mapKeys.count > 0 else {
throw PaddleMobileError.paramError(message: key + " not found in \(map) or maped values is empty")
}
guard let variant = from[mapKeys[0]], let v = variant as? VarType else {
throw PaddleMobileError.paramError(message: mapKeys[0] + " not found in scope")
}
return v
}
static func inputX<VarType: Variant>(inputs: [String : [String]], from: Scope) throws -> VarType {
do {
let tensorX: VarType = try getFirstTensor(key: "X", map: inputs, from: from)
return tensorX
} catch let error {
throw error
}
}
static func input<VarType: Variant>(inputs: [String : [String]], from: Scope) throws -> VarType {
do {
let tensorInput: VarType = try getFirstTensor(key: "Input", map: inputs, from: from)
return tensorInput
} catch let error {
throw error
}
}
static func output<VarType: Variant>(outputs: [String : [String]], from: Scope) throws -> VarType {
do {
let tensorOutput: VarType = try getFirstTensor(key: "Output", map: outputs, from: from)
return tensorOutput
} catch let error {
throw error
}
}
static func outputY<VarType: Variant>(outputs: [String : [String]], from: Scope) throws -> VarType {
do {
let tensorOutputY: VarType = try getFirstTensor(key: "Y", map: outputs, from: from)
return tensorOutputY
} catch let error {
throw error
}
}
static func inputY<VarType: Variant>(inputs: [String : [String]], from: Scope) throws -> VarType {
do {
let tensorY: VarType = try getFirstTensor(key: "Y", map: inputs, from: from)
return tensorY
} catch let error {
throw error
}
}
static func outputOut<VarType: Variant>(outputs: [String : [String]], from: Scope) throws -> VarType {
do {
let out: VarType = try getFirstTensor(key: "Out", map: outputs, from: from)
return out
} catch let error {
throw error
}
}
static func inputFilter<VarType: Variant>(paraInputs: [String : [String]], from: Scope) throws -> VarType {
do {
let tensorFilter: VarType = try getFirstTensor(key: "Filter", map: paraInputs, from: from)
return tensorFilter
} catch let error {
throw error
}
}
static func inputBiase<VarType: Variant>(inputs: [String : [String]], from: Scope) throws -> VarType {
do {
let tensorBias: VarType = try getFirstTensor(key: "Bias", map: inputs, from: from)
return tensorBias
} catch let error {
throw error
}
}
static func inputMean<VarType: Variant>(inputs: [String : [String]], from: Scope) throws -> VarType {
do {
let tensorMean: VarType = try getFirstTensor(key: "Mean", map: inputs, from: from)
return tensorMean
} catch let error {
throw error
}
}
static func inputScale<VarType: Variant>(inputs: [String : [String]], from: Scope) throws -> VarType {
do {
let tensorScale: VarType = try getFirstTensor(key: "Scale", map: inputs, from: from)
return tensorScale
} catch let error {
throw error
}
}
static func inputVariance<VarType: Variant>(inputs: [String : [String]], from: Scope) throws -> VarType {
do {
let tensorVariance: VarType = try getFirstTensor(key: "Variance", map: inputs, from: from)
return tensorVariance
} catch let error {
throw error
}
}
static func getAttr<T>(key: String, attrs: [String : Attr]) throws -> T{
guard let attr = attrs[key] else {
throw PaddleMobileError.paramError(message: "attr \(key) can't found in: \(attrs)" )
}
guard let tAttr = attr as? T else {
throw PaddleMobileError.paramError(message: "key: \(key) attr: \(attr) type error" )
}
return tAttr
}
}
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
import Metal
import Foundation
protocol Fusion {
static func fusionNode() -> Node
static func change() -> [String : [(from: String, to: String)]]
static func fusionType() -> String
}
protocol Runable {
func run(device: MTLDevice, buffer: MTLCommandBuffer) throws
func runImpl(device: MTLDevice,buffer: MTLCommandBuffer) throws
func delogOutput()
}
extension Runable where Self: OperatorProtocol{
func run(device: MTLDevice, buffer: MTLCommandBuffer) throws {
do {
try runImpl(device: device, buffer: buffer)
} catch let error {
throw error
}
// print(type + ": " + para.outputDesc())
}
func delogOutput() {
print(type + ": has no implementation" )
}
}
protocol Creator where Self: OperatorProtocol{
associatedtype OpType: OperatorProtocol & Runable & InferShaperable
static func creat(device: MTLDevice, opDesc: OpDesc, inScope: Scope) throws -> OpType
}
extension Creator where Self: OperatorProtocol {
static func creat(device: MTLDevice, opDesc: OpDesc, inScope: Scope) throws -> OpType {
do {
return try OpType.provide(device:device, opDesc: opDesc, inScope: inScope)
} catch let error {
throw error
}
}
}
protocol InferShaperable {
func inferShape()
}
protocol OperatorProtocol {
associatedtype ParamType
associatedtype KerType: Computable where Self.KerType.ParamType == ParamType
var type: String { get }
var scope: Scope { get }
var inputs: [String : [String]] { get }
var paraInputs: [String : [String]] { get set }
var outpus: [String : [String]] { get }
var attrs: [String : Attr] { get }
var para: ParamType { get }
var kernel: KerType { get }
init(device: MTLDevice, opDesc: OpDesc, inScope: Scope) throws
}
extension OperatorProtocol {
static func provide(device: MTLDevice, opDesc: OpDesc, inScope: Scope) throws -> Self {
do {
return try Self.init(device: device, opDesc: opDesc, inScope: inScope)
} catch let error {
throw error
}
}
}
class Operator <KernelType: Computable , ParameterType>: OperatorProtocol where KernelType.ParamType == ParameterType {
typealias ParamType = ParameterType
typealias KerType = KernelType
let type: String
let inputs: [String : [String]]
var paraInputs: [String : [String]]
let outpus: [String : [String]]
let attrs: [String : Attr]
let para: ParamType
let scope: Scope
var kernel: KerType
required init(device: MTLDevice, opDesc: OpDesc, inScope: Scope) throws {
type = opDesc.type
scope = inScope
inputs = opDesc.inputs
outpus = opDesc.outputs
attrs = opDesc.attrs
paraInputs = opDesc.paraInputs
do {
para = try ParamType.init(opDesc:opDesc, inScope: inScope)
} catch let error {
throw error
}
kernel = KernelType.init(device: device, param: para)
}
}
// op infos
let gFetchType = "fetch"
let gFeedType = "feed"
let gConvType = "conv2d"
let gBatchNormType = "batch_norm"
let gReluType = "relu"
let gElementwiseAdd = "elementwise_add"
let gConvAddBatchNormReluType = "conv_add_batchnorm_relu"
let gPooType = "pool2d"
let gSoftmaxType = "softmax"
let gReshapeType = "reshape"
let gConvAddType = "conv_add"
let opInfos = [gConvType : (inputs: ["Input"], outputs: ["Output"]),
gBatchNormType : (inputs: ["X"], outputs: ["Y"]),
gReluType : (inputs: ["X"], outputs: ["Out"]),
gElementwiseAdd : (inputs: ["X"], outputs: ["Out"]),
gFeedType : (inputs: ["X"], outputs: ["Out"]),
gFetchType : (inputs: ["X"], outputs: ["Out"]),
gConvAddBatchNormReluType : (inputs: ["Input"], outputs: ["Out"]),
gPooType : (inputs: ["X"], outputs: ["Out"]),
gSoftmaxType : (inputs: ["X"], outputs: ["Out"]),
gReshapeType : (inputs: ["X"], outputs: ["Out"]),
gConvAddType : (inputs: ["Input"], outputs: ["Out"])]
///* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License. */
import Foundation
class BatchNormParam<P: PrecisionType>: OpParam {
typealias ParamPrecisionType = P
required init(opDesc: OpDesc, inScope: Scope) throws {
do {
input = try BatchNormParam.inputX(inputs: opDesc.inputs, from: inScope)
output = try BatchNormParam.outputY(outputs: opDesc.outputs, from: inScope)
inputBias = try BatchNormParam.inputBiase(inputs: opDesc.paraInputs, from: inScope)
inputMean = try BatchNormParam.inputMean(inputs: opDesc.paraInputs, from: inScope)
inputScale = try BatchNormParam.inputScale(inputs: opDesc.paraInputs, from: inScope)
inputVariance = try BatchNormParam.inputVariance(inputs: opDesc.paraInputs, from: inScope)
epsilon = try BatchNormParam.getAttr(key: "epsilon", attrs: opDesc.attrs)
momentum = try BatchNormParam.getAttr(key: "momentum", attrs: opDesc.attrs)
is_test = try BatchNormParam.getAttr(key: "is_test", attrs: opDesc.attrs)
} catch let error {
throw error
}
}
let input: Texture<P>
var output: Texture<P>
let inputBias: Tensor<ParamPrecisionType>
let inputMean: Tensor<ParamPrecisionType>
let inputScale: Tensor<ParamPrecisionType>
let inputVariance: Tensor<ParamPrecisionType>
let epsilon: Float
let momentum: Float
let is_test: Bool
}
class BatchNormOp<P: PrecisionType>: Operator<BatchNormKernel<P>, BatchNormParam<P>>, Runable, Creator, InferShaperable{
func inferShape() {
para.output.dim = para.input.dim
}
typealias OpType = BatchNormOp<P>
func runImpl(device: MTLDevice, buffer: MTLCommandBuffer) throws {
do {
try kernel.compute(commandBuffer: buffer, param: para)
} catch let error {
throw error
}
}
}
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
import Foundation
class ConvAddBatchNormReluParam<P: PrecisionType>: OpParam {
typealias ParamPrecisionType = P
required init(opDesc: OpDesc, inScope: Scope) throws {
do {
filter = try ConvAddBatchNormReluParam.inputFilter(paraInputs: opDesc.paraInputs, from: inScope)
input = try ConvAddBatchNormReluParam.input(inputs: opDesc.inputs, from: inScope)
output = try ConvAddBatchNormReluParam.outputOut(outputs: opDesc.outputs, from: inScope)
stride = try ConvAddBatchNormReluParam.getAttr(key: "strides", attrs: opDesc.attrs)
paddings = try ConvAddBatchNormReluParam.getAttr(key: "paddings", attrs: opDesc.attrs)
dilations = try ConvAddBatchNormReluParam.getAttr(key: "dilations", attrs: opDesc.attrs)
epsilon = try ConvAddBatchNormReluParam.getAttr(key: "epsilon", attrs: opDesc.attrs)
groups = try ConvAddBatchNormReluParam.getAttr(key: "groups", attrs: opDesc.attrs)
variance = try ConvAddBatchNormReluParam.inputVariance(inputs: opDesc.paraInputs, from: inScope)
bias = try ConvAddBatchNormReluParam.inputBiase(inputs: opDesc.paraInputs, from: inScope)
scale = try ConvAddBatchNormReluParam.inputScale(inputs: opDesc.paraInputs, from: inScope)
mean = try ConvAddBatchNormReluParam.inputMean(inputs: opDesc.paraInputs, from: inScope)
y = try ConvAddBatchNormReluParam.inputY(inputs: opDesc.paraInputs, from: inScope)
} catch let error {
throw error
}
}
let input: Texture<P>
let variance: Tensor<ParamPrecisionType>
let bias: Tensor<ParamPrecisionType>
let mean: Tensor<ParamPrecisionType>
let scale: Tensor<ParamPrecisionType>
let y: Tensor<ParamPrecisionType>
let filter: Tensor<ParamPrecisionType>
let epsilon: Float32
var newScale: MTLBuffer?
var newBiase: MTLBuffer?
var output: Texture<P>
let stride: [Int32]
let paddings: [Int32]
let dilations: [Int32]
let groups: Int
}
class ConvAddBatchNormReluOp<P: PrecisionType>: Operator<ConvAddBatchNormReluKernel<P>, ConvAddBatchNormReluParam<P>>, Runable, Creator, InferShaperable, Fusion{
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
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)
}
func runImpl(device: MTLDevice, buffer: MTLCommandBuffer) throws {
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: gElementwiseAdd)
--> 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() {
// 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)
}
}
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
import Foundation
class ConvAddParam<P: PrecisionType>: OpParam {
typealias ParamPrecisionType = P
required init(opDesc: OpDesc, inScope: Scope) throws {
do {
filter = try ConvAddParam.inputFilter(paraInputs: opDesc.paraInputs, from: inScope)
input = try ConvAddParam.input(inputs: opDesc.inputs, from: inScope)
output = try ConvAddParam.outputOut(outputs: opDesc.outputs, from: inScope)
stride = try ConvAddParam.getAttr(key: "strides", attrs: opDesc.attrs)
paddings = try ConvAddParam.getAttr(key: "paddings", attrs: opDesc.attrs)
dilations = try ConvAddParam.getAttr(key: "dilations", attrs: opDesc.attrs)
groups = try ConvAddParam.getAttr(key: "groups", attrs: opDesc.attrs)
y = try ConvAddParam.inputY(inputs: opDesc.paraInputs, from: inScope)
} catch let error {
throw error
}
}
let input: Texture<P>
let y: Tensor<ParamPrecisionType>
let filter: Tensor<ParamPrecisionType>
var output: Texture<P>
let stride: [Int32]
let paddings: [Int32]
let dilations: [Int32]
let groups: Int
}
class ConvAddOp<P: PrecisionType>: Operator<ConvAddKernel<P>, ConvAddParam<P>>, Runable, Creator, InferShaperable, Fusion{
static func fusionNode() -> Node {
let beginNode = Node.init(inType: gConvType)
_ = beginNode
--> Node.init(inType: gElementwiseAdd)
return beginNode
}
static func change() -> [String : [(from: String, to: String)]] {
return [:]
}
static func fusionType() -> String {
return gConvAddType
}
typealias OpType = ConvAddOp<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
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)
}
func runImpl(device: MTLDevice, buffer: MTLCommandBuffer) throws {
do {
try kernel.compute(commandBuffer: buffer, param: para)
} catch let error {
throw error
}
}
}
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
import Foundation
class ConvParam<P: PrecisionType>: OpParam {
typealias ParamPrecisionType = P
required init(opDesc: OpDesc, inScope: Scope) throws {
do {
filter = try ConvParam.inputFilter(paraInputs: opDesc.paraInputs, from: inScope)
input = try ConvParam.input(inputs: opDesc.inputs, from: inScope)
output = try ConvParam.output(outputs: opDesc.outputs, from: inScope)
stride = try ConvParam.getAttr(key: "strides", attrs: opDesc.attrs)
paddings = try ConvParam.getAttr(key: "paddings", attrs: opDesc.attrs)
dilations = try ConvParam.getAttr(key: "dilations", attrs: opDesc.attrs)
groups = try ConvParam.getAttr(key: "groups", attrs: opDesc.attrs)
} catch let error {
throw error
}
}
let input: Texture<P>
let filter: Tensor<ParamPrecisionType>
var output: Texture<P>
let stride: [Int32]
let paddings: [Int32]
let dilations: [Int32]
let groups: Int
}
class ConvOp<P: PrecisionType>: Operator<ConvKernel<P>, ConvParam<P>>, Runable, Creator, InferShaperable {
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
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 {
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()
}
}
///* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License. */
import Foundation
class ElementwiseAddParam<P: PrecisionType>: OpParam {
typealias ParamPrecisionType = P
required init(opDesc: OpDesc, inScope: Scope) throws {
do {
input = try ElementwiseAddParam.inputX(inputs: opDesc.inputs, from: inScope)
inputY = try ElementwiseAddParam.inputY(inputs: opDesc.paraInputs, from: inScope)
output = try ElementwiseAddParam.outputOut(outputs: opDesc.outputs, from: inScope)
axis = try ElementwiseAddParam.getAttr(key: "axis", attrs: opDesc.attrs)
} catch let error {
throw error
}
}
let input: Texture<P>
let inputY: Tensor<P>
var output: Texture<P>
let axis: Int
}
class ElementwiseAddOp<P: PrecisionType>: Operator<ElementwiseAddKernel<P>, ElementwiseAddParam<P>>, Runable, Creator, InferShaperable{
func inferShape() {
para.output.dim = para.input.dim
}
typealias OpType = ElementwiseAddOp<P>
func runImpl(device: MTLDevice, buffer: MTLCommandBuffer) throws {
}
}
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
import Foundation
class FeedParam<P: PrecisionType>: OpParam{
var output: Texture<P>
var input: 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
}
}
typealias ParamPrecisionType = P
}
class FeedOp<P: PrecisionType>: Operator<Texture2DTo2DArrayKernel<P>, FeedParam<P>>, Runable, Creator, InferShaperable {
typealias OpType = FeedOp<P>
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
}
// let resizeKernel = ResizeKernel<P>.init(device: device)
// let resizeParam = ResizeParam.init(input: para.input.mtlTexture, output: para.output.metalTexture, expectDim: para.input.expectDim)
// do {
// try resizeKernel.compute(commandBuffer: buffer, param: resizeParam)
// } catch let error {
// throw error
// }
}
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)
}
}
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
import Foundation
class FetchParam<P: PrecisionType>: OpParam{
var output: Texture<P>
let input: Texture<P>
let scope: Scope
required init(opDesc: OpDesc, inScope: Scope) throws {
scope = inScope
do {
input = try FetchParam.inputX(inputs: opDesc.inputs, from: inScope)
output = input
} catch let error {
throw error
}
}
typealias ParamPrecisionType = P
}
class FetchKernel<P: PrecisionType>: Kernel, Computable {
func compute(commandBuffer: MTLCommandBuffer, param: FetchParam<P>) throws {
}
required init(device: MTLDevice, param: FetchParam<P>) {
super.init(device: device, inFunctionName: "texture2d_to_2d_array")
}
}
class FetchOp<P: PrecisionType>: Operator< FetchKernel<P>, FetchParam<P>>, Runable, Creator, InferShaperable{
func inferShape() {
print(para.input.dim)
}
typealias OpType = FetchOp<P>
func runImpl(device: MTLDevice, buffer: MTLCommandBuffer) throws {
scope.setOutput(output: para.output)
}
}
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
import Foundation
class ConvAddKernel<P: PrecisionType>: Kernel, Computable {
var metalParam: MetalConvParam!
required init(device: MTLDevice, param: ConvAddParam<P>) {
super.init(device: device, inFunctionName: "conv_add_1x1")
let offsetX = param.filter.width/2 - Int(param.paddings[0])
let offsetY = param.filter.height/2 - Int(param.paddings[1])
param.filter.initBuffer(device: device, precision: Tensor.BufferPrecision.Float32)
param.y.initBuffer(device: device, precision: Tensor.BufferPrecision.Float32)
print("offset x: \(offsetX)")
print("offset y: \(offsetY)")
let offsetZ = 0.0
metalParam = MetalConvParam.init(offsetX: Int16(offsetX), offsetY: Int16(offsetY), offsetZ: Int16(offsetZ), strideX: UInt16(param.stride[0]), strideY: UInt16(param.stride[1]), paddedZ: UInt16(param.input.metalTexture.arrayLength * 4 - param.input.dim[3]))
}
func compute(commandBuffer: MTLCommandBuffer, param: ConvAddParam<P>) throws {
guard let encoder = commandBuffer.makeComputeCommandEncoder() else {
throw PaddleMobileError.predictError(message: " encode is nil")
}
encoder.setTexture(param.input.metalTexture, index: 0)
encoder.setTexture(param.output.metalTexture, index: 1)
encoder.setBytes(&metalParam, length: MemoryLayout<MetalConvParam>.size, index: 0)
encoder.setBuffer(param.filter.buffer, offset: 0, index: 1)
encoder.setBuffer(param.y.buffer, offset: 0, index: 2)
encoder.dispatch(computePipline: pipline, outTexture: param.output.metalTexture)
encoder.endEncoding()
}
}
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