add half compute

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

@@ -25,7 +25,7 @@ class MobileNet_ssd_hand: Net{
   class MobilenetssdPreProccess: CusomKernel {
     init(device: MTLDevice) {
       let s = CusomKernel.Shape.init(inWidth: 300, inHeight: 300, inChannel: 3)
-      super.init(device: device, inFunctionName: "mobilenet_ssd_preprocess", outputDim: s, usePaddleMobileLib: false)
+      super.init(device: device, inFunctionName: "mobilenet_ssd_preprocess_half", outputDim: s, usePaddleMobileLib: false)
     }
   }
   
@@ -49,9 +49,7 @@ class MobileNet_ssd_hand: Net{
     
     var scoreFormatArr: [Float32] = score.metalTexture.realNHWC(dim: (n: score.originDim[0], h: score.originDim[1], w: score.originDim[2], c: score.originDim[3]))
     
-    var bboxArr = bbox.metalTexture.floatArray { (f) -> Float32 in
-      return f
-    }
+    var bboxArr = bbox.metalTexture.float32Array()
     
     let nmsCompute = NMSCompute.init()
     nmsCompute.scoreThredshold = 0.01

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

@@ -22,7 +22,7 @@ import MetalPerformanceShaders
 
 class ScaleKernel: CusomKernel {
   init(device: MTLDevice, shape: Shape) {
-    super.init(device: device, inFunctionName: "scale", outputDim: shape, usePaddleMobileLib: false)
+    super.init(device: device, inFunctionName: "scale_half", outputDim: shape, usePaddleMobileLib: false)
   }
 }
 
@@ -79,6 +79,8 @@ extension Net {
   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: (dim.w, dim.h)) { (resTexture) in
+      print("after scale")
+      print(resTexture.float32Array().strideArray())
       getTexture(resTexture)
     }
   }

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

@@ -112,6 +112,7 @@ class ViewController: UIViewController {
     selectImage = UIImage.init(named: "hand.jpg")
     selectImageView.image = selectImage
     net.getTexture(image: selectImage!.cgImage!) {[weak self] (texture) in
+      
       self?.toPredictTexture = texture
     }
   }

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

@@ -285,6 +285,23 @@ public extension MTLTexture {
     return fArr
   }
   
+  func float32Array() -> [Float32] {
+    if pixelFormat == .rgba32Float {
+      let float32Array = floatArray { (f: Float32) -> Float32 in
+        return f
+      }
+      return float32Array
+    } else if pixelFormat == .rgba16Float {
+      
+      var float16Array = floatArray { (f: Float16) -> Float16 in
+        return f
+      }
+      return float16To32(input: &float16Array, count: float16Array.count)
+    } else {
+      fatalError()
+    }
+  }
+  
   func logDesc<T>(header: String = "", stridable: Bool = true) -> T? {
     print(header)
     print("texture: \(self)")
@@ -385,7 +402,6 @@ public extension MTLTexture {
 //    print(self)
     
     var textureArray: [Float32]
-    //    if texturePrecision == .Float16
     if pixelFormat == .rgba32Float {
       textureArray = floatArray { (i : Float32) -> Float32 in
         return i

metal/paddle-mobile/paddle-mobile/Executor.swift

@@ -16,7 +16,7 @@ import Foundation
 
 let testTo = 54
 
-let computePrecision: ComputePrecision = .Float32
+let computePrecision: ComputePrecision = .Float16
 
 public class ResultHolder<P: PrecisionType> {
   public let dim: [Int]
@@ -115,6 +115,7 @@ public class Executor<P: PrecisionType> {
 //      let inputArr = resInput.floatArray(res: { (p:P) -> P in
 //        return p
 //      })
+//      print(inputArr.strideArray())
 //
 //      writeToLibrary(fileName: "genet_input_hand", array: inputArr)
 //      print("write to library done")

metal/paddle-mobile/paddle-mobile/Operators/BoxcoderOp.swift

@@ -74,9 +74,14 @@ class BoxcoderOp<P: PrecisionType>: Operator<BoxcoderKernel<P>, BoxcoderParam<P>
 //    print(" target box ")
 //    print(targetBoxArray.strideArray())
     
-    let originDim = para.output.originDim
+    let targetBoxOriginDim = para.targetBox.originDim
+    let targetBoxArray = para.targetBox.metalTexture.realNHWC(dim: (n: targetBoxOriginDim[0], h: targetBoxOriginDim[1], w: targetBoxOriginDim[2], c: targetBoxOriginDim[3]), texturePrecision: computePrecision)
+    print(" target box ")
+    print(targetBoxArray.strideArray())
     
+    let originDim = para.output.originDim
     let outputArray: [Float32] = para.output.metalTexture.realNHWC(dim: (n: originDim[0], h: originDim[1], w: originDim[2], c: originDim[3]), texturePrecision: computePrecision)
+    print(" output ")
     print(outputArray.strideArray())
   }
   

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

@@ -60,9 +60,8 @@ class FeedOp<P: PrecisionType>: Operator<Texture2DTo2DArrayKernel<P>, FeedParam<
   }
   
   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)
+    print(" \(type) output: ")
+    print(para.output.metalTexture.toTensor(dim: (n: para.output.originDim[0], c: para.output.originDim[1], h: para.output.originDim[2], w: para.output.originDim[3]), texturePrecision: computePrecision).strideArray())
   }
 }
 

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

@@ -117,10 +117,10 @@ class ConvBNReluKernel<P: PrecisionType>: Kernel, Computable, Testable {
     var newBiaseBuffer: MTLBuffer
     var newScaleBuffer: MTLBuffer
     
-    if computePrecision == .Float16 {
+    if computePrecision == .Float32 {
       newBiaseBuffer = device.makeBuffer(bytes: newBiase, length: param.bias.buffer.length)!
       newScaleBuffer = device.makeBuffer(bytes: newScale, length: param.scale.buffer.length)!
-    } else if computePrecision == .Float32 {
+    } else if computePrecision == .Float16 {
       
       newBiaseBuffer = device.makeBuffer(length: param.bias.buffer.length / 2)!
       newScaleBuffer = device.makeBuffer(length: param.bias.buffer.length / 2)!

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

@@ -85,7 +85,7 @@ class PriorBoxKernel<P: PrecisionType>: Kernel, Computable{
     }
     
     if computePrecision == .Float16 {
-      let buffer = device.makeBuffer(length: outputAspectRatior.count)
+      let buffer = device.makeBuffer(length: outputAspectRatior.count * MemoryLayout<Float16>.size)
       float32ToFloat16(input: &outputAspectRatior, output:(buffer?.contents())!, count: outputAspectRatior.count)
       param.newAspectRatios = buffer
 

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

@@ -32,7 +32,14 @@ class Texture2DTo2DArrayKernel<P: PrecisionType>: Kernel, Computable{
   }
   
   required init(device: MTLDevice, param: FeedParam<P>) {
-    param.output.initTexture(device: device, inTranspose: [0, 2, 3, 1])
+    param.output.initTexture(device: device, inTranspose: [0, 2, 3, 1], computePrecision: computePrecision)
+    if computePrecision == .Float16 {
+      super.init(device: device, inFunctionName: "texture2d_to_2d_array_half")
+    } else if computePrecision == .Float32 {
       super.init(device: device, inFunctionName: "texture2d_to_2d_array")
+    } else {
+      fatalError()
+    }
+    
   }
 }

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

@@ -44,18 +44,6 @@ kernel void resize(texture2d<half, access::read> inTexture [[texture(0)]],
 }
 
 
-
-//kernel void texture2d_to_2d_array(texture2d<half, access::read> inTexture [[texture(0)]],
-//                               texture2d_array<half, access::write> outTexture [[texture(1)]],
-//                               uint3 gid [[thread_position_in_grid]]) {
-//    if (gid.x >= inTexture.get_width() ||
-//        gid.y >= inTexture.get_height()){
-//        return;
-//    }
-//    const half4 input = inTexture.read(gid.xy);
-//    outTexture.write(input, gid.xy, 0);
-//}
-
 kernel void texture2d_to_2d_array(texture2d<float, access::read> inTexture [[texture(0)]],
                                   texture2d_array<float, access::write> outTexture [[texture(1)]],
                                   uint3 gid [[thread_position_in_grid]]) {
@@ -67,7 +55,6 @@ kernel void texture2d_to_2d_array(texture2d<float, access::read> inTexture [[tex
   outTexture.write(input, gid.xy, 0);
 }
 
-
 kernel void texture2d_to_2d_array_half(texture2d<half, access::read> inTexture [[texture(0)]],
                                       texture2d_array<half, access::write> outTexture [[texture(1)]],
                                       uint3 gid [[thread_position_in_grid]]) {
@@ -80,5 +67,3 @@ kernel void texture2d_to_2d_array_half(texture2d<half, access::read> inTexture [
 }
 
 
-
-

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

@@ -100,8 +100,8 @@ kernel void prior_box(texture2d_array<float, access::read> inTexture [[texture(0
 kernel void prior_box_half(texture2d_array<half, access::read> inTexture [[texture(0)]],
                       texture2d_array<half, access::write> outBoxTexture [[texture(1)]],
                       texture2d_array<half, access::write> varianceTexture [[texture(2)]],
-                      constant PriorBoxMetalParam &param [[buffer(0)]],
-                      const device half *aspect_ratios [[buffer(1)]],
+                      const device half *aspect_ratios [[buffer(0)]],
+                      constant PriorBoxMetalParam &param [[buffer(1)]],
                       const device float4 *variances [[buffer(2)]],
                       uint3 gid [[thread_position_in_grid]]) {
   if (gid.x >= outBoxTexture.get_width() ||

metal/paddle-mobile/paddle-mobile/Operators/PriorBoxOp.swift

@@ -70,17 +70,21 @@ class PriorBoxOp<P: PrecisionType>: Operator<PriorBoxKernel<P>, PriorBoxParam<P>
   
   func delogOutput() {
 
-    // output
     print(" \(type) output: ")
-    let originDim = para.output.originDim
-    if para.output.transpose == [0, 1, 2, 3] {
-      let outputArray: [Float32] = para.output.metalTexture.realNHWC(dim: (n: originDim[0], h: originDim[1], w: originDim[2], c: originDim[3]), texturePrecision: computePrecision)
-      print(outputArray.strideArray())
-    } else if para.output.transpose == [0, 2, 3, 1] {
-      print(para.output.metalTexture.toTensor(dim: (n: originDim[0], c: originDim[1], h: originDim[2], w: originDim[3]), texturePrecision: computePrecision).strideArray())
-    } else {
-      print(" not implement")
-    }
+    // output
+    let outputArray = para.output.metalTexture.float32Array()
+    print(outputArray)
+    // output
+//    print(" \(type) output: ")
+//    let originDim = para.output.originDim
+//    if para.output.transpose == [0, 1, 2, 3] {
+//      let outputArray: [Float32] = para.output.metalTexture.realNHWC(dim: (n: originDim[0], h: originDim[1], w: originDim[2], c: originDim[3]), texturePrecision: computePrecision)
+//      print(outputArray.strideArray())
+//    } else if para.output.transpose == [0, 2, 3, 1] {
+//      print(para.output.metalTexture.toTensor(dim: (n: originDim[0], c: originDim[1], h: originDim[2], w: originDim[3]), texturePrecision: computePrecision).strideArray())
+//    } else {
+//      print(" not implement")
+//    }
     
 //    writeToLibrary(fileName: "box_out", array: outputArray)
     

metal/paddle-mobile/paddle-mobile/Operators/TransposeOp.swift

@@ -48,9 +48,15 @@ class TransposeOp<P: PrecisionType>: Operator<TransposeKernel<P>, TransposeParam
   
   func delogOutput() {
     print(" \(type) output: ")
-    let originDim = para.output.tensorDim
-    let outputArray: [Float32] = para.output.metalTexture.realNHWC(dim: (n: originDim[0], h: originDim[1], w: originDim[2], c: originDim[3]), texturePrecision: computePrecision)
+    let originDim = para.output.originDim
+    if para.output.transpose == [0, 1, 2, 3] {
+      let outputArray = para.output.metalTexture.realNHWC(dim: (n: originDim[0], h: originDim[1], w: originDim[2], c: originDim[3]))
       print(outputArray.strideArray())
+    } else if para.output.transpose == [0, 2, 3, 1] {
+      print(para.output.metalTexture.toTensor(dim: (n: para.output.tensorDim[0], c: para.output.tensorDim[1], h: para.output.tensorDim[2], w: para.output.tensorDim[3])).strideArray())
+    } else {
+      print(" not implement")
+    }
   }
 }