提交 320a6000 编写于 作者: L liuruilong

update

上级 b1ffc144
......@@ -14,7 +14,7 @@
import Foundation
let testTo = 93
let testTo = 94
public class ResultHolder<P: PrecisionType> {
public let dim: [Int]
......
......@@ -61,14 +61,38 @@
}
func delogOutput() {
let outputArray = para.output.metalTexture.floatArray { (o: Float32) -> Float32 in
return o
}
// let outputArray = para.output.metalTexture.floatArray { (o: Float32) -> Float32 in
// return o
// }
let priorBoxOriginDim = para.priorBox.originDim
let priorBoxArray = para.priorBox.metalTexture.realNHWC(dim: (n: priorBoxOriginDim[0], h: priorBoxOriginDim[1], w: priorBoxOriginDim[2], c: priorBoxOriginDim[3]))
print(" prior box ")
print(priorBoxArray.strideArray())
let priorBoxVarOriginDim = para.priorBoxVar.originDim
let priorBoxVarArray = para.priorBoxVar.metalTexture.realNHWC(dim: (n: priorBoxVarOriginDim[0], h: priorBoxVarOriginDim[1], w: priorBoxVarOriginDim[2], c: priorBoxVarOriginDim[3]))
print(" prior box var ")
print(priorBoxVarArray.strideArray())
let targetBoxOriginDim = para.targetBox.originDim
let targetBoxArray = para.targetBox.metalTexture.realNHWC(dim: (n: targetBoxOriginDim[0], h: targetBoxOriginDim[1], w: targetBoxOriginDim[2], c: targetBoxOriginDim[3]))
print(" target box ")
print(targetBoxArray.strideArray())
let originDim = para.output.originDim
let outputArray = para.output.metalTexture.realNHWC(dim: (n: originDim[0], h: originDim[1], w: originDim[2], c: originDim[3]))
print(outputArray.strideArray())
// print(outputArray.strideArray())
//box_coder_0.tmp_0
// writeToLibrary(fileName: "boxcoder_output", array: outputArray)
print(para.output.metalTexture)
print(" write done ")
// print(para.output.metalTexture)
// print(" write done ")
}
}
......
......@@ -60,6 +60,8 @@ class ConcatOp<P: PrecisionType>: Operator<ConcatKernel<P>, ConcatParam<P>>, Run
func delogOutput() {
let originDim = para.output.originDim
let outputArray = para.output.metalTexture.realNHWC(dim: (n: originDim[0], h: originDim[1], w: originDim[2], c: originDim[3]))
print(outputArray.strideArray())
......
......@@ -35,8 +35,18 @@ class PriorBoxKernel<P: PrecisionType>: Kernel, Computable{
required init(device: MTLDevice, param: PriorBoxParam<P>) {
super.init(device: device, inFunctionName: "prior_box")
param.output.initTexture(device: device, inTranspose: [2, 0, 1, 3])
param.outputVariances.initTexture(device: device, inTranspose: [2, 0, 1, 3])
let n = 1
let h = param.output.dim[1]
let w = param.output.dim[2]
let c = param.output.dim[3] * param.output.dim[0]
param.output.dim = Dim.init(inDim: [n, h, w, c])
param.output.transpose = [0, 1, 2, 3]
let imageWidth = Float32(param.inputImage.originDim[3])
let imageHeight = Float32(param.inputImage.originDim[2])
......
......@@ -102,16 +102,14 @@ kernel void reshape(texture2d_array<float, access::read> inTexture [[texture(0)]
outTexture.write(r, gid.xy, gid.z);
}
//
//kernel void reshape_half(texture2d_array<half, access::read> inTexture [[texture(0)]],
// texture2d_array<half, access::write> outTexture [[texture(1)]],
// uint3 gid [[thread_position_in_grid]]) {
// if (gid.x >= outTexture.get_width() ||
// gid.y >= outTexture.get_height() ||
// gid.z >= outTexture.get_array_size()) return;
//
// half4 r = inTexture.read(uint2(0, 0), gid.x);
// outTexture.write(r, gid.xy, gid.z);
//}
kernel void reshape_half(texture2d_array<half, access::read> inTexture [[texture(0)]],
texture2d_array<half, access::write> outTexture [[texture(1)]],
uint3 gid [[thread_position_in_grid]]) {
if (gid.x >= outTexture.get_width() ||
gid.y >= outTexture.get_height() ||
gid.z >= outTexture.get_array_size()) return;
half4 r = inTexture.read(uint2(0, 0), gid.x);
outTexture.write(r, gid.xy, gid.z);
}
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