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提交 11d8528b 编写于 作者: D dolphin8 提交者： GitHub
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Merge pull request #856 from dolphin8/metal 

Metal
上级 81191e32 ca21a861
隐藏空白更改
内联 并排
Showing with 312 addition and 176 deletion
metal/paddle-mobile/paddle-mobile.xcodeproj/project.pbxproj
浏览文件 @ 11d8528b
......@@ -9,6 +9,8 @@
/* Begin PBXBuildFile section */
4AF928772133F1DB005B6C3A /* BoxCoder.metal in Sources */ = {isa = PBXBuildFile; fileRef = 4AF928762133F1DB005B6C3A /* BoxCoder.metal */; };
4AF9287921341661005B6C3A /* Softmax.metal in Sources */ = {isa = PBXBuildFile; fileRef = 4AF9287821341661005B6C3A /* Softmax.metal */; };
4AF928822135673D005B6C3A /* Concat.metal in Sources */ = {isa = PBXBuildFile; fileRef = 4AF928812135673D005B6C3A /* Concat.metal */; };
4AF9288421357BE3005B6C3A /* Elementwise.metal in Sources */ = {isa = PBXBuildFile; fileRef = 4AF9288321357BE3005B6C3A /* Elementwise.metal */; };
D3831F70E7E0B565B9AC22DA /* Pods_paddle_mobile.framework in Frameworks */ = {isa = PBXBuildFile; fileRef = DD2E06330A1E7129C918DB46 /* Pods_paddle_mobile.framework */; };
FC039B6F20E11C3C0081E9F8 /* paddle_mobile.h in Headers */ = {isa = PBXBuildFile; fileRef = FC039B6D20E11C3C0081E9F8 /* paddle_mobile.h */; settings = {ATTRIBUTES = (Public, ); }; };
FC039B9720E11C9A0081E9F8 /* Extensions.swift in Sources */ = {isa = PBXBuildFile; fileRef = FC039B9420E11C9A0081E9F8 /* Extensions.swift */; };
......@@ -90,6 +92,8 @@
/* Begin PBXFileReference section */
4AF928762133F1DB005B6C3A /* BoxCoder.metal */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.metal; path = BoxCoder.metal; sourceTree = "<group>"; };
4AF9287821341661005B6C3A /* Softmax.metal */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.metal; path = Softmax.metal; sourceTree = "<group>"; };
4AF928812135673D005B6C3A /* Concat.metal */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.metal; path = Concat.metal; sourceTree = "<group>"; };
4AF9288321357BE3005B6C3A /* Elementwise.metal */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.metal; path = Elementwise.metal; sourceTree = "<group>"; };
CDF58151D902A1CBAE56A0C2 /* Pods-paddle-mobile.debug.xcconfig */ = {isa = PBXFileReference; includeInIndex = 1; lastKnownFileType = text.xcconfig; name = "Pods-paddle-mobile.debug.xcconfig"; path = "../Pods/Target Support Files/Pods-paddle-mobile/Pods-paddle-mobile.debug.xcconfig"; sourceTree = "<group>"; };
DD2E06330A1E7129C918DB46 /* Pods_paddle_mobile.framework */ = {isa = PBXFileReference; explicitFileType = wrapper.framework; includeInIndex = 0; path = Pods_paddle_mobile.framework; sourceTree = BUILT_PRODUCTS_DIR; };
E2A7957C92EDA5C3BEC0FFC2 /* Pods-paddle-mobile.release.xcconfig */ = {isa = PBXFileReference; includeInIndex = 1; lastKnownFileType = text.xcconfig; name = "Pods-paddle-mobile.release.xcconfig"; path = "../Pods/Target Support Files/Pods-paddle-mobile/Pods-paddle-mobile.release.xcconfig"; sourceTree = "<group>"; };
......@@ -355,6 +359,8 @@
isa = PBXGroup;
children = (
FC27990D21341016000B6BAD /* BoxCoder.metal */,
4AF928812135673D005B6C3A /* Concat.metal */,
4AF9288321357BE3005B6C3A /* Elementwise.metal */,
FC1B16B220EC9A4F00678B91 /* Kernels.metal */,
FC4CB74820F0B954007C0C6D /* ConvKernel.metal */,
4AF928762133F1DB005B6C3A /* BoxCoder.metal */,
......@@ -478,6 +484,7 @@
FCDE8A33212A917900F4A8F6 /* ConvTransposeOp.swift in Sources */,
FCBCCC6B2123071700D94F7E /* BoxcoderOp.swift in Sources */,
FC039B9B20E11CA00081E9F8 /* Executor.swift in Sources */,
4AF9288421357BE3005B6C3A /* Elementwise.metal in Sources */,
FCD04E7020F31B720007374F /* ReshapeKernel.swift in Sources */,
FCD04E7220F343420007374F /* ConvAddOp.swift in Sources */,
FC039BBB20E11CC20081E9F8 /* ProgramDesc.swift in Sources */,
......@@ -515,6 +522,7 @@
FC039BAC20E11CBC0081E9F8 /* BatchNormOp.swift in Sources */,
FCBCCC6F2123097100D94F7E /* MulticlassNMSOp.swift in Sources */,
FC039BBC20E11CC20081E9F8 /* VarDesc.swift in Sources */,
4AF928822135673D005B6C3A /* Concat.metal in Sources */,
FCBCCC632122FCC000D94F7E /* TransposeKernel.swift in Sources */,
FCBCCC71212309A700D94F7E /* MulticlassNMSKernel.swift in Sources */,
FCDC0FEB21099A1D00DC9EFB /* Tools.swift in Sources */,
......
metal/paddle-mobile/paddle-mobile/Operators/ConcatOp.swift
浏览文件 @ 11d8528b
......@@ -25,6 +25,13 @@ class ConcatParam<P: PrecisionType>: OpParam {
guard let variant = inScope[x], let v = variant as? Texture<P> else {
fatalError()
}
if transpose.count == 0 {
transpose = v.transpose
}
if v.transpose != transpose {
fatalError()
}
input.append(v)
}
axis = try ConcatParam.getAttr(key: "axis", attrs: opDesc.attrs)
......@@ -35,6 +42,7 @@ class ConcatParam<P: PrecisionType>: OpParam {
}
var input: [Texture<P>] = []
var output: Texture<P>
var transpose: [Int] = []
let axis: Int
}
......
metal/paddle-mobile/paddle-mobile/Operators/ElementwiseAddOp.swift
浏览文件 @ 11d8528b
......@@ -18,36 +18,42 @@ class ElementwiseAddParam<P: PrecisionType>: OpParam {
typealias ParamPrecisionType = P
required init(opDesc: OpDesc, inScope: Scope) throws {
do {
inputY = try ElementwiseAddParam.inputY(inputs: opDesc.paraInputs, from: inScope)
} catch _ {
do {
inputYTexture = try ElementwiseAddParam.inputX(inputs: opDesc.inputs, from: inScope)
} catch let error {
throw error
}
}
do {
input = try ElementwiseAddParam.inputX(inputs: opDesc.inputs, from: inScope)
inputX = try ElementwiseAddParam.inputX(inputs: opDesc.inputs, 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
}
do {
inputY = try ElementwiseAddParam.inputY(inputs: opDesc.paraInputs, from: inScope)
} catch _ {
let tensorY: Tensor<P> = try ElementwiseAddParam.inputY(inputs: opDesc.paraInputs, from: inScope)
let device = inputX.metalTexture!.device
inputY = Texture.init(device: device, inDim: tensorY.dim)
let value: [P] = Array(UnsafeBufferPointer(start: tensorY.data.pointer, count: tensorY.dim.numel()))
inputY.metalTexture = device.tensor2texture(value: value, dim: tensorY.dim.dims)
}
var offset = axis
if axis == -1 {
offset = inputX.tensorDim.cout() - inputY.tensorDim.cout()
}
for i in 0..<(inputY.tensorDim.cout()) {
assert(inputX.tensorDim[offset + i] == inputY.tensorDim[i])
}
}
var inputYTexture: Texture<P>?
var inputY: Tensor<P>?
var input: Texture<P>
var inputX: Texture<P>
var inputY: Texture<P>
var output: Texture<P>
let axis: Int
var axis: Int
}
class ElementwiseAddOp<P: PrecisionType>: Operator<ElementwiseAddKernel<P>, ElementwiseAddParam<P>>, Runable, Creator, InferShaperable{
typealias OpType = ElementwiseAddOp<P>
func inferShape() {
para.output.dim = para.input.dim
// para.output.dim = para.input.dim
}
func runImpl(device: MTLDevice, buffer: MTLCommandBuffer) throws {
......
metal/paddle-mobile/paddle-mobile/Operators/Kernels/ConcatKernel.swift
浏览文件 @ 11d8528b
......@@ -15,113 +15,117 @@
import Foundation
struct ConcatTestParam: TestParam {
var input: [MTLTexture]
var output: MTLTexture
var dims: [[Int]]
var axis: Int
var odim: [Int]
var input: [MTLTexture]
var output: MTLTexture
var dims: [[Int]]
var axis: Int
var odim: [Int]
}
struct ConcatMetalParam {
var odim: (Int32, Int32, Int32, Int32) = (1, 1, 1, 1)
var axis: Int32 = 0
var offset: Int32 = 0
var vdim: (Int32, Int32, Int32, Int32, Int32, Int32) = (0, 0, 0, 0, 0, 0)
var odim: (Int32, Int32, Int32, Int32) = (1, 1, 1, 1)
var axis: Int32 = 0
var offset: Int32 = 0
var trans: (Int32, Int32, Int32, Int32) = (0, 1, 2, 3)
var vdim: (Int32, Int32, Int32, Int32, Int32, Int32) = (0, 0, 0, 0, 0, 0)
}
class ConcatKernel<P: PrecisionType>: Kernel, Computable{
func encodeTest(_ cmdBuffer: MTLCommandBuffer, _ param: ConcatTestParam, _ istart: Int, _ iend: Int) {
let encoder = cmdBuffer.makeComputeCommandEncoder()!
var p = ConcatMetalParam.init()
var odim: [Int32] = [1, 1, 1, 1]
for i in 0..<param.odim.count {
odim[4-param.odim.count+i] = Int32(param.odim[i])
}
p.odim = (odim[0], odim[1], odim[2], odim[3])
p.axis = Int32(4 - param.odim.count + param.axis)
for i in 0..<istart {
p.offset += Int32(param.dims[i][param.axis])
}
var vdim: [Int32] = []
for i in 0..<(iend - istart) {
encoder.setTexture(param.input[i+istart], index: i)
vdim.append(Int32(param.dims[i+istart][Int(param.axis)]))
}
for i in (iend-istart)..<6 {
encoder.setTexture(param.input[0], index: i)
vdim.append(0)
}
p.vdim = (vdim[0], vdim[1], vdim[2], vdim[3], vdim[4], vdim[5])
encoder.setTexture(param.output, index: 6)
encoder.setTexture(param.output, index: 7)
encoder.setBytes(&p, length: MemoryLayout<ConcatMetalParam>.size, index: 0)
encoder.dispatch(computePipline: pipline, outTexture: param.output)
encoder.endEncoding()
func encodeTest(_ cmdBuffer: MTLCommandBuffer, _ param: ConcatTestParam, _ istart: Int, _ iend: Int) {
let encoder = cmdBuffer.makeComputeCommandEncoder()!
var p = ConcatMetalParam.init()
var odim: [Int32] = [1, 1, 1, 1]
for i in 0..<param.odim.count {
odim[4-param.odim.count+i] = Int32(param.odim[i])
}
func encode(_ cmdBuffer: MTLCommandBuffer, _ param: ConcatParam<P>, _ istart: Int, _ iend: Int) throws {
guard let encoder = cmdBuffer.makeComputeCommandEncoder() else {
throw PaddleMobileError.predictError(message: " encode is nil")
}
var p = ConcatMetalParam.init()
let odim = (0..<4).map { Int32(param.output.dim[$0]) }
p.odim = (odim[0], odim[1], odim[2], odim[3])
p.axis = Int32(4 - param.output.tensorDim.cout() + param.axis)
for i in 0..<istart {
p.offset += Int32(param.input[i+istart].dim[Int(p.axis)])
}
var vdim: [Int32] = []
for i in 0..<(iend - istart) {
encoder.setTexture(param.input[i+istart].metalTexture, index: i)
vdim.append(Int32(param.input[i+istart].dim[Int(p.axis)]))
}
for i in (iend-istart)..<6 {
encoder.setTexture(param.input[0].metalTexture, index: i)
vdim.append(0)
}
p.vdim = (vdim[0], vdim[1], vdim[2], vdim[3], vdim[4], vdim[5])
encoder.setTexture(param.output.metalTexture, index: 6)
encoder.setTexture(param.output.metalTexture, index: 7)
encoder.setBytes(&p, length: MemoryLayout<ConcatMetalParam>.size, index: 0)
encoder.dispatch(computePipline: pipline, outTexture: param.output.metalTexture)
encoder.endEncoding()
p.odim = (odim[0], odim[1], odim[2], odim[3])
p.axis = Int32(4 - param.odim.count + param.axis)
for i in 0..<istart {
p.offset += Int32(param.dims[i][param.axis])
}
func compute(commandBuffer: MTLCommandBuffer, param: ConcatParam<P>) throws {
for i in 0..<param.input.count {
for j in 0..<4 {
assert(param.input[i].transpose[j] == j)
}
}
let group = param.input.count / 6
let remain = param.input.count % 6
for i in 0..<group {
try self.encode(commandBuffer, param, 6 * i, 6 * (i + 1))
}
if remain > 0 {
try self.encode(commandBuffer, param, 6 * group, param.input.count)
}
var vdim: [Int32] = []
for i in 0..<(iend - istart) {
encoder.setTexture(param.input[i+istart], index: i)
vdim.append(Int32(param.dims[i+istart][Int(param.axis)]))
}
func test(cmdBuffer: MTLCommandBuffer, param: ConcatTestParam) {
let group = param.input.count / 6
let remain = param.input.count % 6
for i in 0..<group {
try self.encodeTest(cmdBuffer, param, 6 * i, 6 * (i + 1))
}
if remain > 0 {
try self.encodeTest(cmdBuffer, param, 6 * group, param.input.count)
}
for i in (iend-istart)..<6 {
encoder.setTexture(param.input[0], index: i)
vdim.append(0)
}
required init(device: MTLDevice, param: ConcatParam<P>) {
param.output.initTexture(device: device)
super.init(device: device, inFunctionName: "concat")
p.vdim = (vdim[0], vdim[1], vdim[2], vdim[3], vdim[4], vdim[5])
encoder.setTexture(param.output, index: 6)
encoder.setTexture(param.output, index: 7)
encoder.setBytes(&p, length: MemoryLayout<ConcatMetalParam>.size, index: 0)
encoder.dispatch(computePipline: pipline, outTexture: param.output)
encoder.endEncoding()
}
func encode(_ cmdBuffer: MTLCommandBuffer, _ param: ConcatParam<P>, _ istart: Int, _ iend: Int) throws {
guard let encoder = cmdBuffer.makeComputeCommandEncoder() else {
throw PaddleMobileError.predictError(message: " encode is nil")
}
var p = ConcatMetalParam.init()
let odim = (0..<4).map { Int32(param.output.dim[$0]) }
p.odim = (odim[0], odim[1], odim[2], odim[3])
p.axis = Int32(4 - param.output.tensorDim.cout() + param.axis)
for i in 0..<4 {
if Int32(param.transpose[i]) == p.axis {
p.axis = Int32(i)
break
}
}
for i in 0..<istart {
p.offset += Int32(param.input[i+istart].dim[Int(p.axis)])
}
var vdim: [Int32] = []
for i in 0..<(iend - istart) {
encoder.setTexture(param.input[i+istart].metalTexture, index: i)
vdim.append(Int32(param.input[i+istart].dim[Int(p.axis)]))
}
for i in (iend-istart)..<6 {
encoder.setTexture(param.input[0].metalTexture, index: i)
vdim.append(0)
}
p.trans = (Int32(param.transpose[0]), Int32(param.transpose[1]), Int32(param.transpose[2]), Int32(param.transpose[3]))
p.vdim = (vdim[0], vdim[1], vdim[2], vdim[3], vdim[4], vdim[5])
encoder.setTexture(param.output.metalTexture, index: 6)
encoder.setTexture(param.output.metalTexture, index: 7)
encoder.setBytes(&p, length: MemoryLayout<ConcatMetalParam>.size, index: 0)
encoder.dispatch(computePipline: pipline, outTexture: param.output.metalTexture)
encoder.endEncoding()
}
func compute(commandBuffer: MTLCommandBuffer, param: ConcatParam<P>) throws {
required init(device: MTLDevice, testParam: ConcatTestParam) {
super.init(device: device, inFunctionName: "concat")
let group = param.input.count / 6
let remain = param.input.count % 6
for i in 0..<group {
try self.encode(commandBuffer, param, 6 * i, 6 * (i + 1))
}
if remain > 0 {
try self.encode(commandBuffer, param, 6 * group, param.input.count)
}
}
func test(cmdBuffer: MTLCommandBuffer, param: ConcatTestParam) {
let group = param.input.count / 6
let remain = param.input.count % 6
for i in 0..<group {
self.encodeTest(cmdBuffer, param, 6 * i, 6 * (i + 1))
}
if remain > 0 {
self.encodeTest(cmdBuffer, param, 6 * group, param.input.count)
}
}
required init(device: MTLDevice, param: ConcatParam<P>) {
param.output.initTexture(device: device, inTranspose: param.transpose)
super.init(device: device, inFunctionName: "concat")
}
required init(device: MTLDevice, testParam: ConcatTestParam) {
super.init(device: device, inFunctionName: "concat")
}
}
metal/paddle-mobile/paddle-mobile/Operators/Kernels/ConvTransposeKernel.swift
浏览文件 @ 11d8528b
......@@ -43,6 +43,8 @@ class ConvTransposeKernel<P: PrecisionType>: Kernel, Computable{
let dilationY = UInt16(param.dilations[1])
metalParam = MetalConvTransposeParam.init(kernelW: kernelWidth, kernelH: kernelHeight, strideX: strideX, strideY: strideY, paddingX: paddingX, paddingY: paddingY, dilationX: dilationX, dilationY: dilationY)
param.output.initTexture(device: device, inTranspose: param.input.transpose)
}
func compute(commandBuffer: MTLCommandBuffer, param: ConvTransposeParam<P>) throws {
......
metal/paddle-mobile/paddle-mobile/Operators/Kernels/ElementwiseAddKernel.swift
浏览文件 @ 11d8528b
......@@ -14,14 +14,52 @@
import Foundation
struct ElementwiseAddMetalParam {
var fast: Int32 = 0
var axis: Int32 = 0
var yoff: Int32 = 0
var xdim: (Int32, Int32, Int32, Int32) = (0, 0, 0, 0)
var xtrans: (Int32, Int32, Int32, Int32) = (0, 1, 2, 3)
var ydim: (Int32, Int32, Int32, Int32) = (0, 0, 0, 0)
var ytrans: (Int32, Int32, Int32, Int32) = (0, 1, 2, 3)
}
class ElementwiseAddKernel<P: PrecisionType>: Kernel, Computable {
required init(device: MTLDevice, param: ElementwiseAddParam<P>) {
super.init(device: device, inFunctionName: "elementwise_add")
param.output.initTexture(device: device, inTranspose: param.input.transpose)
param.output.initTexture(device: device, inTranspose: param.inputX.transpose)
}
func compute(commandBuffer: MTLCommandBuffer, param: ElementwiseAddParam<P>) throws {
guard let encoder = commandBuffer.makeComputeCommandEncoder() else {
throw PaddleMobileError.predictError(message: " encode is nil")
}
var emp = ElementwiseAddMetalParam.init()
encoder.setTexture(param.inputX.metalTexture, index: 0)
encoder.setTexture(param.inputY.metalTexture, index: 1)
encoder.setTexture(param.output.metalTexture, index: 2)
let xdim: [Int32] = (0..<4).map { Int32(param.inputX.dim[$0]) }
let ydim: [Int32] = (0..<4).map { Int32(param.inputY.dim[$0]) }
let xtrans: [Int32] = (0..<4).map { Int32(param.inputX.transpose[$0]) }
let ytrans: [Int32] = (0..<4).map { Int32(param.inputY.transpose[$0]) }
emp.xdim = (xdim[0], xdim[1], xdim[2], xdim[3])
emp.ydim = (ydim[0], ydim[1], ydim[2], ydim[3])
emp.xtrans = (xtrans[0], xtrans[1], xtrans[2], xtrans[3])
emp.ytrans = (ytrans[0], ytrans[1], ytrans[2], ytrans[3])
if param.axis == -1 {
emp.axis = 4 - Int32(param.inputY.tensorDim.cout())
} else {
emp.axis = 4 - Int32(param.inputX.tensorDim.cout()) + Int32(param.axis)
}
emp.yoff = 4 - Int32(param.inputY.tensorDim.cout())
if (param.inputX.dim == param.inputY.dim) && (param.inputX.transpose == param.inputY.transpose) {
emp.fast = 1
}
encoder.setBytes(&emp, length: MemoryLayout<ElementwiseAddMetalParam>.size, index: 0)
encoder.dispatch(computePipline: pipline, outTexture: param.output.metalTexture)
encoder.endEncoding()
}
}
metal/paddle-mobile/paddle-mobile/Operators/Kernels/metal/Concat.metal 0 → 100644
浏览文件 @ 11d8528b
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#include <metal_stdlib>
#include "Common.metal"
using namespace metal;
struct ConcatParam {
int32_t odim[4];
int32_t axis;
int32_t offset;
int32_t trans[4];
int32_t vdim[6];
};
kernel void concat(texture2d_array<float, access::read> in0 [[texture(0)]],
texture2d_array<float, access::read> in1 [[texture(1)]],
texture2d_array<float, access::read> in2 [[texture(2)]],
texture2d_array<float, access::read> in3 [[texture(3)]],
texture2d_array<float, access::read> in4 [[texture(4)]],
texture2d_array<float, access::read> in5 [[texture(5)]],
texture2d_array<float, access::read> inx [[texture(6)]],
texture2d_array<float, access::write> out [[texture(7)]],
constant ConcatParam & pm [[buffer(0)]],
uint3 gid [[thread_position_in_grid]]) {
ConcatParam cp = pm;
int xyzn[4] = {int(gid.x), int(gid.y), int(gid.z), 0}, abcd[4], oxyzn[4];
float4 r;
for (int i = 0; i < 4; i++) {
xyzn[3] = i;
xyzn2abcd(cp.odim[3], xyzn, abcd);
int k = abcd[cp.axis] - cp.offset;
int j = 0;
if (k < 0) {
r[i] = inx.read(gid.xy, gid.z)[i];
} else {
for (; j < 6; j++) {
if (k < cp.vdim[j]) {
break;
}
k -= cp.vdim[j];
}
int ta = cp.odim[cp.axis];
abcd[cp.axis] = k;
cp.odim[cp.axis] = cp.vdim[j];
abcd2xyzn(cp.odim[3], abcd, oxyzn);
cp.odim[cp.axis] = ta;
switch (j) {
case 0: r[i] = in0.read(uint2(oxyzn[0], oxyzn[1]), oxyzn[2])[oxyzn[3]]; break;
case 1: r[i] = in1.read(uint2(oxyzn[0], oxyzn[1]), oxyzn[2])[oxyzn[3]]; break;
case 2: r[i] = in2.read(uint2(oxyzn[0], oxyzn[1]), oxyzn[2])[oxyzn[3]]; break;
case 3: r[i] = in3.read(uint2(oxyzn[0], oxyzn[1]), oxyzn[2])[oxyzn[3]]; break;
case 4: r[i] = in4.read(uint2(oxyzn[0], oxyzn[1]), oxyzn[2])[oxyzn[3]]; break;
case 5: r[i] = in5.read(uint2(oxyzn[0], oxyzn[1]), oxyzn[2])[oxyzn[3]]; break;
}
}
}
out.write(r, gid.xy, gid.z);
}
metal/paddle-mobile/paddle-mobile/Operators/Kernels/metal/Elementwise.metal 0 → 100644
浏览文件 @ 11d8528b
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#include <metal_stdlib>
#include "Common.metal"
using namespace metal;
struct ElementwiseAddParam {
int32_t fast;
int32_t axis;
int32_t yoff;
int32_t xdim[4];
int32_t xtrans[4];
int32_t ydim[4];
int32_t ytrans[4];
};
kernel void elementwise_add(texture2d_array<float, access::read> inputX [[texture(0)]],
texture2d_array<float, access::read> inputY [[texture(1)]],
texture2d_array<float, access::write> outTexture [[texture(2)]],
constant ElementwiseAddParam &pm [[buffer(0)]],
uint3 gid [[thread_position_in_grid]]) {
if (gid.x >= outTexture.get_width() ||
gid.y >= outTexture.get_height() ||
gid.z >= outTexture.get_array_size()) return;
float4 rx, ry;
if (pm.fast == 1) {
rx = inputX.read(gid.xy, gid.z);
ry = inputY.read(gid.xy, gid.z);
} else {
rx = inputX.read(gid.xy, gid.z);
int32_t x_xyzn[4] = {int32_t(gid.x), int32_t(gid.y), int32_t(gid.z), 0}, x_abcd[4], t_abcd[4];
int32_t y_abcd[4] = {1, 1, 1, 1}, y_xyzn[4];
int32_t xtrans[4] = {pm.xtrans[0], pm.xtrans[1], pm.xtrans[2], pm.xtrans[3]};
int32_t ytrans[4] = {pm.ytrans[0], pm.ytrans[1], pm.ytrans[2], pm.ytrans[3]};
for (int n = 0; n < 4; n++) {
xyzn2abcd(pm.xdim[3], x_xyzn, x_abcd);
invtrans(xtrans, x_abcd, t_abcd);
for (int k = pm.axis; k < (4 - pm.yoff); k++) {
y_abcd[k+pm.yoff] = t_abcd[k];
}
trans(ytrans, y_abcd, t_abcd);
abcd2xyzn(pm.ydim[3], t_abcd, y_xyzn);
ry[n] = inputY.read(uint2(y_xyzn[0], y_xyzn[1]), y_xyzn[2])[y_xyzn[3]];
}
}
float4 r = rx + ry;
outTexture.write(r, gid.xy, gid.z);
}
metal/paddle-mobile/paddle-mobile/Operators/Kernels/metal/Kernels.metal
浏览文件 @ 11d8528b
......@@ -43,17 +43,6 @@ kernel void resize(texture2d<half, access::read> inTexture [[texture(0)]],
outTexture.write(half4(input.x, input.y, input.z, input.w), gid.xy, gid.z);
}
kernel void elementwise_add(texture2d_array<half, access::read> inTexture [[texture(0)]],
texture2d_array<half, access::write> outTexture [[texture(1)]],
const device half4 *biasTerms [[buffer(0)]],
uint3 gid [[thread_position_in_grid]]) {
if (gid.x >= outTexture.get_width() ||
gid.y >= outTexture.get_height() ||
gid.z >= outTexture.get_array_size()) return;
constexpr sampler s(coord::pixel, filter::nearest, address::clamp_to_zero);
const half4 input = inTexture.read(gid.xy, gid.z);
outTexture.write(input, gid.xy, gid.z);
}
//kernel void texture2d_to_2d_array(texture2d<half, access::read> inTexture [[texture(0)]],
......@@ -200,55 +189,3 @@ kernel void transpose(texture2d_array<float, access::read> inTexture [[texture(0
outTexture.write(r, gid.xy, gid.z);
}
}
struct ConcatParam {
int32_t odim[4];
int32_t axis;
int32_t offset;
int32_t vdim[6];
};
kernel void concat(texture2d_array<float, access::read> in0 [[texture(0)]],
texture2d_array<float, access::read> in1 [[texture(1)]],
texture2d_array<float, access::read> in2 [[texture(2)]],
texture2d_array<float, access::read> in3 [[texture(3)]],
texture2d_array<float, access::read> in4 [[texture(4)]],
texture2d_array<float, access::read> in5 [[texture(5)]],
texture2d_array<float, access::read> inx [[texture(6)]],
texture2d_array<float, access::write> out [[texture(7)]],
constant ConcatParam & pm [[buffer(0)]],
uint3 gid [[thread_position_in_grid]]) {
ConcatParam cp = pm;
int xyzn[4] = {int(gid.x), int(gid.y), int(gid.z), 0}, abcd[4], oxyzn[4];
float4 r;
for (int i = 0; i < 4; i++) {
xyzn[3] = i;
xyzn2abcd(cp.odim[3], xyzn, abcd);
int k = abcd[cp.axis] - cp.offset;
int j = 0;
if (k < 0) {
r[i] = inx.read(gid.xy, gid.z)[i];
} else {
for (; j < 6; j++) {
if (k < cp.vdim[j]) {
break;
}
k -= cp.vdim[j];
}
int ta = cp.odim[cp.axis];
abcd[cp.axis] = k;
cp.odim[cp.axis] = cp.vdim[j];
abcd2xyzn(cp.odim[3], abcd, oxyzn);
cp.odim[cp.axis] = ta;
switch (j) {
case 0: r[i] = in0.read(uint2(oxyzn[0], oxyzn[1]), oxyzn[2])[oxyzn[3]]; break;
case 1: r[i] = in1.read(uint2(oxyzn[0], oxyzn[1]), oxyzn[2])[oxyzn[3]]; break;
case 2: r[i] = in2.read(uint2(oxyzn[0], oxyzn[1]), oxyzn[2])[oxyzn[3]]; break;
case 3: r[i] = in3.read(uint2(oxyzn[0], oxyzn[1]), oxyzn[2])[oxyzn[3]]; break;
case 4: r[i] = in4.read(uint2(oxyzn[0], oxyzn[1]), oxyzn[2])[oxyzn[3]]; break;
case 5: r[i] = in5.read(uint2(oxyzn[0], oxyzn[1]), oxyzn[2])[oxyzn[3]]; break;
}
}
}
out.write(r, gid.xy, gid.z);
}
metal/paddle-mobile/paddle-mobile/Operators/PoolOp.swift
浏览文件 @ 11d8528b
......@@ -26,6 +26,7 @@ class PoolParam<P: PrecisionType>: OpParam {
padding = try PoolParam.getAttr(key: "paddings", attrs: opDesc.attrs)
ceilMode = try PoolParam.getAttr(key: "ceil_mode", attrs: opDesc.attrs)
globalPooling = try PoolParam.getAttr(key: "global_pooling", attrs: opDesc.attrs)
assert(input.transpose == [0, 2, 3, 1])
} catch let error {
throw error
}
......
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