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optimize conv2d h=w=1: use fc

This commit is contained in:
chenzupeng 2020-10-27 09:55:06 +08:00
parent 2fac6d0595
commit 31ac9b51ea
4 changed files with 73 additions and 107 deletions
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89
mindspore/lite/src/runtime/kernel/opencl/cl/fullconnection.cl
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@ -3,7 +3,8 @@
#define UP_DIV(x, y) (((x) + (y) - (1)) / (y))
__constant sampler_t smp_zero = CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST;
__kernel void FullConnection_NHWC4(__read_only image2d_t input, __global FLT16 *weight, __read_only image2d_t bias,
__write_only image2d_t output, int4 in_shape, int2 out_shape) {
__write_only image2d_t output, int4 in_shape, int2 out_shape, float act_min,
float act_max) {
int gidx = get_global_id(0); // CO4
int gidz = get_global_id(2); // N
int lidx = get_local_id(0);
@ -12,9 +13,9 @@ __kernel void FullConnection_NHWC4(__read_only image2d_t input, __global FLT16 *
int hwci4 = ci4 * in_shape.y * in_shape.z;
int co4 = UP_DIV(out_shape.y, C4NUM);
int n = out_shape.x;
bool inside = gidx < co4 && gidz < n;
if (gidx >= co4 || gidz >= n) return;
FLT4 result = (FLT4)(0.0f);
for (uint i = lidy; i < hwci4 && inside; i += 4) {
for (uint i = lidy; i < hwci4; i += 4) {
int index_h = i / (ci4 * in_shape.z);
int index_wci4 = i % (ci4 * in_shape.z);
FLT4 v = READ_IMAGE(input, smp_zero, (int2)(index_wci4, gidz * in_shape.y + index_h));
@ -24,83 +25,15 @@ __kernel void FullConnection_NHWC4(__read_only image2d_t input, __global FLT16 *
result.z += dot(v, w.s89ab);
result.w += dot(v, w.scdef);
}
__local FLT4 temp[32][4];
temp[lidx][lidy] = result;
__local FLT4 temp[4];
temp[lidy] = result;
barrier(CLK_LOCAL_MEM_FENCE);
if (lidy == 0 && inside) {
result += temp[lidx][1];
result += temp[lidx][2];
result += temp[lidx][3];
if (lidy == 0) {
result += temp[1];
result += temp[2];
result += temp[3];
result += READ_IMAGE(bias, smp_zero, (int2)(gidx, 0));
result = clamp(result, (FLT)(act_min), (FLT)(act_max));
WRITE_IMAGE(output, (int2)(gidx, gidz), result);
}
}
__kernel void FullConnection_NHWC4_ReLU(__read_only image2d_t input, __global FLT16 *weight, __read_only image2d_t bias,
__write_only image2d_t output, int4 in_shape, int2 out_shape) {
int gidx = get_global_id(0); // CO4
int gidz = get_global_id(2); // N
int lidx = get_local_id(0);
int lidy = get_local_id(1);
int ci4 = UP_DIV(in_shape.w, C4NUM);
int hwci4 = ci4 * in_shape.y * in_shape.z;
int co4 = UP_DIV(out_shape.y, C4NUM);
int n = out_shape.x;
bool inside = gidx < co4 && gidz < n;
FLT4 result = (FLT4)(0.0f);
for (uint i = lidy; i < hwci4 && inside; i += 4) {
int index_h = i / (ci4 * in_shape.z);
int index_wci4 = i % (ci4 * in_shape.z);
FLT4 v = READ_IMAGE(input, smp_zero, (int2)(index_wci4, gidz * in_shape.y + index_h));
FLT16 w = weight[i * co4 + gidx];
result.x += dot(v, w.s0123);
result.y += dot(v, w.s4567);
result.z += dot(v, w.s89ab);
result.w += dot(v, w.scdef);
}
__local FLT4 temp[32][4];
temp[lidx][lidy] = result;
barrier(CLK_LOCAL_MEM_FENCE);
if (lidy == 0 && inside) {
result += temp[lidx][1];
result += temp[lidx][2];
result += temp[lidx][3];
result += READ_IMAGE(bias, smp_zero, (int2)(gidx, 0));
result = max(result, (FLT4)(0.f));
WRITE_IMAGE(output, (int2)(gidx, gidz), result);
}
}
__kernel void FullConnection_NC4HW4(__read_only image2d_t input, __global FLT16 *weight, __read_only image2d_t bias,
__write_only image2d_t output, int4 in_shape, int2 out_shape) {
int gidx = get_global_id(0); // CO4
int gidz = get_global_id(2); // N
int lidx = get_local_id(0);
int lidy = get_local_id(1);
int ci4 = UP_DIV(in_shape.w, C4NUM);
int hwci4 = ci4 * in_shape.y * in_shape.z;
int co4 = UP_DIV(out_shape.y, C4NUM);
int n = out_shape.x;
bool inside = gidx < co4 && gidz < n;
FLT4 result = (FLT4)(0.0f);
for (uint i = lidy; i < hwci4 && inside; i += 4) {
int index_ci4h = i / in_shape.z;
int index_w = i % in_shape.z;
FLT4 v = READ_IMAGE(input, smp_zero, (int2)(index_w, gidz * in_shape.y * ci4 + index_ci4h));
FLT16 w = weight[i * co4 + gidx];
result.x += dot(v, w.s0123);
result.y += dot(v, w.s4567);
result.z += dot(v, w.s89ab);
result.w += dot(v, w.scdef);
}
__local FLT4 temp[32][4];
temp[lidx][lidy] = result;
barrier(CLK_LOCAL_MEM_FENCE);
if (lidy == 0 && inside) {
result += temp[lidx][1];
result += temp[lidx][2];
result += temp[lidx][3];
result += READ_IMAGE(bias, smp_zero, (int2)(gidx, 0));
WRITE_IMAGE(output, (int2)(0, gidz * co4 + gidx), result);
}
}

42
mindspore/lite/src/runtime/kernel/opencl/kernel/convolution.cc
View File

@ -19,6 +19,7 @@
#include <algorithm>
#include "src/common/utils.h"
#include "src/runtime/kernel/opencl/kernel/convolution.h"
#include "src/runtime/kernel/opencl/kernel/fullconnection.h"
#include "src/runtime/kernel/opencl/utils.h"
#include "src/kernel_registry.h"
#include "include/errorcode.h"
@ -29,6 +30,7 @@ using mindspore::lite::KernelRegistrar;
using mindspore::lite::RET_ERROR;
using mindspore::lite::RET_OK;
using mindspore::schema::PrimitiveType_Conv2D;
using mindspore::schema::PrimitiveType_FullConnection;
namespace mindspore::kernel {
@ -339,12 +341,40 @@ kernel::LiteKernel *OpenCLConvolutionKernelCreator(const std::vector<lite::Tenso
const std::vector<lite::Tensor *> &outputs, OpParameter *opParameter,
const lite::InnerContext *ctx, const kernel::KernelKey &desc,
const mindspore::lite::PrimitiveC *primitive) {
auto *kernel =
new (std::nothrow) ConvolutionOpenCLKernel(reinterpret_cast<OpParameter *>(opParameter), inputs, outputs);
if (kernel == nullptr) {
MS_LOG(ERROR) << "Create OpenCL Convolution kernel failed!";
free(opParameter);
return nullptr;
kernel::LiteKernel *kernel;
bool is_hw1 = inputs[0]->shape().size() == 4 && inputs[0]->shape()[1] == 1 && inputs[0]->shape()[2] == 1 &&
outputs[0]->shape().size() == 4 && outputs[0]->shape()[1] == 1 && outputs[0]->shape()[2] == 1;
auto conv_param = reinterpret_cast<ConvParameter *>(opParameter);
bool is_pad_stride_ok = conv_param->kernel_h_ == 1 && conv_param->kernel_w_ == 1 && conv_param->stride_h_ == 1 &&
conv_param->stride_w_ == 1 && conv_param->pad_u_ == 0 && conv_param->pad_d_ == 0 &&
conv_param->pad_l_ == 0 && conv_param->pad_r_ == 0 && conv_param->dilation_h_ == 1 &&
conv_param->dilation_w_ == 1;
if (is_hw1 && is_pad_stride_ok) {
auto param = static_cast<MatMulParameter *>(malloc(sizeof(MatMulParameter)));
if (param == nullptr) {
MS_LOG(ERROR) << "Create OpenCL FullConnection kernel param failed!";
return nullptr;
}
param->op_parameter_.type_ = PrimitiveType_FullConnection;
param->a_transpose_ = false;
param->b_transpose_ = true;
param->act_type_ = conv_param->act_type_;
kernel = new (std::nothrow) FullConnectionOpenCLKernel(reinterpret_cast<OpParameter *>(param), inputs, outputs);
if (kernel == nullptr) {
MS_LOG(ERROR) << "Create OpenCL FullConnection kernel failed!";
free(param);
free(opParameter);
return nullptr;
} else {
free(opParameter);
}
} else {
kernel = new (std::nothrow) ConvolutionOpenCLKernel(reinterpret_cast<OpParameter *>(opParameter), inputs, outputs);
if (kernel == nullptr) {
MS_LOG(ERROR) << "Create OpenCL Convolution kernel failed!";
free(opParameter);
return nullptr;
}
}
auto ret = kernel->Init();
if (ret != mindspore::lite::RET_OK) {

43
mindspore/lite/src/runtime/kernel/opencl/kernel/fullconnection.cc
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@ -20,6 +20,7 @@
#include "nnacl/fp32/common_func.h"
#include "src/kernel_registry.h"
#include "src/runtime/kernel/opencl/kernel/fullconnection.h"
#include "src/runtime/kernel/opencl/utils.h"
#ifndef PROGRAM_WITH_IL
#include "src/runtime/kernel/opencl/cl/fullconnection.cl.inc"
#endif
@ -43,23 +44,22 @@ int FullConnectionOpenCLKernel::Init() {
transposeB = param->b_transpose_;
enable_fp16_ = ocl_runtime_->GetFp16Enable();
if ((in_tensors_[0]->shape().size() != 4 && in_tensors_[0]->shape().size() != 2) ||
out_tensors_[0]->shape().size() != 2) {
MS_LOG(ERROR) << "fullconnection only support input shape size = 2 or 4";
(out_tensors_[0]->shape().size() != 4 && out_tensors_[0]->shape().size() != 2)) {
MS_LOG(ERROR) << "fullconnection only support input output shape size = 2 or 4";
return RET_ERROR;
}
if (in_tensors_[0]->shape().size() == 4) {
inShape = {in_tensors_[0]->shape()[0], in_tensors_[0]->shape()[1], in_tensors_[0]->shape()[2],
in_tensors_[0]->shape()[3]};
} else {
inShape = {in_tensors_[0]->shape()[0], 1, 1, in_tensors_[0]->shape()[1]};
}
outShape = out_tensors_[0]->shape();
// call default move constructor(elemwised moved)
inShape = Image2DInfo(in_tensors_[0]);
outShape = Image2DInfo(out_tensors_[0]);
switch (param->act_type_) {
case ActType_No:
break;
case ActType_Relu:
kernel_name += "_ReLU";
activation_min_ = 0.f;
break;
case ActType_Relu6:
activation_min_ = 0.f;
activation_max_ = 6.f;
break;
default:
MS_LOG(ERROR) << "Unsupported activation type " << param->act_type_;
@ -81,14 +81,13 @@ int FullConnectionOpenCLKernel::Init() {
}
void FullConnectionOpenCLKernel::PadWeight() {
// ABMCI @ ABCICO = ABMCO
auto allocator = ocl_runtime_->GetAllocator();
int ci = inShape[3];
int ci = inShape.C;
int ci4 = UP_DIV(ci, C4NUM);
int co = outShape[1];
int co = outShape.C;
int co4 = UP_DIV(co, C4NUM);
int h = inShape[1];
int w = inShape[2];
int h = inShape.H;
int w = inShape.W;
size_t dtype_size = enable_fp16_ ? sizeof(uint16_t) : sizeof(float);
padWeight_ = allocator->Malloc(h * w * ci4 * co4 * C4NUM * C4NUM * dtype_size);
@ -172,18 +171,20 @@ void FullConnectionOpenCLKernel::PadWeight() {
int FullConnectionOpenCLKernel::Run() {
MS_LOG(DEBUG) << this->name() << " Running!";
// local size should less than MAX_GROUP_SIZE
std::vector<size_t> local = {32, 4, 1};
std::vector<size_t> global = {UP_DIV(static_cast<size_t>(outShape[1]), C4NUM), 4, static_cast<size_t>(outShape[0])};
std::vector<size_t> local = {1, 4, 1};
std::vector<size_t> global = {UP_DIV(outShape.C, C4NUM), 4, outShape.N};
int arg_count = 0;
cl_int4 in_shape = {inShape[0], inShape[1], inShape[2], inShape[3]};
cl_int2 out_shape = {outShape[0], outShape[1]};
cl_int4 in_shape = {static_cast<int>(inShape.N), static_cast<int>(inShape.H), static_cast<int>(inShape.W),
static_cast<int>(inShape.C)};
cl_int2 out_shape = {static_cast<int>(outShape.N), static_cast<int>(outShape.C)};
ocl_runtime_->SetKernelArg(kernel_, arg_count++, in_tensors_[0]->data_c());
ocl_runtime_->SetKernelArg(kernel_, arg_count++, padWeight_, lite::opencl::MemType::BUF);
ocl_runtime_->SetKernelArg(kernel_, arg_count++, bias_);
ocl_runtime_->SetKernelArg(kernel_, arg_count++, out_tensors_[0]->data_c());
ocl_runtime_->SetKernelArg(kernel_, arg_count++, in_shape);
ocl_runtime_->SetKernelArg(kernel_, arg_count++, out_shape);
ocl_runtime_->SetKernelArg(kernel_, arg_count++, activation_min_);
ocl_runtime_->SetKernelArg(kernel_, arg_count++, activation_max_);
ocl_runtime_->RunKernel(kernel_, global, local, nullptr);
return RET_OK;
}

6
mindspore/lite/src/runtime/kernel/opencl/kernel/fullconnection.h
View File

@ -43,8 +43,10 @@ class FullConnectionOpenCLKernel : public OpenCLKernel {
bool enable_fp16_{false};
bool transposeA{false};
bool transposeB{true};
std::vector<int> inShape;
std::vector<int> outShape;
float activation_min_{-FLT_MAX};
float activation_max_{FLT_MAX};
Image2DInfo inShape = Image2DInfo(nullptr);
Image2DInfo outShape = Image2DInfo(nullptr);
};
} // namespace mindspore::kernel