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!12460 [MS_LITE] fix fp16 conv data type

Browse Source 
From: @YeFeng_24
Reviewed-by: @hangangqiang,@zhanghaibo5
Signed-off-by: @hangangqiang
pull/12460/MERGE
mindspore-ci-bot 4 years ago committed by Gitee
parent cbe2657486 94c65bab90
commit 56e28e1bbd
8 changed files with 38 additions and 24 deletions
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5
mindspore/lite/src/runtime/kernel/arm/fp16/convolution_1x1_fp16.cc
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@ -93,8 +93,7 @@ int Convolution1x1FP16CPUKernel::InitWeightBias() {
MS_LOG(ERROR) << "Conv1x1 Malloc bias_ptr_ error!";
return RET_ERROR;
}
auto bias_tensor = in_tensors_.at(kBiasIndex);
if (bias_tensor->data_type() == kNumberTypeFloat16) {
if (origin_bias_data_type_ == kNumberTypeFloat16) {
memcpy(bias_data_, origin_bias_, output_channel * sizeof(float16_t));
} else {
Float32ToFloat16(reinterpret_cast<float *>(origin_bias_), reinterpret_cast<float16_t *>(bias_data_),
@ -112,7 +111,7 @@ int Convolution1x1FP16CPUKernel::InitWeightBias() {
}
memset(reinterpret_cast<char *>(weight_ptr_) + down_size, 0, size - down_size);
ColMajor2Row8MajorFp16(origin_weight_, weight_ptr_, input_channel, output_channel,
weight_tensor->data_type() == kNumberTypeFloat16);
origin_weight_data_type_ == kNumberTypeFloat16);
return RET_OK;
}

9
mindspore/lite/src/runtime/kernel/arm/fp16/convolution_1x1_fp16.h
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@ -30,10 +30,13 @@ class Convolution1x1FP16CPUKernel : public ConvolutionBaseFP16CPUKernel {
public:
Convolution1x1FP16CPUKernel(OpParameter *parameter, const std::vector<lite::Tensor *> &inputs,
const std::vector<lite::Tensor *> &outputs, const InnerContext *ctx,
const mindspore::lite::PrimitiveC *primitive, void *origin_weight, void *origin_bias)
const mindspore::lite::PrimitiveC *primitive, void *origin_weight, void *origin_bias,
TypeId origin_weight_data_type, TypeId origin_bias_data_type)
: ConvolutionBaseFP16CPUKernel(parameter, inputs, outputs, ctx, primitive),
origin_weight_(origin_weight),
origin_bias_(origin_bias) {}
origin_bias_(origin_bias),
origin_weight_data_type_(origin_weight_data_type),
origin_bias_data_type_(origin_bias_data_type) {}
~Convolution1x1FP16CPUKernel() override;
int Init() override;
@ -62,6 +65,8 @@ class Convolution1x1FP16CPUKernel : public ConvolutionBaseFP16CPUKernel {
float16_t *pack_input_ = nullptr;
float16_t *output_ptr_ = nullptr;
MatMulParameter *matmul_param_ = nullptr;
TypeId origin_weight_data_type_;
TypeId origin_bias_data_type_;
};
} // namespace mindspore::kernel

26
mindspore/lite/src/runtime/kernel/arm/fp16/convolution_delegate_fp16.cc
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@ -67,15 +67,17 @@ int ConvolutionDelegateFP16CPUKernel::Init() {
if (in_tensors_.size() == 3) {
origin_bias_ = CopyData(in_tensors_.at(kBiasIndex));
need_free_ = need_free_ | BIAS_NEED_FREE;
origin_bias_data_type_ = in_tensors_.at(kBiasIndex)->data_type();
}
origin_weight_data_type_ = in_tensors_[1]->data_type();
origin_weight_data_type_ = in_tensors_.at(kWeightIndex)->data_type();
return RET_OK;
}
origin_weight_ = in_tensors_.at(kWeightIndex)->data_c();
if (in_tensors_.size() == 3) {
origin_bias_ = in_tensors_.at(kBiasIndex)->data_c();
origin_bias_data_type_ = in_tensors_.at(kBiasIndex)->data_type();
}
origin_weight_data_type_ = in_tensors_[1]->data_type();
origin_weight_data_type_ = in_tensors_.at(kWeightIndex)->data_type();
return ReSize();
}
@ -84,8 +86,9 @@ int ConvolutionDelegateFP16CPUKernel::ReSize() {
SetInputOutputShapeInfo(reinterpret_cast<ConvParameter *>(op_parameter_), in_tensors_.front(), out_tensors_.front(),
context_);
if (fp16_conv_kernel_ == nullptr) {
fp16_conv_kernel_ = CpuConvFp16KernelSelect(in_tensors_, out_tensors_, op_parameter_, context_, primitive_,
origin_weight_, origin_bias_, origin_weight_data_type_);
fp16_conv_kernel_ =
CpuConvFp16KernelSelect(in_tensors_, out_tensors_, op_parameter_, context_, primitive_, origin_weight_,
origin_bias_, origin_weight_data_type_, origin_bias_data_type_);
if (fp16_conv_kernel_ == nullptr) {
MS_LOG(ERROR) << "Selecting execute kernel failed for conv_kernel, got a nullptr.";
return RET_ERROR;
@ -109,7 +112,8 @@ ConvParameter *CreateNewConvParameterFp16(ConvParameter *parameter) {
kernel::LiteKernel *CpuConvFp16KernelSelect(const std::vector<lite::Tensor *> &inputs,
const std::vector<lite::Tensor *> &outputs, OpParameter *op_parameter,
const lite::InnerContext *ctx, const mindspore::lite::PrimitiveC *primitive,
void *origin_weight, void *origin_bias, TypeId origin_weight_data_type) {
void *origin_weight, void *origin_bias, TypeId origin_weight_data_type,
TypeId origin_bias_data_type) {
auto conv_param = reinterpret_cast<ConvParameter *>(op_parameter);
bool use_winograd = false;
int out_unit;
@ -117,13 +121,15 @@ kernel::LiteKernel *CpuConvFp16KernelSelect(const std::vector<lite::Tensor *> &i
kernel::LiteKernel *kernel = nullptr;
if (conv_param->kernel_h_ == 1 && conv_param->kernel_w_ == 1) {
kernel = new (std::nothrow)
kernel::Convolution1x1FP16CPUKernel(op_parameter, inputs, outputs, ctx, primitive, origin_weight, origin_bias);
kernel::Convolution1x1FP16CPUKernel(op_parameter, inputs, outputs, ctx, primitive, origin_weight, origin_bias,
origin_weight_data_type, origin_bias_data_type);
} else if (use_winograd) {
kernel = new (std::nothrow) kernel::ConvolutionWinogradFP16CPUKernel(op_parameter, inputs, outputs, ctx, primitive,
out_unit, origin_weight, origin_bias);
kernel = new (std::nothrow) kernel::ConvolutionWinogradFP16CPUKernel(
op_parameter, inputs, outputs, ctx, primitive, out_unit, origin_weight, origin_bias, origin_bias_data_type);
} else {
kernel = new (std::nothrow) kernel::ConvolutionFP16CPUKernel(op_parameter, inputs, outputs, ctx, primitive,
origin_weight, origin_bias, origin_weight_data_type);
kernel =
new (std::nothrow) kernel::ConvolutionFP16CPUKernel(op_parameter, inputs, outputs, ctx, primitive, origin_weight,
origin_bias, origin_weight_data_type, origin_bias_data_type);
}
// Once kernel is selected, init func will invoke InitWeightAndBias
auto ret = kernel->Init();

4
mindspore/lite/src/runtime/kernel/arm/fp16/convolution_delegate_fp16.h
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@ -55,12 +55,14 @@ class ConvolutionDelegateFP16CPUKernel : public LiteKernel {
void *origin_bias_ = nullptr;
kernel::LiteKernel *fp16_conv_kernel_ = nullptr;
TypeId origin_weight_data_type_;
TypeId origin_bias_data_type_;
};
kernel::LiteKernel *CpuConvFp16KernelSelect(const std::vector<lite::Tensor *> &inputs,
const std::vector<lite::Tensor *> &outputs, OpParameter *op_parameter,
const lite::InnerContext *ctx, const mindspore::lite::PrimitiveC *primitive,
void *origin_weight, void *origin_bias, TypeId origin_weight_data_type);
void *origin_weight, void *origin_bias, TypeId origin_weight_data_type,
TypeId origin_bias_data_type);
} // namespace mindspore::kernel
#endif // MINDSPORE_LITE_SRC_RUNTIME_KERNEL_ARM_FP16_CONVOLUTION_DELEGATE_FP16_H_

3
mindspore/lite/src/runtime/kernel/arm/fp16/convolution_fp16.cc
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@ -62,8 +62,7 @@ int ConvolutionFP16CPUKernel::InitWeightBias() {
}
memset(bias_data_, 0, oc8 * sizeof(float16_t));
if (in_tensors_.size() == kInputSize2) {
auto bias_tensor = in_tensors_.at(kBiasIndex);
if (bias_tensor->data_type() == kNumberTypeFloat16) {
if (origin_bias_data_type_ == kNumberTypeFloat16) {
memcpy(bias_data_, origin_bias_, out_channel * sizeof(float16_t));
} else {
Float32ToFloat16(reinterpret_cast<float *>(origin_bias_), reinterpret_cast<float16_t *>(bias_data_), out_channel);

6
mindspore/lite/src/runtime/kernel/arm/fp16/convolution_fp16.h
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@ -28,11 +28,12 @@ class ConvolutionFP16CPUKernel : public ConvolutionBaseFP16CPUKernel {
ConvolutionFP16CPUKernel(OpParameter *parameter, const std::vector<lite::Tensor *> &inputs,
const std::vector<lite::Tensor *> &outputs, const InnerContext *ctx,
const mindspore::lite::PrimitiveC *primitive, void *origin_weight, void *origin_bias,
TypeId origin_weight_data_type)
TypeId origin_weight_data_type, TypeId origin_bias_data_type)
: ConvolutionBaseFP16CPUKernel(parameter, inputs, outputs, ctx, primitive),
origin_weight_(origin_weight),
origin_bias_(origin_bias),
origin_weight_data_type_(origin_weight_data_type) {}
origin_weight_data_type_(origin_weight_data_type),
origin_bias_data_type_(origin_bias_data_type) {}
~ConvolutionFP16CPUKernel() override {
if (packed_weight_ != nullptr) {
free(packed_weight_);
@ -65,6 +66,7 @@ class ConvolutionFP16CPUKernel : public ConvolutionBaseFP16CPUKernel {
float16_t *packed_weight_ = nullptr;
float16_t *col_major_input_ = nullptr;
TypeId origin_weight_data_type_;
TypeId origin_bias_data_type_;
};
} // namespace mindspore::kernel

3
mindspore/lite/src/runtime/kernel/arm/fp16/convolution_winograd_fp16.cc
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@ -93,8 +93,7 @@ int ConvolutionWinogradFP16CPUKernel::InitWeightBias() {
memset(bias_data_, 0, oc_block_num * oc_block * sizeof(float16_t));
if (in_tensors_.size() == kInputSize2) {
auto bias_tensor = in_tensors_.at(kBiasIndex);
if (bias_tensor->data_type() == kNumberTypeFloat16) {
if (origin_bias_data_type_ == kNumberTypeFloat16) {
memcpy(bias_data_, origin_bias_, out_channel * sizeof(float16_t));
} else {
Float32ToFloat16(reinterpret_cast<float *>(origin_bias_), reinterpret_cast<float16_t *>(bias_data_), out_channel);

6
mindspore/lite/src/runtime/kernel/arm/fp16/convolution_winograd_fp16.h
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@ -32,11 +32,12 @@ class ConvolutionWinogradFP16CPUKernel : public ConvolutionBaseFP16CPUKernel {
ConvolutionWinogradFP16CPUKernel(OpParameter *parameter, const std::vector<lite::Tensor *> &inputs,
const std::vector<lite::Tensor *> &outputs, const InnerContext *ctx,
const mindspore::lite::PrimitiveC *primitive, int out_unit, void *origin_weight,
void *origin_bias)
void *origin_bias, TypeId origin_bias_data_type)
: ConvolutionBaseFP16CPUKernel(parameter, inputs, outputs, ctx, primitive),
output_unit_(out_unit),
origin_weight_(origin_weight),
origin_bias_(origin_bias) {}
origin_bias_(origin_bias),
origin_bias_data_type_(origin_bias_data_type) {}
~ConvolutionWinogradFP16CPUKernel() override {
if (trans_weight_ != nullptr) {
free(trans_weight_);
@ -86,6 +87,7 @@ class ConvolutionWinogradFP16CPUKernel : public ConvolutionBaseFP16CPUKernel {
TmpBufferAddressFp16 tmp_buffer_address_list_[4];
InputTransFp16Func in_func_;
OutputTransFp16Func out_func_;
TypeId origin_bias_data_type_;
};
} // namespace mindspore::kernel

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