!11284 [MSLITE][DEVELOP] add npu op instance_norm
From: @yangruoqi713 Reviewed-by: @zhang_xue_tong,@zhanghaibo5 Signed-off-by: @zhang_xue_tongpull/11284/MERGE
mindspore-ci-bot
4 years ago
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commit
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/**
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* Copyright 2021 Huawei Technologies Co., Ltd
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#include "src/runtime/kernel/npu/instance_norm_npu.h"
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#include <memory>
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#include "src/kernel_registry.h"
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#include "src/runtime/agent/npu/npu_converter_utils.h"
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using mindspore::kernel::KERNEL_ARCH::kNPU;
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using mindspore::lite::KernelRegistrar;
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using mindspore::schema::PrimitiveType_InstanceNorm;
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namespace mindspore::kernel {
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int LayerNormNPUKernel::IsSupport(const std::vector<lite::Tensor *> &inputs, const std::vector<lite::Tensor *> &outputs,
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OpParameter *opParameter) {
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return RET_OK;
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}
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int LayerNormNPUKernel::SetNPUInputs(const std::vector<lite::Tensor *> &inputs,
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const std::vector<lite::Tensor *> &outputs,
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const std::vector<ge::Operator *> &npu_inputs) {
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op_ = new (std::nothrow) hiai::op::InstanceNorm(name_);
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if (op_ == nullptr) {
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MS_LOG(ERROR) << "New layer norm npu operator for op " << name_ << " failed.";
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return RET_ERROR;
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}
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op_->set_input_x(*npu_inputs[0]);
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auto gamma = new (std::nothrow) hiai::op::Const(name_ + "_gamma");
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if (gamma == nullptr) {
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MS_LOG(ERROR) << "New gamma const failed.";
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return RET_ERROR;
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}
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auto gamma_shape = inputs[1]->shape();
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std::shared_ptr<ge::Tensor> gamma_tensor = std::shared_ptr<ge::Tensor>(new (std::nothrow) ge::Tensor());
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if (gamma_tensor == nullptr) {
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MS_LOG(ERROR) << "new gamma_tensor failed.";
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return RET_ERROR;
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}
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ge::TensorDesc gamma_tensor_desc(lite::ConverterToNPUShape({1, gamma_shape[0], 1, 1}), ge::FORMAT_NCHW,
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lite::ConverterToNPUDataType(inputs[1]->data_type()));
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gamma_tensor->SetTensorDesc(gamma_tensor_desc);
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gamma_tensor->SetData(reinterpret_cast<const uint8_t *>(inputs.data()), inputs[1]->Size());
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op_->set_input_gamma(*gamma);
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auto beta = new (std::nothrow) hiai::op::Const(name_ + "_beta");
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if (beta == nullptr) {
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MS_LOG(ERROR) << "New beta const failed.";
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return RET_ERROR;
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}
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auto beta_shape = inputs[1]->shape();
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std::shared_ptr<ge::Tensor> beta_tensor = std::shared_ptr<ge::Tensor>(new (std::nothrow) ge::Tensor());
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if (beta_tensor == nullptr) {
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MS_LOG(ERROR) << "new beta_tensor failed.";
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return RET_ERROR;
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}
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ge::TensorDesc beta_tensor_desc(lite::ConverterToNPUShape({1, beta_shape[0], 1, 1}), ge::FORMAT_NCHW,
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lite::ConverterToNPUDataType(inputs[1]->data_type()));
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beta_tensor->SetTensorDesc(beta_tensor_desc);
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beta_tensor->SetData(reinterpret_cast<const uint8_t *>(inputs.data()), inputs[1]->Size());
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op_->set_input_beta(*beta);
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op_->set_attr_epsilon(layer_norm_param_->epsilon_);
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return RET_OK;
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}
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ge::Operator *mindspore::kernel::LayerNormNPUKernel::GetNPUOp() { return this->op_; }
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LayerNormNPUKernel::~LayerNormNPUKernel() {
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if (op_ != nullptr) {
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delete op_;
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op_ = nullptr;
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}
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}
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REG_KERNEL(kNPU, kNumberTypeFloat32, PrimitiveType_InstanceNorm, NPUKernelCreator<LayerNormNPUKernel>)
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} // namespace mindspore::kernel
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@ -0,0 +1,45 @@
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/**
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* Copyright 2021 Huawei Technologies Co., Ltd
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#ifndef MINDSPORE_LITE_SRC_RUNTIME_KERNEL_NPU_LAYER_NORM_NPU_H_
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#define MINDSPORE_LITE_SRC_RUNTIME_KERNEL_NPU_LAYER_NORM_NPU_H_
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#include <vector>
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#include "nnacl/layer_norm_parameter.h"
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#include "src/runtime/kernel/npu/npu_kernel.h"
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#include "include/graph/op/all_ops.h"
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namespace mindspore::kernel {
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class LayerNormNPUKernel : public NPUKernel {
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public:
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LayerNormNPUKernel(OpParameter *parameter, const std::vector<lite::Tensor *> &inputs,
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const std::vector<lite::Tensor *> &outputs, const lite::InnerContext *ctx,
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const mindspore::lite::PrimitiveC *primitive)
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: NPUKernel(parameter, inputs, outputs, ctx, primitive) {
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layer_norm_param_ = reinterpret_cast<LayerNormParameter *>(parameter);
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}
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~LayerNormNPUKernel() override;
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int IsSupport(const std::vector<lite::Tensor *> &inputs, const std::vector<lite::Tensor *> &outputs,
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OpParameter *opParameter) override;
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int SetNPUInputs(const std::vector<lite::Tensor *> &inputs, const std::vector<lite::Tensor *> &outputs,
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const std::vector<ge::Operator *> &npu_inputs) override;
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ge::Operator *GetNPUOp() override;
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private:
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hiai::op::InstanceNorm *op_ = nullptr;
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LayerNormParameter *layer_norm_param_;
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};
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} // namespace mindspore::kernel
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#endif // MINDSPORE_LITE_SRC_RUNTIME_KERNEL_NPU_LAYER_NORM_NPU_H_
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