wehub-resource-sync
82 lines
3.4 KiB
C++
82 lines
3.4 KiB
C++
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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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#include "paddle/fluid/platform/densetensor_printer.h"
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#include "paddle/fluid/framework/convert_utils.h"
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#include "paddle/fluid/framework/scope.h"
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namespace phi {
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class DenseTensor;
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} // namespace phi
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namespace paddle::framework {
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class Variable;
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} // namespace paddle::framework
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namespace paddle::platform {
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void PrintVar(framework::Scope* scope,
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const std::string& var_name,
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const std::string& print_info,
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std::stringstream* sstream) {
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framework::Variable* var = scope->FindVar(var_name);
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if (var == nullptr) {
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VLOG(0) << "Variable Name " << var_name << " does not exist in your scope";
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return;
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}
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phi::DenseTensor* tensor = var->GetMutable<phi::DenseTensor>();
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if (tensor == nullptr) {
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VLOG(0) << "tensor of variable " << var_name
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<< " does not exist in your scope";
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return;
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}
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if (!tensor->IsInitialized()) {
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VLOG(0) << "tensor of variable " << var_name
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<< " does not initialized in your scope";
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return;
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}
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*sstream << print_info;
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#define PrintTensorCallback(cpp_type, proto_type) \
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do { \
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if (framework::TransToProtoVarType(tensor->dtype()) == proto_type) { \
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*sstream << "["; \
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const cpp_type* data = nullptr; \
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phi::DenseTensor cpu_tensor; \
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if (phi::is_cpu_place(tensor->place())) { \
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data = tensor->data<cpp_type>(); \
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} else { \
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phi::CPUPlace cpu_place; \
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paddle::framework::TensorCopy(*tensor, cpu_place, &cpu_tensor); \
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data = cpu_tensor.data<cpp_type>(); \
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} \
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auto element_num = tensor->numel(); \
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*sstream << element_num << "]:["; \
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if (element_num > 0) { \
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*sstream << data[0]; \
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for (int j = 1; j < element_num; ++j) { \
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*sstream << " " << data[j]; \
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} \
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} \
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*sstream << "]"; \
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} \
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} while (0)
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_ForEachDataType_(PrintTensorCallback);
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}
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} // namespace paddle::platform
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