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96 lines
2.8 KiB
96 lines
2.8 KiB
/* 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/framework/device_worker.h"
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namespace paddle {
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namespace framework {
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void DeviceWorker::SetRootScope(Scope* root_scope) { root_scope_ = root_scope; }
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void DeviceWorker::SetDataFeed(DataFeed* data_feed) {
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device_reader_ = data_feed;
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}
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template <typename T>
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std::string PrintLodTensorType(LoDTensor* tensor, int64_t start, int64_t end) {
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auto count = tensor->numel();
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if (start < 0 || end > count) {
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VLOG(3) << "access violation";
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return "access violation";
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}
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std::ostringstream os;
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for (int64_t i = start; i < end; i++) {
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os << ":" << tensor->data<T>()[i];
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}
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return os.str();
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}
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std::string PrintLodTensorIntType(LoDTensor* tensor, int64_t start,
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int64_t end) {
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auto count = tensor->numel();
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if (start < 0 || end > count) {
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VLOG(3) << "access violation";
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return "access violation";
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}
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std::ostringstream os;
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for (int64_t i = start; i < end; i++) {
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os << ":" << static_cast<uint64_t>(tensor->data<int64_t>()[i]);
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}
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return os.str();
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}
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std::string PrintLodTensor(LoDTensor* tensor, int64_t start, int64_t end) {
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std::string out_val;
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if (tensor->type() == proto::VarType::FP32) {
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out_val = PrintLodTensorType<float>(tensor, start, end);
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} else if (tensor->type() == proto::VarType::INT64) {
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out_val = PrintLodTensorIntType(tensor, start, end);
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} else if (tensor->type() == proto::VarType::FP64) {
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out_val = PrintLodTensorType<double>(tensor, start, end);
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} else {
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out_val = "unsupported type";
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}
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return out_val;
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}
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std::pair<int64_t, int64_t> GetTensorBound(LoDTensor* tensor, int index) {
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auto& dims = tensor->dims();
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if (tensor->lod().size() != 0) {
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auto& lod = tensor->lod()[0];
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return {lod[index] * dims[1], lod[index + 1] * dims[1]};
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} else {
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return {index * dims[1], (index + 1) * dims[1]};
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}
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}
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bool CheckValidOutput(LoDTensor* tensor, size_t batch_size) {
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auto& dims = tensor->dims();
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if (dims.size() != 2) return false;
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if (tensor->lod().size() != 0) {
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auto& lod = tensor->lod()[0];
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if (lod.size() != batch_size + 1) {
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return false;
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}
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} else {
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if (dims[0] != static_cast<int>(batch_size)) {
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return false;
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}
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}
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return true;
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}
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} // namespace framework
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} // namespace paddle
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