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60 lines
2.1 KiB
60 lines
2.1 KiB
// Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
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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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#pragma once
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#include <algorithm>
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#include <utility>
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#include <vector>
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#include "paddle/fluid/framework/op_registry.h"
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namespace paddle {
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namespace operators {
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using Tensor = framework::Tensor;
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inline std::vector<int64_t> GetNewDataFromShapeTensor(
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const Tensor *new_data_tensor) {
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auto *new_data = new_data_tensor->data<int64_t>();
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if (platform::is_gpu_place(new_data_tensor->place())) {
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framework::Tensor cpu_starts_tensor;
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TensorCopySync(*new_data_tensor, platform::CPUPlace(), &cpu_starts_tensor);
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new_data = cpu_starts_tensor.data<int64_t>();
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}
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std::vector<int64_t> vec_new_data(new_data,
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new_data + new_data_tensor->numel());
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return vec_new_data;
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}
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inline std::vector<int64_t> GetNewDataFromShapeTensorList(
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const std::vector<const Tensor *> &list_new_shape_tensor) {
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std::vector<int64_t> vec_new_shape;
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vec_new_shape.reserve(list_new_shape_tensor.size());
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for (size_t i = 0; i < list_new_shape_tensor.size(); ++i) {
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auto tensor = list_new_shape_tensor[i];
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PADDLE_ENFORCE_EQ(tensor->dims(), framework::make_ddim({1}),
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"shape of dim tensor should be [1]");
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if (platform::is_gpu_place(tensor->place())) {
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framework::Tensor temp;
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TensorCopySync(*tensor, platform::CPUPlace(), &temp);
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vec_new_shape.push_back(*temp.data<int64_t>());
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} else {
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vec_new_shape.push_back(*tensor->data<int64_t>());
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}
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}
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return vec_new_shape;
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}
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} // namespace operators
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} // namespace paddle
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