wehub-resource-sync
113 lines
3.9 KiB
C++
113 lines
3.9 KiB
C++
// Copyright (c) 2021 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 <vector>
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#include "paddle/phi/common/int_array.h"
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#include "paddle/phi/common/scalar.h"
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#include "paddle/phi/core/dense_tensor.h"
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#include "paddle/phi/infermeta/nullary.h"
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#include "paddle/phi/kernels/empty_kernel.h"
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namespace phi {
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template <typename T, typename Context>
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void FullKernel(const Context& dev_ctx,
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const IntArray& shape,
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const Scalar& val,
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DataType dtype,
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DenseTensor* out);
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template <typename T, typename Context>
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void FullWithTensorKernel(const Context& dev_ctx,
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const DenseTensor& value,
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const IntArray& shape,
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DataType dtype,
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DenseTensor* out);
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template <typename T, typename Context>
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void FullLikeKernel(const Context& dev_ctx,
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const DenseTensor& x,
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const Scalar& val,
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DataType dtype,
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DenseTensor* out);
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// In order to be compatible with fill_constant_batch_size_like op
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// that are still used in the 2.x APIs
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template <typename T, typename Context>
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void FullBatchSizeLikeKernel(const Context& dev_ctx,
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const DenseTensor& x,
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const std::vector<int>& shape,
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const Scalar& val,
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DataType dtype,
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int x_batch_size_dim,
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int out_batch_size_dim,
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DenseTensor* out);
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template <typename T, typename Context>
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void Full(const Context& dev_ctx,
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const IntArray& shape,
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const Scalar& val,
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DenseTensor* out) {
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if (!out) return;
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FullKernel<T, Context>(
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dev_ctx, shape, val, CppTypeToDataType<T>::Type(), out);
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}
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template <typename T, typename Context>
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void Full(const Context& dev_ctx,
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const DDim& dims,
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const Scalar& val,
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DenseTensor* out) {
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Full<T, Context>(dev_ctx, IntArray(vectorize(dims)), val, out);
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}
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template <typename T, typename Context>
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DenseTensor Full(const Context& dev_ctx,
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const IntArray& shape,
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const Scalar& val) {
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DenseTensor dense_out;
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MetaTensor meta_out(&dense_out);
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DataType dtype = CppTypeToDataType<T>::Type();
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CreateInferMeta(shape, dtype, &meta_out);
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FullKernel<T, Context>(dev_ctx, shape, val, dtype, &dense_out);
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return dense_out;
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}
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template <typename T, typename Context>
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DenseTensor FullLike(const Context& dev_ctx,
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const DenseTensor& x,
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const Scalar& val) {
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DenseTensor dense_out;
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MetaTensor meta_out(&dense_out);
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DataType dtype = CppTypeToDataType<T>::Type();
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CreateLikeInferMeta(x, dtype, &meta_out);
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FullLikeKernel<T, Context>(dev_ctx, x, val, dtype, &dense_out);
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return dense_out;
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}
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template <typename T, typename Context>
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void FullIntArrayKernel(const Context& dev_ctx,
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const std::vector<int64_t>& shape,
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DataType dtype,
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DenseTensor* out);
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#ifdef _WIN32
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#define INSTANTIATE_FULL_KERNEL(type, context) \
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template PADDLE_API void FullKernel<type, context>( \
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const context&, const IntArray&, const Scalar&, DataType, DenseTensor*);
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#endif
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} // namespace phi
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