wehub-resource-sync
86 lines
2.9 KiB
C++
86 lines
2.9 KiB
C++
// Copyright (c) 2023 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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#include "paddle/phi/kernels/tensor_unfold_kernel.h"
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#include "paddle/common/flags.h"
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#include "paddle/phi/backends/all_context.h"
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#include "paddle/phi/core/kernel_registry.h"
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COMMON_DECLARE_bool(use_stride_kernel);
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namespace phi {
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template <typename Context>
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void TensorUnfoldKernel(const Context& dev_ctx,
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const DenseTensor& input,
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int64_t axis,
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int64_t size,
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int64_t step,
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DenseTensor* out) {
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if (!FLAGS_use_stride_kernel) {
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PADDLE_THROW(common::errors::Fatal(
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"FLAGS_use_stride_kernel is closed. Strided kernel "
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"be called, something wrong has happened!"));
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}
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if (axis < 0) {
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axis += input.dims().size();
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}
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const DDim& input_dims = input.dims();
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const DDim& input_stride = input.strides();
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int64_t max_size =
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input_dims.size() == 0 ? 1 : input_dims[static_cast<int>(axis)];
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PADDLE_ENFORCE_LE(
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size,
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max_size,
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common::errors::InvalidArgument(
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"paddle.unfold size(%d) must be less than shape[axis](%d).",
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size,
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max_size));
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PADDLE_ENFORCE_GT(step,
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0,
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common::errors::InvalidArgument(
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"paddle.unfold step must be greater than 0"));
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std::vector<int64_t> shape(input_dims.size() + 1);
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std::vector<int64_t> stride(input_dims.size() + 1);
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shape[input_dims.size()] = size;
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stride[input_dims.size()] =
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input_dims.size() == 0 ? 1 : input_stride[static_cast<int>(axis)];
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for (int i = 0; i < input_dims.size(); ++i) {
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if (i == axis) {
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shape[i] = (input_dims[i] - size) / step + 1;
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stride[i] = step * input_stride[i];
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} else {
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shape[i] = input_dims[i];
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stride[i] = input_stride[i];
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}
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}
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auto meta = out->meta();
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meta.dims = DDim(shape.data(), static_cast<int>(shape.size()));
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meta.strides = DDim(stride.data(), static_cast<int>(stride.size()));
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meta.offset = input.offset();
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out->set_meta(meta);
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out->ResetHolder(input.Holder());
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out->ShareInplaceVersionCounterWith(input);
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}
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} // namespace phi
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PD_REGISTER_KERNEL_FOR_ALL_BACKEND_DTYPE(tensor_unfold,
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STRIDED,
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phi::TensorUnfoldKernel) {}
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