wehub-resource-sync
98 lines
3.3 KiB
C++
98 lines
3.3 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/diagonal_kernel.h"
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#include "glog/logging.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 DiagonalStridedKernel(const Context& dev_ctx,
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const DenseTensor& x,
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int offset,
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int axis1,
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int axis2,
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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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size_t x_rank = x.dims().size();
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if (axis1 < 0) {
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axis1 += static_cast<int>(x_rank);
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}
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if (axis2 < 0) {
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axis2 += static_cast<int>(x_rank);
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}
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int64_t diag_size = 0;
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int64_t x_offset = static_cast<int64_t>(x.offset());
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if (offset >= 0) {
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diag_size = std::max<int64_t>(
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std::min(x.dims()[axis1], x.dims()[axis2] - offset), 0);
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if (diag_size != 0) {
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x_offset +=
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static_cast<int64_t>(offset * x.strides()[axis2] * SizeOf(x.dtype()));
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}
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} else {
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diag_size = std::max<int64_t>(
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std::min(x.dims()[axis1] + offset, x.dims()[axis2]), 0);
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if (diag_size != 0) {
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x_offset -=
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static_cast<int64_t>(offset * x.strides()[axis1] * SizeOf(x.dtype()));
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}
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}
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std::vector<int64_t> shape = vectorize<int64_t>(x.dims());
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std::vector<int64_t> stride = vectorize<int64_t>(x.strides());
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shape.erase(shape.begin() + std::max(axis1, axis2));
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stride.erase(stride.begin() + std::max(axis1, axis2));
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shape.erase(shape.begin() + std::min(axis1, axis2));
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stride.erase(stride.begin() + std::min(axis1, axis2));
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shape.push_back(diag_size);
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stride.push_back(x.strides()[axis1] + x.strides()[axis2]);
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auto meta = out->meta();
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auto tmp_dim = DDim(shape.data(), static_cast<int>(shape.size()));
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// if (product(meta.dims) > 0 && meta.dims != tmp_dim) {
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// PADDLE_THROW(
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// common::errors::Fatal("Diagonal kernel stride compute diff, infer
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// shape
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// "
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// "is %s, but compute is %s.",
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// meta.dims,
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// tmp_dim));
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// }
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meta.dims = tmp_dim;
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meta.strides = DDim(stride.data(), static_cast<int>(stride.size()));
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meta.offset = x_offset;
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out->set_meta(meta);
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out->ResetHolder(x.Holder());
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out->ShareInplaceVersionCounterWith(x);
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}
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} // namespace phi
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PD_REGISTER_KERNEL_FOR_ALL_BACKEND_DTYPE(diagonal,
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STRIDED,
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phi::DiagonalStridedKernel) {}
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