Files
paddlepaddle--paddle/paddle/phi/kernels/diag_kernel.h
T
2026-07-13 12:40:42 +08:00

62 lines
2.4 KiB
C++

// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#pragma once
#include "paddle/phi/core/dense_tensor.h"
#include "paddle/phi/infermeta/unary.h"
namespace phi {
/**
* @brief If ``x`` is a vector (1-D tensor), a 2-D square tensor with the
* elements of ``x`` as the diagonal is returned.
* If ``x`` is a matrix (2-D tensor), a 1-D tensor with the diagonal
* elements of ``x`` is returned.
*
* The argument ``offset`` controls the diagonal offset:
* If ``offset`` = 0, it is the main diagonal.
* If ``offset`` > 0, it is superdiagonal. If ``offset`` < 0,
* it is subdiagonal.
* @param ctx device context
* @param x The input tensor. Its shape is either 1-D or 2-D.
* @param offset The diagonal offset. A positive value represents
* superdiagonal, 0 represents the main diagonal, and a
* negative value represents subdiagonal.
* @param padding_value Use this value to fill the area outside the specified
* diagonal band. Only takes effect when the input is a
* 1-D Tensor. The default value is 0.
* @param out The output tensor. A square matrix or a vector.
*/
template <typename T, typename Context>
void DiagKernel(const Context& dev_ctx,
const DenseTensor& x,
int offset,
float padding_value,
DenseTensor* out);
template <typename T, typename Context>
DenseTensor Diag(const Context& dev_ctx,
const DenseTensor& x,
int offset,
float padding_value) {
DenseTensor dense_out;
MetaTensor meta_out(&dense_out);
DiagInferMeta(x, offset, padding_value, &meta_out);
DiagKernel<T, Context>(dev_ctx, x, offset, padding_value, &dense_out);
return dense_out;
}
} // namespace phi