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2026-07-13 12:40:42 +08:00

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// 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.
#include "paddle/phi/kernels/tril_indices_kernel.h"
#include "paddle/phi/backends/cpu/cpu_context.h"
#include "paddle/phi/core/kernel_registry.h"
namespace phi {
template <typename T, typename Context>
void TrilIndicesKernel(const Context& dev_ctx,
int rows UNUSED,
int cols,
int offset,
DataType dtype UNUSED,
DenseTensor* out) {
T* out_data = dev_ctx.template Alloc<T>(out);
const auto& out_dims = out->dims();
int64_t tril_size = out_dims[1];
int64_t i = 0;
T r = std::max<int64_t>(0, -offset), c = 0;
while (i < tril_size) {
out_data[i] = r;
out_data[tril_size + i++] = c;
// move to the next column and check if (r, c) is still in bound
c += 1;
if (c > r + offset || c >= cols) {
r += 1;
c = 0;
// NOTE: not necessary to check if r is less than row here, because i
// and tril_size provide the guarantee
}
}
}
} // namespace phi
PD_REGISTER_KERNEL(
tril_indices, CPU, ALL_LAYOUT, phi::TrilIndicesKernel, int, int64_t) {}