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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/warpctc_grad_kernel.h"
#include "paddle/phi/backends/xpu/enforce_xpu.h"
#include "paddle/phi/backends/xpu/xpu_context.h"
#include "paddle/phi/core/kernel_registry.h"
namespace phi {
template <typename T, typename Context>
void WarpctcGradKernel(const Context& dev_ctx,
const DenseTensor& logits,
const optional<DenseTensor>& logits_length,
const DenseTensor& warpctcgrad,
const DenseTensor& loss_grad,
int blank,
bool norm_by_times,
DenseTensor* logits_grad) {
dev_ctx.template Alloc<T>(logits_grad);
bool has_logits_length = logits_length.is_initialized();
if (!has_logits_length) {
PADDLE_THROW(common::errors::External(
"XPU only support logits_length is_initialized"));
}
int64_t max_seq_length = warpctcgrad.dims()[0]; // Tmax
int64_t num_sequences = warpctcgrad.dims()[1]; // B
int64_t seq_width = warpctcgrad.dims()[2]; // D
auto* logits_length_ptr = logits_length.get_ptr();
int r = xpu::ctc_loss_grad<T, int64_t>(dev_ctx.x_context(),
loss_grad.data<T>(),
logits_grad->data<T>(),
warpctcgrad.data<T>(),
max_seq_length,
num_sequences,
seq_width,
logits_length_ptr->data<int64_t>(),
norm_by_times);
PADDLE_ENFORCE_XDNN_SUCCESS(r, "ctc_loss_grad");
}
} // namespace phi
PD_REGISTER_KERNEL(
warpctc_grad, XPU, ALL_LAYOUT, phi::WarpctcGradKernel, float) {}