wehub-resource-sync
43 lines
1.6 KiB
C++
43 lines
1.6 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.
|
|
|
|
#include "paddle/phi/kernels/bce_loss_kernel.h"
|
|
|
|
#include "paddle/phi/backends/xpu/enforce_xpu.h"
|
|
#include "paddle/phi/core/kernel_registry.h"
|
|
|
|
namespace phi {
|
|
|
|
template <typename T, typename Context>
|
|
void BCELossKernel(const Context& dev_ctx,
|
|
const DenseTensor& input,
|
|
const DenseTensor& label,
|
|
DenseTensor* out) {
|
|
using XPUType = typename XPUTypeTrait<T>::Type;
|
|
dev_ctx.template Alloc<T>(out);
|
|
|
|
auto x_numel = input.numel();
|
|
int r =
|
|
xpu::bce_loss<XPUType>(dev_ctx.x_context(),
|
|
reinterpret_cast<const XPUType*>(input.data<T>()),
|
|
reinterpret_cast<const XPUType*>(label.data<T>()),
|
|
reinterpret_cast<XPUType*>(out->data<T>()),
|
|
x_numel);
|
|
PADDLE_ENFORCE_XDNN_SUCCESS(r, "bce_loss");
|
|
}
|
|
|
|
} // namespace phi
|
|
|
|
PD_REGISTER_KERNEL(bce_loss, XPU, ALL_LAYOUT, phi::BCELossKernel, float) {}
|