wehub-resource-sync
104 lines
3.4 KiB
C++
104 lines
3.4 KiB
C++
// Copyright (c) 2023 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/isfinite_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 IsnanKernel(const Context& dev_ctx,
|
|
const DenseTensor& x,
|
|
DenseTensor* out) {
|
|
using XPUType = typename XPUTypeTrait<T>::Type;
|
|
if (out && out->numel() == 0) {
|
|
dev_ctx.template Alloc<bool>(out);
|
|
return;
|
|
}
|
|
auto* out_data = dev_ctx.template Alloc<bool>(out);
|
|
int r = xpu::isnan<XPUType>(dev_ctx.x_context(),
|
|
reinterpret_cast<const XPUType*>(x.data<T>()),
|
|
out_data,
|
|
x.numel());
|
|
PADDLE_ENFORCE_XDNN_SUCCESS(r, "isnan");
|
|
}
|
|
|
|
template <typename T, typename Context>
|
|
void IsfiniteKernel(const Context& dev_ctx,
|
|
const DenseTensor& x,
|
|
DenseTensor* out) {
|
|
using XPUType = typename XPUTypeTrait<T>::Type;
|
|
if (out && out->numel() == 0) {
|
|
dev_ctx.template Alloc<bool>(out);
|
|
return;
|
|
}
|
|
auto* out_data = dev_ctx.template Alloc<bool>(out);
|
|
int r = xpu::isfinite<XPUType>(dev_ctx.x_context(),
|
|
reinterpret_cast<const XPUType*>(x.data<T>()),
|
|
out_data,
|
|
x.numel());
|
|
PADDLE_ENFORCE_XDNN_SUCCESS(r, "isfinite");
|
|
}
|
|
|
|
template <typename T, typename Context>
|
|
void IsinfKernel(const Context& dev_ctx,
|
|
const DenseTensor& x,
|
|
DenseTensor* out) {
|
|
using XPUType = typename XPUTypeTrait<T>::Type;
|
|
if (out && out->numel() == 0) {
|
|
dev_ctx.template Alloc<bool>(out);
|
|
return;
|
|
}
|
|
auto* out_data = dev_ctx.template Alloc<bool>(out);
|
|
int r = xpu::isinf<XPUType>(dev_ctx.x_context(),
|
|
reinterpret_cast<const XPUType*>(x.data<T>()),
|
|
out_data,
|
|
x.numel());
|
|
PADDLE_ENFORCE_XDNN_SUCCESS(r, "isinf");
|
|
}
|
|
|
|
} // namespace phi
|
|
|
|
PD_REGISTER_KERNEL(isnan,
|
|
XPU,
|
|
ALL_LAYOUT,
|
|
phi::IsnanKernel,
|
|
float,
|
|
phi::float16,
|
|
phi::bfloat16) {
|
|
kernel->OutputAt(0).SetDataType(phi::DataType::BOOL);
|
|
}
|
|
|
|
PD_REGISTER_KERNEL(isfinite,
|
|
XPU,
|
|
ALL_LAYOUT,
|
|
phi::IsfiniteKernel,
|
|
float,
|
|
phi::float16,
|
|
phi::bfloat16) {
|
|
kernel->OutputAt(0).SetDataType(phi::DataType::BOOL);
|
|
}
|
|
PD_REGISTER_KERNEL(isinf,
|
|
XPU,
|
|
ALL_LAYOUT,
|
|
phi::IsinfKernel,
|
|
float,
|
|
phi::float16,
|
|
phi::bfloat16) {
|
|
kernel->OutputAt(0).SetDataType(phi::DataType::BOOL);
|
|
}
|