未验证 提交 07db4a9f 编写于 作者: R RuohengMa 提交者: GitHub

Dev (#49591)

* add bitwise and, bitwise not, bitwise or and bitwise xor

* correct typo
上级 292738f3
...@@ -66,6 +66,10 @@ XPUOpMap& get_kl2_ops() { ...@@ -66,6 +66,10 @@ XPUOpMap& get_kl2_ops() {
phi::DataType::INT64})}, phi::DataType::INT64})},
{"bilinear_interp_v2", XPUKernelSet({phi::DataType::FLOAT32})}, {"bilinear_interp_v2", XPUKernelSet({phi::DataType::FLOAT32})},
{"bilinear_interp_v2_grad", XPUKernelSet({phi::DataType::FLOAT32})}, {"bilinear_interp_v2_grad", XPUKernelSet({phi::DataType::FLOAT32})},
{"bitwise_and", XPUKernelSet({phi::DataType::BOOL})},
{"bitwise_not", XPUKernelSet({phi::DataType::BOOL})},
{"bitwise_or", XPUKernelSet({phi::DataType::BOOL})},
{"bitwise_xor", XPUKernelSet({phi::DataType::BOOL})},
{"broadcast", XPUKernelSet({phi::DataType::FLOAT32})}, {"broadcast", XPUKernelSet({phi::DataType::FLOAT32})},
{"c_allgather", {"c_allgather",
XPUKernelSet({phi::DataType::FLOAT16, XPUKernelSet({phi::DataType::FLOAT16,
......
// 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/bitwise_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 BitwiseAndKernel(const Context& ctx,
const DenseTensor& x,
const DenseTensor& y,
DenseTensor* out) {
ctx.template Alloc<T>(out);
int r = xpu::logical_and(
ctx.x_context(), x.data<T>(), y.data<T>(), out->data<T>(), x.numel());
PADDLE_ENFORCE_XDNN_SUCCESS(r, "bitwise and");
}
template <typename T, typename Context>
void BitwiseOrKernel(const Context& ctx,
const DenseTensor& x,
const DenseTensor& y,
DenseTensor* out) {
ctx.template Alloc<T>(out);
int r = xpu::logical_or(
ctx.x_context(), x.data<T>(), y.data<T>(), out->data<T>(), x.numel());
PADDLE_ENFORCE_XDNN_SUCCESS(r, "bitwise or");
}
template <typename T, typename Context>
void BitwiseXorKernel(const Context& ctx,
const DenseTensor& x,
const DenseTensor& y,
DenseTensor* out) {
ctx.template Alloc<T>(out);
int r = xpu::logical_xor(
ctx.x_context(), x.data<T>(), y.data<T>(), out->data<T>(), x.numel());
PADDLE_ENFORCE_XDNN_SUCCESS(r, "bitwise xor");
}
template <typename T, typename Context>
void BitwiseNotKernel(const Context& ctx,
const DenseTensor& x,
DenseTensor* out) {
ctx.template Alloc<T>(out);
int r =
xpu::logical_not(ctx.x_context(), x.data<T>(), out->data<T>(), x.numel());
PADDLE_ENFORCE_XDNN_SUCCESS(r, "bitwise not");
}
} // namespace phi
PD_REGISTER_KERNEL(bitwise_and, XPU, ALL_LAYOUT, phi::BitwiseAndKernel, bool) {}
PD_REGISTER_KERNEL(bitwise_or, XPU, ALL_LAYOUT, phi::BitwiseOrKernel, bool) {}
PD_REGISTER_KERNEL(bitwise_xor, XPU, ALL_LAYOUT, phi::BitwiseXorKernel, bool) {}
PD_REGISTER_KERNEL(bitwise_not, XPU, ALL_LAYOUT, phi::BitwiseNotKernel, bool) {}
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