You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
Paddle/python/paddle/fluid/tests/custom_op/dispatch_test_op.cc

139 lines
4.0 KiB

// Copyright (c) 2021 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 <iostream>
#include <vector>
#include "paddle/extension.h"
template <typename data_t>
void assign_cpu_kernel(const data_t* x_data,
data_t* out_data,
int64_t x_numel) {
for (int i = 0; i < x_numel; ++i) {
out_data[i] = x_data[i];
}
}
std::vector<paddle::Tensor> DispatchTestInterger(const paddle::Tensor& x) {
auto out = paddle::Tensor(paddle::PlaceType::kCPU);
out.reshape(x.shape());
PD_DISPATCH_INTEGRAL_TYPES(
x.type(), "assign_cpu_kernel", ([&] {
assign_cpu_kernel<data_t>(
x.data<data_t>(), out.mutable_data<data_t>(), x.size());
}));
return {out};
}
PD_BUILD_OP(dispatch_test_integer)
.Inputs({"X"})
.Outputs({"Out"})
.SetKernelFn(PD_KERNEL(DispatchTestInterger));
std::vector<paddle::Tensor> DispatchTestFloatAndInteger(
const paddle::Tensor& x) {
auto out = paddle::Tensor(paddle::PlaceType::kCPU);
out.reshape(x.shape());
PD_DISPATCH_FLOATING_AND_INTEGRAL_TYPES(
x.type(), "assign_cpu_kernel", ([&] {
assign_cpu_kernel<data_t>(
x.data<data_t>(), out.mutable_data<data_t>(), x.size());
}));
return {out};
}
PD_BUILD_OP(dispatch_test_float_and_integer)
.Inputs({"X"})
.Outputs({"Out"})
.SetKernelFn(PD_KERNEL(DispatchTestFloatAndInteger));
std::vector<paddle::Tensor> DispatchTestComplex(const paddle::Tensor& x) {
auto out = paddle::Tensor(paddle::PlaceType::kCPU);
out.reshape(x.shape());
PD_DISPATCH_COMPLEX_TYPES(
x.type(), "assign_cpu_kernel", ([&] {
assign_cpu_kernel<data_t>(
x.data<data_t>(), out.mutable_data<data_t>(), x.size());
}));
return {out};
}
PD_BUILD_OP(dispatch_test_complex)
.Inputs({"X"})
.Outputs({"Out"})
.SetKernelFn(PD_KERNEL(DispatchTestComplex));
std::vector<paddle::Tensor> DispatchTestFloatAndComplex(
const paddle::Tensor& x) {
auto out = paddle::Tensor(paddle::PlaceType::kCPU);
out.reshape(x.shape());
PD_DISPATCH_FLOATING_AND_COMPLEX_TYPES(
x.type(), "assign_cpu_kernel", ([&] {
assign_cpu_kernel<data_t>(
x.data<data_t>(), out.mutable_data<data_t>(), x.size());
}));
return {out};
}
PD_BUILD_OP(dispatch_test_float_and_complex)
.Inputs({"X"})
.Outputs({"Out"})
.SetKernelFn(PD_KERNEL(DispatchTestFloatAndComplex));
std::vector<paddle::Tensor> DispatchTestFloatAndIntegerAndComplex(
const paddle::Tensor& x) {
auto out = paddle::Tensor(paddle::PlaceType::kCPU);
out.reshape(x.shape());
PD_DISPATCH_FLOATING_AND_INTEGRAL_AND_COMPLEX_TYPES(
x.type(), "assign_cpu_kernel", ([&] {
assign_cpu_kernel<data_t>(
x.data<data_t>(), out.mutable_data<data_t>(), x.size());
}));
return {out};
}
PD_BUILD_OP(dispatch_test_float_and_integer_and_complex)
.Inputs({"X"})
.Outputs({"Out"})
.SetKernelFn(PD_KERNEL(DispatchTestFloatAndIntegerAndComplex));
std::vector<paddle::Tensor> DispatchTestFloatAndHalf(const paddle::Tensor& x) {
auto out = paddle::Tensor(paddle::PlaceType::kCPU);
out.reshape(x.shape());
PD_DISPATCH_FLOATING_AND_HALF_TYPES(
x.type(), "assign_cpu_kernel", ([&] {
assign_cpu_kernel<data_t>(
x.data<data_t>(), out.mutable_data<data_t>(), x.size());
}));
return {out};
}
PD_BUILD_OP(dispatch_test_float_and_half)
.Inputs({"X"})
.Outputs({"Out"})
.SetKernelFn(PD_KERNEL(DispatchTestFloatAndHalf));