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139 lines
4.0 KiB
139 lines
4.0 KiB
// Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#include <iostream>
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#include <vector>
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#include "paddle/extension.h"
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template <typename data_t>
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void assign_cpu_kernel(const data_t* x_data,
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data_t* out_data,
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int64_t x_numel) {
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for (int i = 0; i < x_numel; ++i) {
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out_data[i] = x_data[i];
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}
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}
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std::vector<paddle::Tensor> DispatchTestInterger(const paddle::Tensor& x) {
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auto out = paddle::Tensor(paddle::PlaceType::kCPU);
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out.reshape(x.shape());
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PD_DISPATCH_INTEGRAL_TYPES(
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x.type(), "assign_cpu_kernel", ([&] {
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assign_cpu_kernel<data_t>(
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x.data<data_t>(), out.mutable_data<data_t>(), x.size());
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}));
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return {out};
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}
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PD_BUILD_OP(dispatch_test_integer)
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.Inputs({"X"})
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.Outputs({"Out"})
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.SetKernelFn(PD_KERNEL(DispatchTestInterger));
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std::vector<paddle::Tensor> DispatchTestFloatAndInteger(
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const paddle::Tensor& x) {
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auto out = paddle::Tensor(paddle::PlaceType::kCPU);
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out.reshape(x.shape());
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PD_DISPATCH_FLOATING_AND_INTEGRAL_TYPES(
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x.type(), "assign_cpu_kernel", ([&] {
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assign_cpu_kernel<data_t>(
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x.data<data_t>(), out.mutable_data<data_t>(), x.size());
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}));
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return {out};
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}
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PD_BUILD_OP(dispatch_test_float_and_integer)
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.Inputs({"X"})
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.Outputs({"Out"})
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.SetKernelFn(PD_KERNEL(DispatchTestFloatAndInteger));
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std::vector<paddle::Tensor> DispatchTestComplex(const paddle::Tensor& x) {
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auto out = paddle::Tensor(paddle::PlaceType::kCPU);
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out.reshape(x.shape());
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PD_DISPATCH_COMPLEX_TYPES(
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x.type(), "assign_cpu_kernel", ([&] {
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assign_cpu_kernel<data_t>(
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x.data<data_t>(), out.mutable_data<data_t>(), x.size());
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}));
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return {out};
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}
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PD_BUILD_OP(dispatch_test_complex)
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.Inputs({"X"})
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.Outputs({"Out"})
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.SetKernelFn(PD_KERNEL(DispatchTestComplex));
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std::vector<paddle::Tensor> DispatchTestFloatAndComplex(
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const paddle::Tensor& x) {
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auto out = paddle::Tensor(paddle::PlaceType::kCPU);
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out.reshape(x.shape());
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PD_DISPATCH_FLOATING_AND_COMPLEX_TYPES(
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x.type(), "assign_cpu_kernel", ([&] {
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assign_cpu_kernel<data_t>(
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x.data<data_t>(), out.mutable_data<data_t>(), x.size());
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}));
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return {out};
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}
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PD_BUILD_OP(dispatch_test_float_and_complex)
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.Inputs({"X"})
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.Outputs({"Out"})
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.SetKernelFn(PD_KERNEL(DispatchTestFloatAndComplex));
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std::vector<paddle::Tensor> DispatchTestFloatAndIntegerAndComplex(
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const paddle::Tensor& x) {
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auto out = paddle::Tensor(paddle::PlaceType::kCPU);
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out.reshape(x.shape());
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PD_DISPATCH_FLOATING_AND_INTEGRAL_AND_COMPLEX_TYPES(
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x.type(), "assign_cpu_kernel", ([&] {
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assign_cpu_kernel<data_t>(
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x.data<data_t>(), out.mutable_data<data_t>(), x.size());
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}));
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return {out};
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}
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PD_BUILD_OP(dispatch_test_float_and_integer_and_complex)
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.Inputs({"X"})
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.Outputs({"Out"})
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.SetKernelFn(PD_KERNEL(DispatchTestFloatAndIntegerAndComplex));
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std::vector<paddle::Tensor> DispatchTestFloatAndHalf(const paddle::Tensor& x) {
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auto out = paddle::Tensor(paddle::PlaceType::kCPU);
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out.reshape(x.shape());
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PD_DISPATCH_FLOATING_AND_HALF_TYPES(
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x.type(), "assign_cpu_kernel", ([&] {
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assign_cpu_kernel<data_t>(
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x.data<data_t>(), out.mutable_data<data_t>(), x.size());
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}));
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return {out};
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}
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PD_BUILD_OP(dispatch_test_float_and_half)
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.Inputs({"X"})
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.Outputs({"Out"})
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.SetKernelFn(PD_KERNEL(DispatchTestFloatAndHalf));
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