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Paddle/python/paddle/fluid/tests/custom_op/attr_test_op.cc

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8.7 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 <cstdlib>
#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];
}
}
void CheckAllForwardAttrs(const bool& bool_attr,
const int& int_attr,
const float& float_attr,
const int64_t& int64_attr,
const std::string& str_attr,
const std::vector<int>& int_vec_attr,
const std::vector<float>& float_vec_attr,
const std::vector<int64_t>& int64_vec_attr,
const std::vector<std::string>& str_vec_attr) {
if (bool_attr != true) {
throw std::runtime_error("bool_attr value error.");
}
if (int_attr != 10) {
throw std::runtime_error("int_attr value error.");
}
if (std::abs(float_attr - 3.14) > 1e-6) {
throw std::runtime_error("float_attr value error.");
}
if (int64_attr != 10000000000) {
throw std::runtime_error("int64_attr value error.");
}
if (str_attr != "StrAttr") {
throw std::runtime_error("str_attr value error.");
}
if (int_vec_attr.size() != 3) {
throw std::runtime_error("int_vec_attr size error.");
} else {
for (auto& value : int_vec_attr) {
if (value != 10) {
throw std::runtime_error("int_vec_attr value error.");
}
}
}
if (float_vec_attr.size() != 3) {
throw std::runtime_error("float_vec_attr size error.");
} else {
for (auto& value : float_vec_attr) {
if (std::abs(value - 3.14) > 1e-6) {
throw std::runtime_error("float_vec_attr value error.");
}
}
}
if (int64_vec_attr.size() != 3) {
throw std::runtime_error("int64_vec_attr size error.");
} else {
for (auto& value : int64_vec_attr) {
if (value != 10000000000) {
throw std::runtime_error("int64_vec_attr value error.");
}
}
}
if (str_vec_attr.size() != 3) {
throw std::runtime_error("str_vec_attr size error.");
} else {
for (auto& value : str_vec_attr) {
if (value != "StrAttr") {
throw std::runtime_error("str_vec_attr value error.");
}
}
}
}
void CheckAllBackwardAttrs(const int& int_attr,
const std::vector<float>& float_vec_attr,
const std::vector<std::string>& str_vec_attr) {
if (int_attr != 10) {
throw std::runtime_error("int_attr value error.");
}
if (float_vec_attr.size() != 3) {
throw std::runtime_error("float_vec_attr size error.");
} else {
for (auto& value : float_vec_attr) {
if (std::abs(value - 3.14) > 1e-6) {
throw std::runtime_error("float_vec_attr value error.");
}
}
}
if (str_vec_attr.size() != 3) {
throw std::runtime_error("str_vec_attr size error.");
} else {
for (auto& value : str_vec_attr) {
if (value != "StrAttr") {
throw std::runtime_error("str_vec_attr value error.");
}
}
}
}
std::vector<paddle::Tensor> AttrTestForward(
const paddle::Tensor& x,
bool bool_attr,
int int_attr,
float float_attr,
int64_t int64_attr,
std::string str_attr,
std::vector<int> int_vec_attr,
std::vector<float> float_vec_attr,
std::vector<int64_t> int64_vec_attr,
std::vector<std::string> str_vec_attr) {
auto out = paddle::Tensor(paddle::PlaceType::kCPU);
out.reshape(x.shape());
PD_DISPATCH_FLOATING_TYPES(
x.type(), "assign_cpu_kernel", ([&] {
assign_cpu_kernel<data_t>(
x.data<data_t>(), out.mutable_data<data_t>(), x.size());
}));
// Check attrs value
CheckAllForwardAttrs(bool_attr,
int_attr,
float_attr,
int64_attr,
str_attr,
int_vec_attr,
float_vec_attr,
int64_vec_attr,
str_vec_attr);
return {out};
}
// The attrs of backward op must be the subset of attrs of forward op
std::vector<paddle::Tensor> AttrTestBackward(
const paddle::Tensor& grad_out,
int int_attr,
std::vector<float> float_vec_attr,
std::vector<std::string> str_vec_attr) {
auto grad_x = paddle::Tensor(paddle::PlaceType::kCPU);
grad_x.reshape(grad_out.shape());
PD_DISPATCH_FLOATING_TYPES(grad_out.type(), "assign_cpu_kernel", ([&] {
assign_cpu_kernel<data_t>(
grad_out.data<data_t>(),
grad_x.mutable_data<data_t>(),
grad_out.size());
}));
CheckAllBackwardAttrs(int_attr, float_vec_attr, str_vec_attr);
return {grad_x};
}
std::vector<paddle::Tensor> ConstAttrTestForward(
const paddle::Tensor& x,
const bool& bool_attr,
const int& int_attr,
const float& float_attr,
const int64_t& int64_attr,
const std::string& str_attr,
const std::vector<int>& int_vec_attr,
const std::vector<float>& float_vec_attr,
const std::vector<int64_t>& int64_vec_attr,
const std::vector<std::string>& str_vec_attr) {
auto out = paddle::Tensor(paddle::PlaceType::kCPU);
out.reshape(x.shape());
PD_DISPATCH_FLOATING_TYPES(
x.type(), "assign_cpu_kernel", ([&] {
assign_cpu_kernel<data_t>(
x.data<data_t>(), out.mutable_data<data_t>(), x.size());
}));
// Check attrs value
CheckAllForwardAttrs(bool_attr,
int_attr,
float_attr,
int64_attr,
str_attr,
int_vec_attr,
float_vec_attr,
int64_vec_attr,
str_vec_attr);
return {out};
}
// The attrs of backward op must be the subset of attrs of forward op
std::vector<paddle::Tensor> ConstAttrTestBackward(
const paddle::Tensor& grad_out,
const int& int_attr,
const std::vector<float>& float_vec_attr,
const std::vector<std::string>& str_vec_attr) {
auto grad_x = paddle::Tensor(paddle::PlaceType::kCPU);
grad_x.reshape(grad_out.shape());
PD_DISPATCH_FLOATING_TYPES(grad_out.type(), "assign_cpu_kernel", ([&] {
assign_cpu_kernel<data_t>(
grad_out.data<data_t>(),
grad_x.mutable_data<data_t>(),
grad_out.size());
}));
CheckAllBackwardAttrs(int_attr, float_vec_attr, str_vec_attr);
return {grad_x};
}
PD_BUILD_OP(attr_test)
.Inputs({"X"})
.Outputs({"Out"})
.Attrs({"bool_attr: bool",
"int_attr: int",
"float_attr: float",
"int64_attr: int64_t",
"str_attr: std::string",
"int_vec_attr: std::vector<int>",
"float_vec_attr: std::vector<float>",
"int64_vec_attr: std::vector<int64_t>",
"str_vec_attr: std::vector<std::string>"})
.SetKernelFn(PD_KERNEL(AttrTestForward));
PD_BUILD_GRAD_OP(attr_test)
.Inputs({paddle::Grad("Out")})
.Outputs({paddle::Grad("X")})
.Attrs({"int_attr: int",
"float_vec_attr: std::vector<float>",
"str_vec_attr: std::vector<std::string>"})
.SetKernelFn(PD_KERNEL(AttrTestBackward));
PD_BUILD_OP(const_attr_test)
.Inputs({"X"})
.Outputs({"Out"})
.Attrs({"bool_attr: bool",
"int_attr: int",
"float_attr: float",
"int64_attr: int64_t",
"str_attr: std::string",
"int_vec_attr: std::vector<int>",
"float_vec_attr: std::vector<float>",
"int64_vec_attr: std::vector<int64_t>",
"str_vec_attr: std::vector<std::string>"})
.SetKernelFn(PD_KERNEL(AttrTestForward));
PD_BUILD_GRAD_OP(const_attr_test)
.Inputs({paddle::Grad("Out")})
.Outputs({paddle::Grad("X")})
.Attrs({"int_attr: int",
"float_vec_attr: std::vector<float>",
"str_vec_attr: std::vector<std::string>"})
.SetKernelFn(PD_KERNEL(AttrTestBackward));