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