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paddlepaddle--paddle/test/cpp/fluid/math/selected_rows_functor_test.cc
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wehub-resource-sync e25996e7db chore: import upstream snapshot with attribution
2026-07-13 12:40:42 +08:00

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/* Copyright (c) 2016 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/funcs/selected_rows_functor.h"
#include "gtest/gtest.h"
#include "paddle/phi/core/memory/allocation/allocator_facade.h"
#include "paddle/phi/kernels/funcs/math_function.h"
TEST(selected_rows_functor, cpu_add) {
phi::CPUPlace cpu_place;
phi::CPUContext ctx(cpu_place);
ctx.SetAllocator(paddle::memory::allocation::AllocatorFacade::Instance()
.GetAllocator(cpu_place)
.get());
phi::funcs::SetConstant<phi::CPUContext, float> functor;
int64_t height = 10;
int64_t row_numel = 10;
std::vector<int64_t> rows1{0, 4, 7};
std::unique_ptr<phi::SelectedRows> selected_rows1{
new phi::SelectedRows(rows1, height)};
auto* in1_value = selected_rows1->mutable_value();
in1_value->mutable_data<float>(
common::make_ddim({static_cast<int64_t>(rows1.size()), row_numel}),
cpu_place);
functor(ctx, in1_value, 1.0);
std::vector<int64_t> rows2{0, 5, 7, 9};
std::unique_ptr<phi::SelectedRows> selected_rows2{
new phi::SelectedRows(rows2, height)};
auto* in2_value = selected_rows2->mutable_value();
in2_value->mutable_data<float>(
common::make_ddim({static_cast<int64_t>(rows2.size()), row_numel}),
cpu_place);
functor(ctx, in2_value, 2.0);
std::unique_ptr<phi::SelectedRows> output{new phi::SelectedRows()};
auto* out_value = output->mutable_value();
// simply concat two SelectedRows
out_value->mutable_data<float>(common::make_ddim({7, 10}), cpu_place);
phi::funcs::SelectedRowsAdd<phi::CPUContext, float> add_functor;
add_functor(ctx, *selected_rows1, *selected_rows2, output.get());
auto out_height = output->height();
EXPECT_EQ(out_height, height);
auto& out_rows = output->rows();
// input1 rows
EXPECT_EQ(out_rows[0], 0);
EXPECT_EQ(out_rows[1], 4);
EXPECT_EQ(out_rows[2], 7);
// input2 rows
EXPECT_EQ(out_rows[3], 0);
EXPECT_EQ(out_rows[4], 5);
EXPECT_EQ(out_rows[5], 7);
EXPECT_EQ(out_rows[6], 9);
auto* out_data = output->value().data<float>();
// input1 value
EXPECT_EQ(out_data[0 * row_numel + 0], 1.0);
EXPECT_EQ(out_data[0 * row_numel + 8], 1.0);
EXPECT_EQ(out_data[1 * row_numel + 1], 1.0);
EXPECT_EQ(out_data[2 * row_numel + 6], 1.0);
// input2 value
EXPECT_EQ(out_data[3 * row_numel + 3], 2.0);
EXPECT_EQ(out_data[3 * row_numel + 8], 2.0);
EXPECT_EQ(out_data[4 * row_numel + 4], 2.0);
EXPECT_EQ(out_data[5 * row_numel + 7], 2.0);
EXPECT_EQ(out_data[6 * row_numel + 9], 2.0);
std::unique_ptr<phi::DenseTensor> tensor1{new phi::DenseTensor()};
tensor1->mutable_data<float>(common::make_ddim({height, row_numel}),
cpu_place);
functor(ctx, tensor1.get(), 3.0);
std::unique_ptr<phi::DenseTensor> tensor2{new phi::DenseTensor()};
tensor2->mutable_data<float>(common::make_ddim({height, row_numel}),
cpu_place);
phi::funcs::SelectedRowsAddTensor<phi::CPUContext, float> add_tensor_functor;
add_tensor_functor(ctx, *output, *tensor1, tensor2.get());
auto* tensor2_data = tensor2->data<float>();
// row0: 1.0 + 2.0 + 3.0
EXPECT_EQ(tensor2_data[0 * row_numel + 0], 6.0);
// row1: 3.0
EXPECT_EQ(tensor2_data[1 * row_numel + 1], 3.0);
// row4 : 1.0 + 3.0
EXPECT_EQ(tensor2_data[4 * row_numel + 6], 4.0);
// row5: 2.0 + 3.0
EXPECT_EQ(tensor2_data[5 * row_numel + 7], 5.0);
// row6: 3.0
EXPECT_EQ(tensor2_data[6 * row_numel + 1], 3.0);
// row7: 1.0 + 2.0 + 3.0
EXPECT_EQ(tensor2_data[7 * row_numel + 3], 6.0);
// row9: 2.0 + 3.0
EXPECT_EQ(tensor2_data[9 * row_numel + 6], 5.0);
}
TEST(selected_rows_functor, cpu_add_to) {
phi::CPUPlace cpu_place;
phi::CPUContext ctx(cpu_place);
ctx.SetAllocator(paddle::memory::allocation::AllocatorFacade::Instance()
.GetAllocator(cpu_place)
.get());
phi::funcs::SetConstant<phi::CPUContext, float> functor;
int64_t height = 10;
int64_t row_numel = 10;
std::vector<int64_t> rows1{0, 4, 7};
std::unique_ptr<phi::SelectedRows> selected_rows1{
new phi::SelectedRows(rows1, height)};
auto* in1_value = selected_rows1->mutable_value();
in1_value->mutable_data<float>(
common::make_ddim({static_cast<int64_t>(rows1.size()), row_numel}),
cpu_place);
functor(ctx, in1_value, 1.0);
std::vector<int64_t> rows2{0, 5, 7, 9};
std::unique_ptr<phi::SelectedRows> selected_rows2{
new phi::SelectedRows(rows2, height)};
auto* in2_value = selected_rows2->mutable_value();
in2_value->mutable_data<float>(
common::make_ddim({static_cast<int64_t>(rows2.size()), row_numel}),
cpu_place);
functor(ctx, in2_value, 2.0);
std::unique_ptr<phi::SelectedRows> output{new phi::SelectedRows()};
output->set_height(height);
auto* out_value = output->mutable_value();
// simply concat two SelectedRows
out_value->mutable_data<float>(common::make_ddim({7, 10}), cpu_place);
phi::funcs::SelectedRowsAddTo<phi::CPUContext, float> add_to_functor;
add_to_functor(ctx, *selected_rows1, 0, output.get());
add_to_functor(ctx, *selected_rows2, in1_value->numel(), output.get());
auto out_height = output->height();
EXPECT_EQ(out_height, height);
auto& out_rows = output->rows();
// input1 rows
EXPECT_EQ(out_rows[0], 0);
EXPECT_EQ(out_rows[1], 4);
EXPECT_EQ(out_rows[2], 7);
// input2 rows
EXPECT_EQ(out_rows[3], 0);
EXPECT_EQ(out_rows[4], 5);
EXPECT_EQ(out_rows[5], 7);
EXPECT_EQ(out_rows[6], 9);
auto* out_data = output->value().data<float>();
// input1 value
EXPECT_EQ(out_data[0 * row_numel + 0], 1.0);
EXPECT_EQ(out_data[0 * row_numel + 8], 1.0);
EXPECT_EQ(out_data[1 * row_numel + 1], 1.0);
EXPECT_EQ(out_data[2 * row_numel + 6], 1.0);
// input2 value
EXPECT_EQ(out_data[3 * row_numel + 3], 2.0);
EXPECT_EQ(out_data[3 * row_numel + 8], 2.0);
EXPECT_EQ(out_data[4 * row_numel + 4], 2.0);
EXPECT_EQ(out_data[5 * row_numel + 7], 2.0);
EXPECT_EQ(out_data[6 * row_numel + 9], 2.0);
std::unique_ptr<phi::DenseTensor> tensor1{new phi::DenseTensor()};
tensor1->mutable_data<float>(common::make_ddim({height, row_numel}),
cpu_place);
functor(ctx, tensor1.get(), 3.0);
phi::funcs::SelectedRowsAddToTensor<phi::CPUContext, float>
add_to_tensor_functor;
add_to_tensor_functor(ctx, *output, tensor1.get());
auto* tensor1_data = tensor1->data<float>();
// row0: 1.0 + 2.0 + 3.0
EXPECT_EQ(tensor1_data[0 * row_numel + 0], 6.0);
// row1: 3.0
EXPECT_EQ(tensor1_data[1 * row_numel + 1], 3.0);
// row4 : 1.0 + 3.0
EXPECT_EQ(tensor1_data[4 * row_numel + 6], 4.0);
// row5: 2.0 + 3.0
EXPECT_EQ(tensor1_data[5 * row_numel + 7], 5.0);
// row6: 3.0
EXPECT_EQ(tensor1_data[6 * row_numel + 1], 3.0);
// row7: 1.0 + 2.0 + 3.0
EXPECT_EQ(tensor1_data[7 * row_numel + 3], 6.0);
// row9: 2.0 + 3.0
EXPECT_EQ(tensor1_data[9 * row_numel + 6], 5.0);
}
TEST(selected_rows_functor, cpu_merge_average_float) {
phi::CPUPlace cpu_place;
phi::CPUContext ctx(cpu_place);
ctx.SetAllocator(paddle::memory::allocation::AllocatorFacade::Instance()
.GetAllocator(cpu_place)
.get());
phi::funcs::SetConstant<phi::CPUContext, float> functor;
int64_t height = 10;
int64_t row_numel = 10;
std::vector<int64_t> rows{0, 4, 4, 7};
std::unique_ptr<phi::SelectedRows> selected_rows{
new phi::SelectedRows(rows, height)};
auto* in_value = selected_rows->mutable_value();
in_value->mutable_data<float>(
common::make_ddim({static_cast<int64_t>(rows.size()), row_numel}),
cpu_place);
functor(ctx, in_value, 1.0);
phi::funcs::scatter::MergeAverage<phi::CPUContext, float>
merge_average_functor;
phi::SelectedRows output = merge_average_functor(ctx, *selected_rows);
auto out_height = output.height();
EXPECT_EQ(out_height, height);
auto& out_rows = output.rows();
EXPECT_EQ(out_rows[0], 0);
EXPECT_EQ(out_rows[1], 4);
EXPECT_EQ(out_rows[2], 7);
auto* out_data = output.value().data<float>();
EXPECT_EQ(out_data[0 * row_numel], 1.0);
EXPECT_EQ(out_data[1 * row_numel], 2.0);
EXPECT_EQ(out_data[2 * row_numel], 1.0);
}
TEST(selected_rows_functor, cpu_merge_add_float) {
phi::CPUPlace cpu_place;
phi::CPUContext ctx(cpu_place);
ctx.SetAllocator(paddle::memory::allocation::AllocatorFacade::Instance()
.GetAllocator(cpu_place)
.get());
phi::funcs::SetConstant<phi::CPUContext, float> functor;
int64_t height = 10;
int64_t row_numel = 10;
std::vector<int64_t> rows{0, 4, 4, 7};
std::unique_ptr<phi::SelectedRows> selected_rows{
new phi::SelectedRows(rows, height)};
auto* in_value = selected_rows->mutable_value();
in_value->mutable_data<float>(
common::make_ddim({static_cast<int64_t>(rows.size()), row_numel}),
cpu_place);
functor(ctx, in_value, 1.0);
std::unique_ptr<phi::SelectedRows> output{new phi::SelectedRows()};
phi::funcs::scatter::MergeAdd<phi::CPUContext, float> merge_add_functor;
merge_add_functor(ctx, *selected_rows, output.get());
auto out_height = output->height();
EXPECT_EQ(out_height, height);
auto& out_rows = output->rows();
EXPECT_EQ(out_rows[0], 0);
EXPECT_EQ(out_rows[1], 4);
EXPECT_EQ(out_rows[2], 7);
auto* out_data = output->value().data<float>();
EXPECT_EQ(out_data[0 * row_numel], 1.0);
EXPECT_EQ(out_data[1 * row_numel], 2.0);
EXPECT_EQ(out_data[2 * row_numel], 1.0);
}
TEST(selected_rows_functor, cpu_merge_add_int) {
phi::CPUPlace cpu_place;
phi::CPUContext ctx(cpu_place);
ctx.SetAllocator(paddle::memory::allocation::AllocatorFacade::Instance()
.GetAllocator(cpu_place)
.get());
phi::funcs::SetConstant<phi::CPUContext, int> functor;
int64_t height = 10;
int64_t row_numel = 10;
std::vector<int64_t> rows{0, 4, 4, 7};
std::unique_ptr<phi::SelectedRows> selected_rows{
new phi::SelectedRows(rows, height)};
auto* in_value = selected_rows->mutable_value();
in_value->mutable_data<int>(
common::make_ddim({static_cast<int64_t>(rows.size()), row_numel}),
cpu_place);
functor(ctx, in_value, 1);
std::unique_ptr<phi::SelectedRows> output{new phi::SelectedRows()};
phi::funcs::scatter::MergeAdd<phi::CPUContext, int> merge_add_functor;
merge_add_functor(ctx, *selected_rows, output.get());
auto out_height = output->height();
EXPECT_EQ(out_height, height);
auto& out_rows = output->rows();
EXPECT_EQ(out_rows[0], 0);
EXPECT_EQ(out_rows[1], 4);
EXPECT_EQ(out_rows[2], 7);
auto* out_data = output->value().data<int>();
EXPECT_EQ(out_data[0 * row_numel], 1);
EXPECT_EQ(out_data[1 * row_numel], 2);
EXPECT_EQ(out_data[2 * row_numel], 1);
}
TEST(selected_rows_functor, cpu_merge_add_multi) {
phi::CPUPlace cpu_place;
phi::CPUContext ctx(cpu_place);
ctx.SetAllocator(paddle::memory::allocation::AllocatorFacade::Instance()
.GetAllocator(cpu_place)
.get());
phi::funcs::SetConstant<phi::CPUContext, float> set_const;
int64_t height = 10;
int64_t row_numel = 8;
std::vector<int64_t> rows1{5, 2, 5, 3, 5};
std::unique_ptr<phi::SelectedRows> selected_rows1{
new phi::SelectedRows(rows1, height)};
auto* in1_value = selected_rows1->mutable_value();
in1_value->mutable_data<float>(
common::make_ddim({static_cast<int64_t>(rows1.size()), row_numel}),
cpu_place);
set_const(ctx, in1_value, 1.0);
std::vector<int64_t> rows2{2, 5, 3, 5, 3};
std::unique_ptr<phi::SelectedRows> selected_rows2{
new phi::SelectedRows(rows2, height)};
auto* in2_value = selected_rows2->mutable_value();
in2_value->mutable_data<float>(
common::make_ddim({static_cast<int64_t>(rows2.size()), row_numel}),
cpu_place);
set_const(ctx, in2_value, 1.0);
std::unique_ptr<phi::SelectedRows> output{new phi::SelectedRows()};
output->set_height(height);
phi::funcs::scatter::MergeAdd<phi::CPUContext, float> merge_add_functor;
std::vector<const phi::SelectedRows*> inputs;
inputs.push_back(selected_rows1.get());
inputs.push_back(selected_rows2.get());
merge_add_functor(ctx, inputs, output.get());
EXPECT_EQ(output->height(), height);
EXPECT_EQ(output->value().dims(), common::make_ddim({3, row_numel}));
std::vector<int64_t> ret_rows{2, 3, 5};
EXPECT_EQ(output->rows(), ret_rows);
auto* out_data = output->value().data<float>();
for (size_t i = 0; i < ret_rows.size(); ++i) {
for (size_t j = 0; j < static_cast<size_t>(row_numel); ++j) {
EXPECT_EQ(out_data[i * row_numel + j], ret_rows[i]);
}
}
}
TEST(selected_rows_functor, cpu_merge_add_multi_noduplicated) {
phi::CPUPlace cpu_place;
phi::CPUContext ctx(cpu_place);
ctx.SetAllocator(paddle::memory::allocation::AllocatorFacade::Instance()
.GetAllocator(cpu_place)
.get());
phi::funcs::SetConstant<phi::CPUContext, float> set_const;
int64_t height = 10;
int64_t row_numel = 8;
std::vector<int64_t> rows1{1, 3, 5, 7, 9};
std::unique_ptr<phi::SelectedRows> selected_rows1{
new phi::SelectedRows(rows1, height)};
auto* in1_value = selected_rows1->mutable_value();
in1_value->mutable_data<float>(
common::make_ddim({static_cast<int64_t>(rows1.size()), row_numel}),
cpu_place);
set_const(ctx, in1_value, 1.0);
std::vector<int64_t> rows2{0, 2, 4, 6, 8};
std::unique_ptr<phi::SelectedRows> selected_rows2{
new phi::SelectedRows(rows2, height)};
auto* in2_value = selected_rows2->mutable_value();
in2_value->mutable_data<float>(
common::make_ddim({static_cast<int64_t>(rows2.size()), row_numel}),
cpu_place);
set_const(ctx, in2_value, 2.0);
std::unique_ptr<phi::SelectedRows> output{new phi::SelectedRows()};
output->set_height(height);
phi::funcs::scatter::MergeAdd<phi::CPUContext, float> merge_add_functor;
std::vector<const phi::SelectedRows*> inputs;
inputs.push_back(selected_rows1.get());
inputs.push_back(selected_rows2.get());
merge_add_functor(ctx, inputs, output.get());
EXPECT_EQ(output->height(), height);
EXPECT_EQ(output->value().dims(), common::make_ddim({10, row_numel}));
std::vector<int64_t> ret_rows{1, 3, 5, 7, 9, 0, 2, 4, 6, 8};
EXPECT_EQ(output->rows(), ret_rows);
auto* out_data = output->value().data<float>();
for (size_t i = 0; i < ret_rows.size(); ++i) {
float data_value = 0;
if (i < 5) {
data_value = 1.0;
} else {
data_value = 2.0;
}
for (size_t j = 0; j < static_cast<size_t>(row_numel); ++j) {
EXPECT_EQ(out_data[i * row_numel + j], data_value);
}
}
}
TEST(selected_rows_functor, cpu_sum_to) {
phi::CPUPlace cpu_place;
phi::CPUContext ctx(cpu_place);
ctx.SetAllocator(paddle::memory::allocation::AllocatorFacade::Instance()
.GetAllocator(cpu_place)
.get());
phi::funcs::SetConstant<phi::CPUContext, float> functor;
int64_t height = 10;
int64_t row_numel = 10;
std::vector<int64_t> rows1{0, 4, 7};
std::unique_ptr<phi::SelectedRows> selected_rows1{
new phi::SelectedRows(rows1, height)};
auto* in1_value = selected_rows1->mutable_value();
in1_value->mutable_data<float>(
common::make_ddim({static_cast<int64_t>(rows1.size()), row_numel}),
cpu_place);
functor(ctx, in1_value, 1.0);
std::vector<int64_t> rows2{0, 5, 7, 9};
std::unique_ptr<phi::SelectedRows> selected_rows2{
new phi::SelectedRows(rows2, height)};
auto* in2_value = selected_rows2->mutable_value();
in2_value->mutable_data<float>(
common::make_ddim({static_cast<int64_t>(rows2.size()), row_numel}),
cpu_place);
functor(ctx, in2_value, 2.0);
std::unique_ptr<phi::SelectedRows> output{new phi::SelectedRows()};
output->set_height(height);
auto* out_value = output->mutable_value();
// simply concat two SelectedRows
out_value->mutable_data<float>(common::make_ddim({7, 10}), cpu_place);
phi::funcs::SelectedRowsSumTo<phi::CPUContext, float> sum_to_functor;
sum_to_functor(ctx,
std::vector<phi::SelectedRows*>(
{selected_rows1.get(), selected_rows2.get()}),
std::vector<int64_t>({0, in1_value->numel()}),
output.get());
auto out_height = output->height();
EXPECT_EQ(out_height, height);
auto& out_rows = output->rows();
// input1 rows
EXPECT_EQ(out_rows[0], 0);
EXPECT_EQ(out_rows[1], 4);
EXPECT_EQ(out_rows[2], 7);
// input2 rows
EXPECT_EQ(out_rows[3], 0);
EXPECT_EQ(out_rows[4], 5);
EXPECT_EQ(out_rows[5], 7);
EXPECT_EQ(out_rows[6], 9);
auto* out_data = output->value().data<float>();
// input1 value
EXPECT_EQ(out_data[0 * row_numel + 0], 1.0);
EXPECT_EQ(out_data[0 * row_numel + 8], 1.0);
EXPECT_EQ(out_data[1 * row_numel + 1], 1.0);
EXPECT_EQ(out_data[2 * row_numel + 6], 1.0);
// input2 value
EXPECT_EQ(out_data[3 * row_numel + 3], 2.0);
EXPECT_EQ(out_data[3 * row_numel + 8], 2.0);
EXPECT_EQ(out_data[4 * row_numel + 4], 2.0);
EXPECT_EQ(out_data[5 * row_numel + 7], 2.0);
EXPECT_EQ(out_data[6 * row_numel + 9], 2.0);
std::unique_ptr<phi::DenseTensor> tensor1{new phi::DenseTensor()};
tensor1->mutable_data<float>(common::make_ddim({height, row_numel}),
cpu_place);
functor(ctx, tensor1.get(), 3.0);
phi::funcs::SelectedRowsAddToTensor<phi::CPUContext, float>
add_to_tensor_functor;
add_to_tensor_functor(ctx, *output, tensor1.get());
auto* tensor1_data = tensor1->data<float>();
// row0: 1.0 + 2.0 + 3.0
EXPECT_EQ(tensor1_data[0 * row_numel + 0], 6.0);
// row1: 3.0
EXPECT_EQ(tensor1_data[1 * row_numel + 1], 3.0);
// row4 : 1.0 + 3.0
EXPECT_EQ(tensor1_data[4 * row_numel + 6], 4.0);
// row5: 2.0 + 3.0
EXPECT_EQ(tensor1_data[5 * row_numel + 7], 5.0);
// row6: 3.0
EXPECT_EQ(tensor1_data[6 * row_numel + 1], 3.0);
// row7: 1.0 + 2.0 + 3.0
EXPECT_EQ(tensor1_data[7 * row_numel + 3], 6.0);
// row9: 2.0 + 3.0
EXPECT_EQ(tensor1_data[9 * row_numel + 6], 5.0);
}
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