chore: import upstream snapshot with attribution
This commit is contained in:
wehub-resource-sync
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/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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 <string>
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#include <vector>
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#include "gtest/gtest.h"
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#include "paddle/fluid/framework/op_registry.h"
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#include "paddle/phi/common/bfloat16.h"
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#include "paddle/phi/common/float16.h"
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#include "paddle/phi/core/kernel_registry.h"
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template <typename T, typename U>
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T* CreateForSaveCombineOp(int x,
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int y,
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const std::vector<int>& lod_info,
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std::string var_name,
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const phi::CPUPlace& place,
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paddle::framework::Scope* scope,
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phi::LegacyLoD* expect_lod) {
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auto var = scope->Var(var_name);
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auto tensor = var->GetMutable<phi::DenseTensor>();
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tensor->Resize({x, y});
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expect_lod->resize(1);
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for (auto item : lod_info) {
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(*expect_lod)[0].push_back(item);
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}
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tensor->set_lod(*expect_lod);
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T* expect = tensor->mutable_data<T>(place);
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for (int64_t i = 0; i < tensor->numel(); ++i) {
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expect[i] = static_cast<T>(
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static_cast<U>(i)); // For FP16, we intend to do float(float16(i))
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}
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return expect;
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}
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phi::DenseTensor* GeneratePlaceholderBeforeLoad(
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const std::string out_var_name, paddle::framework::Scope* scope) {
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auto load_var = scope->Var(out_var_name);
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auto target = load_var->GetMutable<phi::DenseTensor>();
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return target;
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}
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template <typename T>
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T* GetValuesAfterLoadCombineOp(phi::DenseTensor* target,
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const paddle::framework::Scope& scope,
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phi::LegacyLoD* actual_lod) {
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T* actual = target->data<T>();
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*actual_lod = target->lod();
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return actual;
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}
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template <typename T, typename U>
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void CheckValues(T* expect,
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U* actual,
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const phi::LegacyLoD& expect_lod,
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const phi::LegacyLoD& actual_lod,
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const int& numel) {
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for (int i = 0; i < numel; ++i) {
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EXPECT_EQ(expect[i], static_cast<T>(actual[i]));
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}
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EXPECT_EQ(expect_lod.size(), actual_lod.size());
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for (size_t i = 0; i < expect_lod.size(); ++i) { // NOLINT
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for (size_t j = 0; j < expect_lod[i].size(); ++j) {
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EXPECT_EQ(expect_lod[i][j], actual_lod[i][j]);
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}
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}
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}
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// Here, we create 4 DenseTensors and use save_combine_op to first save these
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// in a single file. Then, we use load_combine_op to load these sequentially
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template <typename T, typename U>
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void SaveLoadCombineOp() {
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paddle::framework::Scope scope;
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phi::CPUPlace place;
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std::vector<int> lod1 = {0, 1, 2, 3, 10};
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int numel1 = 100;
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phi::LegacyLoD expect_lod1;
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T* expect1 = CreateForSaveCombineOp<T, U>(
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10, 10, lod1, "test_var1", place, &scope, &expect_lod1);
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std::vector<int> lod2 = {0, 2, 5, 10};
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int numel2 = 200;
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phi::LegacyLoD expect_lod2;
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T* expect2 = CreateForSaveCombineOp<T, U>(
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10, 20, lod2, "test_var2", place, &scope, &expect_lod2);
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std::vector<int> lod3 = {0, 2, 3, 20};
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int numel3 = 4000;
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phi::LegacyLoD expect_lod3;
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T* expect3 = CreateForSaveCombineOp<T, U>(
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20, 200, lod3, "test_var3", place, &scope, &expect_lod3);
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std::vector<int> lod4 = {0, 1, 20};
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int numel4 = 1000;
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phi::LegacyLoD expect_lod4;
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T* expect4 = CreateForSaveCombineOp<T, U>(
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20, 50, lod4, "test_var4", place, &scope, &expect_lod4);
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// Set attributes
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std::string filename = "check_tensor.ls";
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paddle::framework::AttributeMap attrs;
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attrs.insert({"file_path", std::string(filename)});
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// Run the save_combine_op
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auto save_combine_op = paddle::framework::OpRegistry::CreateOp(
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"save_combine",
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{{"X", {"test_var1", "test_var2", "test_var3", "test_var4"}}},
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{},
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attrs);
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save_combine_op->Run(scope, place);
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// Set up output vars
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auto target1 = GeneratePlaceholderBeforeLoad("out_var1", &scope);
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auto target2 = GeneratePlaceholderBeforeLoad("out_var2", &scope);
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auto target3 = GeneratePlaceholderBeforeLoad("out_var3", &scope);
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auto target4 = GeneratePlaceholderBeforeLoad("out_var4", &scope);
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// Run the load_combine_op
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auto load_combine_op = paddle::framework::OpRegistry::CreateOp(
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"load_combine",
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{},
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{{"Out", {"out_var1", "out_var2", "out_var3", "out_var4"}}},
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attrs);
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load_combine_op->Run(scope, place);
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phi::LegacyLoD actual_lod1, actual_lod2, actual_lod3, actual_lod4;
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U* actual1 = GetValuesAfterLoadCombineOp<U>(target1, scope, &actual_lod1);
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U* actual2 = GetValuesAfterLoadCombineOp<U>(target2, scope, &actual_lod2);
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U* actual3 = GetValuesAfterLoadCombineOp<U>(target3, scope, &actual_lod3);
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U* actual4 = GetValuesAfterLoadCombineOp<U>(target4, scope, &actual_lod4);
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CheckValues<T, U>(expect1, actual1, expect_lod1, actual_lod1, numel1);
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CheckValues<T, U>(expect2, actual2, expect_lod2, actual_lod2, numel2);
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CheckValues<T, U>(expect3, actual3, expect_lod3, actual_lod3, numel3);
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CheckValues<T, U>(expect4, actual4, expect_lod4, actual_lod4, numel4);
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}
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TEST(SaveLoadCombineOp, CPU) { SaveLoadCombineOp<int, int>(); }
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TEST(SaveLoadCombineBF16Op, CPU) {
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SaveLoadCombineOp<phi::dtype::bfloat16, phi::dtype::bfloat16>();
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}
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// FP16 version of SaveLoadCombineOp Test, only altering the saving aspect
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// to save as FP16.
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TEST(SaveCombineFP16Op, CPU) {
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paddle::framework::Scope scope;
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phi::CPUPlace place;
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std::vector<int> lod1 = {0, 1, 2, 3, 10};
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int numel1 = 100;
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phi::LegacyLoD expect_lod1;
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float* expect1 = CreateForSaveCombineOp<float, phi::dtype::float16>(
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10, 10, lod1, "test_var1", place, &scope, &expect_lod1);
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std::vector<int> lod2 = {0, 2, 5, 10};
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int numel2 = 200;
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phi::LegacyLoD expect_lod2;
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float* expect2 = CreateForSaveCombineOp<float, phi::dtype::float16>(
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10, 20, lod2, "test_var2", place, &scope, &expect_lod2);
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std::vector<int> lod3 = {0, 20};
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int numel3 = 4000;
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phi::LegacyLoD expect_lod3;
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float* expect3 = CreateForSaveCombineOp<float, phi::dtype::float16>(
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20, 200, lod3, "test_var3", place, &scope, &expect_lod3);
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std::vector<int> lod4 = {0, 1, 20};
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int numel4 = 1000;
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phi::LegacyLoD expect_lod4;
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float* expect4 = CreateForSaveCombineOp<float, phi::dtype::float16>(
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20, 50, lod4, "test_var4", place, &scope, &expect_lod4);
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// Set attributes
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std::string filename = "check_tensor_fp16_save.ls";
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paddle::framework::AttributeMap attrs;
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attrs.insert({"file_path", std::string(filename)});
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attrs.insert({"save_as_fp16", true});
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// Run the save_combine_op
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auto save_combine_op = paddle::framework::OpRegistry::CreateOp(
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"save_combine",
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{{"X", {"test_var1", "test_var2", "test_var3", "test_var4"}}},
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{},
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attrs);
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save_combine_op->Run(scope, place);
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// Set up output vars
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auto target1 = GeneratePlaceholderBeforeLoad("out_var1", &scope);
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auto target2 = GeneratePlaceholderBeforeLoad("out_var2", &scope);
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auto target3 = GeneratePlaceholderBeforeLoad("out_var3", &scope);
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auto target4 = GeneratePlaceholderBeforeLoad("out_var4", &scope);
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// Run the load_combine_op
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auto load_combine_op = paddle::framework::OpRegistry::CreateOp(
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"load_combine",
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{},
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{{"Out", {"out_var1", "out_var2", "out_var3", "out_var4"}}},
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attrs);
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load_combine_op->Run(scope, place);
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phi::LegacyLoD actual_lod1, actual_lod2, actual_lod3, actual_lod4;
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phi::dtype::float16* actual1 =
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GetValuesAfterLoadCombineOp<phi::dtype::float16>(
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target1, scope, &actual_lod1);
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phi::dtype::float16* actual2 =
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GetValuesAfterLoadCombineOp<phi::dtype::float16>(
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target2, scope, &actual_lod2);
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phi::dtype::float16* actual3 =
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GetValuesAfterLoadCombineOp<phi::dtype::float16>(
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target3, scope, &actual_lod3);
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phi::dtype::float16* actual4 =
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GetValuesAfterLoadCombineOp<phi::dtype::float16>(
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target4, scope, &actual_lod4);
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CheckValues<float, phi::dtype::float16>(
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expect1, actual1, expect_lod1, actual_lod1, numel1);
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CheckValues<float, phi::dtype::float16>(
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expect2, actual2, expect_lod2, actual_lod2, numel2);
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CheckValues<float, phi::dtype::float16>(
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expect3, actual3, expect_lod3, actual_lod3, numel3);
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CheckValues<float, phi::dtype::float16>(
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expect4, actual4, expect_lod4, actual_lod4, numel4);
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}
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// FP16 version of SaveLoadCombineOp Test, only altering the loading aspect
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// to load tensors with FP16 precision.
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TEST(LoadCombineFP16Op, CPU) {
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paddle::framework::Scope scope;
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phi::CPUPlace place;
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std::vector<int> lod1 = {0, 1, 2, 3, 10};
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int numel1 = 100;
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phi::LegacyLoD expect_lod1;
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float* expect1 = CreateForSaveCombineOp<float, phi::dtype::float16>(
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10, 10, lod1, "test_var1", place, &scope, &expect_lod1);
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std::vector<int> lod2 = {0, 2, 5, 10};
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int numel2 = 200;
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phi::LegacyLoD expect_lod2;
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float* expect2 = CreateForSaveCombineOp<float, phi::dtype::float16>(
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10, 20, lod2, "test_var2", place, &scope, &expect_lod2);
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std::vector<int> lod3 = {0, 20};
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int numel3 = 4000;
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phi::LegacyLoD expect_lod3;
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float* expect3 = CreateForSaveCombineOp<float, phi::dtype::float16>(
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20, 200, lod3, "test_var3", place, &scope, &expect_lod3);
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std::vector<int> lod4 = {0, 1, 20};
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int numel4 = 1000;
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phi::LegacyLoD expect_lod4;
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float* expect4 = CreateForSaveCombineOp<float, phi::dtype::float16>(
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20, 50, lod4, "test_var4", place, &scope, &expect_lod4);
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// Set attributes
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std::string filename = "check_tensor_fp16_load.ls";
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paddle::framework::AttributeMap attrs;
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attrs.insert({"file_path", std::string(filename)});
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// Run the save_combine_op
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auto save_combine_op = paddle::framework::OpRegistry::CreateOp(
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"save_combine",
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{{"X", {"test_var1", "test_var2", "test_var3", "test_var4"}}},
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{},
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attrs);
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save_combine_op->Run(scope, place);
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// Set up output vars
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auto load_var1 = scope.Var("out_var1");
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auto load_var2 = scope.Var("out_var2");
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auto load_var3 = scope.Var("out_var3");
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auto load_var4 = scope.Var("out_var4");
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attrs.insert({"load_as_fp16", true});
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// Run the load_combine_op
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auto load_combine_op = paddle::framework::OpRegistry::CreateOp(
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"load_combine",
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{},
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{{"Out", {"out_var1", "out_var2", "out_var3", "out_var4"}}},
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attrs);
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load_combine_op->Run(scope, place);
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auto* target1 = load_var1->GetMutable<phi::DenseTensor>();
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auto* target2 = load_var2->GetMutable<phi::DenseTensor>();
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auto* target3 = load_var3->GetMutable<phi::DenseTensor>();
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auto* target4 = load_var4->GetMutable<phi::DenseTensor>();
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phi::LegacyLoD actual_lod1, actual_lod2, actual_lod3, actual_lod4;
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phi::dtype::float16* actual1 =
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GetValuesAfterLoadCombineOp<phi::dtype::float16>(
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target1, scope, &actual_lod1);
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phi::dtype::float16* actual2 =
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GetValuesAfterLoadCombineOp<phi::dtype::float16>(
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target2, scope, &actual_lod2);
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phi::dtype::float16* actual3 =
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GetValuesAfterLoadCombineOp<phi::dtype::float16>(
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target3, scope, &actual_lod3);
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phi::dtype::float16* actual4 =
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GetValuesAfterLoadCombineOp<phi::dtype::float16>(
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target4, scope, &actual_lod4);
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CheckValues<float, phi::dtype::float16>(
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expect1, actual1, expect_lod1, actual_lod1, numel1);
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CheckValues<float, phi::dtype::float16>(
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expect2, actual2, expect_lod2, actual_lod2, numel2);
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CheckValues<float, phi::dtype::float16>(
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expect3, actual3, expect_lod3, actual_lod3, numel3);
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CheckValues<float, phi::dtype::float16>(
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expect4, actual4, expect_lod4, actual_lod4, numel4);
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}
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// Test with original SaveLoadTest
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TEST(SaveLoadTestWithCombineOp, CPU) {
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paddle::framework::Scope scope;
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phi::CPUPlace place;
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auto var = scope.Var("test_var");
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auto tensor = var->GetMutable<phi::DenseTensor>();
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tensor->Resize({3, 4000});
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phi::LegacyLoD expect_lod;
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expect_lod.resize(1);
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expect_lod[0].push_back(0);
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expect_lod[0].push_back(1);
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expect_lod[0].push_back(2);
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expect_lod[0].push_back(3);
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tensor->set_lod(expect_lod);
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int* expect = tensor->mutable_data<int>(place);
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for (int64_t i = 0; i < tensor->numel(); ++i) {
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expect[i] = static_cast<int>(i);
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}
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paddle::framework::AttributeMap attrs;
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attrs.insert({"file_path", std::string("check_t.save")});
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auto save_op = paddle::framework::OpRegistry::CreateOp(
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"save_combine", {{"X", {"test_var"}}}, {}, attrs);
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save_op->Run(scope, place);
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auto load_var = scope.Var("out_var");
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auto target = load_var->GetMutable<phi::DenseTensor>();
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auto load_op = paddle::framework::OpRegistry::CreateOp(
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"load_combine", {}, {{"Out", {"out_var"}}}, attrs);
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load_op->Run(scope, place);
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int* actual = target->data<int>();
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for (int64_t i = 0; i < tensor->numel(); ++i) {
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EXPECT_EQ(expect[i], actual[i]);
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}
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auto& actual_lod = target->lod();
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EXPECT_EQ(expect_lod.size(), actual_lod.size());
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for (size_t i = 0; i < expect_lod.size(); ++i) { // NOLINT
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for (size_t j = 0; j < expect_lod[i].size(); ++j) {
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EXPECT_EQ(expect_lod[i][j], actual_lod[i][j]);
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}
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}
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}
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