mindspore2022/tests/ut/cpp/dataset/concat_op_test.cc

128 lines
4.7 KiB
C++

/**
* Copyright 2020 Huawei Technologies Co., Ltd
*
* 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 <iostream>
#include <memory>
#include <vector>
#include "common/common.h"
#include "utils/ms_utils.h"
#include "minddata/dataset/core/client.h"
#include "minddata/dataset/engine/jagged_connector.h"
#include "gtest/gtest.h"
#include "utils/log_adapter.h"
namespace common = mindspore::common;
using namespace mindspore::dataset;
using mindspore::LogStream;
using mindspore::ExceptionType::NoExceptionType;
using mindspore::MsLogLevel::INFO;
class MindDataTestConcatOp : public UT::DatasetOpTesting {};
TEST_F(MindDataTestConcatOp, TestConcatProject) {
/* Tree:
*
* OpId(2) ConcatOp
* / \
* OpId(0) TFReaderOp OpId(1) TFReaderOp
*
* Start with an empty execution tree
*/
MS_LOG(INFO) << "UT test TestConcatProject.";
auto my_tree = std::make_shared<ExecutionTree>();
std::string dataset_path;
dataset_path = datasets_root_path_ + "/testTFTestAllTypes/test.data";
// TFReaderOp1
std::shared_ptr<ConfigManager> config_manager = GlobalContext::config_manager();
auto op_connector_size = config_manager->op_connector_size();
int32_t num_workers = 1; // only one file -> one worker
int32_t worker_connector_size = 16;
std::vector<std::string> columns_to_load = {};
std::vector<std::string> files = {dataset_path};
std::unique_ptr<DataSchema> schema1 = std::make_unique<DataSchema>();
schema1->LoadSchemaFile(datasets_root_path_ + "/testTFTestAllTypes/datasetSchema1Row.json", {});
// 16 is worker connector size
std::shared_ptr<TFReaderOp> my_tfreader_op1 =
std::make_shared<TFReaderOp>(num_workers, worker_connector_size, 0, files, std::move(schema1), op_connector_size,
columns_to_load, false, 1, 0, false);
Status rc = my_tfreader_op1->Init();
ASSERT_OK(rc);
rc = my_tree->AssociateNode(my_tfreader_op1);
ASSERT_OK(rc);
// TFReaderOp2
std::unique_ptr<DataSchema> schema2 = std::make_unique<DataSchema>();
schema2->LoadSchemaFile(datasets_root_path_ + "/testTFTestAllTypes/datasetSchema1Row.json", {});
// 16 is worker connector size
std::shared_ptr<TFReaderOp> my_tfreader_op2 =
std::make_shared<TFReaderOp>(num_workers, worker_connector_size, 0, files, std::move(schema2), op_connector_size,
columns_to_load, false, 1, 0, false);
rc = my_tfreader_op2->Init();
ASSERT_OK(rc);
rc = my_tree->AssociateNode(my_tfreader_op2);
ASSERT_OK(rc);
// Creating ConcatOp
std::shared_ptr<SamplerRT> concat_sampler = std::make_shared<DistributedSamplerRT>(1, 0, false, 0);
std::vector<std::pair<int, int>> flag_and_nums = {};
std::vector<std::pair<int, int>> children_start_end_index = {};
std::shared_ptr<ConcatOp> concat_op =
std::make_shared<ConcatOp>(std::move(concat_sampler), flag_and_nums, children_start_end_index);
rc = my_tree->AssociateNode(concat_op);
EXPECT_TRUE(rc.IsOk());
rc = concat_op->AddChild(std::move(my_tfreader_op1));
EXPECT_TRUE(rc.IsOk());
rc = concat_op->AddChild(std::move(my_tfreader_op2));
EXPECT_TRUE(rc.IsOk());
rc = my_tree->AssignRoot(concat_op);
EXPECT_TRUE(rc.IsOk());
rc = my_tree->Prepare();
EXPECT_TRUE(rc.IsOk());
// Launch the tree execution to kick off threads and start running the pipeline
MS_LOG(INFO) << "Launching my tree.";
rc = my_tree->Launch();
EXPECT_TRUE(rc.IsOk());
// Simulate a parse of data from our pipeline.
std::shared_ptr<DatasetOp> rootNode = my_tree->root();
DatasetIterator di(my_tree);
TensorRow tensor_list;
rc = di.FetchNextTensorRow(&tensor_list);
EXPECT_TRUE(rc.IsOk());
int row_count = 0;
while (!tensor_list.empty()) {
MS_LOG(INFO) << "Row display for row #: " << row_count << ".";
// Display the tensor by calling the printer on it
for (int i = 0; i < tensor_list.size(); i++) {
std::ostringstream ss;
ss << "(" << tensor_list[i] << "): " << *tensor_list[i] << std::endl;
MS_LOG(INFO) << "Tensor print: " << common::SafeCStr(ss.str()) << ".";
}
rc = di.FetchNextTensorRow(&tensor_list);
EXPECT_TRUE(rc.IsOk());
row_count++;
}
ASSERT_EQ(row_count, 2); // Should be 2 rows fetched
}