mindspore/tests/ut/cpp/dataset/zip_op_test.cc

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/**
* Copyright 2019 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 <chrono>
#include <cstdlib>
#include <cstring>
#include <functional>
#include <iostream>
#include <memory>
#include <string>
#include <thread>
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#include "minddata/dataset/core/client.h"
#include "minddata/dataset/core/constants.h"
#include "minddata/dataset/engine/datasetops/map_op.h"
#include "minddata/dataset/engine/datasetops/zip_op.h"
#include "minddata/dataset/core/tensor.h"
#include "minddata/dataset/core/config_manager.h"
#include "common/common.h"
#include "common/utils.h"
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#include "minddata/dataset/engine/data_buffer.h"
#include "gtest/gtest.h"
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#include "minddata/dataset/core/global_context.h"
#include "utils/log_adapter.h"
namespace common = mindspore::common;
using namespace mindspore::dataset;
using mindspore::MsLogLevel::INFO;
using mindspore::ExceptionType::NoExceptionType;
using mindspore::LogStream;
class MindDataTestZipOp : public UT::DatasetOpTesting {
};
TEST_F(MindDataTestZipOp, MindDataTestZipOpDefault) {
/* Tree:
*
*
* OpId(2) ZipOp
* / \
* OpId(0) TFReaderOp OpId(1) TFReaderOp
* Start with an empty execution tree
*/
Status rc;
MS_LOG(INFO) << "UT test TestZipBasic.";
auto my_tree = std::make_shared<ExecutionTree>();
// Creating TFReaderOp
std::string dataset_path = datasets_root_path_ + "/test_tf_file_3_images/train-0000-of-0001.data";
std::string dataset_path2 = datasets_root_path_ + "/testBatchDataset/test.data";
std::shared_ptr<TFReaderOp> my_tfreader_op;
rc = TFReaderOp::Builder()
.SetDatasetFilesList({dataset_path})
.SetRowsPerBuffer(2)
.SetWorkerConnectorSize(16)
.SetNumWorkers(1)
.Build(&my_tfreader_op);
EXPECT_TRUE(rc.IsOk());
rc = my_tree->AssociateNode(my_tfreader_op);
EXPECT_TRUE(rc.IsOk());
std::shared_ptr<TFReaderOp> my_tfreader_op2;
rc = TFReaderOp::Builder()
.SetDatasetFilesList({dataset_path2})
.SetRowsPerBuffer(2)
.SetWorkerConnectorSize(1)
.SetNumWorkers(1)
.Build(&my_tfreader_op2);
EXPECT_TRUE(rc.IsOk());
rc = my_tree->AssociateNode(my_tfreader_op2);
EXPECT_TRUE(rc.IsOk());
// Creating DatasetOp
std::shared_ptr<ZipOp> zip_op;
rc = ZipOp::Builder().Build(&zip_op);
EXPECT_TRUE(rc.IsOk());
rc = my_tree->AssociateNode(zip_op);
EXPECT_TRUE(rc.IsOk());
rc = zip_op->AddChild(std::move(my_tfreader_op));
EXPECT_TRUE(rc.IsOk());
rc = zip_op->AddChild(std::move(my_tfreader_op2));
EXPECT_TRUE(rc.IsOk());
rc = my_tree->AssignRoot(zip_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, 3); // Should be 3 rows fetched
}
TEST_F(MindDataTestZipOp, MindDataTestZipOpRepeat) {
/* Tree:
* OpId(3) Repeat(3)
*
* OpId(2) ZipOp
* / \
* OpId(0) TFReaderOp OpId(1) TFReaderOp
*
* Start with an empty execution tree
*/
Status rc;
MS_LOG(INFO) << "UT test TestZipRepeat.";
auto my_tree = std::make_shared<ExecutionTree>();
std::string dataset_path = datasets_root_path_ + "/test_tf_file_3_images/train-0000-of-0001.data";
std::string dataset_path2 = datasets_root_path_ + "/testBatchDataset/test.data";
std::shared_ptr<TFReaderOp> my_tfreader_op;
rc = TFReaderOp::Builder()
.SetDatasetFilesList({dataset_path})
.SetRowsPerBuffer(2)
.SetWorkerConnectorSize(16)
.SetNumWorkers(1)
.Build(&my_tfreader_op);
EXPECT_TRUE(rc.IsOk());
rc = my_tree->AssociateNode(my_tfreader_op);
EXPECT_TRUE(rc.IsOk());
std::shared_ptr<TFReaderOp> my_tfreader_op2;
rc = TFReaderOp::Builder()
.SetDatasetFilesList({dataset_path2})
.SetRowsPerBuffer(2)
.SetWorkerConnectorSize(1)
.SetNumWorkers(1)
.Build(&my_tfreader_op2);
EXPECT_TRUE(rc.IsOk());
rc = my_tree->AssociateNode(my_tfreader_op2);
EXPECT_TRUE(rc.IsOk());
// Creating DatasetOp
std::shared_ptr<ZipOp> zip_op;
rc = ZipOp::Builder().Build(&zip_op);
EXPECT_TRUE(rc.IsOk());
rc = my_tree->AssociateNode(zip_op);
EXPECT_TRUE(rc.IsOk());
rc = zip_op->AddChild(std::move(my_tfreader_op));
EXPECT_TRUE(rc.IsOk());
rc = zip_op->AddChild(std::move(my_tfreader_op2));
EXPECT_TRUE(rc.IsOk());
// Builder(num_of_repeats)
std::shared_ptr<RepeatOp> my_repeat_op;
rc = RepeatOp::Builder(3).Build(&my_repeat_op);
EXPECT_TRUE(rc.IsOk());
rc = my_tree->AssociateNode(my_repeat_op);
EXPECT_TRUE(rc.IsOk());
rc = my_repeat_op->AddChild(zip_op);
EXPECT_TRUE(rc.IsOk());
rc = my_tree->AssignRoot(my_repeat_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, 9); // Should be 9 rows fetched
}