forked from mindspore-Ecosystem/mindspore
734 lines
22 KiB
C++
734 lines
22 KiB
C++
/**
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* Copyright 2019 Huawei Technologies Co., Ltd
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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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*/
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#include <iostream>
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#include <memory>
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#include <vector>
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#include "minddata/dataset/core/client.h"
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#include "minddata/dataset/engine/data_schema.h"
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#include "common/common.h"
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#include "common/utils.h"
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#include "gtest/gtest.h"
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#include "utils/log_adapter.h"
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namespace common = mindspore::common;
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using namespace mindspore::dataset;
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using mindspore::MsLogLevel::INFO;
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using mindspore::ExceptionType::NoExceptionType;
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using mindspore::LogStream;
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class MindDataTestTFReaderOp : public UT::DatasetOpTesting {
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};
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TEST_F(MindDataTestTFReaderOp, TestTFReaderBasic1) {
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// Start with an empty execution tree
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auto my_tree = std::make_shared<ExecutionTree>();
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std::string dataset_path;
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dataset_path = datasets_root_path_ + "/testTFTestAllTypes/test.data";
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std::shared_ptr<TFReaderOp> my_tfreader_op;
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TFReaderOp::Builder builder;
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builder.SetDatasetFilesList({dataset_path})
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.SetRowsPerBuffer(16)
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.SetNumWorkers(16);
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std::unique_ptr<DataSchema> schema = std::make_unique<DataSchema>();
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schema->LoadSchemaFile(datasets_root_path_ + "/testTFTestAllTypes/datasetSchema.json", {});
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builder.SetDataSchema(std::move(schema));
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Status rc = builder.Build(&my_tfreader_op);
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ASSERT_TRUE(rc.IsOk());
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rc = my_tree->AssociateNode(my_tfreader_op);
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ASSERT_TRUE(rc.IsOk());
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rc = my_tree->AssignRoot(my_tfreader_op);
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ASSERT_TRUE(rc.IsOk());
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MS_LOG(INFO) << "Launching tree and begin iteration.";
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rc = my_tree->Prepare();
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ASSERT_TRUE(rc.IsOk());
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rc = my_tree->Launch();
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ASSERT_TRUE(rc.IsOk());
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// Start the loop of reading tensors from our pipeline
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DatasetIterator di(my_tree);
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TensorRow tensor_list;
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rc = di.FetchNextTensorRow(&tensor_list);
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ASSERT_TRUE(rc.IsOk());
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int row_count = 0;
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while (!tensor_list.empty()) {
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// Display the tensor by calling the printer on it
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for (int i = 0; i < tensor_list.size(); i++) {
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std::ostringstream ss;
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ss << "(" << tensor_list[i] << "): " << *tensor_list[i] << std::endl;
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MS_LOG(INFO) << "Tensor print: " << ss.str() << ".";
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}
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rc = di.FetchNextTensorRow(&tensor_list);
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ASSERT_TRUE(rc.IsOk());
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row_count++;
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}
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ASSERT_EQ(row_count, 12);
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}
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TEST_F(MindDataTestTFReaderOp, TestTFReaderLargeRowsPerBuffer) {
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// Start with an empty execution tree
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auto my_tree = std::make_shared<ExecutionTree>();
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std::string dataset_path;
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dataset_path = datasets_root_path_ + "/testTFTestAllTypes/test.data";
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std::shared_ptr<TFReaderOp> my_tfreader_op;
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TFReaderOp::Builder builder;
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builder.SetDatasetFilesList({dataset_path})
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.SetRowsPerBuffer(500)
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.SetNumWorkers(16);
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std::unique_ptr<DataSchema> schema = std::make_unique<DataSchema>();
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schema->LoadSchemaFile(datasets_root_path_ + "/testTFTestAllTypes/datasetSchema.json", {});
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builder.SetDataSchema(std::move(schema));
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Status rc = builder.Build(&my_tfreader_op);
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ASSERT_TRUE(rc.IsOk());
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rc = my_tree->AssociateNode(my_tfreader_op);
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ASSERT_TRUE(rc.IsOk());
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rc = my_tree->AssignRoot(my_tfreader_op);
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ASSERT_TRUE(rc.IsOk());
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MS_LOG(INFO) << "Launching tree and begin iteration.";
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rc = my_tree->Prepare();
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ASSERT_TRUE(rc.IsOk());
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rc = my_tree->Launch();
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ASSERT_TRUE(rc.IsOk());
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// Start the loop of reading tensors from our pipeline
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DatasetIterator di(my_tree);
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TensorRow tensor_list;
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rc = di.FetchNextTensorRow(&tensor_list);
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ASSERT_TRUE(rc.IsOk());
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int row_count = 0;
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while (!tensor_list.empty()) {
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// Display the tensor by calling the printer on it
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for (int i = 0; i < tensor_list.size(); i++) {
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std::ostringstream ss;
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ss << "(" << tensor_list[i] << "): " << *tensor_list[i] << std::endl;
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MS_LOG(INFO) << "Tensor print: " << ss.str() << ".";
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}
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rc = di.FetchNextTensorRow(&tensor_list);
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ASSERT_TRUE(rc.IsOk());
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row_count++;
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}
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ASSERT_EQ(row_count, 12);
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}
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TEST_F(MindDataTestTFReaderOp, TestTFReaderSmallRowsPerBuffer) {
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// Start with an empty execution tree
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auto my_tree = std::make_shared<ExecutionTree>();
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std::string dataset_path;
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dataset_path = datasets_root_path_ + "/testTFTestAllTypes/test.data";
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std::shared_ptr<TFReaderOp> my_tfreader_op;
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TFReaderOp::Builder builder;
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builder.SetDatasetFilesList({dataset_path})
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.SetRowsPerBuffer(1)
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.SetNumWorkers(16);
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std::unique_ptr<DataSchema> schema = std::make_unique<DataSchema>();
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schema->LoadSchemaFile(datasets_root_path_ + "/testTFTestAllTypes/datasetSchema.json", {});
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builder.SetDataSchema(std::move(schema));
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Status rc = builder.Build(&my_tfreader_op);
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ASSERT_TRUE(rc.IsOk());
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rc = my_tree->AssociateNode(my_tfreader_op);
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ASSERT_TRUE(rc.IsOk());
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rc = my_tree->AssignRoot(my_tfreader_op);
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ASSERT_TRUE(rc.IsOk());
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MS_LOG(INFO) << "Launching tree and begin iteration.";
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rc = my_tree->Prepare();
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ASSERT_TRUE(rc.IsOk());
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rc = my_tree->Launch();
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ASSERT_TRUE(rc.IsOk());
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// Start the loop of reading tensors from our pipeline
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DatasetIterator di(my_tree);
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TensorRow tensor_list;
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rc = di.FetchNextTensorRow(&tensor_list);
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ASSERT_TRUE(rc.IsOk());
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int row_count = 0;
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while (!tensor_list.empty()) {
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// Display the tensor by calling the printer on it
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for (int i = 0; i < tensor_list.size(); i++) {
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std::ostringstream ss;
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ss << "(" << tensor_list[i] << "): " << *tensor_list[i] << std::endl;
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MS_LOG(INFO) << "Tensor print: " << ss.str() << ".";
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}
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rc = di.FetchNextTensorRow(&tensor_list);
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ASSERT_TRUE(rc.IsOk());
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row_count++;
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}
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ASSERT_EQ(row_count, 12);
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}
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TEST_F(MindDataTestTFReaderOp, TestTFReaderLargeQueueSize) {
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// Start with an empty execution tree
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auto my_tree = std::make_shared<ExecutionTree>();
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std::string dataset_path;
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dataset_path = datasets_root_path_ + "/testTFTestAllTypes/test.data";
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std::shared_ptr<TFReaderOp> my_tfreader_op;
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TFReaderOp::Builder builder;
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builder.SetDatasetFilesList({dataset_path})
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.SetWorkerConnectorSize(1)
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.SetRowsPerBuffer(16)
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.SetNumWorkers(16);
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std::unique_ptr<DataSchema> schema = std::make_unique<DataSchema>();
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schema->LoadSchemaFile(datasets_root_path_ + "/testTFTestAllTypes/datasetSchema.json", {});
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builder.SetDataSchema(std::move(schema));
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Status rc = builder.Build(&my_tfreader_op);
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ASSERT_TRUE(rc.IsOk());
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rc = my_tree->AssociateNode(my_tfreader_op);
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ASSERT_TRUE(rc.IsOk());
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rc = my_tree->AssignRoot(my_tfreader_op);
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ASSERT_TRUE(rc.IsOk());
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MS_LOG(INFO) << "Launching tree and begin iteration.";
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rc = my_tree->Prepare();
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ASSERT_TRUE(rc.IsOk());
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rc = my_tree->Launch();
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ASSERT_TRUE(rc.IsOk());
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// Start the loop of reading tensors from our pipeline
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DatasetIterator di(my_tree);
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TensorRow tensor_list;
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rc = di.FetchNextTensorRow(&tensor_list);
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ASSERT_TRUE(rc.IsOk());
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int row_count = 0;
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while (!tensor_list.empty()) {
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// Display the tensor by calling the printer on it
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for (int i = 0; i < tensor_list.size(); i++) {
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std::ostringstream ss;
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ss << "(" << tensor_list[i] << "): " << *tensor_list[i] << std::endl;
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MS_LOG(INFO) << "Tensor print: " << ss.str() << ".";
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}
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rc = di.FetchNextTensorRow(&tensor_list);
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ASSERT_TRUE(rc.IsOk());
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row_count++;
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}
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ASSERT_EQ(row_count, 12);
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}
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TEST_F(MindDataTestTFReaderOp, TestTFReaderOneThread) {
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// Start with an empty execution tree
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auto my_tree = std::make_shared<ExecutionTree>();
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std::string dataset_path;
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dataset_path = datasets_root_path_ + "/testTFTestAllTypes/test.data";
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std::shared_ptr<TFReaderOp> my_tfreader_op;
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TFReaderOp::Builder builder;
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builder.SetDatasetFilesList({dataset_path})
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.SetRowsPerBuffer(16)
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.SetNumWorkers(1);
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std::unique_ptr<DataSchema> schema = std::make_unique<DataSchema>();
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schema->LoadSchemaFile(datasets_root_path_ + "/testTFTestAllTypes/datasetSchema.json", {});
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builder.SetDataSchema(std::move(schema));
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Status rc = builder.Build(&my_tfreader_op);
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ASSERT_TRUE(rc.IsOk());
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rc = my_tree->AssociateNode(my_tfreader_op);
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ASSERT_TRUE(rc.IsOk());
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rc = my_tree->AssignRoot(my_tfreader_op);
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ASSERT_TRUE(rc.IsOk());
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MS_LOG(INFO) << "Launching tree and begin iteration.";
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rc = my_tree->Prepare();
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ASSERT_TRUE(rc.IsOk());
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rc = my_tree->Launch();
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ASSERT_TRUE(rc.IsOk());
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// Start the loop of reading tensors from our pipeline
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DatasetIterator di(my_tree);
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TensorRow tensor_list;
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rc = di.FetchNextTensorRow(&tensor_list);
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ASSERT_TRUE(rc.IsOk());
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int row_count = 0;
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while (!tensor_list.empty()) {
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// Display the tensor by calling the printer on it
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for (int i = 0; i < tensor_list.size(); i++) {
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std::ostringstream ss;
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ss << "(" << tensor_list[i] << "): " << *tensor_list[i] << std::endl;
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MS_LOG(INFO) << "Tensor print: " << ss.str() << ".";
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}
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rc = di.FetchNextTensorRow(&tensor_list);
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ASSERT_TRUE(rc.IsOk());
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row_count++;
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}
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ASSERT_EQ(row_count, 12);
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}
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TEST_F(MindDataTestTFReaderOp, TestTFReaderRepeat) {
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// Start with an empty execution tree
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auto my_tree = std::make_shared<ExecutionTree>();
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std::string dataset_path;
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dataset_path = datasets_root_path_ + "/testTFTestAllTypes/test.data";
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// TFReaderOp
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std::shared_ptr<TFReaderOp> my_tfreader_op;
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TFReaderOp::Builder builder;
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builder.SetDatasetFilesList({dataset_path})
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.SetRowsPerBuffer(16)
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.SetWorkerConnectorSize(16)
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.SetNumWorkers(16);
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std::unique_ptr<DataSchema> schema = std::make_unique<DataSchema>();
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schema->LoadSchemaFile(datasets_root_path_ + "/testTFTestAllTypes/datasetSchema.json", {});
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builder.SetDataSchema(std::move(schema));
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Status rc= builder.Build(&my_tfreader_op);
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ASSERT_TRUE(rc.IsOk());
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rc = my_tree->AssociateNode(my_tfreader_op);
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ASSERT_TRUE(rc.IsOk());
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// RepeatOp
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std::shared_ptr<RepeatOp> my_repeat_op = std::make_shared<RepeatOp>(3);
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rc = my_tree->AssociateNode(my_repeat_op);
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ASSERT_TRUE(rc.IsOk());
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// Set children/root layout.
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rc = my_repeat_op->AddChild(my_tfreader_op);
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ASSERT_TRUE(rc.IsOk());
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rc = my_tree->AssignRoot(my_repeat_op);
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ASSERT_TRUE(rc.IsOk());
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MS_LOG(INFO) << "Launching tree and begin iteration.";
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rc = my_tree->Prepare();
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ASSERT_TRUE(rc.IsOk());
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rc = my_tree->Launch();
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ASSERT_TRUE(rc.IsOk());
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// Start the loop of reading tensors from our pipeline
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DatasetIterator di(my_tree);
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TensorRow tensor_list;
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rc = di.FetchNextTensorRow(&tensor_list);
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ASSERT_TRUE(rc.IsOk());
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int row_count = 0;
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while (!tensor_list.empty()) {
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MS_LOG(INFO) << "Row display for row #: " << row_count << ".";
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// Display the tensor by calling the printer on it
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for (int i = 0; i < tensor_list.size(); i++) {
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std::ostringstream ss;
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ss << "(" << tensor_list[i] << "): " << *tensor_list[i] << std::endl;
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MS_LOG(INFO) << "Tensor print: " << ss.str() << ".";
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}
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rc = di.FetchNextTensorRow(&tensor_list);
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ASSERT_TRUE(rc.IsOk());
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row_count++;
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}
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ASSERT_EQ(row_count, 12 * 3);
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}
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TEST_F(MindDataTestTFReaderOp, TestTFReaderSchemaConstructor) {
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// Start with an empty execution tree
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auto my_tree = std::make_shared<ExecutionTree>();
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std::string dataset_path;
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dataset_path = datasets_root_path_ + "/testTFTestAllTypes";
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std::unique_ptr<DataSchema> data_schema = std::make_unique<DataSchema>();
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std::vector<std::string> columns_to_load;
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columns_to_load.push_back("col_sint32");
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columns_to_load.push_back("col_binary");
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data_schema->LoadSchemaFile(dataset_path + "/datasetSchema.json", columns_to_load);
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std::shared_ptr<TFReaderOp> my_tfreader_op;
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TFReaderOp::Builder builder;
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builder.SetDatasetFilesList({dataset_path+"/test.data"})
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.SetRowsPerBuffer(16)
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.SetNumWorkers(16)
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.SetDataSchema(std::move(data_schema));
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Status rc = builder.Build(&my_tfreader_op);
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ASSERT_TRUE(rc.IsOk());
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rc = my_tree->AssociateNode(my_tfreader_op);
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ASSERT_TRUE(rc.IsOk());
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rc = my_tree->AssignRoot(my_tfreader_op);
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ASSERT_TRUE(rc.IsOk());
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MS_LOG(INFO) << "Launching tree and begin iteration.";
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rc = my_tree->Prepare();
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ASSERT_TRUE(rc.IsOk());
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rc = my_tree->Launch();
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ASSERT_TRUE(rc.IsOk());
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// Start the loop of reading tensors from our pipeline
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DatasetIterator di(my_tree);
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TensorRow tensor_list;
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rc = di.FetchNextTensorRow(&tensor_list);
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ASSERT_TRUE(rc.IsOk());
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int row_count = 0;
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while (!tensor_list.empty()) {
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// Display the tensor by calling the printer on it
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ASSERT_EQ(tensor_list.size(), columns_to_load.size());
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for (int i = 0; i < tensor_list.size(); i++) {
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std::ostringstream ss;
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ss << "(" << tensor_list[i] << "): " << *tensor_list[i] << std::endl;
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MS_LOG(INFO) << "Tensor print: " << ss.str() << ".";
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}
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rc = di.FetchNextTensorRow(&tensor_list);
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ASSERT_TRUE(rc.IsOk());
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row_count++;
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}
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ASSERT_EQ(row_count, 12);
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}
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TEST_F(MindDataTestTFReaderOp, TestTFReaderTake1Row) {
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// Start with an empty execution tree
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auto my_tree = std::make_shared<ExecutionTree>();
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std::string dataset_path;
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dataset_path = datasets_root_path_ + "/testTFTestAllTypes";
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std::string data_schema_filepath = dataset_path + "/datasetSchema1Row.json";
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// TFReaderOp
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std::shared_ptr<TFReaderOp> my_tfreader_op;
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TFReaderOp::Builder builder;
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builder.SetDatasetFilesList({dataset_path + "/test.data"}).SetRowsPerBuffer(5).SetNumWorkers(16);
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std::unique_ptr<DataSchema> schema = std::make_unique<DataSchema>();
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schema->LoadSchemaFile(datasets_root_path_ + "/testTFTestAllTypes/datasetSchema1Row.json", {});
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builder.SetDataSchema(std::move(schema));
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Status rc= builder.Build(&my_tfreader_op);
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ASSERT_TRUE(rc.IsOk());
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rc = my_tree->AssociateNode(my_tfreader_op);
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ASSERT_TRUE(rc.IsOk());
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rc = my_tree->AssignRoot(my_tfreader_op);
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ASSERT_TRUE(rc.IsOk());
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MS_LOG(INFO) << "Launching tree and begin iteration.";
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rc = my_tree->Prepare();
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ASSERT_TRUE(rc.IsOk());
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rc = my_tree->Launch();
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ASSERT_TRUE(rc.IsOk());
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// Start the loop of reading tensors from our pipeline
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DatasetIterator di(my_tree);
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TensorRow tensor_list;
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rc = di.FetchNextTensorRow(&tensor_list);
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ASSERT_TRUE(rc.IsOk());
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int row_count = 0;
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while (!tensor_list.empty()) {
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MS_LOG(INFO) << "Row display for row #: " << row_count << ".";
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// Display the tensor by calling the printer on it
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for (int i = 0; i < tensor_list.size(); i++) {
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std::ostringstream ss;
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ss << "(" << tensor_list[i] << "): " << *tensor_list[i] << std::endl;
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MS_LOG(INFO) << "Tensor print: " << ss.str() << ".";
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}
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rc = di.FetchNextTensorRow(&tensor_list);
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ASSERT_TRUE(rc.IsOk());
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row_count++;
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}
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ASSERT_EQ(row_count, 1);
|
|
}
|
|
|
|
TEST_F(MindDataTestTFReaderOp, TestTFReaderTake1Buffer) {
|
|
// Start with an empty execution tree
|
|
auto my_tree = std::make_shared<ExecutionTree>();
|
|
|
|
std::string dataset_path;
|
|
dataset_path = datasets_root_path_ + "/testTFTestAllTypes";
|
|
|
|
std::string data_schema_filepath = dataset_path + "/datasetSchema5Rows.json";
|
|
|
|
// TFReaderOp
|
|
std::shared_ptr<TFReaderOp> my_tfreader_op;
|
|
TFReaderOp::Builder builder;
|
|
builder.SetDatasetFilesList({dataset_path + "/test.data"}).SetRowsPerBuffer(5).SetNumWorkers(16);
|
|
std::unique_ptr<DataSchema> schema = std::make_unique<DataSchema>();
|
|
schema->LoadSchemaFile(datasets_root_path_ + "/testTFTestAllTypes/datasetSchema5Rows.json", {});
|
|
builder.SetDataSchema(std::move(schema));
|
|
|
|
Status rc= builder.Build(&my_tfreader_op);
|
|
ASSERT_TRUE(rc.IsOk());
|
|
|
|
rc = my_tree->AssociateNode(my_tfreader_op);
|
|
ASSERT_TRUE(rc.IsOk());
|
|
|
|
rc = my_tree->AssignRoot(my_tfreader_op);
|
|
ASSERT_TRUE(rc.IsOk());
|
|
|
|
MS_LOG(INFO) << "Launching tree and begin iteration.";
|
|
rc = my_tree->Prepare();
|
|
ASSERT_TRUE(rc.IsOk());
|
|
|
|
rc = my_tree->Launch();
|
|
ASSERT_TRUE(rc.IsOk());
|
|
|
|
// Start the loop of reading tensors from our pipeline
|
|
DatasetIterator di(my_tree);
|
|
TensorRow tensor_list;
|
|
rc = di.FetchNextTensorRow(&tensor_list);
|
|
ASSERT_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: " << ss.str() << ".";
|
|
}
|
|
|
|
rc = di.FetchNextTensorRow(&tensor_list);
|
|
ASSERT_TRUE(rc.IsOk());
|
|
row_count++;
|
|
}
|
|
|
|
ASSERT_EQ(row_count, 5);
|
|
}
|
|
|
|
TEST_F(MindDataTestTFReaderOp, TestTFReaderTake7Rows) {
|
|
// Start with an empty execution tree
|
|
auto my_tree = std::make_shared<ExecutionTree>();
|
|
|
|
std::string dataset_path;
|
|
dataset_path = datasets_root_path_ + "/testTFTestAllTypes";
|
|
|
|
std::string data_schema_filepath = dataset_path + "/datasetSchema7Rows.json";
|
|
|
|
// TFReaderOp
|
|
std::shared_ptr<TFReaderOp> my_tfreader_op;
|
|
TFReaderOp::Builder builder;
|
|
builder.SetDatasetFilesList({dataset_path + "/test.data"}).SetRowsPerBuffer(5).SetNumWorkers(16);
|
|
std::unique_ptr<DataSchema> schema = std::make_unique<DataSchema>();
|
|
schema->LoadSchemaFile(datasets_root_path_ + "/testTFTestAllTypes/datasetSchema7Rows.json", {});
|
|
builder.SetDataSchema(std::move(schema));
|
|
|
|
Status rc= builder.Build(&my_tfreader_op);
|
|
ASSERT_TRUE(rc.IsOk());
|
|
|
|
rc = my_tree->AssociateNode(my_tfreader_op);
|
|
ASSERT_TRUE(rc.IsOk());
|
|
|
|
rc = my_tree->AssignRoot(my_tfreader_op);
|
|
ASSERT_TRUE(rc.IsOk());
|
|
|
|
MS_LOG(INFO) << "Launching tree and begin iteration.";
|
|
rc = my_tree->Prepare();
|
|
ASSERT_TRUE(rc.IsOk());
|
|
|
|
rc = my_tree->Launch();
|
|
ASSERT_TRUE(rc.IsOk());
|
|
|
|
// Start the loop of reading tensors from our pipeline
|
|
DatasetIterator di(my_tree);
|
|
TensorRow tensor_list;
|
|
rc = di.FetchNextTensorRow(&tensor_list);
|
|
ASSERT_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: " << ss.str() << ".";
|
|
}
|
|
|
|
rc = di.FetchNextTensorRow(&tensor_list);
|
|
ASSERT_TRUE(rc.IsOk());
|
|
row_count++;
|
|
}
|
|
|
|
ASSERT_EQ(row_count, 7);
|
|
}
|
|
|
|
TEST_F(MindDataTestTFReaderOp, TestTFReaderBasicNoSchema) {
|
|
// Start with an empty execution tree
|
|
auto my_tree = std::make_shared<ExecutionTree>();
|
|
|
|
std::string dataset_path;
|
|
dataset_path = datasets_root_path_ + "/testTFTestAllTypes/test.data";
|
|
|
|
std::shared_ptr<TFReaderOp> my_tfreader_op;
|
|
TFReaderOp::Builder builder;
|
|
builder.SetDatasetFilesList({dataset_path})
|
|
.SetRowsPerBuffer(16)
|
|
.SetNumWorkers(16);
|
|
Status rc = builder.Build(&my_tfreader_op);
|
|
ASSERT_TRUE(rc.IsOk());
|
|
|
|
rc = my_tree->AssociateNode(my_tfreader_op);
|
|
ASSERT_TRUE(rc.IsOk());
|
|
|
|
rc = my_tree->AssignRoot(my_tfreader_op);
|
|
ASSERT_TRUE(rc.IsOk());
|
|
|
|
MS_LOG(INFO) << "Launching tree and begin iteration.";
|
|
rc = my_tree->Prepare();
|
|
ASSERT_TRUE(rc.IsOk());
|
|
|
|
rc = my_tree->Launch();
|
|
ASSERT_TRUE(rc.IsOk());
|
|
|
|
// Start the loop of reading tensors from our pipeline
|
|
DatasetIterator di(my_tree);
|
|
TensorRow tensor_list;
|
|
rc = di.FetchNextTensorRow(&tensor_list);
|
|
ASSERT_TRUE(rc.IsOk());
|
|
|
|
int row_count = 0;
|
|
while (!tensor_list.empty()) {
|
|
// Display the tensor by calling the printer on it
|
|
ASSERT_EQ(tensor_list.size(), 9);
|
|
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: " << ss.str() << ".";
|
|
}
|
|
|
|
rc = di.FetchNextTensorRow(&tensor_list);
|
|
ASSERT_TRUE(rc.IsOk());
|
|
row_count++;
|
|
}
|
|
|
|
ASSERT_EQ(row_count, 12);
|
|
}
|
|
|
|
TEST_F(MindDataTestTFReaderOp, TestTotalRowsBasic) {
|
|
std::string tf_file = datasets_root_path_ + "/testTFTestAllTypes/test.data";
|
|
|
|
std::vector<std::string> filenames;
|
|
|
|
for (int i = 0; i < 5; i++) {
|
|
filenames.push_back(tf_file);
|
|
}
|
|
|
|
int64_t total_rows = 0;
|
|
TFReaderOp::CountTotalRows(&total_rows, filenames, 1);
|
|
ASSERT_EQ(total_rows, 60);
|
|
TFReaderOp::CountTotalRows(&total_rows, filenames, 2);
|
|
ASSERT_EQ(total_rows, 60);
|
|
TFReaderOp::CountTotalRows(&total_rows, filenames, 3);
|
|
ASSERT_EQ(total_rows, 60);
|
|
TFReaderOp::CountTotalRows(&total_rows, filenames, 4);
|
|
ASSERT_EQ(total_rows, 60);
|
|
TFReaderOp::CountTotalRows(&total_rows, filenames, 5);
|
|
ASSERT_EQ(total_rows, 60);
|
|
TFReaderOp::CountTotalRows(&total_rows, filenames, 6);
|
|
ASSERT_EQ(total_rows, 60);
|
|
TFReaderOp::CountTotalRows(&total_rows, filenames, 729);
|
|
ASSERT_EQ(total_rows, 60);
|
|
TFReaderOp::CountTotalRows(&total_rows, filenames, 1, true);
|
|
ASSERT_EQ(total_rows, 60);
|
|
TFReaderOp::CountTotalRows(&total_rows, filenames, 2, true);
|
|
ASSERT_EQ(total_rows, 60);
|
|
TFReaderOp::CountTotalRows(&total_rows, filenames, 3, true);
|
|
ASSERT_EQ(total_rows, 60);
|
|
TFReaderOp::CountTotalRows(&total_rows, filenames, 4, true);
|
|
ASSERT_EQ(total_rows, 60);
|
|
TFReaderOp::CountTotalRows(&total_rows, filenames, 5, true);
|
|
ASSERT_EQ(total_rows, 60);
|
|
TFReaderOp::CountTotalRows(&total_rows, filenames, 6, true);
|
|
ASSERT_EQ(total_rows, 60);
|
|
TFReaderOp::CountTotalRows(&total_rows, filenames, 729, true);
|
|
ASSERT_EQ(total_rows, 60);
|
|
}
|
|
|
|
TEST_F(MindDataTestTFReaderOp, TestTFReaderInvalidFiles) {
|
|
// Start with an empty execution tree
|
|
auto my_tree = std::make_shared<ExecutionTree>();
|
|
|
|
std::string valid_file = datasets_root_path_ + "/testTFTestAllTypes/test.data";
|
|
std::string schema_file = datasets_root_path_ + "/testTFTestAllTypes/datasetSchema.json";
|
|
std::string invalid_file = datasets_root_path_ + "/testTFTestAllTypes/invalidFile.txt";
|
|
std::string nonexistent_file = "this/file/doesnt/exist";
|
|
|
|
std::shared_ptr<TFReaderOp> my_tfreader_op;
|
|
TFReaderOp::Builder builder;
|
|
builder.SetDatasetFilesList({invalid_file, valid_file, schema_file})
|
|
.SetRowsPerBuffer(16)
|
|
.SetNumWorkers(16);
|
|
|
|
std::unique_ptr<DataSchema> schema = std::make_unique<DataSchema>();
|
|
schema->LoadSchemaFile(schema_file, {});
|
|
builder.SetDataSchema(std::move(schema));
|
|
|
|
Status rc = builder.Build(&my_tfreader_op);
|
|
ASSERT_TRUE(!rc.IsOk());
|
|
|
|
builder.SetDatasetFilesList({invalid_file, valid_file, schema_file, nonexistent_file})
|
|
.SetRowsPerBuffer(16)
|
|
.SetNumWorkers(16);
|
|
|
|
schema = std::make_unique<DataSchema>();
|
|
schema->LoadSchemaFile(schema_file, {});
|
|
builder.SetDataSchema(std::move(schema));
|
|
|
|
rc = builder.Build(&my_tfreader_op);
|
|
ASSERT_TRUE(!rc.IsOk());
|
|
}
|