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

142 lines
5.0 KiB
C++

/**
* Copyright 2019-2021 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 <memory>
#include <string>
#include "minddata/dataset/core/client.h"
// #include "minddata/dataset/core/pybind_support.h"
// #include "minddata/dataset/core/tensor.h"
// #include "minddata/dataset/core/tensor_shape.h"
// #include "minddata/dataset/engine/datasetops/batch_op.h"
#include "minddata/dataset/engine/datasetops/source/tf_reader_op.h"
#include "common/common.h"
#include "gtest/gtest.h"
#include "utils/log_adapter.h"
#include "securec.h"
#include "minddata/dataset/util/status.h"
// #include "pybind11/numpy.h"
// #include "pybind11/pybind11.h"
// #include "utils/ms_utils.h"
// #include "minddata/dataset/engine/db_connector.h"
// #include "minddata/dataset/kernels/data/data_utils.h"
namespace common = mindspore::common;
namespace de = mindspore::dataset;
using namespace mindspore::dataset;
using mindspore::LogStream;
using mindspore::ExceptionType::NoExceptionType;
using mindspore::MsLogLevel::ERROR;
class MindDataTestBatchOp : public UT::DatasetOpTesting {
protected:
};
// This test has been disabled because PadInfo is not currently supported in the C++ API.
// Feature: Test Batch op with padding on TFReader
// Description: Create Batch operation with padding on a TFReader dataset
// Expectation: The data within the created object should match the expected data
TEST_F(MindDataTestBatchOp, DISABLED_TestSimpleBatchPadding) {
std::string schema_file = datasets_root_path_ + "/testBatchDataset/test.data";
PadInfo m;
std::shared_ptr<Tensor> pad_value;
Tensor::CreateEmpty(TensorShape::CreateScalar(), DataType(DataType::DE_FLOAT32), &pad_value);
pad_value->SetItemAt<float>({}, -1);
m.insert({"col_1d", std::make_pair(TensorShape({4}), pad_value)});
/*
std::shared_ptr<ConfigManager> config_manager = GlobalContext::config_manager();
auto op_connector_size = config_manager->op_connector_size();
auto num_workers = config_manager->num_parallel_workers();
std::vector<std::string> input_columns = {};
std::vector<std::string> output_columns = {};
pybind11::function batch_size_func;
pybind11::function batch_map_func;
*/
int32_t batch_size = 12;
bool drop = false;
std::shared_ptr<BatchOp> op = Batch(batch_size, drop, m);
// std::make_shared<BatchOp>(batch_size, drop, pad, op_connector_size, num_workers, input_columns, output_columns,
// batch_size_func, batch_map_func, m);
auto tree = Build({TFReader(schema_file), op});
tree->Prepare();
Status rc = tree->Launch();
if (rc.IsError()) {
MS_LOG(ERROR) << "Return code error detected during tree launch: " << rc.ToString() << ".";
} else {
int64_t payload[] = {-9223372036854775807 - 1,
1,
-1,
-1,
2,
3,
-1,
-1,
4,
5,
-1,
-1,
6,
7,
-1,
-1,
8,
9,
-1,
-1,
10,
11,
-1,
-1,
12,
13,
-1,
-1,
14,
15,
-1,
-1,
16,
17,
-1,
-1,
18,
19,
-1,
-1,
20,
21,
-1,
-1,
22,
23,
-1,
-1};
std::shared_ptr<de::Tensor> t;
rc = de::Tensor::CreateFromMemory(de::TensorShape({12, 4}), de::DataType(DataType::DE_INT64),
(unsigned char *)payload, &t);
de::DatasetIterator di(tree);
TensorMap tensor_map;
rc = di.GetNextAsMap(&tensor_map);
EXPECT_TRUE((*t) == (*(tensor_map["col_1d"])));
rc = di.GetNextAsMap(&tensor_map);
EXPECT_TRUE(tensor_map.size() == 0);
EXPECT_TRUE(rc.IsOk());
}
}