forked from huawei/mindspore2022
142 lines
5.0 KiB
C++
142 lines
5.0 KiB
C++
/**
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* Copyright 2019-2021 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 <memory>
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#include <string>
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#include "minddata/dataset/core/client.h"
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// #include "minddata/dataset/core/pybind_support.h"
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// #include "minddata/dataset/core/tensor.h"
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// #include "minddata/dataset/core/tensor_shape.h"
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// #include "minddata/dataset/engine/datasetops/batch_op.h"
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#include "minddata/dataset/engine/datasetops/source/tf_reader_op.h"
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#include "common/common.h"
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#include "gtest/gtest.h"
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#include "utils/log_adapter.h"
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#include "securec.h"
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#include "minddata/dataset/util/status.h"
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// #include "pybind11/numpy.h"
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// #include "pybind11/pybind11.h"
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// #include "utils/ms_utils.h"
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// #include "minddata/dataset/engine/db_connector.h"
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// #include "minddata/dataset/kernels/data/data_utils.h"
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namespace common = mindspore::common;
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namespace de = mindspore::dataset;
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using namespace mindspore::dataset;
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using mindspore::LogStream;
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using mindspore::ExceptionType::NoExceptionType;
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using mindspore::MsLogLevel::ERROR;
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class MindDataTestBatchOp : public UT::DatasetOpTesting {
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protected:
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};
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// This test has been disabled because PadInfo is not currently supported in the C++ API.
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// Feature: Test Batch op with padding on TFReader
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// Description: Create Batch operation with padding on a TFReader dataset
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// Expectation: The data within the created object should match the expected data
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TEST_F(MindDataTestBatchOp, DISABLED_TestSimpleBatchPadding) {
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std::string schema_file = datasets_root_path_ + "/testBatchDataset/test.data";
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PadInfo m;
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std::shared_ptr<Tensor> pad_value;
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Tensor::CreateEmpty(TensorShape::CreateScalar(), DataType(DataType::DE_FLOAT32), &pad_value);
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pad_value->SetItemAt<float>({}, -1);
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m.insert({"col_1d", std::make_pair(TensorShape({4}), pad_value)});
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/*
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std::shared_ptr<ConfigManager> config_manager = GlobalContext::config_manager();
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auto op_connector_size = config_manager->op_connector_size();
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auto num_workers = config_manager->num_parallel_workers();
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std::vector<std::string> input_columns = {};
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std::vector<std::string> output_columns = {};
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pybind11::function batch_size_func;
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pybind11::function batch_map_func;
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*/
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int32_t batch_size = 12;
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bool drop = false;
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std::shared_ptr<BatchOp> op = Batch(batch_size, drop, m);
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// std::make_shared<BatchOp>(batch_size, drop, pad, op_connector_size, num_workers, input_columns, output_columns,
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// batch_size_func, batch_map_func, m);
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auto tree = Build({TFReader(schema_file), op});
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tree->Prepare();
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Status rc = tree->Launch();
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if (rc.IsError()) {
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MS_LOG(ERROR) << "Return code error detected during tree launch: " << rc.ToString() << ".";
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} else {
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int64_t payload[] = {-9223372036854775807 - 1,
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1,
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-1,
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-1,
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2,
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3,
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-1,
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-1,
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4,
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5,
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-1,
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-1,
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6,
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7,
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-1,
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-1,
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8,
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9,
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-1,
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-1,
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10,
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11,
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-1,
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-1,
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12,
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13,
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-1,
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-1,
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14,
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15,
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-1,
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-1,
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16,
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17,
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-1,
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-1,
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18,
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19,
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-1,
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-1,
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20,
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21,
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-1,
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-1,
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22,
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23,
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-1,
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-1};
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std::shared_ptr<de::Tensor> t;
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rc = de::Tensor::CreateFromMemory(de::TensorShape({12, 4}), de::DataType(DataType::DE_INT64),
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(unsigned char *)payload, &t);
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de::DatasetIterator di(tree);
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TensorMap tensor_map;
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rc = di.GetNextAsMap(&tensor_map);
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EXPECT_TRUE((*t) == (*(tensor_map["col_1d"])));
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rc = di.GetNextAsMap(&tensor_map);
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EXPECT_TRUE(tensor_map.size() == 0);
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EXPECT_TRUE(rc.IsOk());
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}
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}
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