#!/usr/bin/env python # 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. # ============================================================================== import os import pytest import mindspore.dataset as ds from mindspore.mindrecord import FileWriter CV_FILE_NAME = "./imagenet.mindrecord" CV1_FILE_NAME = "./imagenet1.mindrecord" def create_cv_mindrecord(files_num): """tutorial for cv dataset writer.""" if os.path.exists(CV_FILE_NAME): os.remove(CV_FILE_NAME) if os.path.exists("{}.db".format(CV_FILE_NAME)): os.remove("{}.db".format(CV_FILE_NAME)) writer = FileWriter(CV_FILE_NAME, files_num) cv_schema_json = {"file_name": {"type": "string"}, "label": {"type": "int32"}, "data": {"type": "bytes"}} data = [{"file_name": "001.jpg", "label": 43, "data": bytes('0xffsafdafda', encoding='utf-8')}] writer.add_schema(cv_schema_json, "img_schema") writer.add_index(["file_name", "label"]) writer.write_raw_data(data) writer.commit() def create_diff_schema_cv_mindrecord(files_num): """tutorial for cv dataset writer.""" if os.path.exists(CV1_FILE_NAME): os.remove(CV1_FILE_NAME) if os.path.exists("{}.db".format(CV1_FILE_NAME)): os.remove("{}.db".format(CV1_FILE_NAME)) writer = FileWriter(CV1_FILE_NAME, files_num) cv_schema_json = {"file_name_1": {"type": "string"}, "label": {"type": "int32"}, "data": {"type": "bytes"}} data = [{"file_name_1": "001.jpg", "label": 43, "data": bytes('0xffsafdafda', encoding='utf-8')}] writer.add_schema(cv_schema_json, "img_schema") writer.add_index(["file_name_1", "label"]) writer.write_raw_data(data) writer.commit() def create_diff_page_size_cv_mindrecord(files_num): """tutorial for cv dataset writer.""" if os.path.exists(CV1_FILE_NAME): os.remove(CV1_FILE_NAME) if os.path.exists("{}.db".format(CV1_FILE_NAME)): os.remove("{}.db".format(CV1_FILE_NAME)) writer = FileWriter(CV1_FILE_NAME, files_num) writer.set_page_size(1 << 26) # 64MB cv_schema_json = {"file_name": {"type": "string"}, "label": {"type": "int32"}, "data": {"type": "bytes"}} data = [{"file_name": "001.jpg", "label": 43, "data": bytes('0xffsafdafda', encoding='utf-8')}] writer.add_schema(cv_schema_json, "img_schema") writer.add_index(["file_name", "label"]) writer.write_raw_data(data) writer.commit() def test_cv_lack_json(): """tutorial for cv minderdataset.""" create_cv_mindrecord(1) columns_list = ["data", "file_name", "label"] num_readers = 4 with pytest.raises(Exception): ds.MindDataset(CV_FILE_NAME, "no_exist.json", columns_list, num_readers) os.remove(CV_FILE_NAME) os.remove("{}.db".format(CV_FILE_NAME)) def test_cv_lack_mindrecord(): """tutorial for cv minderdataset.""" columns_list = ["data", "file_name", "label"] num_readers = 4 with pytest.raises(Exception, match="does not exist or permission denied"): _ = ds.MindDataset("no_exist.mindrecord", columns_list, num_readers) def test_invalid_mindrecord(): with open('dummy.mindrecord', 'w') as f: f.write('just for test') columns_list = ["data", "file_name", "label"] num_readers = 4 with pytest.raises(RuntimeError, match="Unexpected error. Invalid file " "content, incorrect file or file header is exceeds the upper limit."): data_set = ds.MindDataset( 'dummy.mindrecord', columns_list, num_readers) for _ in data_set.create_dict_iterator(num_epochs=1, output_numpy=True): pass os.remove('dummy.mindrecord') def test_minddataset_lack_db(): create_cv_mindrecord(1) os.remove("{}.db".format(CV_FILE_NAME)) columns_list = ["data", "file_name", "label"] num_readers = 4 with pytest.raises(RuntimeError, match="Unexpected error. Invalid database file, path:"): data_set = ds.MindDataset(CV_FILE_NAME, columns_list, num_readers) num_iter = 0 for _ in data_set.create_dict_iterator(num_epochs=1, output_numpy=True): num_iter += 1 try: assert num_iter == 0 except Exception as error: os.remove(CV_FILE_NAME) raise error else: os.remove(CV_FILE_NAME) def test_cv_minddataset_pk_sample_error_class_column(): create_cv_mindrecord(1) columns_list = ["data", "file_name", "label"] num_readers = 4 sampler = ds.PKSampler(5, None, True, 'no_exist_column') with pytest.raises(RuntimeError, match="Unexpected error. Failed to launch read threads."): data_set = ds.MindDataset( CV_FILE_NAME, columns_list, num_readers, sampler=sampler) num_iter = 0 for _ in data_set.create_dict_iterator(num_epochs=1, output_numpy=True): num_iter += 1 os.remove(CV_FILE_NAME) os.remove("{}.db".format(CV_FILE_NAME)) def test_cv_minddataset_pk_sample_exclusive_shuffle(): create_cv_mindrecord(1) columns_list = ["data", "file_name", "label"] num_readers = 4 sampler = ds.PKSampler(2) with pytest.raises(Exception, match="sampler and shuffle cannot be specified at the same time."): data_set = ds.MindDataset(CV_FILE_NAME, columns_list, num_readers, sampler=sampler, shuffle=False) num_iter = 0 for _ in data_set.create_dict_iterator(num_epochs=1, output_numpy=True): num_iter += 1 os.remove(CV_FILE_NAME) os.remove("{}.db".format(CV_FILE_NAME)) def test_cv_minddataset_reader_different_schema(): create_cv_mindrecord(1) create_diff_schema_cv_mindrecord(1) columns_list = ["data", "label"] num_readers = 4 with pytest.raises(RuntimeError, match="Unexpected error. Invalid data, " "MindRecord files meta data is not consistent."): data_set = ds.MindDataset([CV_FILE_NAME, CV1_FILE_NAME], columns_list, num_readers) num_iter = 0 for _ in data_set.create_dict_iterator(num_epochs=1): num_iter += 1 os.remove(CV_FILE_NAME) os.remove("{}.db".format(CV_FILE_NAME)) os.remove(CV1_FILE_NAME) os.remove("{}.db".format(CV1_FILE_NAME)) def test_cv_minddataset_reader_different_page_size(): create_cv_mindrecord(1) create_diff_page_size_cv_mindrecord(1) columns_list = ["data", "label"] num_readers = 4 with pytest.raises(RuntimeError, match="Unexpected error. Invalid data, " "MindRecord files meta data is not consistent."): data_set = ds.MindDataset([CV_FILE_NAME, CV1_FILE_NAME], columns_list, num_readers) num_iter = 0 for _ in data_set.create_dict_iterator(num_epochs=1): num_iter += 1 os.remove(CV_FILE_NAME) os.remove("{}.db".format(CV_FILE_NAME)) os.remove(CV1_FILE_NAME) os.remove("{}.db".format(CV1_FILE_NAME)) def test_minddataset_invalidate_num_shards(): create_cv_mindrecord(1) columns_list = ["data", "label"] num_readers = 4 with pytest.raises(Exception) as error_info: data_set = ds.MindDataset( CV_FILE_NAME, columns_list, num_readers, True, 1, 2) num_iter = 0 for _ in data_set.create_dict_iterator(num_epochs=1): num_iter += 1 try: assert 'Input shard_id is not within the required interval of [0, 0].' in str( error_info.value) except Exception as error: os.remove(CV_FILE_NAME) os.remove("{}.db".format(CV_FILE_NAME)) raise error else: os.remove(CV_FILE_NAME) os.remove("{}.db".format(CV_FILE_NAME)) def test_minddataset_invalidate_shard_id(): create_cv_mindrecord(1) columns_list = ["data", "label"] num_readers = 4 with pytest.raises(Exception) as error_info: data_set = ds.MindDataset( CV_FILE_NAME, columns_list, num_readers, True, 1, -1) num_iter = 0 for _ in data_set.create_dict_iterator(num_epochs=1): num_iter += 1 try: assert 'Input shard_id is not within the required interval of [0, 0].' in str( error_info.value) except Exception as error: os.remove(CV_FILE_NAME) os.remove("{}.db".format(CV_FILE_NAME)) raise error else: os.remove(CV_FILE_NAME) os.remove("{}.db".format(CV_FILE_NAME)) def test_minddataset_shard_id_bigger_than_num_shard(): create_cv_mindrecord(1) columns_list = ["data", "label"] num_readers = 4 with pytest.raises(Exception) as error_info: data_set = ds.MindDataset( CV_FILE_NAME, columns_list, num_readers, True, 2, 2) num_iter = 0 for _ in data_set.create_dict_iterator(num_epochs=1): num_iter += 1 try: assert 'Input shard_id is not within the required interval of [0, 1].' in str( error_info.value) except Exception as error: os.remove(CV_FILE_NAME) os.remove("{}.db".format(CV_FILE_NAME)) raise error with pytest.raises(Exception) as error_info: data_set = ds.MindDataset( CV_FILE_NAME, columns_list, num_readers, True, 2, 5) num_iter = 0 for _ in data_set.create_dict_iterator(num_epochs=1): num_iter += 1 try: assert 'Input shard_id is not within the required interval of [0, 1].' in str( error_info.value) except Exception as error: os.remove(CV_FILE_NAME) os.remove("{}.db".format(CV_FILE_NAME)) raise error else: os.remove(CV_FILE_NAME) os.remove("{}.db".format(CV_FILE_NAME)) def test_cv_minddataset_partition_num_samples_equals_0(): """tutorial for cv minddataset.""" create_cv_mindrecord(1) columns_list = ["data", "label"] num_readers = 4 def partitions(num_shards): for partition_id in range(num_shards): data_set = ds.MindDataset(CV_FILE_NAME, columns_list, num_readers, num_shards=num_shards, shard_id=partition_id, num_samples=-1) num_iter = 0 for _ in data_set.create_dict_iterator(num_epochs=1): num_iter += 1 with pytest.raises(ValueError) as error_info: partitions(5) try: assert 'num_samples exceeds the boundary between 0 and 9223372036854775807(INT64_MAX)' in str( error_info.value) except Exception as error: os.remove(CV_FILE_NAME) os.remove("{}.db".format(CV_FILE_NAME)) raise error else: os.remove(CV_FILE_NAME) os.remove("{}.db".format(CV_FILE_NAME)) def test_mindrecord_exception(): """tutorial for exception scenario of minderdataset + map would print error info.""" def exception_func(item): raise Exception("Error occur!") create_cv_mindrecord(1) columns_list = ["data", "file_name", "label"] with pytest.raises(RuntimeError, match="The corresponding data files"): data_set = ds.MindDataset(CV_FILE_NAME, columns_list, shuffle=False) data_set = data_set.map(operations=exception_func, input_columns=["data"], num_parallel_workers=1) num_iter = 0 for _ in data_set.create_dict_iterator(num_epochs=1, output_numpy=True): num_iter += 1 with pytest.raises(RuntimeError, match="The corresponding data files"): data_set = ds.MindDataset(CV_FILE_NAME, columns_list, shuffle=False) data_set = data_set.map(operations=exception_func, input_columns=["file_name"], num_parallel_workers=1) num_iter = 0 for _ in data_set.create_dict_iterator(num_epochs=1, output_numpy=True): num_iter += 1 with pytest.raises(RuntimeError, match="The corresponding data files"): data_set = ds.MindDataset(CV_FILE_NAME, columns_list, shuffle=False) data_set = data_set.map(operations=exception_func, input_columns=["label"], num_parallel_workers=1) num_iter = 0 for _ in data_set.create_dict_iterator(num_epochs=1, output_numpy=True): num_iter += 1 os.remove(CV_FILE_NAME) os.remove("{}.db".format(CV_FILE_NAME)) if __name__ == '__main__': test_cv_lack_json() test_cv_lack_mindrecord() test_invalid_mindrecord() test_minddataset_lack_db() test_cv_minddataset_pk_sample_error_class_column() test_cv_minddataset_pk_sample_exclusive_shuffle() test_cv_minddataset_reader_different_schema() test_cv_minddataset_reader_different_page_size() test_minddataset_invalidate_num_shards() test_minddataset_invalidate_shard_id() test_minddataset_shard_id_bigger_than_num_shard() test_cv_minddataset_partition_num_samples_equals_0() test_mindrecord_exception()