forked from huawei/mindspore2022
224 lines
8.4 KiB
Python
Executable File
224 lines
8.4 KiB
Python
Executable File
# Copyright 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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"""
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Test Caltech256 dataset operators
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"""
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import numpy as np
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import pytest
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import mindspore.dataset as ds
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import mindspore.dataset.vision.c_transforms as c_vision
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from mindspore import log as logger
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IMAGE_DATA_DIR = "../data/dataset/testPK/data"
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WRONG_DIR = "../data/dataset/notExist"
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def test_caltech256_basic():
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"""
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Feature: Caltech256Dataset
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Description: basic test of Caltech256Dataset
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Expectation: the data is processed successfully
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"""
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logger.info("Test Caltech256Dataset Op")
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# case 1: test read all data
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all_data_1 = ds.Caltech256Dataset(IMAGE_DATA_DIR, shuffle=False)
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all_data_2 = ds.Caltech256Dataset(IMAGE_DATA_DIR, shuffle=False)
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num_iter = 0
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for item1, item2 in zip(all_data_1.create_dict_iterator(num_epochs=1, output_numpy=True),
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all_data_2.create_dict_iterator(num_epochs=1, output_numpy=True)):
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np.testing.assert_array_equal(item1["label"], item2["label"])
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num_iter += 1
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assert num_iter == 44
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# case 2: test decode
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all_data_1 = ds.Caltech256Dataset(IMAGE_DATA_DIR, decode=True, shuffle=False)
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all_data_2 = ds.Caltech256Dataset(IMAGE_DATA_DIR, decode=True, shuffle=False)
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num_iter = 0
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for item1, item2 in zip(all_data_1.create_dict_iterator(num_epochs=1, output_numpy=True),
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all_data_2.create_dict_iterator(num_epochs=1, output_numpy=True)):
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np.testing.assert_array_equal(item1["label"], item2["label"])
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num_iter += 1
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assert num_iter == 44
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# case 3: test num_samples
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all_data = ds.Caltech256Dataset(IMAGE_DATA_DIR, num_samples=4)
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num_iter = 0
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for _ in all_data.create_dict_iterator(num_epochs=1):
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num_iter += 1
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assert num_iter == 4
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# case 4: test repeat
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all_data = ds.Caltech256Dataset(IMAGE_DATA_DIR, num_samples=4)
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all_data = all_data.repeat(2)
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num_iter = 0
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for _ in all_data.create_dict_iterator(num_epochs=1):
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num_iter += 1
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assert num_iter == 8
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# case 5: test get_dataset_size, resize and batch
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all_data = ds.Caltech256Dataset(IMAGE_DATA_DIR, num_samples=4)
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all_data = all_data.map(operations=[c_vision.Decode(), c_vision.Resize((224, 224))], input_columns=["image"],
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num_parallel_workers=1)
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assert all_data.get_dataset_size() == 4
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assert all_data.get_batch_size() == 1
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# drop_remainder is default to be False
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all_data = all_data.batch(batch_size=3)
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assert all_data.get_batch_size() == 3
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assert all_data.get_dataset_size() == 2
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num_iter = 0
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for _ in all_data.create_dict_iterator(num_epochs=1):
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num_iter += 1
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assert num_iter == 2
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def test_caltech256_decode():
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"""
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Feature: Caltech256Dataset
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Description: validate Caltech256Dataset with decode
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Expectation: the data is processed successfully
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"""
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logger.info("Validate Caltech256Dataset with decode")
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# define parameters
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repeat_count = 1
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data1 = ds.Caltech256Dataset(IMAGE_DATA_DIR, decode=True)
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data1 = data1.repeat(repeat_count)
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num_iter = 0
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# each data is a dictionary
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for item in data1.create_dict_iterator(num_epochs=1):
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# in this example, each dictionary has keys "image" and "label"
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logger.info("image is {}".format(item["image"]))
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logger.info("label is {}".format(item["label"]))
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num_iter += 1
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logger.info("Number of data in data1: {}".format(num_iter))
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assert num_iter == 44
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def test_caltech256_sequential_sampler():
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"""
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Feature: Caltech256Dataset
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Description: test Caltech256Dataset with SequentialSampler
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Expectation: the data is processed successfully
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"""
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logger.info("Test Caltech256Dataset Op with SequentialSampler")
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num_samples = 4
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sampler = ds.SequentialSampler(num_samples=num_samples)
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all_data_1 = ds.Caltech256Dataset(IMAGE_DATA_DIR, sampler=sampler)
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all_data_2 = ds.Caltech256Dataset(IMAGE_DATA_DIR, shuffle=False, num_samples=num_samples)
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label_list_1, label_list_2 = [], []
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num_iter = 0
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for item1, item2 in zip(all_data_1.create_dict_iterator(num_epochs=1),
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all_data_2.create_dict_iterator(num_epochs=1)):
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label_list_1.append(item1["label"].asnumpy())
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label_list_2.append(item2["label"].asnumpy())
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num_iter += 1
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np.testing.assert_array_equal(label_list_1, label_list_2)
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assert num_iter == num_samples
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def test_caltech256_random_sampler():
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"""
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Feature: Caltech256Dataset
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Description: test Caltech256Dataset with RandomSampler
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Expectation: the data is processed successfully
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"""
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logger.info("Test Caltech256Dataset Op with RandomSampler")
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# define parameters
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repeat_count = 1
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# apply dataset operations
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sampler = ds.RandomSampler()
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data1 = ds.Caltech256Dataset(IMAGE_DATA_DIR, sampler=sampler)
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data1 = data1.repeat(repeat_count)
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num_iter = 0
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# each data is a dictionary
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for item in data1.create_dict_iterator(num_epochs=1):
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# in this example, each dictionary has keys "image" and "label"
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logger.info("image is {}".format(item["image"]))
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logger.info("label is {}".format(item["label"]))
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num_iter += 1
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logger.info("Number of data in data1: {}".format(num_iter))
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assert num_iter == 44
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def test_caltech256_exception():
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"""
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Feature: Caltech256Dataset
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Description: test error cases for Caltech256Dataset
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Expectation: throw correct error and message
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"""
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logger.info("Test error cases for Caltech256Dataset")
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error_msg_1 = "sampler and shuffle cannot be specified at the same time"
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with pytest.raises(RuntimeError, match=error_msg_1):
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ds.Caltech256Dataset(IMAGE_DATA_DIR, shuffle=False, sampler=ds.SequentialSampler(1))
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error_msg_2 = "sampler and sharding cannot be specified at the same time"
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with pytest.raises(RuntimeError, match=error_msg_2):
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ds.Caltech256Dataset(IMAGE_DATA_DIR, sampler=ds.SequentialSampler(1), num_shards=2, shard_id=0)
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error_msg_3 = "num_shards is specified and currently requires shard_id as well"
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with pytest.raises(RuntimeError, match=error_msg_3):
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ds.Caltech256Dataset(IMAGE_DATA_DIR, num_shards=10)
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error_msg_4 = "shard_id is specified but num_shards is not"
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with pytest.raises(RuntimeError, match=error_msg_4):
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ds.Caltech256Dataset(IMAGE_DATA_DIR, shard_id=0)
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error_msg_5 = "Input shard_id is not within the required interval"
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with pytest.raises(ValueError, match=error_msg_5):
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ds.Caltech256Dataset(IMAGE_DATA_DIR, num_shards=5, shard_id=-1)
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with pytest.raises(ValueError, match=error_msg_5):
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ds.Caltech256Dataset(IMAGE_DATA_DIR, num_shards=5, shard_id=5)
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with pytest.raises(ValueError, match=error_msg_5):
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ds.Caltech256Dataset(IMAGE_DATA_DIR, num_shards=2, shard_id=5)
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error_msg_6 = "num_parallel_workers exceeds"
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with pytest.raises(ValueError, match=error_msg_6):
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ds.Caltech256Dataset(IMAGE_DATA_DIR, shuffle=False, num_parallel_workers=0)
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with pytest.raises(ValueError, match=error_msg_6):
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ds.Caltech256Dataset(IMAGE_DATA_DIR, shuffle=False, num_parallel_workers=256)
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with pytest.raises(ValueError, match=error_msg_6):
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ds.Caltech256Dataset(IMAGE_DATA_DIR, shuffle=False, num_parallel_workers=-2)
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error_msg_7 = "Argument shard_id"
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with pytest.raises(TypeError, match=error_msg_7):
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ds.Caltech256Dataset(IMAGE_DATA_DIR, num_shards=2, shard_id="0")
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error_msg_8 = "does not exist or is not a directory or permission denied!"
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with pytest.raises(ValueError, match=error_msg_8):
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all_data = ds.Caltech256Dataset(WRONG_DIR)
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for _ in all_data.create_dict_iterator(num_epochs=1):
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pass
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if __name__ == '__main__':
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test_caltech256_basic()
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test_caltech256_decode()
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test_caltech256_sequential_sampler()
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test_caltech256_random_sampler()
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test_caltech256_exception()
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