224 lines
8.4 KiB
Python
224 lines
8.4 KiB
Python
# Copyright 2022 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 foNtest_resr 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 Gtzan 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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from mindspore import log as logger
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DATA_DIR = "../data/dataset/testGTZANData"
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def test_gtzan_basic():
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"""
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Feature: GTZANDataset
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Description: Test basic usage of GTZAN
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Expectation: The dataset is as expected
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"""
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logger.info("Test GTZANDataset Op")
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# case 1: test loading whole dataset.
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data1 = ds.GTZANDataset(DATA_DIR)
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num_iter1 = 0
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for _ in data1.create_dict_iterator(output_numpy=True, num_epochs=1):
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num_iter1 += 1
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assert num_iter1 == 3
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# case 2: test num_samples.
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data2 = ds.GTZANDataset(DATA_DIR, num_samples=2)
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num_iter2 = 0
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for _ in data2.create_dict_iterator(output_numpy=True, num_epochs=1):
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num_iter2 += 1
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assert num_iter2 == 2
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# case 3: test repeat.
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data3 = ds.GTZANDataset(DATA_DIR, num_samples=2)
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data3 = data3.repeat(5)
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num_iter3 = 0
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for _ in data3.create_dict_iterator(output_numpy=True, num_epochs=1):
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num_iter3 += 1
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assert num_iter3 == 10
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# case 4: test batch with drop_remainder=False.
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data4 = ds.GTZANDataset(DATA_DIR, num_samples=3)
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assert data4.get_dataset_size() == 3
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assert data4.get_batch_size() == 1
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data4 = data4.batch(batch_size=2) # drop_remainder is default to be False.
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assert data4.get_dataset_size() == 2
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assert data4.get_batch_size() == 2
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# case 5: test batch with drop_remainder=True.
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data5 = ds.GTZANDataset(DATA_DIR, num_samples=3)
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assert data5.get_dataset_size() == 3
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assert data5.get_batch_size() == 1
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# the rest of incomplete batch will be dropped.
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data5 = data5.batch(batch_size=2, drop_remainder=True)
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assert data5.get_dataset_size() == 1
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assert data5.get_batch_size() == 2
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def test_gtzan_distribute_sampler():
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"""
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Feature: GTZANDataset
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Description: Test GTZAN dataset with DistributedSampler
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Expectation: The results are as expected
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"""
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logger.info("Test GTZAN with DistributedSampler")
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label_list1, label_list2 = [], []
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num_shards = 3
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shard_id = 0
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data1 = ds.GTZANDataset(DATA_DIR, usage="all", num_shards=num_shards, shard_id=shard_id)
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count = 0
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for item1 in data1.create_dict_iterator(output_numpy=True, num_epochs=1):
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label_list1.append(item1["label"])
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count = count + 1
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assert count == 1
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num_shards = 3
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shard_id = 0
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sampler = ds.DistributedSampler(num_shards, shard_id)
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data2 = ds.GTZANDataset(DATA_DIR, usage="all", sampler=sampler)
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count = 0
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for item2 in data2.create_dict_iterator(output_numpy=True, num_epochs=1):
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label_list2.append(item2["label"])
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count = count + 1
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np.testing.assert_array_equal(label_list1, label_list2)
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assert count == 1
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def test_gtzan_exception():
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"""
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Feature: GTZANDataset
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Description: Test error cases for GTZANDataset
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Expectation: The results are as expected
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"""
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logger.info("Test error cases for GTZANDataset")
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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.GTZANDataset(DATA_DIR, shuffle=False, sampler=ds.PKSampler(3))
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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.GTZANDataset(DATA_DIR, sampler=ds.PKSampler(3),
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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.GTZANDataset(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.GTZANDataset(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.GTZANDataset(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.GTZANDataset(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.GTZANDataset(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.GTZANDataset(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.GTZANDataset(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.GTZANDataset(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.GTZANDataset(DATA_DIR, num_shards=2, shard_id="0")
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def exception_func(item):
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raise Exception("Error occur!")
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error_msg_8 = "The corresponding data files"
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with pytest.raises(RuntimeError, match=error_msg_8):
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data = ds.GTZANDataset(DATA_DIR)
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data = data.map(operations=exception_func, input_columns=["waveform"], num_parallel_workers=1)
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for _ in data.create_dict_iterator(output_numpy=True, num_epochs=1):
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pass
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def test_gtzan_sequential_sampler():
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"""
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Feature: GTZANDataset
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Description: Test GTZANDataset with SequentialSampler
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Expectation: The results are as expected
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"""
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logger.info("Test GTZANDataset Op with SequentialSampler")
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num_samples = 2
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sampler = ds.SequentialSampler(num_samples=num_samples)
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data1 = ds.GTZANDataset(DATA_DIR, sampler=sampler)
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data2 = ds.GTZANDataset(DATA_DIR, shuffle=False, num_samples=num_samples)
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label_list1, label_list2 = [], []
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num_iter = 0
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for item1, item2 in zip(data1.create_dict_iterator(output_numpy=True, num_epochs=1),
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data2.create_dict_iterator(output_numpy=True, num_epochs=1)):
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label_list1.append(item1["label"])
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label_list2.append(item2["label"])
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num_iter += 1
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np.testing.assert_array_equal(label_list1, label_list2)
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assert num_iter == num_samples
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def test_gtzan_usage():
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"""
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Feature: GTZANDataset
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Description: Test GTZANDataset usage
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Expectation: The results are as expected
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"""
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logger.info("Test GTZANDataset usage")
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def test_config(usage, gtzan_path=None):
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gtzan_path = DATA_DIR if gtzan_path is None else gtzan_path
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try:
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data = ds.GTZANDataset(gtzan_path, usage=usage, shuffle=False)
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num_rows = 0
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for _ in data.create_dict_iterator(num_epochs=1, output_numpy=True):
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num_rows += 1
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except (ValueError, TypeError, RuntimeError) as e:
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return str(e)
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return num_rows
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assert test_config("valid") == 3
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assert test_config("all") == 3
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assert "usage is not within the valid set of ['train', 'valid', 'test', 'all']" in test_config("invalid")
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assert "Argument usage with value ['list'] is not of type [<class 'str'>]" in test_config(["list"])
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# change this directory to the folder that contains all gtzan files.
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all_files_path = None
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# the following tests on the entire datasets.
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if all_files_path is not None:
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assert test_config("train", all_files_path) == 3
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assert test_config("valid", all_files_path) == 3
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assert ds.GTZANDataset(all_files_path, usage="train").get_dataset_size() == 3
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assert ds.GTZANDataset(all_files_path, usage="valid").get_dataset_size() == 3
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if __name__ == '__main__':
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test_gtzan_basic()
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test_gtzan_distribute_sampler()
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test_gtzan_exception()
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test_gtzan_sequential_sampler()
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test_gtzan_usage()
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