forked from huawei/mindspore2022
236 lines
9.3 KiB
Python
236 lines
9.3 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 LibriTTS 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/testLibriTTSData"
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def test_libri_tts_basic():
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"""
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Feature: LibriTTSDataset
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Description: test basic usage of LibriTTS
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Expectation: the dataset is as expected
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"""
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logger.info("Test LibriTTSDataset Op")
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# case 1: test loading fault dataset.
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data1 = ds.LibriTTSDataset(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.LibriTTSDataset(DATA_DIR, num_samples=1)
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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 == 1
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# case 3: test repeat.
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data3 = ds.LibriTTSDataset(DATA_DIR, usage="all", num_samples=3)
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data3 = data3.repeat(3)
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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 == 9
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# case 4: test batch with drop_remainder=False.
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data4 = ds.LibriTTSDataset(DATA_DIR, usage="train-clean-100", 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.LibriTTSDataset(DATA_DIR, usage="train-clean-100", 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_libri_tts_distribute_sampler():
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"""
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Feature: LibriTTSDataset
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Description: test LibriTTS dataset with DisributeSampler
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Expectation: the results are as expected
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"""
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logger.info("Test LibriTTS with sharding")
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list1, list2 = [], []
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num_shards = 3
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shard_id = 0
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data1 = ds.LibriTTSDataset(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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list1.append(item1["original_text"])
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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.LibriTTSDataset(DATA_DIR, usage="train-clean-100", 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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list2.append(item2["original_text"])
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count = count + 1
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assert count == 1
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def test_libri_tts_exception():
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"""
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Feature: LibriTTSDataset
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Description: test error cases for LibriTTSDataset
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Expectation: the results are as expected
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"""
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logger.info("Test error cases for LibriTTSDataset")
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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.LibriTTSDataset(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.LibriTTSDataset(DATA_DIR, sampler=ds.PKSampler(3), 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.LibriTTSDataset(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.LibriTTSDataset(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.LibriTTSDataset(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.LibriTTSDataset(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.LibriTTSDataset(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.LibriTTSDataset(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.LibriTTSDataset(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.LibriTTSDataset(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.LibriTTSDataset(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.LibriTTSDataset(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_libri_tts_sequential_sampler():
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"""
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Feature: LibriTTSDataset
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Description: test LibriTTSDataset with SequentialSampler
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Expectation: the results are as expected
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"""
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logger.info("Test LibriTTSDataset 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.LibriTTSDataset(DATA_DIR, usage="train-clean-100", sampler=sampler)
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data2 = ds.LibriTTSDataset(DATA_DIR, usage="train-clean-100", shuffle=False, num_samples=num_samples)
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list1, list2 = [], []
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list_expected = [24000, b'good morning', b'Good morning', 2506, 11267, b'2506_11267_000001_000000',
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24000, b'good afternoon', b'Good afternoon', 2506, 11267, b'2506_11267_000002_000000']
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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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list1.append(item1["sample_rate"])
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list2.append(item2["sample_rate"])
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list1.append(item1["original_text"])
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list2.append(item2["original_text"])
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list1.append(item1["normalized_text"])
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list2.append(item2["normalized_text"])
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list1.append(item1["speaker_id"])
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list2.append(item2["speaker_id"])
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list1.append(item1["chapter_id"])
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list2.append(item2["chapter_id"])
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list1.append(item1["utterance_id"])
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list2.append(item2["utterance_id"])
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num_iter += 1
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np.testing.assert_array_equal(list1, list_expected)
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np.testing.assert_array_equal(list2, list_expected)
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assert num_iter == num_samples
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def test_libri_tts_usage():
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"""
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Feature: LibriTTSDataset
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Description: test LibriTTSDataset usage
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Expectation: the results are as expected
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"""
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logger.info("Test LibriTTSDataset usage")
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def test_config(usage, libri_tts_path=None):
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libri_tts_path = DATA_DIR if libri_tts_path is None else libri_tts_path
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try:
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data = ds.LibriTTSDataset(libri_tts_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("all") == 3
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assert test_config("train-clean-100") == 3
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assert "Input usage is not within the valid set of ['dev-clean', 'dev-other', 'test-clean', 'test-other', " \
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"'train-clean-100', 'train-clean-360', 'train-other-500', '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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all_files_path = None
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if all_files_path is not None:
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assert test_config("train-clean-100", all_files_path) == 3
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assert ds.LibriTTSDataset(all_files_path, usage="train-clean-100").get_dataset_size() == 3
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assert test_config("all", all_files_path) == 3
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assert ds.LibriTTSDataset(all_files_path, usage="all").get_dataset_size() == 3
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if __name__ == '__main__':
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test_libri_tts_basic()
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test_libri_tts_distribute_sampler()
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test_libri_tts_exception()
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test_libri_tts_sequential_sampler()
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test_libri_tts_usage()
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