forked from huawei/mindspore2022
162 lines
6.1 KiB
Python
162 lines
6.1 KiB
Python
# 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 LJSpeech 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.audio.transforms as audio
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from mindspore import log as logger
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DATA_DIR = "../data/dataset/testLJSpeechData/"
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def test_lj_speech_basic():
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"""
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Feature: LJSpeechDataset
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Description: basic test of LJSpeechDataset
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Expectation: the data is processed successfully
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"""
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logger.info("Test LJSpeechDataset Op")
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# case 1: test loading whole dataset
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data1 = ds.LJSpeechDataset(DATA_DIR)
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num_iter1 = 0
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for _ in data1.create_dict_iterator(num_epochs=1, output_numpy=True):
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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.LJSpeechDataset(DATA_DIR, num_samples=3)
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num_iter2 = 0
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for _ in data2.create_dict_iterator(num_epochs=1, output_numpy=True):
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num_iter2 += 1
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assert num_iter2 == 3
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# case 3: test repeat
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data3 = ds.LJSpeechDataset(DATA_DIR, num_samples=3)
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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(num_epochs=1, output_numpy=True):
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num_iter3 += 1
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assert num_iter3 == 15
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def test_lj_speech_sequential_sampler():
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"""
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Feature: LJSpeechDataset
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Description: test LJSpeechDataset with SequentialSampler
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Expectation: the data is processed successfully
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"""
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logger.info("Test LJSpeechDataset Op with SequentialSampler")
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num_samples = 3
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sampler = ds.SequentialSampler(num_samples=num_samples)
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data1 = ds.LJSpeechDataset(DATA_DIR, sampler=sampler)
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data2 = ds.LJSpeechDataset(DATA_DIR, shuffle=False, num_samples=num_samples)
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sample_rate_list1, sample_rate_list2 = [], []
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num_iter = 0
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for item1, item2 in zip(data1.create_dict_iterator(num_epochs=1, output_numpy=True),
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data2.create_dict_iterator(num_epochs=1, output_numpy=True)):
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sample_rate_list1.append(item1["sample_rate"])
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sample_rate_list2.append(item2["sample_rate"])
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num_iter += 1
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np.testing.assert_array_equal(sample_rate_list1, sample_rate_list2)
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assert num_iter == num_samples
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def test_lj_speech_exception():
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"""
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Feature: LJSpeechDataset
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Description: test error cases for LJSpeechDataset
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Expectation: throw correct error and message
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"""
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logger.info("Test error cases for LJSpeechDataset")
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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.LJSpeechDataset(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.LJSpeechDataset(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.LJSpeechDataset(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.LJSpeechDataset(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.LJSpeechDataset(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.LJSpeechDataset(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.LJSpeechDataset(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.LJSpeechDataset(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.LJSpeechDataset(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.LJSpeechDataset(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.LJSpeechDataset(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.LJSpeechDataset(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.__iter__():
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pass
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with pytest.raises(RuntimeError, match=error_msg_8):
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data = ds.LJSpeechDataset(DATA_DIR)
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data = data.map(operations=exception_func, input_columns=["sample_rate"], num_parallel_workers=1)
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for _ in data.__iter__():
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pass
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def test_lj_speech_pipeline():
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"""
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Feature: LJSpeechDataset
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Description: Read a sample
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Expectation: The amount of each function are equal
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"""
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# Original waveform
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dataset = ds.LJSpeechDataset(DATA_DIR)
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band_biquad_op = audio.BandBiquad(8000, 200.0)
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# Filtered waveform by bandbiquad
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dataset = dataset.map(input_columns=["waveform"], operations=band_biquad_op, num_parallel_workers=2)
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i = 0
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for _ in dataset.create_dict_iterator(num_epochs=1, output_numpy=True):
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i += 1
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assert i == 3
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if __name__ == '__main__':
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test_lj_speech_basic()
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test_lj_speech_sequential_sampler()
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test_lj_speech_exception()
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test_lj_speech_pipeline()
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