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import pytest | |
from src import output, config | |
import test_config | |
def test_write_audio(): | |
""" | |
Tests write_audio function, takes in an audio tensor with a file path and writes the audio to a file. | |
""" | |
import torch | |
test_path = test_config.data_path / 'test_audio.wav' | |
audio_path = test_config.data_path / 'test_audio.pt' | |
audio_list = torch.load(audio_path) | |
output.write_audio(audio_list, test_path) | |
assert test_path.is_file() | |
assert test_path.stat().st_size == 592858 | |
test_path.unlink() | |
def test_assemble_zip(): | |
""" | |
Tests assemble_zip function, which collects all the audio files from the output directory, | |
and zips them up into a zip directory. | |
""" | |
from shutil import copy2 | |
if not config.output_path.exists(): | |
config.output_path.mkdir() | |
title = "speaker_samples" | |
zip_path = config.output_path / 'speaker_samples.zip' | |
wav1_path = config.output_path / 'speaker_en_0.wav' | |
wav2_path = config.output_path / 'speaker_en_110.wav' | |
for file_path in config.resource_path.iterdir(): | |
if file_path.suffix == '.wav': | |
copy2(file_path, config.output_path) | |
_ = output.assemble_zip(title) | |
assert zip_path.is_file() | |
assert not wav1_path.is_file() | |
assert not wav2_path.is_file() | |
zip_path.unlink() | |