26 lines
729 B
Python
26 lines
729 B
Python
import pytest
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import torch
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import numpy as np
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from enhancer.inference import Inference
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@pytest.mark.parametrize("audio",["tests/data/vctk/clean_testset_wav/p257_166.wav",torch.rand(1,2,48000)])
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def test_read_input(audio):
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read_audio = Inference.read_input(audio,48000,16000)
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assert isinstance(read_audio,torch.Tensor)
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assert read_audio.shape[0] == 1
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def test_batchify():
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rand = torch.rand(1,1000)
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batched_rand = Inference.batchify(rand, window_size = 100, step_size=100)
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assert batched_rand.shape[0] == 12
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def test_aggregate():
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rand = torch.rand(12,1,100)
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agg_rand = Inference.aggreagate(data=rand,window_size=100,total_frames=1000,step_size=100)
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assert agg_rand.shape[-1] == 1000
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