54 lines
1.5 KiB
Python
54 lines
1.5 KiB
Python
from modules.utils.paths import *
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from modules.whisper.whisper_factory import WhisperFactory
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from modules.whisper.data_classes import *
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from test_config import *
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from test_transcription import download_file, test_transcribe
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import gradio as gr
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import pytest
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import torch
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import os
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@pytest.mark.skipif(
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not is_cuda_available(),
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reason="Skipping because the test only works on GPU"
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)
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@pytest.mark.parametrize(
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"whisper_type,vad_filter,bgm_separation,diarization",
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[
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(WhisperImpl.WHISPER.value, False, True, False),
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(WhisperImpl.FASTER_WHISPER.value, False, True, False),
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(WhisperImpl.INSANELY_FAST_WHISPER.value, False, True, False)
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]
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)
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def test_bgm_separation_pipeline(
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whisper_type: str,
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vad_filter: bool,
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bgm_separation: bool,
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diarization: bool,
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):
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test_transcribe(whisper_type, vad_filter, bgm_separation, diarization)
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@pytest.mark.skipif(
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not is_cuda_available(),
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reason="Skipping because the test only works on GPU"
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)
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@pytest.mark.parametrize(
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"whisper_type,vad_filter,bgm_separation,diarization",
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[
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(WhisperImpl.WHISPER.value, True, True, False),
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(WhisperImpl.FASTER_WHISPER.value, True, True, False),
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(WhisperImpl.INSANELY_FAST_WHISPER.value, True, True, False)
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]
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)
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def test_bgm_separation_with_vad_pipeline(
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whisper_type: str,
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vad_filter: bool,
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bgm_separation: bool,
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diarization: bool,
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):
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test_transcribe(whisper_type, vad_filter, bgm_separation, diarization)
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