forked from camenduru/ai-voice-cloning
rocm5.2 works for me desu so I bumped it back up
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e680d84a13
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@ -7,7 +7,7 @@ python3 -m venv venv
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source ./venv/bin/activate
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source ./venv/bin/activate
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python3 -m pip install --upgrade pip # just to be safe
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python3 -m pip install --upgrade pip # just to be safe
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# ROCM
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# ROCM
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pip3 install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/rocm5.1.1 # 5.2 does not work for me desu
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pip3 install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/rocm5.2
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# install requirements
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# install requirements
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python3 -m pip install -r ./modules/tortoise-tts/requirements.txt # install TorToiSe requirements
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python3 -m pip install -r ./modules/tortoise-tts/requirements.txt # install TorToiSe requirements
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python3 -m pip install -e ./modules/tortoise-tts/ # install TorToiSe
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python3 -m pip install -e ./modules/tortoise-tts/ # install TorToiSe
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10
src/utils.py
10
src/utils.py
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@ -1079,7 +1079,7 @@ def prepare_dataset( files, outdir, language=None, skip_existings=False, slice_a
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if match[0] not in previous_list:
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if match[0] not in previous_list:
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previous_list.append(f'{match[0].split("/")[-1]}.wav')
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previous_list.append(f'{match[0].split("/")[-1]}.wav')
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def validate_waveform( waveform, sample_rate, name ):
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def validate_waveform( waveform, sample_rate ):
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if not torch.any(waveform < 0):
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if not torch.any(waveform < 0):
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return False
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return False
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@ -1102,8 +1102,8 @@ def prepare_dataset( files, outdir, language=None, skip_existings=False, slice_a
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num_channels, num_frames = waveform.shape
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num_channels, num_frames = waveform.shape
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if not slice_audio:
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if not slice_audio:
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if not validate_waveform( waveform, sampling_rate, name ):
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if not validate_waveform( waveform, sampling_rate ):
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print(f"Segment invalid: {name}, skipping...")
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print(f"Invalid waveform: {basename}, skipping...")
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continue
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continue
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torchaudio.save(f"{outdir}/audio/{basename}", waveform, sampling_rate)
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torchaudio.save(f"{outdir}/audio/{basename}", waveform, sampling_rate)
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@ -1120,8 +1120,8 @@ def prepare_dataset( files, outdir, language=None, skip_existings=False, slice_a
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sliced_waveform = waveform[:, start:end]
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sliced_waveform = waveform[:, start:end]
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sliced_name = basename.replace(".wav", f"_{pad(idx, 4)}.wav")
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sliced_name = basename.replace(".wav", f"_{pad(idx, 4)}.wav")
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if not validate_waveform( sliced_waveform, sampling_rate, sliced_name ):
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if not validate_waveform( sliced_waveform, sampling_rate ):
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print(f"Trimmed segment invalid: {sliced_name}, skipping...")
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print(f"Invalid waveform segment ({segment['start']}:{segment['end']}): {sliced_name}, skipping...")
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continue
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continue
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torchaudio.save(f"{outdir}/audio/{sliced_name}", sliced_waveform, sampling_rate)
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torchaudio.save(f"{outdir}/audio/{sliced_name}", sliced_waveform, sampling_rate)
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