Change the utils.download_emo_models (#199)
* Change the utils.download_emo_models Change utils.download_emo_models(config.mirror, model_name, REPO_ID) to utils.download_emo_models(config.mirror, REPO_ID, model_name) * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
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@@ -6,6 +6,7 @@ import librosa
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import numpy as np
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import torch
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import torch.nn as nn
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from torch.utils.data import Dataset
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from torch.utils.data import DataLoader, Dataset
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from tqdm import tqdm
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from transformers import Wav2Vec2Processor
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@@ -108,7 +109,7 @@ def get_emo(path):
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wav, sr = librosa.load(path, 16000)
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device = config.bert_gen_config.device
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return process_func(
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np.expand_dims(wav, 0).astype(np.float64),
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np.expand_dims(wav, 0).astype(np.float),
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sr,
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model,
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processor,
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@@ -134,7 +135,7 @@ if __name__ == "__main__":
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model_name = "./emotional/wav2vec2-large-robust-12-ft-emotion-msp-dim"
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REPO_ID = "audeering/wav2vec2-large-robust-12-ft-emotion-msp-dim"
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if not Path(model_name).joinpath("pytorch_model.bin").exists():
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utils.download_emo_models(config.mirror, model_name, REPO_ID)
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utils.download_emo_models(config.mirror, REPO_ID, model_name)
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processor = Wav2Vec2Processor.from_pretrained(model_name)
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model = EmotionModel.from_pretrained(model_name).to(device)
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