mirror of https://github.com/coqui-ai/TTS.git
update config.json
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@ -34,7 +34,7 @@
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"signal_norm": true, // normalize spec values. Mean-Var normalization if 'stats_path' is defined otherwise range normalization defined by the other params.
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"min_level_db": -100, // lower bound for normalization
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"symmetric_norm": true, // move normalization to range [-1, 1]
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"max_norm": 1.0, // scale normalization to range [-max_norm, max_norm] or [0, max_norm]
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"max_norm": 4.0, // scale normalization to range [-max_norm, max_norm] or [0, max_norm]
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"clip_norm": true, // clip normalized values into the range.
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"stats_path": null // DO NOT USE WITH MULTI_SPEAKER MODEL. scaler stats file computed by 'compute_statistics.py'. If it is defined, mean-std based notmalization is used and other normalization params are ignored
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},
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@ -9,7 +9,7 @@ def check_update(model, grad_clip, ignore_stopnet=False):
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grad_norm = torch.nn.utils.clip_grad_norm_([param for name, param in model.named_parameters() if 'stopnet' not in name], grad_clip)
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else:
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grad_norm = torch.nn.utils.clip_grad_norm_(model.parameters(), grad_clip)
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if np.isinf(grad_norm):
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if torch.isinf(grad_norm):
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print(" | > Gradient is INF !!")
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skip_flag = True
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return grad_norm, skip_flag
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