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debug: print is_inference() status before failing conv_pre call

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Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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Ethanfel
2026-04-09 02:41:51 +02:00
parent 78f8aa98ad
commit 9df855ee0e
1 changed files with 11 additions and 0 deletions
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nodes/selva_bigvgan_trainer.py
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@@ -305,6 +305,17 @@ def _do_train(vocoder, mel_converter, clips,
with torch.no_grad(): with torch.no_grad():
target_mel = mel_converter(target_flat) # [B, n_mels, T_mel] target_mel = mel_converter(target_flat) # [B, n_mels, T_mel]
if step == 0:
print(f"[BigVGAN DEBUG] inference_mode={torch.is_inference_mode_enabled()}", flush=True)
print(f"[BigVGAN DEBUG] clips[0].is_inference()={clips[0].is_inference()}", flush=True)
print(f"[BigVGAN DEBUG] mel_basis.is_inference()={mel_converter.mel_basis.is_inference()}", flush=True)
print(f"[BigVGAN DEBUG] target_flat.is_inference()={target_flat.is_inference()}", flush=True)
print(f"[BigVGAN DEBUG] target_mel.is_inference()={target_mel.is_inference()}", flush=True)
cp = vocoder.conv_pre
print(f"[BigVGAN DEBUG] conv_pre.weight.is_inference()={cp.weight.is_inference()}", flush=True)
if cp.bias is not None:
print(f"[BigVGAN DEBUG] conv_pre.bias.is_inference()={cp.bias.is_inference()}", flush=True)
pred_wav = vocoder(target_mel) # [B, 1, T_wav] pred_wav = vocoder(target_mel) # [B, 1, T_wav]
T = min(pred_wav.shape[-1], target_wav.shape[-1]) T = min(pred_wav.shape[-1], target_wav.shape[-1])