Description
@gokulkarthik I am trying to run an inference with the following command
python3 -m TTS.bin.synthesize --text "राजस्थान और उत्तर प्रदेश से लेकर हरियाणा मध्य प्रदेश एवं उत्तराखंड में सेना में भर्ती से जुड़ी अग्निपथ स्कीमका विरोध जारी है"
--model_path /home/raj/Downloads/ai4bharat/text2speech/models/v1/hi/fastpitch/best_model.pth
--config_path /home/raj/Downloads/ai4bharat/text2speech/models/v1/hi/fastpitch/config.json
--vocoder_path /home/raj/Downloads/ai4bharat/text2speech/models/v1/hi/hifigan/best_model.pth
--vocoder_config_path /home/raj/Downloads/ai4bharat/text2speech/models/v1/hi/hifigan/config.json
--out_path /home/raj/Downloads/ai4bharat/output
I am getting this error
> Using model: fast_pitch
> Setting up Audio Processor...
| > sample_rate:22050
| > resample:False
| > num_mels:80
| > log_func:np.log
| > min_level_db:-100
| > frame_shift_ms:None
| > frame_length_ms:None
| > ref_level_db:20
| > fft_size:1024
| > power:1.5
| > preemphasis:0.0
| > griffin_lim_iters:60
| > signal_norm:False
| > symmetric_norm:True
| > mel_fmin:0
| > mel_fmax:8000.0
| > pitch_fmin:0.0
| > pitch_fmax:640.0
| > spec_gain:1.0
| > stft_pad_mode:reflect
| > max_norm:4.0
| > clip_norm:True
| > do_trim_silence:True
| > trim_db:60
| > do_sound_norm:False
| > do_amp_to_db_linear:True
| > do_amp_to_db_mel:True
| > do_rms_norm:False
| > db_level:None
| > stats_path:None
| > base:2.718281828459045
| > hop_length:256
| > win_length:1024
> Init speaker_embedding layer.
> Vocoder Model: hifigan
> Setting up Audio Processor...
| > sample_rate:22050
| > resample:False
| > num_mels:80
| > log_func:np.log
| > min_level_db:-100
| > frame_shift_ms:None
| > frame_length_ms:None
| > ref_level_db:20
| > fft_size:1024
| > power:1.5
| > preemphasis:0.0
| > griffin_lim_iters:60
| > signal_norm:False
| > symmetric_norm:True
| > mel_fmin:0
| > mel_fmax:8000.0
| > pitch_fmin:0.0
| > pitch_fmax:640.0
| > spec_gain:1.0
| > stft_pad_mode:reflect
| > max_norm:4.0
| > clip_norm:True
| > do_trim_silence:True
| > trim_db:60
| > do_sound_norm:False
| > do_amp_to_db_linear:True
| > do_amp_to_db_mel:True
| > do_rms_norm:False
| > db_level:None
| > stats_path:None
| > base:2.718281828459045
| > hop_length:256
| > win_length:1024
> Generator Model: hifigan_generator
> Discriminator Model: hifigan_discriminator
Removing weight norm...
Text: राजस्थान और उत्तर प्रदेश से लेकर हरियाणा मध्य प्रदेश एवं
उत्तराखंड में सेना में भर्ती से जुड़ी अग्निपथ स्कीमका विरोध जारी है
> Text splitted to sentences.
['राजस्थान और उत्तर प्रदेश से लेकर हरियाणा मध्य प्रदेश एवं उत्तराखंड में सेना में भर्ती से जुड़ी अग्निपथ स्कीमका विरोध जारी है']
Traceback (most recent call last):
File "/home/raj/anaconda3/envs/tts-env/lib/python3.10/runpy.py", line 196, in _run_module_as_main
return _run_code(code, main_globals, None,
File "/home/raj/anaconda3/envs/tts-env/lib/python3.10/runpy.py", line 86, in _run_code
exec(code, run_globals)
File "/home/raj/.local/lib/python3.10/site-packages/TTS/bin/synthesize.py", line 418, in
main()
File "/home/raj/.local/lib/python3.10/site-packages/TTS/bin/synthesize.py", line 396, in main
wav = synthesizer.tts(
File "/home/raj/.local/lib/python3.10/site-packages/TTS/utils/synthesizer.py", line 323, in tts
outputs = synthesis(
File "/home/raj/.local/lib/python3.10/site-packages/TTS/tts/utils/synthesis.py", line 213, in synthesis
outputs = run_model_torch(
File "/home/raj/.local/lib/python3.10/site-packages/TTS/tts/utils/synthesis.py", line 50, in run_model_torch
outputs = _func(
File "/home/raj/.local/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
File "/home/raj/.local/lib/python3.10/site-packages/TTS/tts/models/forward_tts.py", line 684, in inference
o_en, x_mask, g, _ = self._forward_encoder(x, x_mask, g)
File "/home/raj/.local/lib/python3.10/site-packages/TTS/tts/models/forward_tts.py", line 399, in _forward_encoder
g = self.emb_g(g) # [B, C, 1]
File "/home/raj/.local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "/home/raj/.local/lib/python3.10/site-packages/torch/nn/modules/sparse.py", line 162, in forward
return F.embedding(
File "/home/raj/.local/lib/python3.10/site-packages/torch/nn/functional.py", line 2210, in embedding
return torch.embedding(weight, input, padding_idx, scale_grad_by_freq, sparse)
TypeError: embedding(): argument 'indices' (position 2) must be Tensor, not NoneType