It seems that the Tacotron GST doesn't support interactive inference.
Here model.py:395, when we do interactive mode, the code will call the create_interactive_placeholders() instead of the build_graph().
However, Tacotron GST requires "mel_spec" and "spec_length" input_tensors['source_tensors'] list, which were built here data/text2speech.py:366 in the build_graph() function.
So when running in interactive mode, the code will prompt an error when it runs this line
File "t2s_interactive_run.py", line 36, in <module> model_T2S, checkpoint_T2S = get_model(args_T2S, "T2S") File "t2s_interactive_run.py", line 33, in get_model args, base_config, config_module, base_model, None) File "/xxxx/OpenSeq2Seq/open_seq2seq/utils/utils.py", line 790, in create_model model.compile(checkpoint=checkpoint) File "/xxxx/OpenSeq2Seq/open_seq2seq/models/model.py", line 411, in compile gpu_id=gpu_cnt File "/xxxx/OpenSeq2Seq/open_seq2seq/models/encoder_decoder.py", line 157, in _build_forward_pass_graph encoder_output = self.encoder.encode(input_dict=encoder_input) File "/xxxx/OpenSeq2Seq/open_seq2seq/encoders/encoder.py", line 138, in encode return self._encode(self._cast_types(input_dict)) File "/xxxx/OpenSeq2Seq/open_seq2seq/encoders/tacotron2_encoder.py", line 163, in _encode style_spec = input_dict['source_tensors'][2]
It does not support interactive inference.
The tacotron gst config does not have interactive_infer_params. But it will be fairly easy for you to add such functionality if you want.
It seems that the Tacotron GST doesn't support interactive inference.
Here model.py:395, when we do interactive mode, the code will call the create_interactive_placeholders() instead of the build_graph().
However, Tacotron GST requires "mel_spec" and "spec_length" input_tensors['source_tensors'] list, which were built here data/text2speech.py:366 in the build_graph() function.
So when running in interactive mode, the code will prompt an error when it runs this line
File "t2s_interactive_run.py", line 36, in <module> model_T2S, checkpoint_T2S = get_model(args_T2S, "T2S") File "t2s_interactive_run.py", line 33, in get_model args, base_config, config_module, base_model, None) File "/xxxx/OpenSeq2Seq/open_seq2seq/utils/utils.py", line 790, in create_model model.compile(checkpoint=checkpoint) File "/xxxx/OpenSeq2Seq/open_seq2seq/models/model.py", line 411, in compile gpu_id=gpu_cnt File "/xxxx/OpenSeq2Seq/open_seq2seq/models/encoder_decoder.py", line 157, in _build_forward_pass_graph encoder_output = self.encoder.encode(input_dict=encoder_input) File "/xxxx/OpenSeq2Seq/open_seq2seq/encoders/encoder.py", line 138, in encode return self._encode(self._cast_types(input_dict)) File "/xxxx/OpenSeq2Seq/open_seq2seq/encoders/tacotron2_encoder.py", line 163, in _encode style_spec = input_dict['source_tensors'][2]