save/load ckpt, inference #1
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ddlBoJack
reviewed
Nov 27, 2023
| prompt_length = len(prompt_ids) | ||
| speech_length = (speech_mel.shape[0] + 1) // 2 # ad-hoc for whisper for 2x downsample from mel to feats | ||
| speech_pseudo = torch.full((speech_length,),-1) | ||
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| example = prompt + answer | ||
| example_ids = self.tokenizer.encode(example) # [prompt,answer] | ||
| example_ids = self.tokenizer.encode(answer) # FIX(GZF): [answer] |
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need fix for tokenizer.encode(will add a bos token)
ddlBoJack
reviewed
Nov 27, 2023
| self.speech_encoder_projector = nn.Linear(self.speech_encoder.ln_post.normalized_shape[0] ,self.llm.config.hidden_size) | ||
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| self.speech_encoder_projector = nn.Linear(self.speech_encoder.ln_post.normalized_shape[0], self.llm.config.hidden_size) | ||
| ckpt_path = kwargs.get("ckpt_path", None) |
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load checkpoint will move to model_factory: setup_model
ddlBoJack
reviewed
Nov 27, 2023
| @@ -152,18 +163,90 @@ def forward(self, | |||
| speech_encoder_outs = None | |||
| if speech_mel is not None: | |||
| speech_encoder_outs = self.speech_encoder.extract_variable_length_features(speech_mel.permute(0, 2, 1)) | |||
| speech_encoder_outs = self.speech_encoder_projector(speech_encoder_outs) | |||
| speech_encoder_outs = self.speech_encoder_projector.to(speech_encoder_outs.device)(speech_encoder_outs) | |||
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need fix, move to finetune.py: main
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