Absorb non-MM OpenAI dialog parsing into generic input parsing #1248
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/torchchat/1248
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit 29f5204 with merge base edaa15c ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
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Oct 1, 2024
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| assert ( | ||
| max_new_tokens is not None | ||
| ), "max_new_tokens must be specified for Flamingo models" | ||
| assert isinstance( | ||
| prompt, str | ||
| ), "(Currently) prompt must be a str for Flamingo models" | ||
|
|
||
| is_multimodal = images is not None | ||
| content = [{"type": "text", "content": prompt}] | ||
| is_multimodal = images is not None | ||
| content = [{"type": "text", "content": prompt}] | ||
|
|
||
| if is_multimodal: | ||
| content = [{"type": "image", "content": images[0]}] + content | ||
| if is_multimodal: | ||
| content = [{"type": "image", "content": images[0]}] + content | ||
|
|
||
| messages = [ | ||
| Message( | ||
| role="user", | ||
| content=content, | ||
| eot=True, | ||
| ), | ||
| Message(role="assistant", content=""), | ||
| ] | ||
| messages = [ | ||
| Message( | ||
| role="user", | ||
| content=content, | ||
| eot=True, | ||
| ), | ||
| Message(role="assistant", content=""), | ||
| ] | ||
|
|
||
| transform = llama3_2_vision_transform(str(self.tokenizer_args.tokenizer_path)) | ||
| transform = llama3_2_vision_transform(str(self.tokenizer_args.tokenizer_path)) | ||
|
|
||
| device = torch.device(device=self.builder_args.device) | ||
| device = torch.device(device=self.builder_args.device) | ||
|
|
||
| with device, set_default_dtype(self.dtype): | ||
| data = transform({"messages": messages}, inference=True) | ||
| with device, set_default_dtype(self.dtype): | ||
| data = transform({"messages": messages}, inference=True) | ||
|
|
||
| if is_multimodal: | ||
| batch = padded_collate_tiled_images_and_mask( | ||
| [data], pad_direction="left", pad_max_images=1 | ||
| ) | ||
| encoded = batch.pop("tokens").to(device).view(-1) | ||
| seq_len = encoded.size(0) | ||
| batch["encoder_mask"] = batch["encoder_mask"][:, :seq_len] | ||
| batch["encoder_input"]["images"] = batch["encoder_input"]["images"].to(self.dtype) | ||
| else: | ||
| encoded = torch.tensor( | ||
| data["tokens"], device=device | ||
| ).view(-1) | ||
| seq_len = encoded.size(0) | ||
| batch = {} | ||
|
|
||
| total_response_length = seq_len + max_new_tokens | ||
| batch["causal_mask"] = torch.tril( | ||
| torch.ones( | ||
| size=(total_response_length, total_response_length), | ||
| dtype=torch.bool, | ||
| ) | ||
| ) | ||
| else: | ||
| encoded = self.encode_tokens( | ||
| prompt, bos=True, device=self.builder_args.device | ||
| if is_multimodal: | ||
| batch = padded_collate_tiled_images_and_mask( | ||
| [data], pad_direction="left", pad_max_images=1 | ||
| ) | ||
| encoded = batch.pop("tokens").to(device).view(-1) | ||
| seq_len = encoded.size(0) | ||
| batch["encoder_mask"] = batch["encoder_mask"][:, :seq_len] | ||
| batch["encoder_input"]["images"] = batch["encoder_input"]["images"].to( | ||
| self.dtype | ||
| ) | ||
| else: | ||
| encoded = torch.tensor(data["tokens"], device=device).view(-1) | ||
| seq_len = encoded.size(0) | ||
| batch = {} | ||
|
|
||
| total_response_length = seq_len + max_new_tokens | ||
| batch["causal_mask"] = torch.tril( | ||
| torch.ones( | ||
| size=(total_response_length, total_response_length), | ||
| dtype=torch.bool, | ||
| ) |
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byjlw
approved these changes
Oct 1, 2024
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Refactor the OpenAI parsing logic for non-MM dialog into
_gen_model_inputof generate.pyTested via Browser
Then test in browser with 1B (Text only - Saw it can do multiturn) and 11B (Multimodal - No multiturn as expected)