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oobabooga 2023-05-09 20:20:35 -03:00
parent e9e75a9ec7
commit 8fa5f651d6
3 changed files with 9 additions and 10 deletions
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8
extensions/multimodal/multimodal_embedder.py
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@ -46,12 +46,12 @@ class MultimodalEmbedder:
break
# found an image, append image start token to the text
if match.start() > 0:
parts.append(PromptPart(text=prompt[curr:curr+match.start()]+self.pipeline.image_start()))
parts.append(PromptPart(text=prompt[curr:curr + match.start()] + self.pipeline.image_start()))
else:
parts.append(PromptPart(text=self.pipeline.image_start()))
# append the image
parts.append(PromptPart(
text=match.group(0),
text=match.group(0),
image=Image.open(BytesIO(base64.b64decode(match.group(1)))) if load_images else None,
is_image=True
))
@ -94,14 +94,14 @@ class MultimodalEmbedder:
def _encode_text(self, state, parts: List[PromptPart]) -> List[PromptPart]:
"""Encode text to token_ids, also truncate the prompt, if necessary.
The chat/instruct mode should make prompts that fit in get_max_prompt_length, but if max_new_tokens are set
such that the context + min_rows don't fit, we can get a prompt which is too long.
We can't truncate image embeddings, as it leads to broken generation, so remove the images instead and warn the user
"""
encoded: List[PromptPart] = []
for i, part in enumerate(parts):
encoded.append(self._encode_single_text(part, i==0 and state['add_bos_token']))
encoded.append(self._encode_single_text(part, i == 0 and state['add_bos_token']))
# truncation:
max_len = get_max_prompt_length(state)

2
extensions/multimodal/pipeline_loader.py
View File

@ -26,7 +26,7 @@ def load_pipeline(params: dict) -> Tuple[AbstractMultimodalPipeline, str]:
if shared.args.multimodal_pipeline is not None:
for k in pipeline_modules:
if hasattr(pipeline_modules[k], 'get_pipeline'):
if hasattr(pipeline_modules[k], 'get_pipeline'):
pipeline = getattr(pipeline_modules[k], 'get_pipeline')(shared.args.multimodal_pipeline, params)
if pipeline is not None:
return (pipeline, k)

9
extensions/multimodal/script.py
View File

@ -42,14 +42,13 @@ def add_chat_picture(picture, text, visible_text):
longest_edge = int(shortest_edge * aspect_ratio)
w = shortest_edge if picture.width < picture.height else longest_edge
h = shortest_edge if picture.width >= picture.height else longest_edge
picture = picture.resize((w,h))
picture = picture.resize((w, h))
buffer = BytesIO()
picture.save(buffer, format="JPEG")
img_str = base64.b64encode(buffer.getvalue()).decode('utf-8')
image = f'<img src="data:image/jpeg;base64,{img_str}">'
if '<image>' in text:
text = text.replace('<image>', image)
else:
@ -80,8 +79,8 @@ def tokenizer_modifier(state, prompt, input_ids, input_embeds):
prompt, input_ids, input_embeds, total_embedded = multimodal_embedder.forward(prompt, state, params)
logging.info(f'Embedded {total_embedded} image(s) in {time.time()-start_ts:.2f}s')
return (prompt,
input_ids.unsqueeze(0).to(shared.model.device, dtype=torch.int64),
input_embeds.unsqueeze(0).to(shared.model.device, dtype=shared.model.dtype))
input_ids.unsqueeze(0).to(shared.model.device, dtype=torch.int64),
input_embeds.unsqueeze(0).to(shared.model.device, dtype=shared.model.dtype))
def ui():
@ -97,7 +96,7 @@ def ui():
[picture_select],
None
)
picture_select.clear(lambda: input_hijack.update({"state": False, "value": ["",""]}), None, None)
picture_select.clear(lambda: input_hijack.update({"state": False, "value": ["", ""]}), None, None)
single_image_checkbox.change(lambda x: params.update({"add_all_images_to_prompt": x}), single_image_checkbox, None)
shared.gradio['Generate'].click(lambda: None, None, picture_select)
shared.gradio['textbox'].submit(lambda: None, None, picture_select)