ryanzhangfan
commited on
Commit
•
bf2ce69
1
Parent(s):
e7d43f2
add support for batch image generation
Browse files- processing_emu3.py +7 -4
- utils_emu3.py +11 -5
processing_emu3.py
CHANGED
@@ -84,7 +84,7 @@ class Emu3Processor(ProcessorMixin):
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image: Optional[Image.Image | List[Image.Image]] = None,
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*,
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mode: str = "G",
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-
ratio: str = "1:1",
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image_area: int = 518400,
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**kwargs,
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) -> BatchFeature:
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@@ -129,8 +129,11 @@ class Emu3Processor(ProcessorMixin):
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if image is not None:
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raise ValueError("You have to specify only `text` in generation mode")
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if
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-
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else:
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if image is None:
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raise ValueError("Invalid input image. Please provide exactly one PIL.Image.Image per text.")
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@@ -165,7 +168,7 @@ class Emu3Processor(ProcessorMixin):
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)
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prompt += self.chat_template.format(image_prompt=image_prompt, text_prompt=text_prompt)
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else:
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-
h, w = self.calculate_generate_size(ratio, image_area, self.vision_tokenizer.spatial_scale_factor)
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image_prompt = (
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self.tokenizer.boi_token +
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self.prefix_template.format(H=h, W=w) +
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image: Optional[Image.Image | List[Image.Image]] = None,
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*,
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mode: str = "G",
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+
ratio: str | List[str] = "1:1",
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image_area: int = 518400,
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**kwargs,
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) -> BatchFeature:
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if image is not None:
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raise ValueError("You have to specify only `text` in generation mode")
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+
if isinstance(ratio, str):
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ratio = [ratio] * len(text)
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+
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if len(ratio) != len(text):
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raise ValueError("ratio number must match text number")
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else:
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if image is None:
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raise ValueError("Invalid input image. Please provide exactly one PIL.Image.Image per text.")
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)
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prompt += self.chat_template.format(image_prompt=image_prompt, text_prompt=text_prompt)
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else:
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+
h, w = self.calculate_generate_size(ratio[idx], image_area, self.vision_tokenizer.spatial_scale_factor)
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image_prompt = (
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self.tokenizer.boi_token +
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self.prefix_template.format(H=h, W=w) +
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utils_emu3.py
CHANGED
@@ -47,16 +47,22 @@ class Emu3PrefixConstrainedLogitsHelper:
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position = torch.nonzero(input_ids == self.img_token, as_tuple=True)[0][0]
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self.offset_cache[batch_id] = position
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offset = input_ids.shape[0] - self.offset_cache[batch_id]
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-
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return (self.eol_token, )
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-
elif offset == (
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return (self.eof_token, )
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-
elif offset == (
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return (self.eoi_token, )
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-
elif offset == (
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return (self.eos_token, )
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-
elif offset > (
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return (self.pad_token, )
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else:
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return self.visual_tokens
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position = torch.nonzero(input_ids == self.img_token, as_tuple=True)[0][0]
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self.offset_cache[batch_id] = position
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height = self.height[batch_id] if self.height.shape[0] > 1 else self.height[0]
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width = self.width[batch_id] if self.width.shape[0] > 1 else self.width[0]
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offset = input_ids.shape[0] - self.offset_cache[batch_id]
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height = height.to(offset.device)
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width = width.to(offset.device)
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+
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if offset % (width + 1) == 0:
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return (self.eol_token, )
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elif offset == (width + 1) * height + 1:
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return (self.eof_token, )
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elif offset == (width + 1) * height + 2:
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return (self.eoi_token, )
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elif offset == (width + 1) * height + 3:
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return (self.eos_token, )
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elif offset > (width + 1) * height + 3:
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return (self.pad_token, )
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else:
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return self.visual_tokens
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