hezhihui commited on
Commit
c8d5c00
1 Parent(s): 85ffc0b

adapt for coming batch input

Browse files
config.json CHANGED
@@ -1,5 +1,6 @@
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  {
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  "_name_or_path": "openbmb/MiniCPM-V-2",
 
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  "architectures": [
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  "MiniCPMV"
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  ],
 
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  {
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  "_name_or_path": "openbmb/MiniCPM-V-2",
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+ "version": 2.0,
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  "architectures": [
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  "MiniCPMV"
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  ],
image_processing_minicpmv.py CHANGED
@@ -401,7 +401,7 @@ class MiniCPMVImageProcessor(BaseImageProcessor):
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  tgt_sizes = np.vstack(tgt_sizes)
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  return MiniCPMVBatchFeature(
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- data={"pixel_values": new_images, "image_sizes": image_sizes, "tgt_sizes": tgt_sizes}, tensor_type=return_tensors
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  )
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  AutoImageProcessor.register("MiniCPMVImageProcessor", MiniCPMVImageProcessor)
 
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  tgt_sizes = np.vstack(tgt_sizes)
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  return MiniCPMVBatchFeature(
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+ data={"pixel_values": [new_images], "image_sizes": [image_sizes], "tgt_sizes": [tgt_sizes]}, tensor_type=return_tensors
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  )
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  AutoImageProcessor.register("MiniCPMVImageProcessor", MiniCPMVImageProcessor)
processing_minicpmv.py CHANGED
@@ -125,18 +125,18 @@ class MiniCPMVProcessor(ProcessorMixin):
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  images, image_sizes = images["pixel_values"], images["image_sizes"]
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  image_tags = re.findall(pattern, texts)
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- assert len(image_tags) == len(image_sizes)
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  text_chunks = texts.split(pattern)
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  final_texts = ""
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  for i in range(len(image_tags)):
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- final_texts = final_texts + text_chunks[i] + self.image_processor.get_slice_image_placeholder(image_sizes[i])
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  final_texts += text_chunks[-1]
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  input_ids, image_bounds = self._convert(final_texts, max_length)
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  return MiniCPMVBatchFeature(data={
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  "input_ids": input_ids,
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- "pixel_values": [images],
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- "image_sizes": [image_sizes],
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  "image_bounds": [image_bounds]
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  }, tensor_type=return_tensors)
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  images, image_sizes = images["pixel_values"], images["image_sizes"]
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  image_tags = re.findall(pattern, texts)
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+ assert len(image_tags) == len(image_sizes[0])
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  text_chunks = texts.split(pattern)
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  final_texts = ""
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  for i in range(len(image_tags)):
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+ final_texts = final_texts + text_chunks[i] + self.image_processor.get_slice_image_placeholder(image_sizes[0][i])
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  final_texts += text_chunks[-1]
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  input_ids, image_bounds = self._convert(final_texts, max_length)
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  return MiniCPMVBatchFeature(data={
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  "input_ids": input_ids,
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+ "pixel_values": images,
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+ "image_sizes": image_sizes,
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  "image_bounds": [image_bounds]
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  }, tensor_type=return_tensors)
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