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[Bugfix] Fix phi3v batch inference when images have different aspect ratio (#7392)

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This commit is contained in:
Isotr0py
2024-08-11 00:19:33 +08:00
committed by GitHub
parent baa240252e
commit 4c5d8e8ea9
4 changed files with 24 additions and 18 deletions
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24
vllm/model_executor/models/phi3v.py
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@@ -189,7 +189,7 @@ class Phi3HDImageEmbedding(Phi3ImageEmbeddingBase):
global_image_features_hd_newline = self.add_image_newline(
global_image_features_hd)
all_image_embeddings = []
batch_image_features_proj = []
# need a for loop to process each image because of different image sizes
# (patch arrangement is different for each image)
for i, img_size in enumerate(image_sizes):
@@ -207,19 +207,17 @@ class Phi3HDImageEmbedding(Phi3ImageEmbeddingBase):
sub_image_features_hd)
# [sub features, separator, global features]
all_image_embeddings.append(
torch.cat([
sub_image_features_hd_newline.squeeze(
0), # (h_crop*12*(w_crop*12+1), 4096)
self.glb_GN.squeeze(0),
global_image_features_hd_newline[i],
]))
image_embeddings = torch.cat([
sub_image_features_hd_newline.squeeze(
0), # (h_crop*12*(w_crop*12+1), 4096)
self.glb_GN.squeeze(0),
global_image_features_hd_newline[i],
])
img_proj = self.img_projection(
image_embeddings.to(target_device, target_dtype))
batch_image_features_proj.append(img_proj)
image_features_proj = self.img_projection(
torch.stack(all_image_embeddings).to(target_device, target_dtype)
) # (num_images, (h_crop*12*(w_crop*12+1)+1), hidden_size)
return image_features_proj
return batch_image_features_proj
def reshape_hd_patches_2x2merge(self, image_features, h_crop, w_crop):
"""