Commit
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660fe4c
1
Parent(s):
725b8ba
chore: remove prints
Browse filesSigned-off-by: jupyterjazz <[email protected]>
modeling_jina_embeddings_v4.py
CHANGED
@@ -309,13 +309,7 @@ class JinaEmbeddingsV4Model(Qwen2_5_VLForConditionalGeneration):
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with torch.no_grad():
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batch = {k: v.to(self.device) for k, v in batch.items()}
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with torch.autocast(device_type=torch.device(self.device).type):
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for key, value in batch.items():
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if hasattr(value, 'shape'):
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print(f"{key}: {value.shape}")
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else:
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print(f"{key}: {type(value)}")
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embeddings = self(**batch)
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print(embeddings.single_vec_emb.shape, embeddings.multi_vec_emb.shape)
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if vector_type == "single_vector":
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embeddings = embeddings.single_vec_emb
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if truncate_dim is not None:
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@@ -446,8 +440,6 @@ class JinaEmbeddingsV4Model(Qwen2_5_VLForConditionalGeneration):
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encode_kwargs = self._validate_encoding_params(vector_type, truncate_dim)
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is_single = len(images) == 1
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print(is_single)
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print(len(images))
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embeddings = self._process_batches(
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data=images,
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processor_fn=self.processor.process_images,
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with torch.no_grad():
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batch = {k: v.to(self.device) for k, v in batch.items()}
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with torch.autocast(device_type=torch.device(self.device).type):
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embeddings = self(**batch)
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if vector_type == "single_vector":
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embeddings = embeddings.single_vec_emb
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if truncate_dim is not None:
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encode_kwargs = self._validate_encoding_params(vector_type, truncate_dim)
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is_single = len(images) == 1
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embeddings = self._process_batches(
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data=images,
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processor_fn=self.processor.process_images,
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