LinWeizheDragon
commited on
Commit
•
114f133
1
Parent(s):
e082b5c
Update modeling_flmr.py
Browse files- modeling_flmr.py +16 -14
modeling_flmr.py
CHANGED
@@ -584,13 +584,14 @@ class FLMRModelForRetrieval(FLMRPretrainedModelForRetrieval):
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self.text_encoder_embedding_size = self.config.text_config.hidden_size
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self.late_interaction_embedding_size = self.config.dim
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self.
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(
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)
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if self.config.use_vision_encoder:
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self.context_vision_encoder = FLMRVisionModel(config.vision_config)
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@@ -636,13 +637,14 @@ class FLMRModelForRetrieval(FLMRPretrainedModelForRetrieval):
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self.query_text_encoder_linear = self.context_text_encoder_linear
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self._tied_weights_keys += ["context_text_encoder", "context_text_encoder_linear"]
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if self.config.
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self.
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if self.config.load_cpu_extension:
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try:
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@@ -1304,7 +1306,7 @@ class FLMRModelForRetrieval(FLMRPretrainedModelForRetrieval):
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# TODO: fix the engine to support masks with discontinuous 0 and 1.
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D = torch.cat([vision_embeddings, text_embeddings], dim=1)
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# concatenate the mask
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mask = torch.cat([
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elif concat_output_from_vision_encoder:
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D = vision_embeddings
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mask = image_mask
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self.text_encoder_embedding_size = self.config.text_config.hidden_size
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self.late_interaction_embedding_size = self.config.dim
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if self.config.use_vision_encoder:
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self.context_vision_projection = FLMRMultiLayerPerceptron(
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(
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self.vision_encoder_embedding_size,
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(self.late_interaction_embedding_size * self.mapping_network_prefix_length) // 2,
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self.late_interaction_embedding_size * self.mapping_network_prefix_length,
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)
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)
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if self.config.use_vision_encoder:
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self.context_vision_encoder = FLMRVisionModel(config.vision_config)
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self.query_text_encoder_linear = self.context_text_encoder_linear
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self._tied_weights_keys += ["context_text_encoder", "context_text_encoder_linear"]
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if self.config.use_vision_encoder:
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if self.config.separate_query_and_context_vision_encoder:
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self.query_vision_encoder = copy.deepcopy(self.context_vision_encoder)
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self.query_vision_projection = copy.deepcopy(self.context_vision_projection)
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else:
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self.query_vision_encoder = self.context_vision_encoder
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self.query_vision_projection = self.context_vision_projection
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self._tied_weights_keys += ["context_vision_encoder", "context_vision_projection"]
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if self.config.load_cpu_extension:
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try:
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# TODO: fix the engine to support masks with discontinuous 0 and 1.
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D = torch.cat([vision_embeddings, text_embeddings], dim=1)
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# concatenate the mask
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mask = torch.cat([image_mask, mask], dim=1)
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elif concat_output_from_vision_encoder:
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D = vision_embeddings
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mask = image_mask
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