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github.com/apple/ml-streambridge
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Functions
393 in github.com/apple/ml-streambridge
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Functions
393
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Types & classes
89
Method
__init__
(self, config: SigLipVisionConfig)
streambridge/model/multimodal_encoder/siglip_encoder.py:150
Method
__init__
(self, config)
streambridge/model/multimodal_encoder/siglip_encoder.py:182
Method
__init__
(self, config: SigLipVisionConfig)
streambridge/model/multimodal_encoder/siglip_encoder.py:261
Method
__init__
(self, config: SigLipVisionConfig)
streambridge/model/multimodal_encoder/siglip_encoder.py:334
Method
__init__
(self, config: SigLipVisionConfig)
streambridge/model/multimodal_encoder/siglip_encoder.py:410
Method
__init__
(self, config: SigLipVisionConfig)
streambridge/model/multimodal_encoder/siglip_encoder.py:463
Method
__init__
(self, config: SigLipVisionConfig)
streambridge/model/multimodal_encoder/siglip_encoder.py:489
Method
__init__
(self, vision_tower, vision_tower_cfg, delay_load=False)
streambridge/model/multimodal_encoder/siglip_encoder.py:540
Method
__init__
( self, dtype=torch.bfloat16, img_size=384, pooling_factor=4, ckpt = N
eval/streaming_models/online_oryx.py:44
Method
__init__
( self, dtype=torch.bfloat16, img_size=384, pooling_factor=4, ckpt = N
eval/streaming_models/online_llava_ov.py:47
Method
__init__
( self, dtype=torch.bfloat16, img_size=384, pooling_factor=2, ckpt = N
eval/streaming_models/online_qwen2_vl.py:46
Function
_convert_to_rgb
(image)
streambridge/utils.py:163
Function
_convert_to_rgb
(image)
eval/utils.py:15
Method
_init_weights
Initialize the weights
streambridge/model/multimodal_resampler/qformer.py:675
Method
_init_weights
(self, module)
streambridge/model/multimodal_encoder/qwen2_vit.py:1010
Method
_init_weights
Initialize the weights
streambridge/model/multimodal_encoder/siglip_encoder.py:319
Method
_prune_heads
Prunes heads of the model. heads_to_prune: dict of {layer_num: list of heads to prune in this layer} See base class PreTrainedModel
streambridge/model/multimodal_resampler/qformer.py:716
Method
_reorder_cache
(self, past, beam_idx)
streambridge/model/multimodal_resampler/qformer.py:1131
Method
append_message
(self, role, message)
streambridge/conversation.py:187
Function
build_logger
(logger_name, logger_filename)
streambridge/utils.py:41
Method
config
(self)
streambridge/model/multimodal_resampler/masked_drop.py:51
Method
config
(self)
streambridge/model/multimodal_resampler/qformer.py:1286
Method
config
(self)
streambridge/model/multimodal_resampler/builder.py:21
Method
config
(self)
streambridge/model/multimodal_resampler/vlm_attention.py:334
Method
config
(self)
streambridge/model/multimodal_resampler/spatial_pool.py:40
Method
config
(self)
streambridge/model/multimodal_resampler/perceiver.py:88
Method
config
(self)
streambridge/model/multimodal_projector/builder.py:19
Method
config
(self)
streambridge/model/multimodal_encoder/oryx_vit.py:831
Method
create_custom_forward
(module)
streambridge/model/multimodal_resampler/qformer.py:544
Method
custom_forward
(*inputs)
streambridge/model/multimodal_resampler/qformer.py:545
Method
device
(self)
streambridge/model/multimodal_encoder/oryx_vit.py:823
Method
device
(self)
streambridge/model/multimodal_encoder/siglip_encoder.py:606
Method
dict
(self)
streambridge/conversation.py:278
Function
disable_torch_init
Disable the redundant torch default initialization to accelerate model creation.
streambridge/utils.py:117
Function
disabled_train
Overwrite model.train with this function to make sure train/eval mode does not change anymore.
streambridge/model/multimodal_resampler/qformer.py:56
Function
dist_barrier
()
streambridge/utils.py:36
Method
dtype
(self)
streambridge/model/multimodal_encoder/oryx_vit.py:819
Method
dtype
(self)
streambridge/model/multimodal_encoder/siglip_encoder.py:601
Method
dummy_feature
(self)
streambridge/model/multimodal_encoder/oryx_vit.py:815
Method
dummy_feature
(self)
streambridge/model/multimodal_encoder/siglip_encoder.py:597
Function
evaluate
(rank, stream_data_split)
eval/eval_benchmarks/parallel_videomme.py:19
Function
evaluate
(rank, stream_data_split)
eval/eval_benchmarks/parallel_ovo_bench.py:18
Method
expand2square
(pil_img, background_color=(122, 116, 104))
streambridge/conversation.py:193
Method
extra_repr
(self)
streambridge/model/multimodal_encoder/qwen2_vit.py:498
Method
feed_forward_chunk
(self, attention_output)
streambridge/model/multimodal_resampler/qformer.py:487
Method
feed_forward_chunk_query
(self, attention_output)
streambridge/model/multimodal_resampler/qformer.py:492
Method
flush
(self)
streambridge/utils.py:111
Method
forward
(self, image_features)
streambridge/model/activate_videollm.py:36
Method
forward
(self, samples)
streambridge/model/activate_videollm.py:194
Method
forward
(self, image_features, *args, **kwargs)
streambridge/model/multimodal_resampler/masked_drop.py:21
Method
forward
( self, input_ids=None, position_ids=None, query_embeds=None, past_key
streambridge/model/multimodal_resampler/qformer.py:89
Method
forward
( self, hidden_states, attention_mask=None, head_mask=None, encoder_hi
streambridge/model/multimodal_resampler/qformer.py:180
Method
forward
(self, hidden_states, input_tensor)
streambridge/model/multimodal_resampler/qformer.py:296
Method
forward
( self, hidden_states, attention_mask=None, head_mask=None, encoder_hi
streambridge/model/multimodal_resampler/qformer.py:333
Method
forward
(self, hidden_states)
streambridge/model/multimodal_resampler/qformer.py:369
Method
forward
(self, hidden_states, input_tensor)
streambridge/model/multimodal_resampler/qformer.py:382
Method
forward
( self, hidden_states, attention_mask=None, head_mask=None, encoder_hi
streambridge/model/multimodal_resampler/qformer.py:413
Method
forward
( self, hidden_states, attention_mask=None, head_mask=None, encoder_hi
streambridge/model/multimodal_resampler/qformer.py:506
Method
forward
(self, hidden_states)
streambridge/model/multimodal_resampler/qformer.py:609
Method
forward
(self, hidden_states)
streambridge/model/multimodal_resampler/qformer.py:628
Method
forward
(self, hidden_states)
streambridge/model/multimodal_resampler/qformer.py:649
Method
forward
(self, sequence_output)
streambridge/model/multimodal_resampler/qformer.py:660
Method
forward
r""" encoder_hidden_states (:obj:`torch.FloatTensor` of shape :obj:`(batch_size, sequence_length, hidden_size)`, `optional`): Seq
streambridge/model/multimodal_resampler/qformer.py:815
Method
forward
r""" encoder_hidden_states (:obj:`torch.FloatTensor` of shape :obj:`(batch_size, sequence_length, hidden_size)`, `optional`): Seq
streambridge/model/multimodal_resampler/qformer.py:998
Method
forward
r""" labels (:obj:`torch.LongTensor` of shape :obj:`(batch_size, sequence_length)`, `optional`): Labels for computing the masked l
streambridge/model/multimodal_resampler/qformer.py:1161
Method
forward
(self, image_features, *args, **kwargs)
streambridge/model/multimodal_resampler/qformer.py:1267
Method
forward
(self, x, *args, **kwargs)
streambridge/model/multimodal_resampler/builder.py:17
Method
forward
(self, image_features, prompts=None, image_counts=None, long_video=False)
streambridge/model/multimodal_resampler/vlm_attention.py:136
Method
forward
(self, image_features, images, *args, **kwargs)
streambridge/model/multimodal_resampler/spatial_pool.py:28
Method
forward
(self, image_features, forward_type, image_size=None, pooling_factor=None)
streambridge/model/multimodal_resampler/perceiver.py:35
Method
forward
( self, input_ids: torch.LongTensor = None, attention_mask: Optional[torch.Tensor] = N
streambridge/model/language_model/qwen2vl_qwen.py:46
Method
forward
( self, input_ids: torch.LongTensor = None, attention_mask: Optional[torch.Tensor] = N
streambridge/model/language_model/llava_qwen.py:68
Method
forward
( self, input_ids: torch.LongTensor = None, attention_mask: Optional[torch.Tensor] = N
streambridge/model/language_model/oryx_qwen.py:47
Method
forward
(self, x, *args, **kwargs)
streambridge/model/multimodal_projector/builder.py:15
Method
forward
(self, x)
streambridge/model/multimodal_projector/builder.py:33
Method
forward
(self, x, size=(16,16), x2=None, size2=(16, 16), modalities='image')
streambridge/model/multimodal_projector/builder.py:87
Method
forward
(self, x: torch.Tensor, cu_slens=None)
streambridge/model/multimodal_encoder/oryx_vit.py:146
Method
forward
(self, x: torch.Tensor)
streambridge/model/multimodal_encoder/oryx_vit.py:200
Method
forward
(self, x: torch.Tensor, cu_slens=None)
streambridge/model/multimodal_encoder/oryx_vit.py:248
Method
forward
(self, x, cal_attn_pool=False)
streambridge/model/multimodal_encoder/oryx_vit.py:621
Method
forward
(self, images, cal_attn_pool=False)
streambridge/model/multimodal_encoder/oryx_vit.py:809
Method
forward
(self, x, position_ids)
streambridge/model/multimodal_encoder/qwen2_vit.py:176
Method
forward
(self, seqlen: int)
streambridge/model/multimodal_encoder/qwen2_vit.py:280
Method
forward
(self, hidden_states: torch.Tensor)
streambridge/model/multimodal_encoder/qwen2_vit.py:303
Method
forward
(self, x: torch.Tensor)
streambridge/model/multimodal_encoder/qwen2_vit.py:328
Method
forward
(self, x)
streambridge/model/multimodal_encoder/qwen2_vit.py:343
Method
forward
( self, hidden_states: torch.Tensor, cu_seqlens: torch.Tensor, rotary_pos_emb: torch.Tensor = None
streambridge/model/multimodal_encoder/qwen2_vit.py:355
Method
forward
( self, hidden_states: torch.Tensor, cu_seqlens: torch.Tensor, rotary_pos_emb: torch.Tensor = None
streambridge/model/multimodal_encoder/qwen2_vit.py:389
Method
forward
( self, hidden_states: torch.Tensor, cu_seqlens: torch.Tensor, rotary_pos_emb: torch.Tensor = None
streambridge/model/multimodal_encoder/qwen2_vit.py:412
Method
forward
(self, hidden_states, cu_seqlens, rotary_pos_emb)
streambridge/model/multimodal_encoder/qwen2_vit.py:473
Method
forward
(self, hidden_states)
streambridge/model/multimodal_encoder/qwen2_vit.py:491
Method
forward
( self, hidden_states: torch.Tensor, attention_mask: Optional[torch.Tensor] = None,
streambridge/model/multimodal_encoder/qwen2_vit.py:574
Method
forward
( self, hidden_states: torch.Tensor, attention_mask: Optional[torch.Tensor] = None,
streambridge/model/multimodal_encoder/qwen2_vit.py:671
Method
forward
( self, hidden_states: torch.Tensor, attention_mask: Optional[torch.Tensor] = None,
streambridge/model/multimodal_encoder/qwen2_vit.py:793
Method
forward
Args: hidden_states (`torch.FloatTensor`): input to the layer of shape `(batch, seq_len, embed_dim)` attention_mask (
streambridge/model/multimodal_encoder/qwen2_vit.py:910
Method
forward
(self, hidden_states: torch.Tensor, grid_thw: torch.Tensor)
streambridge/model/multimodal_encoder/qwen2_vit.py:1088
Method
forward
(self, pixel_values: torch.FloatTensor)
streambridge/model/multimodal_encoder/siglip_encoder.py:170
Method
forward
Input shape: Batch x Time x Channel
streambridge/model/multimodal_encoder/siglip_encoder.py:198
Method
forward
(self, hidden_states: torch.Tensor)
streambridge/model/multimodal_encoder/siglip_encoder.py:252
Method
forward
Args: hidden_states (`torch.FloatTensor`): Input to the layer of shape `(batch, seq_len, embed_dim)`.
streambridge/model/multimodal_encoder/siglip_encoder.py:270
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