↓ 2 callersMethodprepare_inputs_labels_for_multimodal(
self, input_ids, position_ids, attention_mask, past_key_values, labels, images
)
videollava/model/llava_arch.py:148
↓ 1 callersMethod__call__(self, images=None, text=None, context_length=77, return_tensors=None, **kwargs)
videollava/model/multimodal_encoder/languagebind/image/processing_image.py:46
↓ 1 callersMethod__call__(self, images=None, text=None, context_length=77, return_tensors=None, **kwargs)
videollava/model/multimodal_encoder/languagebind/video/processing_video.py:127
↓ 1 callersMethod__init__(self, d_model: int, n_heads: int, attn_impl: str='triton', clip_qkv: Optional[float]=None, qk_ln: bool=False,
videollava/model/language_model/mpt/attention.py:158
↓ 1 callersFunctionattn_bias_shape(attn_impl, n_heads, seq_len, alibi, prefix_lm, causal, use_sequence_id)
videollava/model/language_model/mpt/attention.py:258
↓ 1 callersFunctionbuild_alibi_bias(n_heads, seq_len, full=False, alibi_bias_max=8, device=None, dtype=None)
videollava/model/language_model/mpt/attention.py:292
↓ 1 callersFunctionbuild_attn_bias(attn_impl, attn_bias, n_heads, seq_len, causal=False, alibi=False, alibi_bias_max=8)
videollava/model/language_model/mpt/attention.py:272
↓ 1 callersFunctioncreate_data_loader(questions, image_folder, tokenizer, image_processor, model_config, batch_size=1, num_workers=4)
videollava/eval/model_vqa_loader.py:65
↓ 1 callersFunctioncreate_one_example_chatbot(format, question, context, choice, answer, lecture, solution, test_example=True)
scripts/convert_sqa_to_llava_base_prompt.py:41