↓ 5 callersFunctiongeneric_param_init_fn_(module: nn.Module, init_fn_, n_layers: int, d_model: Optional[int]=None, init_div_is_residual: Union[int, flo
llava/model/mpt/param_init_fns.py:28
↓ 2 callersFunction_normal_param_init_fn_(module: nn.Module, std: float, n_layers: int, d_model: Optional[int]=None, init_div_is_residual: Union[int, f
llava/model/mpt/param_init_fns.py:124
↓ 2 callersFunctionbuild_prompt_chatbot(problems, shot_qids, prompt_format, use_caption=False, options=["A", "B", "C", "D", "E"], is_test=False)
scripts/convert_sqa_to_llava_base_prompt.py:221
↓ 2 callersFunctioncreate_one_example(format, question, context, choice, answer, lecture, solution, test_example=True)
scripts/convert_sqa_to_llava_base_prompt.py:106
↓ 2 callersFunctioncreate_one_example_gpt4(format, question, context, choice, answer, lecture, solution, test_example=True)
scripts/convert_sqa_to_llava_base_prompt.py:162
↓ 1 callersMethod__init__(self, d_model: int, n_heads: int, attn_impl: str='triton', clip_qkv: Optional[float]=None, qk_ln: bool=False,
llava/model/mpt/attention.py:122
↓ 1 callersFunctionattn_bias_shape(attn_impl, n_heads, seq_len, alibi, prefix_lm, causal, use_sequence_id)
llava/model/mpt/attention.py:234
↓ 1 callersFunctionbuild_alibi_bias(n_heads, seq_len, full=False, alibi_bias_max=8, device=None, dtype=None)
llava/model/mpt/attention.py:268
↓ 1 callersFunctionbuild_attn_bias(attn_impl, attn_bias, n_heads, seq_len, causal=False, alibi=False, alibi_bias_max=8)
llava/model/mpt/attention.py:248
↓ 1 callersFunctioncreate_one_example_chatbot(format, question, context, choice, answer, lecture, solution, test_example=True)
scripts/convert_sqa_to_llava_base_prompt.py:41