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chore: import upstream snapshot with attribution
2026-07-13 11:57:37 +08:00

36 lines
1.1 KiB
Python

import torch
from transformers.modeling_outputs import CausalLMOutputWithPast
from transformers.models.llama.modeling_llama import LlamaModel
from ...cache_utils import Cache
# example where we need some deps and some functions
class SuperModel(LlamaModel):
def forward(
self,
input_ids: torch.LongTensor = None,
attention_mask: torch.Tensor | None = None,
position_ids: torch.LongTensor | None = None,
past_key_values: Cache | None = None,
inputs_embeds: torch.FloatTensor | None = None,
use_cache: bool | None = None,
output_attentions: bool | None = None,
output_hidden_states: bool | None = None,
return_dict: bool | None = None,
) -> tuple | CausalLMOutputWithPast:
out = super().forward(
input_ids,
attention_mask,
position_ids,
past_key_values,
inputs_embeds,
use_cache,
output_attentions,
output_hidden_states,
return_dict,
)
out.logits *= 2**4
return out