29 lines
1.1 KiB
Python
29 lines
1.1 KiB
Python
from typing import Optional, Union
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import torch
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from transformers.models.bert.modeling_bert import BertModel
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from ...modeling_outputs import BaseModelOutputWithPoolingAndCrossAttentions
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class DummyBertModel(BertModel):
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def forward(
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self,
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input_ids: Optional[torch.Tensor] = None,
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attention_mask: Optional[torch.Tensor] = None,
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token_type_ids: Optional[torch.Tensor] = None,
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position_ids: Optional[torch.Tensor] = None,
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head_mask: Optional[torch.Tensor] = None,
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inputs_embeds: Optional[torch.Tensor] = None,
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encoder_hidden_states: Optional[torch.Tensor] = None,
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encoder_attention_mask: Optional[torch.Tensor] = None,
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past_key_values: Optional[list[torch.FloatTensor]] = None,
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use_cache: Optional[bool] = None,
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output_attentions: Optional[bool] = None,
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output_hidden_states: Optional[bool] = None,
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return_dict: Optional[bool] = None,
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cache_position: Optional[torch.Tensor] = None,
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) -> Union[tuple[torch.Tensor], BaseModelOutputWithPoolingAndCrossAttentions]:
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return super().forward(input_ids)
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