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Unverified Commit 4a353cac authored by mowafess's avatar mowafess Committed by GitHub
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added type hints to yoso (#16163)

parent c1c17bd0
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Showing with 44 additions and 43 deletions
src/transformers/models/yoso/modeling_yoso.py
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...@@ -17,6 +17,7 @@ ...@@ -17,6 +17,7 @@
import math import math
import os import os
from typing import Optional, Tuple, Union
import torch import torch
import torch.utils.checkpoint import torch.utils.checkpoint
...@@ -779,16 +780,16 @@ class YosoModel(YosoPreTrainedModel): ...@@ -779,16 +780,16 @@ class YosoModel(YosoPreTrainedModel):
) )
def forward( def forward(
self, self,
input_ids=None, input_ids: Optional[torch.Tensor] = None,
attention_mask=None, attention_mask: Optional[torch.Tensor] = None,
token_type_ids=None, token_type_ids: Optional[torch.Tensor] = None,
position_ids=None, position_ids: Optional[torch.Tensor] = None,
head_mask=None, head_mask: Optional[torch.Tensor] = None,
inputs_embeds=None, inputs_embeds: Optional[torch.Tensor] = None,
output_attentions=None, output_attentions: Optional[bool] = None,
output_hidden_states=None, output_hidden_states: Optional[bool] = None,
return_dict=None, return_dict: Optional[bool] = None,
): ) -> Union[Tuple, BaseModelOutputWithCrossAttentions]:
output_attentions = output_attentions if output_attentions is not None else self.config.output_attentions output_attentions = output_attentions if output_attentions is not None else self.config.output_attentions
output_hidden_states = ( output_hidden_states = (
output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states
...@@ -882,17 +883,17 @@ class YosoForMaskedLM(YosoPreTrainedModel): ...@@ -882,17 +883,17 @@ class YosoForMaskedLM(YosoPreTrainedModel):
) )
def forward( def forward(
self, self,
input_ids=None, input_ids: Optional[torch.Tensor] = None,
attention_mask=None, attention_mask: Optional[torch.Tensor] = None,
token_type_ids=None, token_type_ids: Optional[torch.Tensor] = None,
position_ids=None, position_ids: Optional[torch.Tensor] = None,
head_mask=None, head_mask: Optional[torch.Tensor] = None,
inputs_embeds=None, inputs_embeds: Optional[torch.Tensor] = None,
labels=None, labels: Optional[torch.Tensor] = None,
output_attentions=None, output_attentions: Optional[bool] = None,
output_hidden_states=None, output_hidden_states: Optional[bool] = None,
return_dict=None, return_dict: Optional[bool] = None,
): ) -> Union[Tuple, MaskedLMOutput]:
r""" r"""
labels (`torch.LongTensor` of shape `(batch_size, sequence_length)`, *optional*): labels (`torch.LongTensor` of shape `(batch_size, sequence_length)`, *optional*):
Labels for computing the masked language modeling loss. Indices should be in `[-100, 0, ..., Labels for computing the masked language modeling loss. Indices should be in `[-100, 0, ...,
...@@ -978,17 +979,17 @@ class YosoForSequenceClassification(YosoPreTrainedModel): ...@@ -978,17 +979,17 @@ class YosoForSequenceClassification(YosoPreTrainedModel):
) )
def forward( def forward(
self, self,
input_ids=None, input_ids: Optional[torch.Tensor] = None,
attention_mask=None, attention_mask: Optional[torch.Tensor] = None,
token_type_ids=None, token_type_ids: Optional[torch.Tensor] = None,
position_ids=None, position_ids: Optional[torch.Tensor] = None,
head_mask=None, head_mask: Optional[torch.Tensor] = None,
inputs_embeds=None, inputs_embeds: Optional[torch.Tensor] = None,
labels=None, labels: Optional[torch.Tensor] = None,
output_attentions=None, output_attentions: Optional[bool] = None,
output_hidden_states=None, output_hidden_states: Optional[bool] = None,
return_dict=None, return_dict: Optional[bool] = None,
): ) -> Union[Tuple, SequenceClassifierOutput]:
r""" r"""
labels (`torch.LongTensor` of shape `(batch_size,)`, *optional*): labels (`torch.LongTensor` of shape `(batch_size,)`, *optional*):
Labels for computing the sequence classification/regression loss. Indices should be in `[0, ..., Labels for computing the sequence classification/regression loss. Indices should be in `[0, ...,
...@@ -1071,17 +1072,17 @@ class YosoForMultipleChoice(YosoPreTrainedModel): ...@@ -1071,17 +1072,17 @@ class YosoForMultipleChoice(YosoPreTrainedModel):
) )
def forward( def forward(
self, self,
input_ids=None, input_ids: Optional[torch.Tensor] = None,
attention_mask=None, attention_mask: Optional[torch.Tensor] = None,
token_type_ids=None, token_type_ids: Optional[torch.Tensor] = None,
position_ids=None, position_ids: Optional[torch.Tensor] = None,
head_mask=None, head_mask: Optional[torch.Tensor] = None,
inputs_embeds=None, inputs_embeds: Optional[torch.Tensor] = None,
labels=None, labels: Optional[torch.Tensor] = None,
output_attentions=None, output_attentions: Optional[bool] = None,
output_hidden_states=None, output_hidden_states: Optional[bool] = None,
return_dict=None, return_dict: Optional[bool] = None,
): ) -> Union[Tuple, MultipleChoiceModelOutput]:
r""" r"""
labels (`torch.LongTensor` of shape `(batch_size,)`, *optional*): labels (`torch.LongTensor` of shape `(batch_size,)`, *optional*):
Labels for computing the multiple choice classification loss. Indices should be in `[0, ..., Labels for computing the multiple choice classification loss. Indices should be in `[0, ...,
......
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