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Merged
Rocketknight1 merged 5 commits into from
May 4, 2022
Merged

Type hint complete Albert model file. #16682

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99d9c62
Type hint complete Albert model file.
karthikrangasai Apr 9, 2022
686bfd8
Merge branch 'main' into refactor/type_hint_albert_model
karthikrangasai Apr 20, 2022
8ca65ac
Update typing.
karthikrangasai Apr 20, 2022
55996c2
Update src/transformers/models/albert/modeling_albert.py
Rocketknight1 May 4, 2022
aecb666
Merge branch 'main' into refactor/type_hint_albert_model
karthikrangasai May 4, 2022
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357 changes: 234 additions & 123 deletions src/transformers/models/albert/modeling_albert.py
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11 changes: 8 additions & 3 deletions src/transformers/models/bert/modeling_bert.py
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Original file line number Diff line number Diff line change
Expand Up @@ -187,8 +187,13 @@ def __init__(self, config):
)

def forward(
self, input_ids=None, token_type_ids=None, position_ids=None, inputs_embeds=None, past_key_values_length=0
):
self,
input_ids: Optional[torch.LongTensor] = None,
token_type_ids: Optional[torch.LongTensor] = None,
position_ids: Optional[torch.LongTensor] = None,
inputs_embeds: Optional[torch.FloatTensor] = None,
past_key_values_length: int = 0,
) -> torch.Tensor:
if input_ids is not None:
input_shape = input_ids.size()
else:
Expand Down Expand Up @@ -250,7 +255,7 @@ def __init__(self, config, position_embedding_type=None):

self.is_decoder = config.is_decoder

def transpose_for_scores(self, x):
def transpose_for_scores(self, x: torch.Tensor) -> torch.Tensor:
new_x_shape = x.size()[:-1] + (self.num_attention_heads, self.attention_head_size)
x = x.view(new_x_shape)
return x.permute(0, 2, 1, 3)
Expand Down
2 changes: 1 addition & 1 deletion src/transformers/models/data2vec/modeling_data2vec_text.py
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Original file line number Diff line number Diff line change
Expand Up @@ -186,7 +186,7 @@ def __init__(self, config, position_embedding_type=None):

self.is_decoder = config.is_decoder

def transpose_for_scores(self, x):
def transpose_for_scores(self, x: torch.Tensor) -> torch.Tensor:
new_x_shape = x.size()[:-1] + (self.num_attention_heads, self.attention_head_size)
x = x.view(new_x_shape)
return x.permute(0, 2, 1, 3)
Expand Down
11 changes: 8 additions & 3 deletions src/transformers/models/electra/modeling_electra.py
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Original file line number Diff line number Diff line change
Expand Up @@ -179,8 +179,13 @@ def __init__(self, config):

# Copied from transformers.models.bert.modeling_bert.BertEmbeddings.forward
def forward(
self, input_ids=None, token_type_ids=None, position_ids=None, inputs_embeds=None, past_key_values_length=0
):
self,
input_ids: Optional[torch.LongTensor] = None,
token_type_ids: Optional[torch.LongTensor] = None,
position_ids: Optional[torch.LongTensor] = None,
inputs_embeds: Optional[torch.FloatTensor] = None,
past_key_values_length: int = 0,
) -> torch.Tensor:
if input_ids is not None:
input_shape = input_ids.size()
else:
Expand Down Expand Up @@ -243,7 +248,7 @@ def __init__(self, config, position_embedding_type=None):

self.is_decoder = config.is_decoder

def transpose_for_scores(self, x):
def transpose_for_scores(self, x: torch.Tensor) -> torch.Tensor:
new_x_shape = x.size()[:-1] + (self.num_attention_heads, self.attention_head_size)
x = x.view(new_x_shape)
return x.permute(0, 2, 1, 3)
Expand Down
2 changes: 1 addition & 1 deletion src/transformers/models/layoutlm/modeling_layoutlm.py
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Original file line number Diff line number Diff line change
Expand Up @@ -158,7 +158,7 @@ def __init__(self, config, position_embedding_type=None):

self.is_decoder = config.is_decoder

def transpose_for_scores(self, x):
def transpose_for_scores(self, x: torch.Tensor) -> torch.Tensor:
new_x_shape = x.size()[:-1] + (self.num_attention_heads, self.attention_head_size)
x = x.view(new_x_shape)
return x.permute(0, 2, 1, 3)
Expand Down
2 changes: 1 addition & 1 deletion src/transformers/models/megatron_bert/modeling_megatron_bert.py
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Original file line number Diff line number Diff line change
Expand Up @@ -221,7 +221,7 @@ def __init__(self, config, position_embedding_type=None):

self.is_decoder = config.is_decoder

def transpose_for_scores(self, x):
def transpose_for_scores(self, x: torch.Tensor) -> torch.Tensor:
new_x_shape = x.size()[:-1] + (self.num_attention_heads, self.attention_head_size)
x = x.view(new_x_shape)
return x.permute(0, 2, 1, 3)
Expand Down
10 changes: 8 additions & 2 deletions src/transformers/models/qdqbert/modeling_qdqbert.py
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Original file line number Diff line number Diff line change
Expand Up @@ -19,6 +19,7 @@
import math
import os
import warnings
from typing import Optional

import torch
import torch.utils.checkpoint
Expand Down Expand Up @@ -172,8 +173,13 @@ def __init__(self, config):
)

def forward(
self, input_ids=None, token_type_ids=None, position_ids=None, inputs_embeds=None, past_key_values_length=0
):
self,
input_ids: Optional[torch.LongTensor] = None,
token_type_ids: Optional[torch.LongTensor] = None,
position_ids: Optional[torch.LongTensor] = None,
inputs_embeds: Optional[torch.FloatTensor] = None,
past_key_values_length: int = 0,
) -> torch.Tensor:
if input_ids is not None:
input_shape = input_ids.size()
else:
Expand Down
11 changes: 8 additions & 3 deletions src/transformers/models/realm/modeling_realm.py
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Original file line number Diff line number Diff line change
Expand Up @@ -193,8 +193,13 @@ def __init__(self, config):
)

def forward(
self, input_ids=None, token_type_ids=None, position_ids=None, inputs_embeds=None, past_key_values_length=0
):
self,
input_ids: Optional[torch.LongTensor] = None,
token_type_ids: Optional[torch.LongTensor] = None,
position_ids: Optional[torch.LongTensor] = None,
inputs_embeds: Optional[torch.FloatTensor] = None,
past_key_values_length: int = 0,
) -> torch.Tensor:
if input_ids is not None:
input_shape = input_ids.size()
else:
Expand Down Expand Up @@ -257,7 +262,7 @@ def __init__(self, config, position_embedding_type=None):

self.is_decoder = config.is_decoder

def transpose_for_scores(self, x):
def transpose_for_scores(self, x: torch.Tensor) -> torch.Tensor:
new_x_shape = x.size()[:-1] + (self.num_attention_heads, self.attention_head_size)
x = x.view(new_x_shape)
return x.permute(0, 2, 1, 3)
Expand Down
2 changes: 1 addition & 1 deletion src/transformers/models/roberta/modeling_roberta.py
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Original file line number Diff line number Diff line change
Expand Up @@ -186,7 +186,7 @@ def __init__(self, config, position_embedding_type=None):

self.is_decoder = config.is_decoder

def transpose_for_scores(self, x):
def transpose_for_scores(self, x: torch.Tensor) -> torch.Tensor:
new_x_shape = x.size()[:-1] + (self.num_attention_heads, self.attention_head_size)
x = x.view(new_x_shape)
return x.permute(0, 2, 1, 3)
Expand Down
2 changes: 1 addition & 1 deletion src/transformers/models/splinter/modeling_splinter.py
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Original file line number Diff line number Diff line change
Expand Up @@ -130,7 +130,7 @@ def __init__(self, config, position_embedding_type=None):

self.is_decoder = config.is_decoder

def transpose_for_scores(self, x):
def transpose_for_scores(self, x: torch.Tensor) -> torch.Tensor:
new_x_shape = x.size()[:-1] + (self.num_attention_heads, self.attention_head_size)
x = x.view(new_x_shape)
return x.permute(0, 2, 1, 3)
Expand Down
2 changes: 1 addition & 1 deletion src/transformers/models/xlm_roberta_xl/modeling_xlm_roberta_xl.py
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Original file line number Diff line number Diff line change
Expand Up @@ -180,7 +180,7 @@ def __init__(self, config, position_embedding_type=None):

self.is_decoder = config.is_decoder

def transpose_for_scores(self, x):
def transpose_for_scores(self, x: torch.Tensor) -> torch.Tensor:
new_x_shape = x.size()[:-1] + (self.num_attention_heads, self.attention_head_size)
x = x.view(new_x_shape)
return x.permute(0, 2, 1, 3)
Expand Down