remove defaults to None if optional (#11703)

examples/research_projects/wav2vec2/run_asr.py

@@ -144,7 +144,7 @@ class Orthography:
     Args:
         do_lower_case (:obj:`bool`, `optional`, defaults to :obj:`False`):
             Whether or not to accept lowercase input and lowercase the output when decoding.
-        vocab_file (:obj:`str`, `optional`, defaults to :obj:`None`):
+        vocab_file (:obj:`str`, `optional`):
             File containing the vocabulary.
         word_delimiter_token (:obj:`str`, `optional`, defaults to :obj:`"|"`):
             The token used for delimiting words; it needs to be in the vocabulary.
@@ -152,7 +152,7 @@ class Orthography:
             Table to use with `str.translate()` when preprocessing text (e.g., "-" -> " ").
         words_to_remove (:obj:`Set[str]`, `optional`, defaults to :obj:`set()`):
             Words to remove when preprocessing text (e.g., "sil").
-        untransliterator (:obj:`Callable[[str], str]`, `optional`, defaults to :obj:`None`):
+        untransliterator (:obj:`Callable[[str], str]`, `optional`):
             Function that untransliterates text back into native writing system.
     """
 

src/transformers/debug_utils.py

@@ -118,7 +118,7 @@ class DebugUnderflowOverflow:
             How many frames back to record
         trace_batch_nums(:obj:`List[int]`, `optional`, defaults to ``[]``):
             Which batch numbers to trace (turns detection off)
-        abort_after_batch_num  (:obj:`int`, `optional`, defaults to :obj:`None`):
+        abort_after_batch_num  (:obj:`int`, `optional`):
             Whether to abort after a certain batch number has finished
 
     """

src/transformers/modeling_tf_utils.py

@@ -1128,7 +1128,7 @@ class TFPreTrainedModel(tf.keras.Model, TFModelUtilsMixin, TFGenerationMixin, Pu
                 The specific model version to use. It can be a branch name, a tag name, or a commit id, since we use a
                 git-based system for storing models and other artifacts on huggingface.co, so ``revision`` can be any
                 identifier allowed by git.
-            mirror(:obj:`str`, `optional`, defaults to :obj:`None`):
+            mirror(:obj:`str`, `optional`):
                 Mirror source to accelerate downloads in China. If you are from China and have an accessibility
                 problem, you can set this option to resolve it. Note that we do not guarantee the timeliness or safety.
                 Please refer to the mirror site for more information.

src/transformers/modeling_utils.py

@@ -975,7 +975,7 @@ class PreTrainedModel(nn.Module, ModuleUtilsMixin, GenerationMixin, PushToHubMix
                 The specific model version to use. It can be a branch name, a tag name, or a commit id, since we use a
                 git-based system for storing models and other artifacts on huggingface.co, so ``revision`` can be any
                 identifier allowed by git.
-            mirror(:obj:`str`, `optional`, defaults to :obj:`None`):
+            mirror(:obj:`str`, `optional`):
                 Mirror source to accelerate downloads in China. If you are from China and have an accessibility
                 problem, you can set this option to resolve it. Note that we do not guarantee the timeliness or safety.
                 Please refer to the mirror site for more information.

src/transformers/models/albert/tokenization_albert_fast.py

@@ -172,7 +172,7 @@ class AlbertTokenizerFast(PreTrainedTokenizerFast):
         Args:
             token_ids_0 (:obj:`List[int]`):
                 List of IDs to which the special tokens will be added
-            token_ids_1 (:obj:`List[int]`, `optional`, defaults to :obj:`None`):
+            token_ids_1 (:obj:`List[int]`, `optional`):
                 Optional second list of IDs for sequence pairs.
 
         Returns:
@@ -201,7 +201,7 @@ class AlbertTokenizerFast(PreTrainedTokenizerFast):
         Args:
             token_ids_0 (:obj:`List[int]`):
                 List of ids.
-            token_ids_1 (:obj:`List[int]`, `optional`, defaults to :obj:`None`):
+            token_ids_1 (:obj:`List[int]`, `optional`):
                 Optional second list of IDs for sequence pairs.
 
         Returns:

src/transformers/models/big_bird/tokenization_big_bird_fast.py

@@ -152,7 +152,7 @@ class BigBirdTokenizerFast(PreTrainedTokenizerFast):
         Args:
             token_ids_0 (:obj:`List[int]`):
                 List of IDs to which the special tokens will be added
-            token_ids_1 (:obj:`List[int]`, `optional`, defaults to :obj:`None`):
+            token_ids_1 (:obj:`List[int]`, `optional`):
                 Optional second list of IDs for sequence pairs.
 
         Returns:
@@ -174,7 +174,7 @@ class BigBirdTokenizerFast(PreTrainedTokenizerFast):
         Args:
             token_ids_0 (:obj:`List[int]`):
                 List of ids.
-            token_ids_1 (:obj:`List[int]`, `optional`, defaults to :obj:`None`):
+            token_ids_1 (:obj:`List[int]`, `optional`):
                 Optional second list of IDs for sequence pairs.
             already_has_special_tokens (:obj:`bool`, `optional`, defaults to :obj:`False`):
                 Set to True if the token list is already formatted with special tokens for the model
@@ -212,7 +212,7 @@ class BigBirdTokenizerFast(PreTrainedTokenizerFast):
         Args:
             token_ids_0 (:obj:`List[int]`):
                 List of ids.
-            token_ids_1 (:obj:`List[int]`, `optional`, defaults to :obj:`None`):
+            token_ids_1 (:obj:`List[int]`, `optional`):
                 Optional second list of IDs for sequence pairs.
 
         Returns:

src/transformers/models/ibert/quant_modules.py

@@ -124,7 +124,7 @@ class QuantAct(nn.Module):
             Momentum for updating the activation quantization range.
         per_channel (:obj:`bool`, `optional`, defaults to :obj:`False`):
             Whether to or not use channel-wise quantization.
-        channel_len (:obj:`int`, `optional`, defaults to :obj:`None`):
+        channel_len (:obj:`int`, `optional`):
             Specify the channel length when set the `per_channel` True.
         quant_mode (:obj:`bool`, `optional`, defaults to :obj:`False`):
             Whether or not the layer is quantized.
@@ -755,9 +755,9 @@ class FixedPointMul(Function):
             Quantization bitwidth.
         z_scaling_factor (:obj:`torch.Tensor`):
             Scaling factor of the output tensor.
-        identity (:obj:`torch.Tensor`, `optional`, defaults to :obj:`None`):
+        identity (:obj:`torch.Tensor`, `optional`):
             Identity tensor, if exists.
-        identity_scaling_factor (:obj:`torch.Tensor`, `optional`, defaults to :obj:`None`):
+        identity_scaling_factor (:obj:`torch.Tensor`, `optional`):
             Scaling factor of the identity tensor `identity`, if exists.
 
     Returns:

src/transformers/models/mpnet/modeling_mpnet.py

@@ -444,7 +444,7 @@ MPNET_INPUTS_DOCSTRING = r"""
             details.
 
             `What are input IDs? <../glossary.html#input-ids>`__
-        attention_mask (:obj:`torch.FloatTensor` of shape :obj:`(batch_size, sequence_length)`, `optional`, defaults to :obj:`None`):
+        attention_mask (:obj:`torch.FloatTensor` of shape :obj:`(batch_size, sequence_length)`, `optional`):
             Mask to avoid performing attention on padding token indices. Mask values selected in ``[0, 1]``:
 
             - 1 for tokens that are **not masked**,

src/transformers/models/mpnet/tokenization_mpnet.py

@@ -235,7 +235,7 @@ class MPNetTokenizer(PreTrainedTokenizer):
         Args:
             token_ids_0 (:obj:`List[int]`):
                 List of IDs to which the special tokens will be added
-            token_ids_1 (:obj:`List[int]`, `optional`, defaults to :obj:`None`):
+            token_ids_1 (:obj:`List[int]`, `optional`):
                 Optional second list of IDs for sequence pairs.
 
         Returns:

src/transformers/models/xlm_prophetnet/tokenization_xlm_prophetnet.py

@@ -290,7 +290,7 @@ class XLMProphetNetTokenizer(PreTrainedTokenizer):
         Args:
             token_ids_0 (:obj:`List[int]`):
                 List of IDs to which the special tokens will be added
-            token_ids_1 (:obj:`List[int]`, `optional`, defaults to :obj:`None`):
+            token_ids_1 (:obj:`List[int]`, `optional`):
                 Optional second list of IDs for sequence pairs.
 
         Returns:

src/transformers/pipelines/text2text_generation.py

@@ -295,10 +295,10 @@ class TranslationPipeline(Text2TextGenerationPipeline):
                 Whether or not to include the decoded texts in the outputs.
             clean_up_tokenization_spaces (:obj:`bool`, `optional`, defaults to :obj:`False`):
                 Whether or not to clean up the potential extra spaces in the text output.
-            src_lang (:obj:`str`, `optional`, defaults to :obj:`None`):
+            src_lang (:obj:`str`, `optional`):
                 The language of the input. Might be required for multilingual models. Will not have any effect for
                 single pair translation models
-            tgt_lang (:obj:`str`, `optional`, defaults to :obj:`None`):
+            tgt_lang (:obj:`str`, `optional`):
                 The language of the desired output. Might be required for multilingual models. Will not have any effect
                 for single pair translation models
             generate_kwargs: