From d97e9d171c878efd6fcab4d87afac8f35a21ed74 Mon Sep 17 00:00:00 2001
From: Lysandre <lysandre.debut@reseau.eseo.fr>
Date: Tue, 27 Oct 2020 08:10:06 -0400
Subject: [PATCH] Fix DeBERTa docs

---
 src/transformers/modeling_deberta.py | 22 +++++++++++++---------
 1 file changed, 13 insertions(+), 9 deletions(-)

diff --git a/src/transformers/modeling_deberta.py b/src/transformers/modeling_deberta.py
index 060e762f9f0c59..a5558f31ea9f28 100644
--- a/src/transformers/modeling_deberta.py
+++ b/src/transformers/modeling_deberta.py
@@ -797,13 +797,18 @@ def _init_weights(self, module):
 
             `What are input IDs? <../glossary.html#input-ids>`__
         attention_mask (:obj:`torch.FloatTensor` of shape :obj:`{0}`, `optional`):
-            Mask to avoid performing attention on padding token indices. Mask values selected in ``[0, 1]``: ``1`` for
-            tokens that are NOT MASKED, ``0`` for MASKED tokens.
+            Mask to avoid performing attention on padding token indices. Mask values selected in ``[0, 1]``:
+
+            - 1 for tokens that are **not masked**,
+            - 0 for tokens that are **masked**.
 
             `What are attention masks? <../glossary.html#attention-mask>`__
         token_type_ids (:obj:`torch.LongTensor` of shape :obj:`{0}`, `optional`):
             Segment token indices to indicate first and second portions of the inputs. Indices are selected in ``[0,
-            1]``: ``0`` corresponds to a `sentence A` token, ``1`` corresponds to a `sentence B` token
+            1]``:
+
+            - 0 corresponds to a `sentence A` token,
+            - 1 corresponds to a `sentence B` token.
 
             `What are token type IDs? <../glossary.html#token-type-ids>`_
         position_ids (:obj:`torch.LongTensor` of shape :obj:`{0}`, `optional`):
@@ -816,14 +821,13 @@ def _init_weights(self, module):
             This is useful if you want more control over how to convert `input_ids` indices into associated vectors
             than the model's internal embedding lookup matrix.
         output_attentions (:obj:`bool`, `optional`):
-            If set to ``True``, the attentions tensors of all attention layers are returned. See ``attentions`` under
-            returned tensors for more detail.
-        output_hidden_states (:obj:`bool`, `optional`):
-            If set to ``True``, the hidden states of all layers are returned. See ``hidden_states`` under returned
+            Whether or not to return the attentions tensors of all attention layers. See ``attentions`` under returned
             tensors for more detail.
+        output_hidden_states (:obj:`bool`, `optional`):
+            Whether or not to return the hidden states of all layers. See ``hidden_states`` under returned tensors for
+            more detail.
         return_dict (:obj:`bool`, `optional`):
-            If set to ``True``, the model will return a :class:`~transformers.file_utils.ModelOutput` instead of a
-            plain tuple.
+            Whether or not to return a :class:`~transformers.file_utils.ModelOutput` instead of a plain tuple.
 """