Doc fixes and filter warning in wandb (#8189)

src/transformers/integrations.py

@@ -29,7 +29,8 @@ try:
     wandb.ensure_configured()
     if wandb.api.api_key is None:
         _has_wandb = False
-        wandb.termwarn("W&B installed but not logged in.  Run `wandb login` or set the WANDB_API_KEY env variable.")
+        if os.getenv("WANDB_DISABLED"):
+            logger.warning("W&B installed but not logged in. Run `wandb login` or set the WANDB_API_KEY env variable.")
     else:
         _has_wandb = False if os.getenv("WANDB_DISABLED") else True
 except (ImportError, AttributeError):

src/transformers/modeling_albert.py

@@ -478,7 +478,7 @@ class AlbertPreTrainedModel(PreTrainedModel):
 @dataclass
 class AlbertForPreTrainingOutput(ModelOutput):
     """
-    Output type of :class:`~transformers.AlbertForPreTrainingModel`.
+    Output type of :class:`~transformers.AlbertForPreTraining`.
 
     Args:
         loss (`optional`, returned when ``labels`` is provided, ``torch.FloatTensor`` of shape :obj:`(1,)`):

src/transformers/modeling_bert.py

@@ -606,7 +606,7 @@ class BertPreTrainedModel(PreTrainedModel):
 @dataclass
 class BertForPreTrainingOutput(ModelOutput):
     """
-    Output type of :class:`~transformers.BertForPreTrainingModel`.
+    Output type of :class:`~transformers.BertForPreTraining`.
 
     Args:
         loss (`optional`, returned when ``labels`` is provided, ``torch.FloatTensor`` of shape :obj:`(1,)`):

src/transformers/modeling_electra.py

@@ -555,7 +555,7 @@ class ElectraPreTrainedModel(PreTrainedModel):
 @dataclass
 class ElectraForPreTrainingOutput(ModelOutput):
     """
-    Output type of :class:`~transformers.ElectraForPreTrainingModel`.
+    Output type of :class:`~transformers.ElectraForPreTraining`.
 
     Args:
         loss (`optional`, returned when ``labels`` is provided, ``torch.FloatTensor`` of shape :obj:`(1,)`):

src/transformers/modeling_funnel.py

@@ -798,7 +798,7 @@ class FunnelClassificationHead(nn.Module):
 @dataclass
 class FunnelForPreTrainingOutput(ModelOutput):
     """
-    Output type of :class:`~transformers.FunnelForPreTrainingModel`.
+    Output type of :class:`~transformers.FunnelForPreTraining`.
 
     Args:
         loss (`optional`, returned when ``labels`` is provided, ``torch.FloatTensor`` of shape :obj:`(1,)`):

src/transformers/modeling_lxmert.py

@@ -144,7 +144,7 @@ class LxmertForQuestionAnsweringOutput(ModelOutput):
 @dataclass
 class LxmertForPreTrainingOutput(ModelOutput):
     """
-    Output type of :class:`~transformers.LxmertForPreTrainingModel`.
+    Output type of :class:`~transformers.LxmertForPreTraining`.
 
     Args:
         loss (`optional`, returned when ``labels`` is provided, ``torch.FloatTensor`` of shape :obj:`(1,)`):

src/transformers/modeling_mobilebert.py

@@ -695,7 +695,7 @@ class MobileBertPreTrainedModel(PreTrainedModel):
 @dataclass
 class MobileBertForPreTrainingOutput(ModelOutput):
     """
-    Output type of :class:`~transformers.MobileBertForPreTrainingModel`.
+    Output type of :class:`~transformers.MobileBertForPreTraining`.
 
     Args:
         loss (`optional`, returned when ``labels`` is provided, ``torch.FloatTensor`` of shape :obj:`(1,)`):

src/transformers/modeling_tf_albert.py

@@ -628,7 +628,7 @@ class TFAlbertMainLayer(tf.keras.layers.Layer):
 @dataclass
 class TFAlbertForPreTrainingOutput(ModelOutput):
     """
-    Output type of :class:`~transformers.TFAlbertForPreTrainingModel`.
+    Output type of :class:`~transformers.TFAlbertForPreTraining`.
 
     Args:
         prediction_logits (:obj:`tf.Tensor` of shape :obj:`(batch_size, sequence_length, config.vocab_size)`):

src/transformers/modeling_tf_bert.py

@@ -666,7 +666,7 @@ class TFBertPreTrainedModel(TFPreTrainedModel):
 @dataclass
 class TFBertForPreTrainingOutput(ModelOutput):
     """
-    Output type of :class:`~transformers.TFBertForPreTrainingModel`.
+    Output type of :class:`~transformers.TFBertForPreTraining`.
 
     Args:
         prediction_logits (:obj:`tf.Tensor` of shape :obj:`(batch_size, sequence_length, config.vocab_size)`):

src/transformers/modeling_tf_electra.py

@@ -598,7 +598,7 @@ class TFElectraMainLayer(tf.keras.layers.Layer):
 @dataclass
 class TFElectraForPreTrainingOutput(ModelOutput):
     """
-    Output type of :class:`~transformers.TFElectraForPreTrainingModel`.
+    Output type of :class:`~transformers.TFElectraForPreTraining`.
 
     Args:
         loss (`optional`, returned when ``labels`` is provided, ``tf.Tensor`` of shape :obj:`(1,)`):

src/transformers/modeling_tf_funnel.py

@@ -1031,7 +1031,7 @@ class TFFunnelPreTrainedModel(TFPreTrainedModel):
 @dataclass
 class TFFunnelForPreTrainingOutput(ModelOutput):
     """
-    Output type of :class:`~transformers.FunnelForPreTrainingModel`.
+    Output type of :class:`~transformers.FunnelForPreTraining`.
 
     Args:
         logits (:obj:`tf.Tensor` of shape :obj:`(batch_size, sequence_length)`):

src/transformers/modeling_tf_lxmert.py

@@ -96,7 +96,7 @@ class TFLxmertModelOutput(ModelOutput):
 @dataclass
 class TFLxmertForPreTrainingOutput(ModelOutput):
     """
-    Output type of :class:`~transformers.LxmertForPreTrainingModel`.
+    Output type of :class:`~transformers.LxmertForPreTraining`.
 
     Args:
         loss (`optional`, returned when ``labels`` is provided, ``tf.Tensor`` of shape :obj:`(1,)`):

src/transformers/modeling_tf_mobilebert.py

@@ -833,7 +833,7 @@ class TFMobileBertPreTrainedModel(TFPreTrainedModel):
 @dataclass
 class TFMobileBertForPreTrainingOutput(ModelOutput):
     """
-    Output type of :class:`~transformers.TFMobileBertForPreTrainingModel`.
+    Output type of :class:`~transformers.TFMobileBertForPreTraining`.
 
     Args:
         prediction_logits (:obj:`tf.Tensor` of shape :obj:`(batch_size, sequence_length, config.vocab_size)`):