Fix make fix-copies with type annotations (#13586)

src/transformers/models/hubert/modeling_hubert.py

@@ -109,6 +109,10 @@ def _compute_mask_indices(
     # scatter indices to mask
     spec_aug_mask = spec_aug_mask.scatter(1, spec_aug_mask_idxs, True)
 
+    if attention_mask is not None:
+        # make sure padded input ids cannot be masked
+        spec_aug_mask = torch.where(attention_mask.bool(), spec_aug_mask, False)
+
     return spec_aug_mask
 
 

src/transformers/models/hubert/modeling_tf_hubert.py

@@ -258,7 +258,7 @@ def _compute_mask_indices(
         tf.ones_like(spec_aug_mask_idxs), spec_aug_mask_idxs, spec_aug_mask.shape
     )
 
-    return tf.cast(spec_aug_mask, tf.float32)
+    return spec_aug_mask
 
 
 # Copied from transformers.models.bart.modeling_tf_bart._expand_mask

src/transformers/models/roberta/modeling_tf_roberta.py

@@ -508,9 +508,9 @@ class TFRobertaMainLayer(tf.keras.layers.Layer):
         if inputs["input_ids"] is not None and inputs["inputs_embeds"] is not None:
             raise ValueError("You cannot specify both input_ids and inputs_embeds at the same time")
         elif inputs["input_ids"] is not None:
-            input_shape = shape_list(tensor=inputs["input_ids"])
+            input_shape = shape_list(inputs["input_ids"])
         elif inputs["inputs_embeds"] is not None:
-            input_shape = shape_list(tensor=inputs["inputs_embeds"])[:-1]
+            input_shape = shape_list(inputs["inputs_embeds"])[:-1]
         else:
             raise ValueError("You have to specify either input_ids or inputs_embeds")
 

utils/check_copies.py

@@ -52,7 +52,7 @@ LOCALIZED_READMES = {
 
 
 def _should_continue(line, indent):
-    return line.startswith(indent) or len(line) <= 1 or re.search(r"^\s*\):\s*$", line) is not None
+    return line.startswith(indent) or len(line) <= 1 or re.search(r"^\s*\)(\s*->.*:|:)\s*$", line) is not None
 
 
 def find_code_in_transformers(object_name):