[cleanup] Hoist ModelTester objects to top level (#4939)

Co-authored-by: Sam Shleifer <sshleifer@gmail.com>

tests/test_modeling_longformer.py

@@ -36,56 +36,33 @@ if is_torch_available():
     )
 
 
-class LongformerModelTester(object):
+class LongformerModelTester:
     def __init__(
-        self,
-        parent,
-        batch_size=13,
-        seq_length=7,
-        is_training=True,
-        use_input_mask=True,
-        use_token_type_ids=True,
-        use_labels=True,
-        vocab_size=99,
-        hidden_size=32,
-        num_hidden_layers=5,
-        num_attention_heads=4,
-        intermediate_size=37,
-        hidden_act="gelu",
-        hidden_dropout_prob=0.1,
-        attention_probs_dropout_prob=0.1,
-        max_position_embeddings=512,
-        type_vocab_size=16,
-        type_sequence_label_size=2,
-        initializer_range=0.02,
-        num_labels=3,
-        num_choices=4,
-        scope=None,
-        attention_window=4,
+        self, parent,
     ):
         self.parent = parent
-        self.batch_size = batch_size
-        self.seq_length = seq_length
-        self.is_training = is_training
-        self.use_input_mask = use_input_mask
-        self.use_token_type_ids = use_token_type_ids
-        self.use_labels = use_labels
-        self.vocab_size = vocab_size
-        self.hidden_size = hidden_size
-        self.num_hidden_layers = num_hidden_layers
-        self.num_attention_heads = num_attention_heads
-        self.intermediate_size = intermediate_size
-        self.hidden_act = hidden_act
-        self.hidden_dropout_prob = hidden_dropout_prob
-        self.attention_probs_dropout_prob = attention_probs_dropout_prob
-        self.max_position_embeddings = max_position_embeddings
-        self.type_vocab_size = type_vocab_size
-        self.type_sequence_label_size = type_sequence_label_size
-        self.initializer_range = initializer_range
-        self.num_labels = num_labels
-        self.num_choices = num_choices
-        self.scope = scope
-        self.attention_window = attention_window
+        self.batch_size = 13
+        self.seq_length = 7
+        self.is_training = True
+        self.use_input_mask = True
+        self.use_token_type_ids = True
+        self.use_labels = True
+        self.vocab_size = 99
+        self.hidden_size = 32
+        self.num_hidden_layers = 5
+        self.num_attention_heads = 4
+        self.intermediate_size = 37
+        self.hidden_act = "gelu"
+        self.hidden_dropout_prob = 0.1
+        self.attention_probs_dropout_prob = 0.1
+        self.max_position_embeddings = 512
+        self.type_vocab_size = 16
+        self.type_sequence_label_size = 2
+        self.initializer_range = 0.02
+        self.num_labels = 3
+        self.num_choices = 4
+        self.scope = None
+        self.attention_window = 4
 
         # `ModelTesterMixin.test_attention_outputs` is expecting attention tensors to be of size
         # [num_attention_heads, encoder_seq_length, encoder_key_length], but LongformerSelfAttention