Purge unused ModelTester code (#37085)

* Purge correctly this time

* Remove more methods from recent PRs

* make fixup

tests/models/wav2vec2_bert/test_modeling_wav2vec2_bert.py

@@ -246,32 +246,6 @@ class Wav2Vec2BertModelTester:
             result.last_hidden_state.shape, (self.batch_size, self.output_seq_length, self.hidden_size)
         )
 
-    def create_and_check_batch_inference(self, config, input_features, *args):
-        # test does not pass for models making use of `group_norm`
-        # check: https://github.com/pytorch/fairseq/issues/3227
-        model = Wav2Vec2BertModel(config=config)
-        model.to(torch_device)
-        model.eval()
-
-        input_features = input_features[:3]
-        attention_mask = torch.ones(input_features.shape, device=torch_device, dtype=torch.bool)
-
-        input_lengths = [input_features.shape[-1] // i for i in [4, 2, 1]]
-
-        # pad input
-        for i in range(len(input_lengths)):
-            input_features[i, input_lengths[i] :] = 0.0
-            attention_mask[i, input_lengths[i] :] = 0.0
-
-        batch_outputs = model(input_features, attention_mask=attention_mask).last_hidden_state
-
-        for i in range(input_features.shape[0]):
-            input_slice = input_features[i : i + 1, : input_lengths[i]]
-            output = model(input_slice).last_hidden_state
-
-            batch_output = batch_outputs[i : i + 1, : output.shape[1]]
-            self.parent.assertTrue(torch.allclose(output, batch_output, atol=1e-3))
-
     def check_ctc_loss(self, config, input_features, *args):
         model = Wav2Vec2BertForCTC(config=config)
         model.to(torch_device)