Purge unused ModelTester code (#37085)

* Purge correctly this time

* Remove more methods from recent PRs

* make fixup

tests/models/data2vec/test_modeling_data2vec_audio.py

@@ -184,32 +184,6 @@ class Data2VecAudioModelTester:
             (self.batch_size, self.adapter_output_seq_length, config.output_hidden_size),
         )
 
-    def create_and_check_batch_inference(self, config, input_values, *args):
-        # test does not pass for models making use of `group_norm`
-        # check: https://github.com/pytorch/fairseq/issues/3227
-        model = Data2VecAudioModel(config=config)
-        model.to(torch_device)
-        model.eval()
-
-        input_values = input_values[:3]
-        attention_mask = torch.ones(input_values.shape, device=torch_device, dtype=torch.bool)
-
-        input_lengths = [input_values.shape[-1] // i for i in [4, 2, 1]]
-
-        # pad input
-        for i in range(len(input_lengths)):
-            input_values[i, input_lengths[i] :] = 0.0
-            attention_mask[i, input_lengths[i] :] = 0.0
-
-        batch_outputs = model(input_values, attention_mask=attention_mask).last_hidden_state
-
-        for i in range(input_values.shape[0]):
-            input_slice = input_values[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_values, *args):
         model = Data2VecAudioForCTC(config=config)
         model.to(torch_device)