Clean up Emformer module (#2091)

Summary:
* Removes redundant declaration `right_context_blocks = []`, as flagged by kobenaxie.
* Adds random seed to tests, as flagged by carolineechen in other PRs.

Pull Request resolved: https://github.com/pytorch/audio/pull/2091

Reviewed By: mthrok

Differential Revision: D33340964

Pulled By: hwangjeff

fbshipit-source-id: a9de43e28d1bae7bd4806b280717b0d822bb42fc

test/torchaudio_unittest/prototype/emformer_test_impl.py

@@ -24,6 +24,10 @@ class EmformerTestImpl(TestBaseMixin):
         )
         return input, lengths
 
+    def setUp(self):
+        super().setUp()
+        torch.random.manual_seed(29)
+
     def test_torchscript_consistency_forward(self):
         r"""Verify that scripting Emformer does not change the behavior of method `forward`."""
         input_dim = 128

torchaudio/prototype/models/emformer.py

@@ -669,8 +669,7 @@ class Emformer(torch.nn.Module):
         self.max_memory_size = max_memory_size
 
     def _gen_right_context(self, input: torch.Tensor) -> torch.Tensor:
-        right_context_blocks = []
-        T, B, D = input.shape
+        T = input.shape[0]
         num_segs = math.ceil((T - self.right_context_length) / self.segment_length)
         right_context_blocks = []
         for seg_idx in range(num_segs - 1):
@@ -765,7 +764,7 @@ class Emformer(torch.nn.Module):
         return attention_mask
 
     def forward(self, input: torch.Tensor, lengths: torch.Tensor) -> Tuple[torch.Tensor, torch.Tensor]:
-        r"""Forward pass for training.
+        r"""Forward pass for training and non-streaming inference.
 
         B: batch size;
         T: number of frames;
@@ -806,7 +805,7 @@ class Emformer(torch.nn.Module):
         lengths: torch.Tensor,
         states: Optional[List[List[torch.Tensor]]] = None,
     ) -> Tuple[torch.Tensor, torch.Tensor, List[List[torch.Tensor]]]:
-        r"""Forward pass for inference.
+        r"""Forward pass for streaming inference.
 
         B: batch size;
         T: number of frames;