From 9c7d1256f81600c236fd65309ff04304e502f08e Mon Sep 17 00:00:00 2001
From: dohe0342 <kimdohe1070@gmail.com>
Date: Wed, 4 Jan 2023 00:11:22 +0900
Subject: [PATCH] from local

---
 .../.conformer.py.swp                         | Bin 90112 -> 90112 bytes
 .../pruned_transducer_stateless5/conformer.py |   6 ------
 2 files changed, 6 deletions(-)

diff --git a/egs/librispeech/ASR/pruned_transducer_stateless5/.conformer.py.swp b/egs/librispeech/ASR/pruned_transducer_stateless5/.conformer.py.swp
index 048f58734d1e1e1a6b051c37930b392cb71d43cc..6b909d661ce8346756c76f10c4ea73ee17fc61d2 100644
GIT binary patch
delta 763
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delta 875
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diff --git a/egs/librispeech/ASR/pruned_transducer_stateless5/conformer.py b/egs/librispeech/ASR/pruned_transducer_stateless5/conformer.py
index 8dd61b213..9b4b2a1ef 100644
--- a/egs/librispeech/ASR/pruned_transducer_stateless5/conformer.py
+++ b/egs/librispeech/ASR/pruned_transducer_stateless5/conformer.py
@@ -197,8 +197,6 @@ class Conformer(EncoderInterface):
 
         x = x.permute(1, 0, 2)  # (T, N, C) ->(N, T, C)
 
-        layer_output = [x.permute(1, 0, 2) for x in layer_output]
-
         return x, lengths
 
     @torch.jit.export
@@ -695,8 +693,6 @@ class ConformerEncoder(nn.Module):
 
         outputs = []
         
-        layer_output = []
-
         for i, mod in enumerate(self.layers):
             output = mod(
                 output,
@@ -708,8 +704,6 @@ class ConformerEncoder(nn.Module):
             if i in self.aux_layers:
                 outputs.append(output)
 
-            layer_output.append(output)
-
         output = self.combiner(outputs)
 
         return output, layer_output