From 7307f1c6bc0cb7535f23c6453acc90f14144efb6 Mon Sep 17 00:00:00 2001 From: yaozengwei Date: Mon, 30 May 2022 22:37:47 +0800 Subject: [PATCH] fix typos --- .../ASR/conv_emformer_transducer_stateless/emformer.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/egs/librispeech/ASR/conv_emformer_transducer_stateless/emformer.py b/egs/librispeech/ASR/conv_emformer_transducer_stateless/emformer.py index 3bae13d7e..65c1b8ced 100644 --- a/egs/librispeech/ASR/conv_emformer_transducer_stateless/emformer.py +++ b/egs/librispeech/ASR/conv_emformer_transducer_stateless/emformer.py @@ -818,7 +818,7 @@ class EmformerEncoderLayer(nn.Module): ) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor]: """Unpack cached states including: 1) output memory from previous chunks in the lower layer; - 2) attention key and value of left context from proceeding chunk's + 2) attention key and value of left context from preceding chunk's computation. """ past_length = state[3][0][0].item() @@ -934,7 +934,7 @@ class EmformerEncoderLayer(nn.Module): """Apply attention module in inference mode. 1) Unpack cached states including: - memory from previous chunks in the lower layer; - - attention key and value of left context from proceeding + - attention key and value of left context from preceding chunk's compuation; 2) Apply attention computation; 3) Pack updated states including: @@ -1468,7 +1468,7 @@ class EmformerEncoder(nn.Module): utterance frames for i-th batch element in x, which contains the right_context at the end. states (List[List[torch.Tensor]], optional): - Cached states from proceeding chunk's computation, where each + Cached states from preceding chunk's computation, where each element (List[torch.Tensor]) corresponds to each emformer layer. (default: None) conv_caches (List[torch.Tensor], optional): @@ -1650,7 +1650,7 @@ class Emformer(EncoderInterface): utterance frames for i-th batch element in x, containing the right_context at the end. states (List[List[torch.Tensor]], optional): - Cached states from proceeding chunk's computation, where each + Cached states from preceding chunk's computation, where each element (List[torch.Tensor]) corresponds to each emformer layer. (default: None) conv_caches (List[torch.Tensor], optional):