From b2667588031cf20528ba21fe1ea8d7c71b1254e2 Mon Sep 17 00:00:00 2001
From: dohe0342 <kimdohe1070@gmail.com>
Date: Mon, 9 Jan 2023 20:29:10 +0900
Subject: [PATCH] from local

---
 .../incremental_transf/.identity_train.py.swp | Bin 73728 -> 77824 bytes
 .../ASR/incremental_transf/identity_train.py  |  17 +++++++++++++++++
 2 files changed, 17 insertions(+)

diff --git a/egs/librispeech/ASR/incremental_transf/.identity_train.py.swp b/egs/librispeech/ASR/incremental_transf/.identity_train.py.swp
index 675b070b1a32b0608f3f108fa8535d66b9ad48ef..45201a4049b4847b0a4a917a71c0805bac358108 100644
GIT binary patch
delta 375
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z8yf0^TV%ssnj*rXAt-7NnzJJ473sjkIh@0R*K&pRCL&Xb(ZQiuUrz!o1Mq!UrfcVs
zkFaJ+ud%CT<et%Hw$!hz&PIc)%EmzWA|@vElm~FU-19l3Oe?OXo11`ZA8<kiN>c}E
zR29GhWvPpP_*$hqx}r;RRDNCe$QwJUDt1j1BeU~4>1<}ja(!?QTjl+6w;J9$E3Zw?
z08f6P7-%H;4|p2}R%x7i3G^HSTq@BRwbQ%Ks8pgID$ok$DMfMm4FZp(Xq#-x(P9u$
iEO1Ctls*~aflkS$VnAu))i1x6LbCs8U(Id2c>e%V*G`ZC

delta 162
zcmZp8z|wGlMKsAE%+puFQqO<^2m}}y?)}`Id~T!YTYg4?$;<-1jG2=s3W#q$Az;Bj
z@q)r81(pO}W}w2uj1bkCn*|$`86COV7#Q}kGB7L!;u;`!17am0W&`4DEDQ__fH(<=
s4S<*dh_3<7xB$d^fp`xP@7`S6$jh|dMwjsj)AT$YM&8ZAZEI%&0DAEyE&u=k

diff --git a/egs/librispeech/ASR/incremental_transf/identity_train.py b/egs/librispeech/ASR/incremental_transf/identity_train.py
index 68a2e4a24..beb6c930e 100755
--- a/egs/librispeech/ASR/incremental_transf/identity_train.py
+++ b/egs/librispeech/ASR/incremental_transf/identity_train.py
@@ -444,6 +444,23 @@ def get_params() -> AttributeDict:
     return params
 
 
+def get_tempencoder_model(params: AttributeDict) -> nn.Module:
+    # TODO: We can add an option to switch between Conformer and Transformer
+    encoder = Tempformer(
+        num_features=params.feature_dim,
+        subsampling_factor=params.subsampling_factor,
+        d_model=params.encoder_dim,
+        nhead=params.nhead,
+        dim_feedforward=params.dim_feedforward,
+        num_encoder_layers=params.num_encoder_layers,
+        dynamic_chunk_training=params.dynamic_chunk_training,
+        short_chunk_size=params.short_chunk_size,
+        num_left_chunks=params.num_left_chunks,
+        causal=params.causal_convolution,
+    )
+    return encoder
+
+
 def get_encoder_model(params: AttributeDict) -> nn.Module:
     # TODO: We can add an option to switch between Conformer and Transformer
     encoder = Conformer(