From bbd50fda4c47c03d1fafc7381367fd04cc3b6dfa Mon Sep 17 00:00:00 2001
From: dohe0342 <kimdohe1070@gmail.com>
Date: Tue, 10 Jan 2023 01:04:23 +0900
Subject: [PATCH] from local

---
 .../ASR/incremental_transf/.train.py.swp      | Bin 61440 -> 61440 bytes
 .../ASR/incremental_transf/train.py           |  21 +++++++++++-------
 2 files changed, 13 insertions(+), 8 deletions(-)

diff --git a/egs/librispeech/ASR/incremental_transf/.train.py.swp b/egs/librispeech/ASR/incremental_transf/.train.py.swp
index ee9785d9212db8a1aaacbe3f089f1799a28848a3..a9966d01f35384d6700457b69c16297bc0849bd8 100644
GIT binary patch
delta 430
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delta 335
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diff --git a/egs/librispeech/ASR/incremental_transf/train.py b/egs/librispeech/ASR/incremental_transf/train.py
index dfcedf504..bf0cdcec1 100755
--- a/egs/librispeech/ASR/incremental_transf/train.py
+++ b/egs/librispeech/ASR/incremental_transf/train.py
@@ -966,14 +966,19 @@ def run(rank, world_size, args):
     logging.info("About to create model")
     model = get_transducer_model(params)
     
-    path = '/home/work/workspace/icefall/egs/librispeech/ASR/incremental_transf/conformer_24layers.pt'
-    pre_trained = torch.load(path)
-    pre_trained_model = pre_trained["model"]
-    #for n, p in model.named_parameters():
-    #    if 'layer' not in n:
-    for n, p in pre_trained_model.items():
-        print(n)
-    exit()
+    path1 = '/home/work/workspace/icefall/egs/librispeech/ASR/incremental_transf/conformer_12layers.pt'
+    pre_trained1 = torch.load(path1)
+    pre_trained_model1 = pre_trained1["model"]
+    
+    path2 = '/home/work/workspace/icefall/egs/librispeech/ASR/incremental_transf/conformer_24layers.pt'
+    pre_trained2 = torch.load(path2)
+    pre_trained_model2 = pre_trained2["model"]
+
+    for n, p in model.named_parameters():
+        if 'layer' not in n:
+
+            layer_name_splited = n.split('.')
+            
 
     num_param = sum([p.numel() for p in model.parameters()])
     logging.info(f"Number of model parameters: {num_param}")