[lint] fix quick-checks

wenet-e2e · Sep 4, 2024 · 69e4449 · 69e4449
1 parent a57af63
commit 69e4449
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diff --git a/examples/librimix/tse/v1/README.md b/examples/librimix/tse/v1/README.md
@@ -208,9 +208,9 @@ data/
         |__ embed.ark, embed.scp, ... # files generated by Stage 1
         |__ shard.list
         |__ shards/
-        	|__ shards_000000000.tar
-        	|__ ...
-        	|__ shards_000000013.tar
+            |__ shards_000000000.tar
+            |__ ...
+            |__ shards_000000013.tar
 ```
 
 ------
@@ -402,11 +402,11 @@ ${exp_dir}/
 |__ train.log
 |__ config.yaml
 |__ models/
-	|__ checkpoint_1.pt
-	|__ ...
-	|__ checkpoint_150.pt
-	|__ final_checkpoint.pt -> checkpoint_150.pt
-	|__ latest_checkpoint.pt -> checkpoint_150.pt
+    |__ checkpoint_1.pt
+    |__ ...
+    |__ checkpoint_150.pt
+    |__ final_checkpoint.pt -> checkpoint_150.pt
+    |__ latest_checkpoint.pt -> checkpoint_150.pt
 ```
 
 ------
@@ -436,10 +436,10 @@ ${exp_dir}/
 |__ models/
 |__ infer.log
 |__ audio/
-	|__ spk1.scp # each line records two space-separated columns: `target_wav_id` and `target_wav_path`
-	|__ Utt1001-4992-41806-0008_6930-75918-0015-T4992.wav
-	|__ ...
-	|__ Utt999-61-70968-0003_2830-3980-0008-T61.wav
+    |__ spk1.scp # each line records two space-separated columns: `target_wav_id` and `target_wav_path`
+    |__ Utt1001-4992-41806-0008_6930-75918-0015-T4992.wav
+    |__ ...
+    |__ Utt999-61-70968-0003_2830-3980-0008-T61.wav
 ```
 
 ------
@@ -453,8 +453,8 @@ At the end of this stage, a markdown file `RESULTS.md` will be created under `ex
 ```
 exp/BSRNN/
 |__ ${exp_dir}
-|	|__ train.log, ... # files and directories generated in Stage 4
-|	|__ scoring/
+|    |__ train.log, ... # files and directories generated in Stage 4
+|    |__ scoring/
 |
 |__ RESULTS.md
 ```

diff --git a/examples/librimix/tse/v2/README.md b/examples/librimix/tse/v2/README.md
@@ -207,9 +207,9 @@ data/
         |__ single.utt2spk, single.wav.scp, ... # files generated by Stage 1
         |__ shard.list
         |__ shards/
-        	|__ shards_000000000.tar
-        	|__ ...
-        	|__ shards_000000013.tar
+          |__ shards_000000000.tar
+          |__ ...
+          |__ shards_000000013.tar
 ```
 
 ------
@@ -440,11 +440,11 @@ ${exp_dir}/
 |__ train.log
 |__ config.yaml
 |__ models/
-	|__ checkpoint_1.pt
-	|__ ...
-	|__ checkpoint_150.pt
-	|__ final_checkpoint.pt -> checkpoint_150.pt
-	|__ latest_checkpoint.pt -> checkpoint_150.pt
+  |__ checkpoint_1.pt
+  |__ ...
+  |__ checkpoint_150.pt
+  |__ final_checkpoint.pt -> checkpoint_150.pt
+  |__ latest_checkpoint.pt -> checkpoint_150.pt
 ```
 
 ------
@@ -488,10 +488,10 @@ ${exp_dir}/
 |__ models/
 |__ infer.log
 |__ audio/
-	|__ spk1.scp # each line records two space-separated columns: `target_wav_id` and `target_wav_path`
-	|__ Utt1001-4992-41806-0008_6930-75918-0015-T4992.wav
-	|__ ...
-	|__ Utt999-61-70968-0003_2830-3980-0008-T61.wav
+  |__ spk1.scp # each line records two space-separated columns: `target_wav_id` and `target_wav_path`
+  |__ Utt1001-4992-41806-0008_6930-75918-0015-T4992.wav
+  |__ ...
+  |__ Utt999-61-70968-0003_2830-3980-0008-T61.wav
 ```
 
 ------
@@ -505,8 +505,8 @@ At the end of this stage, a markdown file `RESULTS.md` will be created under `ex
 ```
 exp/BSRNN/
 |__ ${exp_dir}
-|	|__ train.log, ... # files and directories generated in Stage 5
-|	|__ scoring/
+|  |__ train.log, ... # files and directories generated in Stage 5
+|  |__ scoring/
 |
 |__ RESULTS.md
-```
+```
diff --git a/wesep/modules/tasnet/separator.py b/wesep/modules/tasnet/separator.py
@@ -5,11 +5,11 @@
 
 class Separation(nn.Module):
     """
-    R	Number of repeats
-    X	Number of convolutional blocks in each repeat
-    B	Number of channels in bottleneck and the residual paths
-    H	Number of channels in convolutional blocks
-    P	Kernel size in convolutional blocks
+    R    Number of repeats
+    X    Number of convolutional blocks in each repeat
+    B    Number of channels in bottleneck and the residual paths
+    H    Number of channels in convolutional blocks
+    P    Kernel size in convolutional blocks
     norm The type of normalization(gln, cl, bn)
     causal  Two choice(causal or noncausal)
     skip_con Whether to use skip connection