Fix CI errors.

.github/workflows/run-pretrained.yml

@@ -82,6 +82,7 @@ jobs:
       - name: Run CTC decoding
         shell: bash
         run: |
+          export PYTHONPATH=$PWD:PYTHONPATH
           cd egs/librispeech/ASR
           ./conformer_ctc/pretrained.py \
             --checkpoint ./tmp/icefall_asr_librispeech_conformer_ctc/exp/pretrained.pt \
@@ -94,6 +95,7 @@ jobs:
       - name: Run HLG decoding
         shell: bash
         run: |
+          export PYTHONPATH=$PWD:$PYTHONPATH
           cd egs/librispeech/ASR
           ./conformer_ctc/pretrained.py \
             --checkpoint ./tmp/icefall_asr_librispeech_conformer_ctc/exp/pretrained.pt \
@@ -101,5 +103,3 @@ jobs:
             ./tmp/icefall_asr_librispeech_conformer_ctc/test_wavs/1089-134686-0001.flac \
             ./tmp/icefall_asr_librispeech_conformer_ctc/test_wavs/1221-135766-0001.flac \
             ./tmp/icefall_asr_librispeech_conformer_ctc/test_wavs/1221-135766-0002.flac
-
-

egs/librispeech/ASR/conformer_ctc/train.py

@@ -96,6 +96,26 @@ def get_parser():
         """,
     )
 
+    parser.add_argument(
+        "--exp-dir",
+        type=str,
+        default="conformer_ctc/exp",
+        help="""The experiment dir.
+        It specifies the directory where all training related
+        files, e.g., checkpoints, log, etc, are saved
+        """,
+    )
+
+    parser.add_argument(
+        "--lang-dir",
+        type=str,
+        default="data/lang_bpe",
+        help="""The lang dir
+        It contains language related input files such as
+        "lexicon.txt"
+        """,
+    )
+
     return parser
 
 
@@ -110,12 +130,6 @@ def get_params() -> AttributeDict:
 
     Explanation of options saved in `params`:
 
-        - exp_dir: It specifies the directory where all training related
-                   files, e.g., checkpoints, log, etc, are saved
-
-        - lang_dir: It contains language related input files such as
-                    "lexicon.txt"
-
         - best_train_loss: Best training loss so far. It is used to select
                            the model that has the lowest training loss. It is
                            updated during the training.
@@ -166,8 +180,6 @@ def get_params() -> AttributeDict:
     """
     params = AttributeDict(
         {
-            "exp_dir": Path("conformer_ctc/exp"),
-            "lang_dir": Path("data/lang_bpe"),
             "best_train_loss": float("inf"),
             "best_valid_loss": float("inf"),
             "best_train_epoch": -1,
@@ -638,6 +650,8 @@ def main():
     parser = get_parser()
     LibriSpeechAsrDataModule.add_arguments(parser)
     args = parser.parse_args()
+    args.exp_dir = Path(args.exp_dir)
+    args.lang_dir = Path(args.lang_dir)
 
     world_size = args.world_size
     assert world_size >= 1