fixed broken softlinks (#1381)

* removed broken softlinks

* fixed dependencies

* fixed file permission

icefall/shared/convert-k2-to-openfst.py

@@ -0,0 +1,102 @@
+#!/usr/bin/env python3
+# Copyright    2022  Xiaomi Corp.        (authors: Fangjun Kuang)
+#
+# See ../../../../LICENSE for clarification regarding multiple authors
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""
+This script takes as input an FST in k2 format and convert it
+to an FST in OpenFST format.
+
+The generated FST is saved into a binary file and its type is
+StdVectorFst.
+
+Usage examples:
+(1) Convert an acceptor
+
+  ./convert-k2-to-openfst.py in.pt binary.fst
+
+(2) Convert a transducer
+
+  ./convert-k2-to-openfst.py --olabels aux_labels in.pt binary.fst
+"""
+
+import argparse
+import logging
+from pathlib import Path
+
+import k2
+import kaldifst.utils
+import torch
+
+
+def get_args():
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        "--olabels",
+        type=str,
+        default=None,
+        help="""If not empty, the input FST is assumed to be a transducer
+        and we use its attribute specified by "olabels" as the output labels.
+        """,
+    )
+    parser.add_argument(
+        "input_filename",
+        type=str,
+        help="Path to the input FST in k2 format",
+    )
+
+    parser.add_argument(
+        "output_filename",
+        type=str,
+        help="Path to the output FST in OpenFst format",
+    )
+
+    return parser.parse_args()
+
+
+def main():
+    args = get_args()
+    logging.info(f"{vars(args)}")
+
+    input_filename = args.input_filename
+    output_filename = args.output_filename
+    olabels = args.olabels
+
+    if Path(output_filename).is_file():
+        logging.info(f"{output_filename} already exists - skipping")
+        return
+
+    assert Path(input_filename).is_file(), f"{input_filename} does not exist"
+    logging.info(f"Loading {input_filename}")
+    k2_fst = k2.Fsa.from_dict(torch.load(input_filename))
+    if olabels:
+        assert hasattr(k2_fst, olabels), f"No such attribute: {olabels}"
+
+    p = Path(output_filename).parent
+    if not p.is_dir():
+        logging.info(f"Creating {p}")
+        p.mkdir(parents=True)
+
+    logging.info("Converting (May take some time if the input FST is large)")
+    fst = kaldifst.utils.k2_to_openfst(k2_fst, olabels=olabels)
+    logging.info(f"Saving to {output_filename}")
+    fst.write(output_filename)
+
+
+if __name__ == "__main__":
+    formatter = "%(asctime)s %(levelname)s [%(filename)s:%(lineno)d] %(message)s"
+
+    logging.basicConfig(format=formatter, level=logging.INFO)
+    main()