Fine-tune recipe for Zipformer (#1484)

1. support finetune zipformer
2. update the usage; set a very large batch count

egs/gigaspeech/ASR/local/compute_fbank_gigaspeech_splits.py

@@ -51,6 +51,14 @@ def get_parser():
         "Determines batch size dynamically.",
     )
 
+    parser.add_argument(
+        "--subset",
+        type=str,
+        default="XL",
+        choices=["XL", "L", "M", "S", "XS"],
+        help="Which subset to work with",
+    )
+
     parser.add_argument(
         "--num-splits",
         type=int,
@@ -76,7 +84,7 @@ def get_parser():
 
 def compute_fbank_gigaspeech_splits(args):
     num_splits = args.num_splits
-    output_dir = "data/fbank/XL_split"
+    output_dir = f"data/fbank/{args.subset}_split"
     output_dir = Path(output_dir)
     assert output_dir.exists(), f"{output_dir} does not exist!"
 
@@ -96,15 +104,15 @@ def compute_fbank_gigaspeech_splits(args):
     logging.info(f"device: {device}")
 
     for i in range(start, stop):
-        idx = f"{i + 1}".zfill(num_digits)
+        idx = f"{i}".zfill(num_digits)
         logging.info(f"Processing {idx}/{num_splits}")
 
-        cuts_path = output_dir / f"cuts_XL.{idx}.jsonl.gz"
+        cuts_path = output_dir / f"cuts_{args.subset}.{idx}.jsonl.gz"
         if cuts_path.is_file():
             logging.info(f"{cuts_path} exists - skipping")
             continue
 
-        raw_cuts_path = output_dir / f"cuts_XL_raw.{idx}.jsonl.gz"
+        raw_cuts_path = output_dir / f"cuts_{args.subset}_raw.{idx}.jsonl.gz"
 
         logging.info(f"Loading {raw_cuts_path}")
         cut_set = CutSet.from_file(raw_cuts_path)
@@ -113,7 +121,7 @@ def compute_fbank_gigaspeech_splits(args):
 
         cut_set = cut_set.compute_and_store_features_batch(
             extractor=extractor,
-            storage_path=f"{output_dir}/feats_XL_{idx}",
+            storage_path=f"{output_dir}/feats_{args.subset}_{idx}",
             num_workers=args.num_workers,
             batch_duration=args.batch_duration,
             overwrite=True,

egs/librispeech/ASR/tdnn_lstm_ctc/asr_datamodule.py

@@ -1,4 +1,4 @@
-# Copyright      2021  Piotr Żelasko
+#  Copyright      2021  Piotr Żelasko
 # Copyright      2022  Xiaomi Corporation     (Author: Mingshuang Luo)
 #
 # See ../../../../LICENSE for clarification regarding multiple authors
@@ -475,3 +475,18 @@ class LibriSpeechAsrDataModule:
         return load_manifest_lazy(
             self.args.manifest_dir / "librispeech_cuts_test-other.jsonl.gz"
         )
+
+    @lru_cache()
+    def gigaspeech_subset_small_cuts(self) -> CutSet:
+        logging.info("About to get Gigaspeech subset-S cuts")
+        return load_manifest_lazy(self.args.manifest_dir / "cuts_S.jsonl.gz")
+
+    @lru_cache()
+    def gigaspeech_dev_cuts(self) -> CutSet:
+        logging.info("About to get Gigaspeech dev cuts")
+        return load_manifest_lazy(self.args.manifest_dir / "cuts_DEV.jsonl.gz")
+
+    @lru_cache()
+    def gigaspeech_test_cuts(self) -> CutSet:
+        logging.info("About to get Gigaspeech test cuts")
+        return load_manifest_lazy(self.args.manifest_dir / "cuts_TEST.jsonl.gz")