fix code style

egs/tal_csasr/ASR/lstm_transducer_stateless3/streaming_decode.py

@@ -55,9 +55,9 @@ Usage:
       --max-contexts 4 \
       --max-states 8
 """
-import re
 import argparse
 import logging
+import re
 import warnings
 from pathlib import Path
 from typing import Dict, List, Optional, Tuple
@@ -72,12 +72,13 @@ from beam_search import Hypothesis, HypothesisList, get_hyps_shape
 from kaldifeat import Fbank, FbankOptions
 from lhotse import CutSet
 from lhotse.cut import Cut
-from lstm import LOG_EPSILON, stack_states, unstack_states
 from local.text_normalize import text_normalize
+from lstm import LOG_EPSILON, stack_states, unstack_states
 from stream import Stream
 from torch.nn.utils.rnn import pad_sequence
 from train import add_model_arguments, get_params, get_transducer_model
 
+from icefall.char_graph_compiler import CharCtcTrainingGraphCompiler
 from icefall.checkpoint import (
     average_checkpoints,
     average_checkpoints_with_averaged_model,
@@ -85,7 +86,6 @@ from icefall.checkpoint import (
     load_checkpoint,
 )
 from icefall.decode import one_best_decoding
-from icefall.char_graph_compiler import CharCtcTrainingGraphCompiler
 from icefall.lexicon import Lexicon
 from icefall.utils import (
     AttributeDict,
@@ -622,8 +622,8 @@ def create_streaming_feature_extractor() -> Fbank:
     opts.mel_opts.num_bins = 80
     return Fbank(opts)
 
+
 def filter_zh_en(text: str):
-    import re
     pattern = re.compile(r"([\u4e00-\u9fff])")
 
     chars = pattern.split(text.upper())
@@ -634,6 +634,7 @@ def filter_zh_en(text: str):
             chars_new.extend(tokens)
     return chars_new
 
+
 def decode_dataset(
     cuts: CutSet,
     model: nn.Module,

egs/tal_csasr/ASR/lstm_transducer_stateless3/train.py

@@ -62,9 +62,9 @@ from joiner import Joiner
 from lhotse.cut import Cut
 from lhotse.dataset.sampling.base import CutSampler
 from lhotse.utils import fix_random_seed
-from lstm import RNN
 from local.text_normalize import text_normalize
 from local.tokenize_with_bpe_model import tokenize_by_bpe_model
+from lstm import RNN
 from model import Transducer
 from optim import Eden, Eve
 from torch import Tensor
@@ -161,7 +161,7 @@ def add_model_arguments(parser: argparse.ArgumentParser):
         "--is-pnnx",
         type=str2bool,
         default=False,
-        help="Only used when exporting model with pnnx."
+        help="Only used when exporting model with pnnx.",
     )
 
 
@@ -643,7 +643,7 @@ def compute_loss(
     feature_lens = supervisions["num_frames"].to(device)
 
     texts = batch["supervisions"]["text"]
-    #import pdb; pdb.set_trace()
+    # import pdb; pdb.set_trace()
     y = graph_compiler.texts_to_ids_with_bpe(texts)
     if type(y) == list:
         y = k2.RaggedTensor(y).to(device)