isort

egs/seame/ASR/local/cer.py

@@ -9,6 +9,7 @@
 """
 
 import argparse
+
 import jiwer
 
 

egs/seame/ASR/local/compute_fbank_gpu_seame.py

@@ -23,20 +23,19 @@
 The generated fbank features are saved in data_seame/fbank.
 """
 
+import argparse
 import logging
 import os
 from pathlib import Path
-import argparse
 
 from lhotse import CutSet, LilcomChunkyWriter
-from lhotse.recipes.utils import read_manifests_if_cached
-
 from lhotse.features.kaldifeat import (
     KaldifeatFbank,
     KaldifeatFbankConfig,
     KaldifeatFrameOptions,
     KaldifeatMelOptions,
 )
+from lhotse.recipes.utils import read_manifests_if_cached
 
 
 def get_args():

egs/seame/ASR/local/compute_fbank_gpu_seame_sample.py

@@ -23,13 +23,12 @@
 The generated fbank features are saved in data_seame/fbank.
 """
 
+import argparse
 import logging
 import os
 from pathlib import Path
-import argparse
 
 from lhotse import CutSet, LilcomChunkyWriter
-
 from lhotse.features.kaldifeat import (
     KaldifeatFbank,
     KaldifeatFbankConfig,

egs/seame/ASR/local/cuts_validate.py

@@ -1,11 +1,12 @@
 #!/usr/bin/python
 
-from lhotse import RecordingSet, SupervisionSet, CutSet
 import argparse
 import logging
-from lhotse.qa import fix_manifests, validate_recordings_and_supervisions
 import pdb
 
+from lhotse import CutSet, RecordingSet, SupervisionSet
+from lhotse.qa import fix_manifests, validate_recordings_and_supervisions
+
 
 def get_parser():
     parser = argparse.ArgumentParser(

egs/seame/ASR/local/prepare_lang_bpe.py

@@ -35,6 +35,7 @@
 """
 
 import argparse
+import pdb
 from pathlib import Path
 from typing import Dict, List, Tuple
 
@@ -50,7 +51,6 @@
 )
 
 from icefall.utils import str2bool
-import pdb
 
 
 def lexicon_to_fst_no_sil(

egs/seame/ASR/local/prepare_transcripts.py

@@ -5,12 +5,13 @@
 This script prepares transcript_words.txt from cutset
 """
 
-from lhotse import CutSet
 import argparse
 import logging
+import os
 import pdb
 from pathlib import Path
-import os
+
+from lhotse import CutSet
 
 
 def get_parser():

egs/seame/ASR/local/sample_hours.py

@@ -5,12 +5,13 @@
 Sample data given duration in seconds.
 """
 
-from lhotse import RecordingSet, SupervisionSet, CutSet
 import argparse
 import logging
 import os
 from pathlib import Path
 
+from lhotse import CutSet, RecordingSet, SupervisionSet
+
 
 def get_parser():
     parser = argparse.ArgumentParser(

egs/seame/ASR/local/train_bpe_model.py

@@ -29,6 +29,7 @@
 import shutil
 from pathlib import Path
 from typing import Dict
+
 import sentencepiece as spm
 
 

egs/seame/ASR/local/wer_lang.py

@@ -5,11 +5,16 @@
 Compute WER per language
 """
 
-import sys, codecs, math, pickle, unicodedata, re
-from collections import Counter
 import argparse
+import codecs
+import math
+import pickle
+import re
+import sys
+import unicodedata
+from collections import Counter, defaultdict
+
 from kaldialign import align
-from collections import defaultdict
 
 
 def get_parser():

egs/seame/ASR/zipformer/decode.py

@@ -64,6 +64,8 @@
 import logging
 import math
 import os
+import re
+import string
 from collections import defaultdict
 from pathlib import Path
 from typing import Dict, List, Optional, Tuple
@@ -105,9 +107,6 @@
     str2bool,
     write_error_stats,
 )
-import string
-import re
-
 
 LOG_EPS = math.log(1e-10)
 

egs/seame/ASR/zipformer/profile.py

@@ -22,24 +22,24 @@
 
 import argparse
 import logging
-import sentencepiece as spm
-import torch
-
 from typing import Tuple
-from torch import Tensor, nn
 
-from icefall.utils import make_pad_mask
-from icefall.profiler import get_model_profile
+import sentencepiece as spm
+import torch
 from scaling import BiasNorm
+from torch import Tensor, nn
 from train import (
+    add_model_arguments,
     get_encoder_embed,
     get_encoder_model,
     get_joiner_model,
-    add_model_arguments,
     get_params,
 )
 from zipformer import BypassModule
 
+from icefall.profiler import get_model_profile
+from icefall.utils import make_pad_mask
+
 
 def get_parser():
     parser = argparse.ArgumentParser(

egs/seame/ASR/zipformer_hat/decode.py

@@ -52,6 +52,8 @@
 import logging
 import math
 import os
+import re
+import string
 from collections import defaultdict
 from pathlib import Path
 from typing import Dict, List, Optional, Tuple
@@ -64,8 +66,8 @@
 from beam_search import (
     greedy_search_batch,
     modified_beam_search,
-    modified_beam_search_lm_shallow_fusion,
     modified_beam_search_lm_rescore_LODR,
+    modified_beam_search_lm_shallow_fusion,
     modified_beam_search_LODR,
 )
 from train import add_model_arguments, get_model, get_params
@@ -86,8 +88,6 @@
     str2bool,
     write_error_stats,
 )
-import string
-import re
 
 LOG_EPS = math.log(1e-10)
 

egs/seame/ASR/zipformer_hat/model.py

@@ -22,9 +22,9 @@
 import torch
 import torch.nn as nn
 from encoder_interface import EncoderInterface
+from scaling import ScaledLinear
 
 from icefall.utils import add_sos, make_pad_mask
-from scaling import ScaledLinear
 
 
 class AsrModel(nn.Module):

egs/seame/ASR/zipformer_hat_lid/decode.py

@@ -75,22 +75,28 @@
 import logging
 import math
 import os
+import re
+import string
 from collections import defaultdict
 from pathlib import Path
 from typing import Dict, List, Optional, Tuple
 
 import k2
+import matplotlib.pyplot as plt
+import seaborn as sns
 import sentencepiece as spm
 import torch
 import torch.nn as nn
 from asr_datamodule import SeameAsrDataModule
 from beam_search import (
     greedy_search_batch,
     modified_beam_search,
-    modified_beam_search_lm_shallow_fusion,
     modified_beam_search_lm_rescore_LODR,
+    modified_beam_search_lm_shallow_fusion,
     modified_beam_search_LODR,
 )
+from kaldialign import align
+from sklearn.metrics import classification_report, confusion_matrix, f1_score
 from train import add_model_arguments, get_model, get_params
 
 from icefall import ContextGraph, LmScorer, NgramLm
@@ -109,12 +115,6 @@
     str2bool,
     write_error_stats,
 )
-from kaldialign import align
-from sklearn.metrics import f1_score, classification_report, confusion_matrix
-import string
-import re
-import seaborn as sns
-import matplotlib.pyplot as plt
 
 LOG_EPS = math.log(1e-10)
 

egs/seame/ASR/zipformer_hat_lid/joiner.py

@@ -14,10 +14,11 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+from typing import Optional
+
 import torch
 import torch.nn as nn
 from scaling import ScaledLinear
-from typing import Optional
 
 
 class Joiner(nn.Module):

egs/seame/ASR/zipformer_hat_lid/model.py

@@ -23,9 +23,9 @@
 import torch
 import torch.nn as nn
 from encoder_interface import EncoderInterface
+from scaling import ScaledLinear
 
 from icefall.utils import add_sos, make_pad_mask
-from scaling import ScaledLinear
 
 
 class AsrModel(nn.Module):

egs/seame/ASR/zipformer_hat_lid/train.py

@@ -100,7 +100,7 @@
 from pathlib import Path
 from shutil import copyfile
 from typing import Any, Dict, Optional, Tuple, Union
-from torch.optim import Optimizer
+
 import k2
 import optim
 import sentencepiece as spm
@@ -120,6 +120,7 @@
 from torch import Tensor
 from torch.cuda.amp import GradScaler
 from torch.nn.parallel import DistributedDataParallel as DDP
+from torch.optim import Optimizer
 from torch.utils.tensorboard import SummaryWriter
 from zipformer import Zipformer2
 

egs/seame/ASR/zipformer_hat_lid/zipformer.py

@@ -17,28 +17,33 @@
 # limitations under the License.
 
 import copy
+import logging
 import math
+import random
 import warnings
 from typing import List, Optional, Tuple, Union
-import logging
+
 import torch
-import random
 from encoder_interface import EncoderInterface
 from scaling import (
+    Identity,  # more friendly to backward hooks than nn.Identity(), for diagnostic reasons.
+)
+from scaling import (
+    ScaledLinear,  # not as in other dirs.. just scales down initial parameter values.
+)
+from scaling import (
+    ActivationDropoutAndLinear,
     Balancer,
     BiasNorm,
-    Dropout2,
     ChunkCausalDepthwiseConv1d,
-    ActivationDropoutAndLinear,
-    ScaledLinear,  # not as in other dirs.. just scales down initial parameter values.
+    Dropout2,
+    FloatLike,
+    ScheduledFloat,
     Whiten,
-    Identity,  # more friendly to backward hooks than nn.Identity(), for diagnostic reasons.
+    convert_num_channels,
+    limit_param_value,
     penalize_abs_values_gt,
     softmax,
-    ScheduledFloat,
-    FloatLike,
-    limit_param_value,
-    convert_num_channels,
 )
 from torch import Tensor, nn