[codemod][usort] apply import merging for fbcode (8 of 11)

Summary:
Applies new import merging and sorting from µsort v1.0.

When merging imports, µsort will make a best-effort to move associated
comments to match merged elements, but there are known limitations due to
the diynamic nature of Python and developer tooling. These changes should
not produce any dangerous runtime changes, but may require touch-ups to
satisfy linters and other tooling.

Note that µsort uses case-insensitive, lexicographical sorting, which
results in a different ordering compared to isort. This provides a more
consistent sorting order, matching the case-insensitive order used when
sorting import statements by module name, and ensures that "frog", "FROG",
and "Frog" always sort next to each other.

For details on µsort's sorting and merging semantics, see the user guide:
https://usort.readthedocs.io/en/stable/guide.html#sorting

Reviewed By: lisroach

Differential Revision: D36402214

fbshipit-source-id: b641bfa9d46242188524d4ae2c44998922a62b4c

examples/asr/emformer_rnnt/eval.py

@@ -11,7 +11,7 @@ from argparse import ArgumentParser, RawTextHelpFormatter
 
 import torch
 import torchaudio
-from common import MODEL_TYPE_LIBRISPEECH, MODEL_TYPE_TEDLIUM3, MODEL_TYPE_MUSTC
+from common import MODEL_TYPE_LIBRISPEECH, MODEL_TYPE_MUSTC, MODEL_TYPE_TEDLIUM3
 from librispeech.lightning import LibriSpeechRNNTModule
 from mustc.lightning import MuSTCRNNTModule
 from tedlium3.lightning import TEDLIUM3RNNTModule

examples/asr/emformer_rnnt/global_stats.py

@@ -14,8 +14,8 @@ import torch
 import torchaudio
 from common import (
     MODEL_TYPE_LIBRISPEECH,
-    MODEL_TYPE_TEDLIUM3,
     MODEL_TYPE_MUSTC,
+    MODEL_TYPE_TEDLIUM3,
     piecewise_linear_log,
     spectrogram_transform,
 )

examples/asr/emformer_rnnt/librispeech/lightning.py

@@ -7,16 +7,16 @@ import torch
 import torchaudio
 from common import (
     Batch,
+    batch_by_token_count,
     FunctionalModule,
     GlobalStatsNormalization,
-    WarmupLR,
-    batch_by_token_count,
     piecewise_linear_log,
     post_process_hypos,
     spectrogram_transform,
+    WarmupLR,
 )
 from pytorch_lightning import LightningModule
-from torchaudio.models import RNNTBeamSearch, emformer_rnnt_base
+from torchaudio.models import emformer_rnnt_base, RNNTBeamSearch
 
 
 class CustomDataset(torch.utils.data.Dataset):

examples/asr/emformer_rnnt/mustc/lightning.py

@@ -6,16 +6,16 @@ import torch
 import torchaudio
 from common import (
     Batch,
+    batch_by_token_count,
     FunctionalModule,
     GlobalStatsNormalization,
-    WarmupLR,
-    batch_by_token_count,
     piecewise_linear_log,
     post_process_hypos,
     spectrogram_transform,
+    WarmupLR,
 )
 from pytorch_lightning import LightningModule
-from torchaudio.models import RNNTBeamSearch, emformer_rnnt_base
+from torchaudio.models import emformer_rnnt_base, RNNTBeamSearch
 
 from .dataset import MUSTC
 

examples/asr/emformer_rnnt/pipeline_demo.py

@@ -15,9 +15,11 @@ import torch
 import torchaudio
 from common import MODEL_TYPE_LIBRISPEECH, MODEL_TYPE_MUSTC, MODEL_TYPE_TEDLIUM3
 from mustc.dataset import MUSTC
-from torchaudio.pipelines import EMFORMER_RNNT_BASE_LIBRISPEECH
-from torchaudio.pipelines import RNNTBundle
-from torchaudio.prototype.pipelines import EMFORMER_RNNT_BASE_MUSTC, EMFORMER_RNNT_BASE_TEDLIUM3
+from torchaudio.pipelines import EMFORMER_RNNT_BASE_LIBRISPEECH, RNNTBundle
+from torchaudio.prototype.pipelines import (
+    EMFORMER_RNNT_BASE_MUSTC,
+    EMFORMER_RNNT_BASE_TEDLIUM3,
+)
 
 logger = logging.getLogger(__name__)
 

examples/asr/emformer_rnnt/tedlium3/lightning.py

@@ -7,16 +7,16 @@ import torch
 import torchaudio
 from common import (
     Batch,
+    batch_by_token_count,
     FunctionalModule,
     GlobalStatsNormalization,
-    WarmupLR,
-    batch_by_token_count,
     piecewise_linear_log,
     post_process_hypos,
     spectrogram_transform,
+    WarmupLR,
 )
 from pytorch_lightning import LightningModule
-from torchaudio.models import RNNTBeamSearch, emformer_rnnt_base
+from torchaudio.models import emformer_rnnt_base, RNNTBeamSearch
 
 
 class CustomDataset(torch.utils.data.Dataset):

examples/asr/emformer_rnnt/train.py

@@ -3,7 +3,7 @@ import logging
 import pathlib
 from argparse import ArgumentParser
 
-from common import MODEL_TYPE_LIBRISPEECH, MODEL_TYPE_TEDLIUM3, MODEL_TYPE_MUSTC
+from common import MODEL_TYPE_LIBRISPEECH, MODEL_TYPE_MUSTC, MODEL_TYPE_TEDLIUM3
 from librispeech.lightning import LibriSpeechRNNTModule
 from mustc.lightning import MuSTCRNNTModule
 from pytorch_lightning import Trainer

examples/asr/librispeech_conformer_rnnt/lightning.py

@@ -9,7 +9,7 @@ from data_module import LibriSpeechDataModule
 from pytorch_lightning import LightningModule
 from torchaudio.models import Hypothesis, RNNTBeamSearch
 from torchaudio.prototype.models import conformer_rnnt_base
-from transforms import Batch, TrainTransform, ValTransform, TestTransform
+from transforms import Batch, TestTransform, TrainTransform, ValTransform
 
 logger = logging.getLogger()
 

examples/asr/librispeech_conformer_rnnt/train.py

@@ -2,8 +2,8 @@ import pathlib
 from argparse import ArgumentParser
 
 from lightning import ConformerRNNTModule, get_data_module
-from pytorch_lightning import Trainer, seed_everything
-from pytorch_lightning.callbacks import ModelCheckpoint, LearningRateMonitor
+from pytorch_lightning import seed_everything, Trainer
+from pytorch_lightning.callbacks import LearningRateMonitor, ModelCheckpoint
 from pytorch_lightning.plugins import DDPPlugin
 
 

examples/asr/librispeech_ctc_decoder/inference.py

@@ -4,7 +4,7 @@ from typing import Optional
 
 import torch
 import torchaudio
-from torchaudio.prototype.ctc_decoder import lexicon_decoder, download_pretrained_files
+from torchaudio.prototype.ctc_decoder import download_pretrained_files, lexicon_decoder
 
 
 logger = logging.getLogger(__name__)

examples/hubert/dataset/__init__.py

-from .hubert_dataset import (
-    BucketizeBatchSampler,
-    CollateFnHubert,
-    HuBERTDataSet,
-)
+from .hubert_dataset import BucketizeBatchSampler, CollateFnHubert, HuBERTDataSet
 
 
 __all__ = [

examples/hubert/preprocess.py

@@ -11,12 +11,7 @@ from argparse import ArgumentParser, RawTextHelpFormatter
 from pathlib import Path
 
 import torch
-from utils import (
-    create_tsv,
-    dump_features,
-    learn_kmeans,
-    get_km_label,
-)
+from utils import create_tsv, dump_features, get_km_label, learn_kmeans
 
 
 def _init_logger(debug=False):

examples/hubert/utils/__init__.py

 from .common_utils import create_tsv
 from .feature_utils import dump_features
-from .kmeans import learn_kmeans, get_km_label
+from .kmeans import get_km_label, learn_kmeans
 
 __all__ = [
     "create_tsv",

examples/hubert/utils/common_utils.py

@@ -9,10 +9,7 @@ Data pre-processing: create tsv files for training (and valiation).
 import logging
 import re
 from pathlib import Path
-from typing import (
-    Tuple,
-    Union,
-)
+from typing import Tuple, Union
 
 import torch
 import torchaudio

examples/hubert/utils/feature_utils.py

@@ -5,11 +5,7 @@
 # https://github.com/pytorch/fairseq/blob/265df7144c79446f5ea8d835bda6e727f54dad9d/LICENSE
 import logging
 from pathlib import Path
-from typing import (
-    Optional,
-    Tuple,
-    Union,
-)
+from typing import Optional, Tuple, Union
 
 import torch
 import torchaudio

examples/hubert/utils/kmeans.py

@@ -5,9 +5,7 @@
 # https://github.com/pytorch/fairseq/blob/265df7144c79446f5ea8d835bda6e727f54dad9d/LICENSE
 import logging
 from pathlib import Path
-from typing import (
-    Tuple,
-)
+from typing import Tuple
 
 import joblib
 import torch

examples/interactive_asr/asr.py

@@ -13,7 +13,12 @@ import datetime as dt
 import logging
 
 from fairseq import options
-from interactive_asr.utils import add_asr_eval_argument, setup_asr, get_microphone_transcription, transcribe_file
+from interactive_asr.utils import (
+    add_asr_eval_argument,
+    get_microphone_transcription,
+    setup_asr,
+    transcribe_file,
+)
 
 
 def main(args):

examples/interactive_asr/utils.py

@@ -13,7 +13,7 @@ import sentencepiece as spm
 import torch
 import torchaudio
 from fairseq import tasks
-from fairseq.utils import load_ensemble_for_inference, import_user_module
+from fairseq.utils import import_user_module, load_ensemble_for_inference
 from interactive_asr.vad import get_microphone_chunks
 
 

examples/pipeline_tacotron2/datasets.py

@@ -25,7 +25,7 @@
 #
 # *****************************************************************************
 
-from typing import Tuple, Callable, List
+from typing import Callable, List, Tuple
 
 import torch
 from torch import Tensor

examples/pipeline_tacotron2/inference.py

@@ -13,13 +13,12 @@ import torch
 import torchaudio
 from datasets import InverseSpectralNormalization
 from text.text_preprocessing import (
-    available_symbol_set,
     available_phonemizers,
+    available_symbol_set,
     get_symbol_list,
     text_to_sequence,
 )
-from torchaudio.models import Tacotron2
-from torchaudio.models import tacotron2 as pretrained_tacotron2
+from torchaudio.models import Tacotron2, tacotron2 as pretrained_tacotron2
 from utils import prepare_input_sequence
 
 
@@ -27,8 +26,12 @@ def parse_args():
     r"""
     Parse commandline arguments.
     """
-    from torchaudio.models.tacotron2 import _MODEL_CONFIG_AND_URLS as tacotron2_config_and_urls
-    from torchaudio.models.wavernn import _MODEL_CONFIG_AND_URLS as wavernn_config_and_urls
+    from torchaudio.models.tacotron2 import (
+        _MODEL_CONFIG_AND_URLS as tacotron2_config_and_urls,
+    )
+    from torchaudio.models.wavernn import (
+        _MODEL_CONFIG_AND_URLS as wavernn_config_and_urls,
+    )
 
     parser = argparse.ArgumentParser(description=__doc__)
     parser.add_argument(