Fix style issue (#3410)

Summary: Pull Request resolved: https://github.com/pytorch/audio/pull/3410

Differential Revision: D46496786

Pulled By: mthrok

fbshipit-source-id: e517b273c40b340f39ce7db7ab1be1c3eb5f2059

examples/asr/avsr_rnnt/average_checkpoints.py

@@ -27,5 +27,5 @@ def ensemble(args):
         os.path.join(args.exp_dir, args.experiment_name, f"epoch={n}.ckpt")
         for n in range(args.epochs - 10, args.epochs)
     ]
-    model_path = os.path.join(args.exp_dir, args.experiment_name, f"model_avg_10.pth")
+    model_path = os.path.join(args.exp_dir, args.experiment_name, "model_avg_10.pth")
     torch.save({"state_dict": average_checkpoints(last)}, model_path)

examples/asr/avsr_rnnt/data_module.py

-import os
 import random
 
 import torch
-import torchaudio
 
 from lrs3 import LRS3
 from pytorch_lightning import LightningDataModule

examples/asr/avsr_rnnt/lightning.py

 import itertools
-import logging
 import math
 
 from collections import namedtuple

examples/asr/avsr_rnnt/lightning_av.py

 import itertools
-import logging
 import math
 
 from collections import namedtuple

examples/asr/avsr_rnnt/lrs3.py

 import os
-from pathlib import Path
-from typing import Tuple, Union
 
-import torch
 import torchaudio
 import torchvision
-from torch import Tensor
 from torch.utils.data import Dataset
 
 
@@ -15,7 +11,7 @@ def _load_list(args, *filenames):
     for filename in filenames:
         filepath = os.path.join(os.path.dirname(args.dataset_path), filename)
         for line in open(filepath).read().splitlines():
-            dataset_name, rel_path, input_length = line.split(",")[0], line.split(",")[1], line.split(",")[2]
+            rel_path, input_length = line.split(",")[1:3]
             path = os.path.normpath(os.path.join(args.dataset_path, rel_path[:-4] + ".mp4"))
             length.append(int(input_length))
             output.append(path)

examples/asr/avsr_rnnt/models/emformer_rnnt.py

 from torchaudio.models.rnnt import emformer_rnnt_model
 
+
 # https://pytorch.org/audio/master/_modules/torchaudio/models/rnnt.html#emformer_rnnt_base
 def emformer_rnnt():
     return emformer_rnnt_model(

examples/asr/avsr_rnnt/train.py

 import logging
 import os
-import pathlib
 from argparse import ArgumentParser
 
 import sentencepiece as spm
@@ -19,7 +18,7 @@ def get_trainer(args):
         monitor="monitoring_step",
         mode="max",
         save_last=True,
-        filename=f"{{epoch}}",
+        filename="{{epoch}}",
         save_top_k=10,
     )
     lr_monitor = LearningRateMonitor(logging_interval="step")

examples/asr/avsr_rnnt/transforms.py

-import json
-import math
 import random
-from functools import partial
 from typing import List
 
 import sentencepiece as spm
 import torch
-import torchaudio
 import torchvision
 from data_module import LRS3DataModule
 from lightning import Batch

test/torchaudio_unittest/backend/dispatcher/sox/load_test.py

@@ -2,7 +2,6 @@ import itertools
 from functools import partial
 
 import torch
-import torchaudio
 from parameterized import parameterized
 from torchaudio._backend.utils import get_load_func
 from torchaudio_unittest.common_utils import (

test/torchaudio_unittest/backend/sox_io/load_test.py

-import io
 import itertools
-import tarfile
 
 import torch
-import torchaudio
 from parameterized import parameterized
-from torchaudio._internal import module_utils as _mod_utils
 from torchaudio.backend import sox_io_backend
 from torchaudio_unittest.common_utils import (
     get_asset_path,
     get_wav_data,
-    HttpServerMixin,
     load_wav,
     nested_params,
     PytorchTestCase,
     save_wav,
     skipIfNoExec,
-    skipIfNoModule,
     skipIfNoSox,
     sox_utils,
     TempDirMixin,
@@ -25,10 +19,6 @@ from torchaudio_unittest.common_utils import (
 from .common import name_func
 
 
-if _mod_utils.is_module_available("requests"):
-    import requests
-
-
 class LoadTestBase(TempDirMixin, PytorchTestCase):
     def assert_format(
         self,

test/torchaudio_unittest/backend/sox_io/save_test.py

-import io
 import os
 
 import torch

test/torchaudio_unittest/backend/sox_io/smoke_test.py

-import io
 import itertools
 
 from parameterized import parameterized