Change isort settings with localfolders and sections.

Signed-off-by: Stanislav Beliaev <[email protected]>

examples/applications/asr_service/app/__init__.py

@@ -1,12 +1,12 @@
 # Copyright (c) 2019 NVIDIA Corporation
 import os
 
+from app import routes  # noqa
+from flask import Flask
 from ruamel.yaml import YAML
 
 import nemo
 import nemo.collections.asr as nemo_asr
-from app import routes  # noqa
-from flask import Flask
 
 app = Flask(__name__)
 # make sure WORK_DIR exists before calling your service

examples/applications/asr_service/app/routes.py

@@ -3,8 +3,6 @@
 import os
 import time
 
-import nemo
-import nemo.collections.asr as nemo_asr
 from app import (
     ENABLE_NGRAM,
     MODEL_YAML,
@@ -19,6 +17,9 @@
 from flask import request
 from werkzeug.utils import secure_filename
 
+import nemo
+import nemo.collections.asr as nemo_asr
+
 try:
     from app import beam_search_with_lm
 except ImportError:

examples/nlp/bert_pretraining.py

@@ -63,14 +63,14 @@
 import os
 
 import torch
+from pytorch_transformers import BertConfig
 
 import nemo
 import nemo.collections.nlp as nemo_nlp
 from nemo.collections.nlp.data.datasets.utils import BERTPretrainingDataDesc
 from nemo.collections.nlp.transformer.utils import gelu
 from nemo.collections.nlp.utils.callbacks.bert_pretraining import eval_epochs_done_callback, eval_iter_callback
 from nemo.utils.lr_policies import get_lr_policy
-from pytorch_transformers import BertConfig
 
 parser = argparse.ArgumentParser(description='BERT pretraining')
 parser.add_argument("--local_rank", default=None, type=int)

examples/tts/tts_infer.py

@@ -8,11 +8,11 @@
 import numpy as np
 from ruamel.yaml import YAML
 from scipy.io.wavfile import write
+from tacotron2 import create_NMs
 
 import nemo
 import nemo.collections.asr as nemo_asr
 import nemo.collections.tts as nemo_tts
-from tacotron2 import create_NMs
 
 
 def parse_args():

nemo/backends/pytorch/actions.py

@@ -13,8 +13,6 @@
 import torch.optim as optim
 
 import nemo
-from nemo.backends.pytorch.nm import TrainableNM
-
 from ...core import DeploymentFormat, DeviceType, NeuralModule, NmTensor
 from ...core.callbacks import ActionCallback, EvaluatorCallback, SimpleLossLoggerCallback
 from ...core.neural_factory import Actions, ModelMode, Optimization
@@ -23,6 +21,7 @@
 from .module_wrapper import TrainableNeuralModuleWrapper
 from .nm import DataLayerNM
 from .optimizers import AdamW, Novograd, master_params
+from nemo.backends.pytorch.nm import TrainableNM
 
 # these imports will happen on as-needed basis
 amp = None

nemo/collections/asr/__init__.py

@@ -12,15 +12,14 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # =============================================================================
-from nemo.core import Backend
-
 from .audio_preprocessing import *
 from .beam_search_decoder import BeamSearchDecoderWithLM
 from .data_layer import AudioToTextDataLayer, KaldiFeatureDataLayer, TranscriptDataLayer
 from .greedy_ctc_decoder import GreedyCTCDecoder
 from .jasper import JasperDecoderForCTC, JasperEncoder
 from .las.misc import JasperRNNConnector
 from .losses import CTCLossNM
+from nemo.core import Backend
 
 __all__ = [
     'Backend',

nemo/collections/asr/audio_preprocessing.py

@@ -30,13 +30,12 @@
 
 import torch
 
+from .parts.features import FilterbankFeatures
+from .parts.spectr_augment import SpecAugment, SpecCutout
 from nemo.backends.pytorch import NonTrainableNM
 from nemo.core import Optimization
 from nemo.core.neural_types import *
 
-from .parts.features import FilterbankFeatures
-from .parts.spectr_augment import SpecAugment, SpecCutout
-
 try:
     import torchaudio
 

nemo/collections/asr/data_layer.py

@@ -6,14 +6,13 @@
 import torch
 
 import nemo
+from .parts.dataset import AudioDataset, KaldiFeatureDataset, TranscriptDataset, seq_collate_fn
+from .parts.features import WaveformFeaturizer
 from nemo.backends.pytorch import DataLayerNM
 from nemo.core import DeviceType
 from nemo.core.neural_types import *
 from nemo.utils.misc import pad_to
 
-from .parts.dataset import AudioDataset, KaldiFeatureDataset, TranscriptDataset, seq_collate_fn
-from .parts.features import WaveformFeaturizer
-
 __all__ = [
     'AudioToTextDataLayer',
     'KaldiFeatureDataLayer',

nemo/collections/asr/helpers.py

@@ -3,7 +3,6 @@
 import torch
 
 import nemo
-
 from .metrics import word_error_rate
 
 

nemo/collections/asr/jasper.py

@@ -5,6 +5,7 @@
 import torch.nn as nn
 import torch.nn.functional as F
 
+from .parts.jasper import JasperBlock, init_weights, jasper_activations
 from nemo.backends.pytorch.nm import TrainableNM
 from nemo.core.neural_types import (
     AxisType,
@@ -17,8 +18,6 @@
     TimeTag,
 )
 
-from .parts.jasper import JasperBlock, init_weights, jasper_activations
-
 
 class JasperEncoder(TrainableNM):
     """

nemo/collections/asr/parts/features.py

@@ -8,7 +8,6 @@
 from torch_stft import STFT
 
 import nemo
-
 from .perturb import AudioAugmentor
 from .segment import AudioSegment
 

nemo/collections/asr/parts/perturb.py

@@ -5,9 +5,8 @@
 import librosa
 from scipy import signal
 
-from nemo.collections.asr.parts import collections, parsers
-
 from .segment import AudioSegment
+from nemo.collections.asr.parts import collections, parsers
 
 
 class Perturbation(object):

nemo/collections/nlp/__init__.py

@@ -14,7 +14,6 @@
 # =============================================================================
 
 import nemo
-
 from .data import *
 from .huggingface import *
 from .modules import *

nemo/collections/nlp/data/data_layers.py

@@ -31,11 +31,10 @@
 from torch.utils import data as pt_data
 
 import nemo
+from .datasets import *
 from nemo.backends.pytorch.nm import DataLayerNM
 from nemo.core.neural_types import *
 
-from .datasets import *
-
 
 class TextDataLayer(DataLayerNM):
     """

nemo/collections/nlp/data/datasets/punctuation_capitalization.py

@@ -28,7 +28,6 @@
 from torch.utils.data import Dataset
 
 import nemo
-
 from . import utils
 
 

nemo/collections/nlp/data/datasets/sentence_classification.py

@@ -26,7 +26,6 @@
 from torch.utils.data import Dataset
 
 import nemo
-
 from . import utils
 
 

nemo/collections/nlp/data/datasets/squad.py

@@ -27,8 +27,6 @@
 from tqdm import tqdm
 
 import nemo
-from nemo.collections.nlp.utils.nlp_utils import _is_whitespace
-
 from ...utils.metrics.squad_metrics import (
     _compute_softmax,
     _get_best_indexes,
@@ -42,6 +40,7 @@
     normalize_answer,
 )
 from .utils import DataProcessor
+from nemo.collections.nlp.utils.nlp_utils import _is_whitespace
 
 
 """

nemo/collections/nlp/data/datasets/token_classification.py

@@ -28,7 +28,6 @@
 from torch.utils.data import Dataset
 
 import nemo
-
 from . import utils
 
 

nemo/collections/nlp/data/datasets/utils.py

@@ -14,7 +14,6 @@
 from tqdm import tqdm
 
 import nemo
-
 from ...utils.nlp_utils import get_vocab, label2idx, write_vocab, write_vocab_in_order
 
 DATABASE_EXISTS_TMP = '{} dataset has already been processed and stored at {}'

nemo/collections/nlp/modules/classifiers.py

@@ -8,13 +8,12 @@
 
 import torch.nn as nn
 
+from ..transformer.utils import transformer_weights_init
 from nemo.backends.pytorch.common import MultiLayerPerceptron
 from nemo.backends.pytorch.nm import LossNM, TrainableNM
 from nemo.collections.nlp.transformer.utils import gelu
 from nemo.core.neural_types import *
 
-from ..transformer.utils import transformer_weights_init
-
 ACT2FN = {"gelu": gelu, "relu": nn.functional.relu}
 
 

nemo/collections/nlp/modules/losses.py

@@ -1,11 +1,10 @@
 import torch
 from torch import nn
 
-from nemo.backends.pytorch.nm import LossNM
-from nemo.core.neural_types import *
-
 from ..utils.nlp_utils import mask_padded_tokens
 from .pytorch_utils import SmoothedCrossEntropyLoss
+from nemo.backends.pytorch.nm import LossNM
+from nemo.core.neural_types import *
 
 __all__ = [
     'JointIntentSlotLoss',

nemo/collections/nlp/modules/transformer_nm.py

@@ -11,9 +11,6 @@
 
 import math
 
-from nemo.backends.pytorch.nm import LossNM, TrainableNM
-from nemo.core.neural_types import *
-
 from ..transformer import (
     BeamSearchSequenceGenerator,
     GreedySequenceGenerator,
@@ -22,6 +19,8 @@
     TransformerEncoder,
 )
 from ..transformer.utils import transformer_weights_init
+from nemo.backends.pytorch.nm import LossNM, TrainableNM
+from nemo.core.neural_types import *
 
 
 class TransformerEncoderNM(TrainableNM):

nemo/collections/nlp/utils/callbacks/translation.py

@@ -3,9 +3,8 @@
 
 import numpy as np
 
-from nemo.collections.asr.metrics import word_error_rate
-
 from ..metrics.sacrebleu import corpus_bleu
+from nemo.collections.asr.metrics import word_error_rate
 
 GLOBAL_KEYS = ["eval_loss", "ref", "sys", "sent_ids", "nonpad_tokens"]
 

nemo/collections/nlp/utils/metrics/sacrebleu.py

@@ -36,9 +36,8 @@
 from itertools import zip_longest
 from typing import Iterable, List, Tuple, Union
 
-from nemo import logging
-
 from .fairseq_tokenizer import tokenize_en
+from nemo import logging
 
 VERSION = '1.3.5'
 

nemo/collections/simple_gan/__init__.py

@@ -12,8 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # =============================================================================
-from nemo.core import Backend
-
 from .gan import *
+from nemo.core import Backend
 
 backend = Backend.PyTorch

nemo/collections/tts/data_layers.py

@@ -2,12 +2,11 @@
 import torch
 
 import nemo
+from .parts.datasets import AudioOnlyDataset
 from nemo.backends.pytorch.nm import DataLayerNM
 from nemo.core import DeviceType
 from nemo.core.neural_types import *
 
-from .parts.datasets import AudioOnlyDataset
-
 
 class AudioDataLayer(DataLayerNM):
     """

nemo/collections/tts/tacotron2_modules.py

@@ -5,11 +5,10 @@
 from torch import nn
 from torch.nn.functional import pad
 
-from nemo.backends.pytorch.nm import LossNM, NonTrainableNM, TrainableNM
-from nemo.core.neural_types import *
-
 from .parts.layers import get_mask_from_lengths
 from .parts.tacotron2 import Decoder, Encoder, Postnet
+from nemo.backends.pytorch.nm import LossNM, NonTrainableNM, TrainableNM
+from nemo.core.neural_types import *
 
 __all__ = [
     "MakeGate",

nemo/collections/tts/waveglow_modules.py

@@ -3,11 +3,10 @@
 import numpy as np
 import torch
 
+from .parts.waveglow import WaveGlow
 from nemo.backends.pytorch.nm import LossNM, TrainableNM
 from nemo.core.neural_types import *
 
-from .parts.waveglow import WaveGlow
-
 __all__ = ["WaveGlowNM", "WaveGlowInferNM", "WaveGlowLoss"]
 
 

nemo/core/callbacks.py

@@ -8,7 +8,6 @@
 from collections import namedtuple
 
 import nemo
-
 from ..utils import get_checkpoint_from_dir
 
 

nemo/core/neural_factory.py

@@ -18,7 +18,6 @@
 import numpy as np
 
 import nemo
-
 from ..utils import ExpManager
 from .callbacks import ActionCallback, EvaluatorCallback
 from .neural_types import *

nemo/core/neural_modules.py

@@ -11,9 +11,6 @@
 from inspect import getargvalues, stack
 from typing import Dict, List, Optional, Set, Tuple
 
-from nemo.core import NeuralModuleFactory
-from nemo.utils.decorators.deprecated import deprecated
-
 from .neural_factory import DeviceType, Optimization
 from .neural_types import (
     CanNotInferResultNeuralType,
@@ -23,6 +20,8 @@
     NeuralTypeComparisonResult,
     NmTensor,
 )
+from nemo.core import NeuralModuleFactory
+from nemo.utils.decorators.deprecated import deprecated
 
 
 class WeightShareTransform(Enum):