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remove feature extraction config (#10457)

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Patrick von Platen 2021-03-01 12:30:12 +03:00 committed by GitHub
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commit 11655fafdd
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src/transformers/models/wav2vec2/configuration_wav2vec2.py
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@ -92,8 +92,6 @@ class Wav2Vec2Config(PretrainedConfig):
Whether do apply `stable` layer norm architecture of the Transformer encoder. ``do_stable_layer_norm is
True`` corresponds to applying layer norm before the attention layer, whereas ``do_stable_layer_norm is
False`` corresponds to applying layer norm after the attention layer.
freeze_feat_extract_train (:obj:`bool`, `optional`, defaults to :obj:`True`):
Whether to freeze the weights of the feature extractor when training.
apply_spec_augment (:obj:`bool`, `optional`, defaults to :obj:`True`):
Whether to apply *SpecAugment* data augmentation to the outputs of the feature extractor. For reference see
`SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition
@ -160,7 +158,6 @@ class Wav2Vec2Config(PretrainedConfig):
num_conv_pos_embeddings=128,
num_conv_pos_embedding_groups=16,
do_stable_layer_norm=False,
freeze_feat_extract_train=True,
apply_spec_augment=True,
mask_time_prob=0.05,
mask_time_length=10,
@ -199,7 +196,6 @@ class Wav2Vec2Config(PretrainedConfig):
self.initializer_range = initializer_range
self.vocab_size = vocab_size
self.do_stable_layer_norm = do_stable_layer_norm
self.freeze_feat_extract_train = freeze_feat_extract_train
self.gradient_checkpointing = gradient_checkpointing
if (