Использование двунаправленного слоя LSTM не влияет на длину последовательности. Я проверил это с помощью следующего кода:
from keras.models import Sequential
from keras.layers import Bidirectional,LSTM,BatchNormalization,Dropout,Input
model = Sequential()
lstm1_size = 50
seq_length = 128
feature_dim = 20
model.add(Bidirectional(LSTM(lstm1_size, input_shape=(seq_length, feature_dim), return_sequences=True)))
model.add(BatchNormalization())
model.add(Dropout(0.2))
batch_size = 32
model.build(input_shape=(batch_size,seq_length, feature_dim))
model.summary()
Это привело к следующему выводу для двунаправленного
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
bidirectional_1 (Bidirection (32, 128, 100) 28400
_________________________________________________________________
batch_normalization_1 (Batch (32, 128, 100) 400
_________________________________________________________________
dropout_1 (Dropout) (32, 128, 100) 0
=================================================================
Total params: 28,800
Trainable params: 28,600
Non-trainable params: 200
Нет двунаправленного слоя:
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
lstm_1 (LSTM) (None, 128, 50) 14200
_________________________________________________________________
batch_normalization_1 (Batch (None, 128, 50) 200
_________________________________________________________________
dropout_1 (Dropout) (None, 128, 50) 0
=================================================================
Total params: 14,400
Trainable params: 14,300
Non-trainable params: 100
_________________________________________________________________