maxpooling2d keras вообще не делает пул

Question

Я пишу CNN для классификации текста. Слой max pooling2D, кажется, не работает, поскольку форма вывода такая же, как и в conv2D. Я приложил свой код и форму вывода ниже. Спасибо за помощь!

    from keras.layers import Dense, Input, Flatten
    from keras.layers import Conv2D, MaxPooling2D, Embedding, Reshape, Concatenate, Dropout
    from keras import optimizers
    from keras.models import Model

    convs = []
    filter_sizes = [2,4,8]
    BATCH_SIZE = 10

    sequence_input = Input(shape=(MAX_SEQUENCE_LENGTH,), dtype='int32')
    embedded_sequences = embedding_layer(sequence_input)
    reshape = Reshape((MAX_SEQUENCE_LENGTH, EMBEDDING_DIM,1))(embedded_sequences)

    conv_0 = Conv2D(filters = 128, kernel_size=(MAX_SEQUENCE_LENGTH, filter_sizes[0]), activation='relu')(reshape)
    conv_1 = Conv2D(filters = 128, kernel_size=(MAX_SEQUENCE_LENGTH, filter_sizes[1]), activation='relu')(reshape)
    conv_2 = Conv2D(filters = 128, kernel_size=(MAX_SEQUENCE_LENGTH, filter_sizes[2]), activation='relu')(reshape)

    maxpool_0 = MaxPooling2D(pool_size=(MAX_SEQUENCE_LENGTH - filter_sizes[0] + 1,1), strides=(1,1), padding='same')(conv_0)
    maxpool_1 = MaxPooling2D(pool_size=(MAX_SEQUENCE_LENGTH - filter_sizes[1] + 1, 1), strides=(1,1), padding='same')(conv_1)
    maxpool_2 = MaxPooling2D(pool_size=(MAX_SEQUENCE_LENGTH - filter_sizes[2] + 1, 1), strides=(1,1), padding='same')(conv_2)

    concatenated_tensor = Concatenate(axis = 2)([maxpool_0, maxpool_1, maxpool_2])
    flatten = Flatten()(concatenated_tensor)
    dense = Dense(2048, activation='relu')(flatten)
    dense_out = Dropout(0.5)(dense)
    preds = Dense(label_dim, activation='sigmoid')(dense_out)

    model = Model(sequence_input, preds)
    opt = optimizers.Adam(lr=0.0001)
    model.compile(loss='binary_crossentropy',
          optimizer=opt,
          metrics=['acc'])

форма вывода для каждого слоя