kerasのfunction apiでベクトルを結合したい

現在、kerasのfunction apiを用いて入力データを4種類のカーネルサイズで畳み込みしたのち、それを統合したベクトルを作成したいのですが、うまくいきません。
どうすればよいのでしょうか？
#ソースコード

# input image dimensions
img_rows, img_cols = 100, 200

batch_size = 128
num_classes = 2
epochs = 12
conv_filters = 128

x_train = x_train.reshape(x_train.shape[0], img_rows, img_cols, 1)
x_test = x_test.reshape(x_test.shape[0], img_rows, img_cols, 1)
input_shape = (img_rows, img_cols, 1)

inp = Input(shape=(img_rows, img_cols, 1))

# Specify each convolution layer and their kernel siz i.e. n-grams
conv1_1 = Conv2D(filters=conv_filters, kernel_size=(3,200))(inp)
btch1_1 = BatchNormalization()(conv1_1)
drp1_1  = Dropout(0.2)(btch1_1)
actv1_1 = Activation('relu')(drp1_1)
glmp1_1 = MaxPooling2D(pool_size=(98, 1))(actv1_1)

conv1_2 = Conv2D(filters=conv_filters, kernel_size=(4,200))(inp)
btch1_2 = BatchNormalization()(conv1_2)
drp1_2  = Dropout(0.2)(btch1_2)
actv1_2 = Activation('relu')(drp1_2)
glmp1_2 = MaxPooling2D(pool_size=(97, 1))(actv1_2)

conv1_3 = Conv2D(filters=conv_filters, kernel_size=(5,200))(inp)
btch1_3 = BatchNormalization()(conv1_3)
drp1_3  = Dropout(0.2)(btch1_3)
actv1_3 = Activation('relu')(drp1_3)
glmp1_3 = MaxPooling2D(pool_size=(96, 1))(actv1_3)

conv1_4 = Conv2D(filters=conv_filters, kernel_size=(6,200))(inp)
btch1_4 = BatchNormalization()(conv1_4)
drp1_4  = Dropout(0.2)(btch1_4)
actv1_4 = Activation('relu')(drp1_4)
glmp1_4 = MaxPooling2D(pool_size=(95, 1))(actv1_4)

# Gather all convolution layers
cnct = concatenate([glmp1_1, glmp1_2, glmp1_3, glmp1_4], axis=1)
drp = Dropout(0.2)(cnct)

out = Dense(num_classes, activation='sigmoid')(drp)

model = Model(inputs=inp, outputs=out)

model.summary()

model.compile(loss=keras.losses.categorical_crossentropy,
              optimizer=keras.optimizers.Adadelta(),
              metrics=['accuracy'])
fit = model.fit(x_train, y_train,
          batch_size=batch_size,
          epochs=epochs,
          verbose=1,
          validation_data=(x_test, y_test))

#エラーメッセージ

Traceback (most recent call last):
  File "keras_model.py", line 78, in <module>
    validation_data=(x_test, y_test))
  File "C:\Users\brain\Anaconda3\lib\site-packages\keras\engine\training.py", line 1630, in fit
    batch_size=batch_size)
  File "C:\Users\brain\Anaconda3\lib\site-packages\keras\engine\training.py", line 1480, in _standardize_user_data
    exception_prefix='target')
  File "C:\Users\brain\Anaconda3\lib\site-packages\keras\engine\training.py", line 113, in _standardize_input_data
    'with shape ' + str(data_shape))
ValueError: Error when checking target: expected dense_1 to have 4 dimensions, but got array with shape (26456, 2)