I am trying to create a cnn model.My code is as follows:
from keras.layers import Convolution1D, Dense, Dropout, Flatten, MaxPooling1D
from keras.layers import Input, Dense, concatenate
from keras.layers import InputLayer
import keras
inputs = Input(shape=(41,1))
cnn = Sequential()
X=cnn.add(Convolution1D(64, 3, border_mode="same",activation="relu")(inputs))
X=cnn.add(Convolution1D(128, 3, border_mode="same", activation="relu"))
X=cnn.add(MaxPooling1D(pool_length=(2)))
X=cnn.add(Convolution1D(256, 3, border_mode="same", activation="relu"))
X=cnn.add(MaxPooling1D(pool_length=(2)))
X=cnn.add(Flatten())
X=cnn.add(Dense(128, activation="relu"))
X=cnn.add(Dropout(0.5))
X=cnn.add(Dense(2, activation="sigmoid"))
cnn.compile(loss="binary_crossentropy", optimizer="adam",metrics=['accuracy'])
It works fine with following line of code X=cnn.add(Convolution1D(64,3,border_mode="same",activation="relu", input_shape=(41, 1)))
But i need to extract layer outputs and i am doing it by using following lines of code:
from keras.models import Model
intermediate_layer_model = Model(inputs= inputs, outputs=X)
intermediate_output = intermediate_layer_model.predict(Xtrain)
So i need to pass inputs to my cnn layer that i cannot do so if i hard code my inputs_shape. But my above code is not working and giving following error:
Kindly tell me how i can solve this problem.