Model definition for the CNN Visualization Demo

model.py

sequence_input = Input(shape=(maxlen_text,))

x = Embedding(name='embedding_layer', 
              input_dim=max_words_to_keep, 
              output_dim=token_vec_size, 
              input_length=maxlen_text)(sequence_input)
x = Dropout(.20)(x)

x = Conv1D(64, 5, activation='relu', name='1-conv1d', padding='same')(x)
x = MaxPooling1D(pool_size=4)(x)
x = Dropout(.20)(x)

x = Conv1D(64, 5, activation='relu', name='2-conv1d', padding='same')(x)
x = MaxPooling1D(pool_size=2)(x)
x = Dropout(.20)(x)

x = Flatten()(x)

output = Dense(units=output_dim,activation='softmax')(x)