3filters.py

3filters.py

from keras.layers import Merge
import keras.backend.tensorflow_backend as K
with K.tf.device('/gpu:0'):
    filter_sizes = [3,4,5]
    drop_out_rate = 0.5
    hidden_dims = 50
    
    model.add(Embedding(vocab_size, 100, input_length=max_length))
    for idx, sz in enumerate(filter_sizes):
        model.add(Conv1D(filters=100, kernel_size=sz, activation='relu', strides=1, padding='valid'))
        model.add((MaxPooling1D(pool_size=2)))
        
    
    model.add(Dropout(drop_out_rate))          
    model.add(Flatten())
    model.add(Dense(hidden_dims, activation="relu"))
    model.add(Dense(10, activation='softmax'))
    print(model.summary())