Python Deep Learning Projects

CNN encoder

Now let's define the CNN encoder that will be the single, fully connected layer followed by the ReLU activation:

class CNN_Encoder(tf.keras.Model):    # Since we have already extracted the features and dumped it using pickle    # This encoder passes those features through a Fully connected layer    def __init__(self, embedding_dim):        super(CNN_Encoder, self).__init__()        # shape after fc == (batch_size, 64, embedding_dim)        self.fc = tf.keras.layers.Dense(embedding_dim)            def call(self, x):        x = self.fc(x)        x = tf.nn.relu(x)        return x