INNER CODE UNIT · Python

c6

aiff22/DPED · models.py:30

        c6 = tf.nn.relu(_instance_norm(conv2d(c5, W6) + b6))

        W7 = weight_variable([3, 3, 64, 64], name="W7"); b7 = bias_variable([64], name="b7");
        c7 = tf.nn.relu(_instance_norm(conv2d(c6, W7) + b7)) + c5

        # residual 4

        W8 = weight_variable([3, 3, 64, 64], name="W8"); b8 = bias_variable([64], name="b8");
        c8 = tf.nn.relu(_instance_norm(conv2d(c7, W8) + b8))

        W9 = weight_variable([3, 3, 64, 64], name="W9"); b9 = bias_variable([64], name="b9");
        c9 = tf.nn.relu(_instance_norm(conv2d(c8, W9) + b9)) + c7

        # Convolutional

        W10 = weight_variable([3, 3, 64, 64], name="W10"); b10 = bias_variable([64], name="b10");
        c10 = tf.nn.relu(conv2d(c9, W10) + b10)

View source record →