INNER CODE UNIT · Python

adversarial

aiff22/DPED · models.py:59

def adversarial(image_):

    with tf.compat.v1.variable_scope("discriminator"):

        conv1 = _conv_layer(image_, 48, 11, 4, batch_nn = False)
        conv2 = _conv_layer(conv1, 128, 5, 2)
        conv3 = _conv_layer(conv2, 192, 3, 1)
        conv4 = _conv_layer(conv3, 192, 3, 1)
        conv5 = _conv_layer(conv4, 128, 3, 2)
        
        flat_size = 128 * 7 * 7
        conv5_flat = tf.reshape(conv5, [-1, flat_size])

        W_fc = tf.Variable(tf.compat.v1.truncated_normal([flat_size, 1024], stddev=0.01))
        bias_fc = tf.Variable(tf.constant(0.01, shape=[1024]))

        fc = leaky_relu(tf.matmul(conv5_flat, W_fc) + bias_fc)

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