def __init__()

in supervised_reptile/models.py [0:0]

• 15 lines of code
• 2 McCabe index (conditional complexity)

    def __init__(self, num_classes, optimizer=DEFAULT_OPTIMIZER, **optim_kwargs):
        self.input_ph = tf.placeholder(tf.float32, shape=(None, 84, 84, 3))
        out = self.input_ph
        for _ in range(4):
            out = tf.layers.conv2d(out, 32, 3, padding='same')
            out = tf.layers.batch_normalization(out, training=True)
            out = tf.layers.max_pooling2d(out, 2, 2, padding='same')
            out = tf.nn.relu(out)
        out = tf.reshape(out, (-1, int(np.prod(out.get_shape()[1:]))))
        self.logits = tf.layers.dense(out, num_classes)
        self.label_ph = tf.placeholder(tf.int32, shape=(None,))
        self.loss = tf.nn.sparse_softmax_cross_entropy_with_logits(labels=self.label_ph,
                                                                   logits=self.logits)
        self.predictions = tf.argmax(self.logits, axis=-1)
        self.minimize_op = optimizer(**optim_kwargs).minimize(self.loss)