06e9e1f8737c47869ae092c0e769f1e754d4de61,cleverhans/picklable_model.py,PerImageStandardize,fprop,#PerImageStandardize#Any#,562

Before Change

  def fprop(self, x, **kwargs):
    // TODO: before adding dataset augmentation, we didn"t have to do this.
    // Why?
    with tf.device("/CPU:0"):
      out = tf.map_fn(
          lambda ex: tf.image.per_image_standardization(ex), x)
    return out


class Dropout(Layer):

After Change

  def fprop(self, x, **kwargs):
    // TODO: before adding dataset augmentation, we didn"t have to do this.
    // Why?
    axis = [1, 2, 3]
    mean = tf.reduce_mean(x, axis=axis, keepdims=True)
    variance = tf.reduce_mean(
        tf.square(x), axis=axis, keepdims=True) - tf.square(mean)
    variance = tf.nn.relu(variance)
    stddev = tf.sqrt(variance)

    num_pixels = tf.reduce_prod(tf.shape(x)[1:])

    min_stddev = tf.rsqrt(tf.to_float(num_pixels))

Instances