def preprocess(x):
"""Cast to float, normalize, and concatenate images along last axis."""
x = nest.map_structure(
lambda image: tf.image.convert_image_dtype(image, tf.float32), x)
x = nest.flatten(x)
x = tf.concat(x, axis=-1)
x = (tf.image.convert_image_dtype(x, tf.float32) - 0.5) * 2.0
return x
def preprocess(x):
"""Cast to float, normalize, and concatenate images along last axis."""
import tensorflow as tf
x = nest.map_structure(
lambda image: tf.image.convert_image_dtype(image, tf.float32), x)
x = nest.flatten(x)
x = tf.concat(x, axis=-1)
# x = (tf.image.convert_image_dtype(x, tf.float32) - 0.5) * 2.0
# TODO: Why is the image being converted to float32 twice? Once in the
# nest and once down here?
x = (high - low) * tf.image.convert_image_dtype(x, tf.float32) + low
return x
def cast_and_concat(x):
x = nest.map_structure(lambda element: tf.cast(element, tf.float32), x)
x = nest.flatten(x)
x = tf.concat(x, axis=-1)
return x
def cast_and_concat(x):
x = nest.map_structure(training_utils.cast_if_floating_dtype, x)
x = nest.flatten(x)
x = tf.concat(x, axis=-1)
return x