def context(self):
# We can't create the context in __init__, since it would then wind up in
# the wrong TensorFlow graph.
context = subsettable_context.split_rate_context(
penalty_predictions=tf.constant(self._penalty_predictions,
dtype=tf.float32),
constraint_predictions=tf.constant(self._constraint_predictions,
dtype=tf.float32),
penalty_labels=tf.constant(self._penalty_labels, dtype=tf.float32),
constraint_labels=tf.constant(self._constraint_labels,
dtype=tf.float32),
penalty_weights=tf.constant(self._penalty_weights,
dtype=tf.float32),
constraint_weights=tf.constant(self._constraint_weights,
dtype=tf.float32))
return context.subset(self._penalty_predicate,
self._constraint_predicate)
def _split_context(self):
"""Creates a new split and subsetted context."""
# We can't create the context in __init__, since it would then wind up in
# the wrong TensorFlow graph.
penalty_predictions = tf.constant(
self._penalty_predictions, dtype=tf.float32)
constraint_predictions = tf.constant(
self._constraint_predictions, dtype=tf.float32)
penalty_labels = tf.constant(self._penalty_labels, dtype=tf.float32)
constraint_labels = tf.constant(self._constraint_labels, dtype=tf.float32)
penalty_weights = tf.constant(self._penalty_weights, dtype=tf.float32)
constraint_weights = tf.constant(self._constraint_weights, dtype=tf.float32)
context = subsettable_context.split_rate_context(
penalty_predictions=lambda: penalty_predictions,
constraint_predictions=lambda: constraint_predictions,
penalty_labels=lambda: penalty_labels,
constraint_labels=lambda: constraint_labels,
penalty_weights=lambda: penalty_weights,
constraint_weights=lambda: constraint_weights)
return context.subset(self._penalty_predicate, self._constraint_predicate)