def testRefSelect(self):
index = tf.placeholder(tf.int32)
# All inputs unknown.
p1 = tf.placeholder(tf.float32_ref)
p2 = tf.placeholder(tf.float32_ref)
p3 = tf.placeholder(tf.float32_ref)
s = control_flow_ops.ref_select(index, [p1, p2, p3])
self.assertIs(None, s.get_shape().ndims)
# All inputs known but different.
p1 = tf.placeholder(tf.float32_ref, shape=[1, 2])
p2 = tf.placeholder(tf.float32_ref, shape=[2, 1])
s = control_flow_ops.ref_select(index, [p1, p2])
self.assertIs(None, s.get_shape().ndims)
# All inputs known but same.
p1 = tf.placeholder(tf.float32_ref, shape=[1, 2])
p2 = tf.placeholder(tf.float32_ref, shape=[1, 2])
s = control_flow_ops.ref_select(index, [p1, p2])
self.assertEqual([1, 2], s.get_shape())
# Possibly the same but not guaranteed.
p1 = tf.placeholder(tf.float32_ref, shape=[1, 2])
p2 = tf.placeholder(tf.float32_ref)
p2.set_shape([None, 2])
s = control_flow_ops.ref_select(index, [p1, p2])
self.assertEqual(None, s.get_shape())
def testRefSelect(self):
index = tf.placeholder(tf.int32)
# All inputs unknown.
p1 = tf.placeholder(tf.float32_ref)
p2 = tf.placeholder(tf.float32_ref)
p3 = tf.placeholder(tf.float32_ref)
s = control_flow_ops.ref_select(index, [p1, p2, p3])
self.assertIs(None, s.get_shape().ndims)
# All inputs known but different.
p1 = tf.placeholder(tf.float32_ref, shape=[1, 2])
p2 = tf.placeholder(tf.float32_ref, shape=[2, 1])
s = control_flow_ops.ref_select(index, [p1, p2])
self.assertIs(None, s.get_shape().ndims)
# All inputs known but same.
p1 = tf.placeholder(tf.float32_ref, shape=[1, 2])
p2 = tf.placeholder(tf.float32_ref, shape=[1, 2])
s = control_flow_ops.ref_select(index, [p1, p2])
self.assertEqual([1, 2], s.get_shape())
# Possibly the same but not guaranteed.
p1 = tf.placeholder(tf.float32_ref, shape=[1, 2])
p2 = tf.placeholder(tf.float32_ref)
p2.set_shape([None, 2])
s = control_flow_ops.ref_select(index, [p1, p2])
self.assertEqual(None, s.get_shape())
def from_list(index, queues):
"""Create a queue using the queue reference from `queues[index]`.
Args:
index: An integer scalar tensor that determines the input that gets
selected.
queues: A list of `QueueBase` objects.
Returns:
A `QueueBase` object.
Raises:
TypeError: When `queues` is not a list of `QueueBase` objects,
or when the data types of `queues` are not all the same.
"""
if ((not queues) or (not isinstance(queues, list))
or (not all(isinstance(x, QueueBase) for x in queues))):
raise TypeError("A list of queues expected")
dtypes = queues[0].dtypes
if not all([dtypes == q.dtypes for q in queues[1:]]):
raise TypeError("Queues do not have matching component dtypes.")
queue_refs = [x.queue_ref for x in queues]
selected_queue = control_flow_ops.ref_select(index, queue_refs)
# TODO(josh11b): Unify the shapes of the queues too?
return QueueBase(dtypes=dtypes, shapes=None, queue_ref=selected_queue)
def from_list(index, queues):
"""Create a queue using the queue reference from `queues[index]`.
Args:
index: An integer scalar tensor that determines the input that gets
selected.
queues: A list of `QueueBase` objects.
Returns:
A `QueueBase` object.
Raises:
TypeError: When `queues` is not a list of `QueueBase` objects,
or when the data types of `queues` are not all the same.
"""
if ((not queues) or
(not isinstance(queues, list)) or
(not all(isinstance(x, QueueBase) for x in queues))):
raise TypeError("A list of queues expected")
dtypes = queues[0].dtypes
if not all([dtypes == q.dtypes for q in queues[1:]]):
raise TypeError("Queues do not have matching component dtypes.")
queue_refs = [x.queue_ref for x in queues]
selected_queue = control_flow_ops.ref_select(index, queue_refs)
# TODO(josh11b): Unify the shapes of the queues too?
return QueueBase(dtypes=dtypes, shapes=None, queue_ref=selected_queue)
