def test_out_of_order_execution2(self):
with self.test_session() as session:
batcher = dynamic_batching._Batcher(minimum_batch_size=1,
maximum_batch_size=1,
timeout_ms=None)
tp = pool.ThreadPool(10)
r0 = tp.apply_async(session.run, batcher.compute([[1]],
[tf.int32]))
(input0, ), computation_id0 = session.run(
batcher.get_inputs([tf.int32]))
r1 = tp.apply_async(session.run, batcher.compute([[2]],
[tf.int32]))
(input1, ), computation_id1 = session.run(
batcher.get_inputs([tf.int32]))
self.assertAllEqual([1], input0)
self.assertAllEqual([2], input1)
# These two runs are switched from testOutOfOrderExecution1.
session.run(batcher.set_outputs([input1 + 42], computation_id1))
session.run(batcher.set_outputs([input0 + 42], computation_id0))
self.assertAllEqual([43], r0.get())
self.assertAllEqual([44], r1.get())
def test_op_shape(self):
with self.test_session():
batcher = dynamic_batching._Batcher(minimum_batch_size=1,
maximum_batch_size=1,
timeout_ms=None)
_, computation_id = batcher.get_inputs([tf.int32])
self.assertEqual([], computation_id.shape)
def test_op_shape(self):
with self.test_session():
batcher = dynamic_batching._Batcher(minimum_batch_size=1,
maximum_batch_size=1,
timeout_ms=None)
_, computation_id = batcher.get_inputs([tf.int32])
self.assertEqual([], computation_id.shape)
def test_invalid_computation_id(self):
with self.test_session() as session:
batcher = dynamic_batching._Batcher(minimum_batch_size=1,
maximum_batch_size=1,
timeout_ms=None)
tp = pool.ThreadPool(10)
tp.apply_async(session.run, batcher.compute([[1]], [tf.int32]))
(input0, ), _ = session.run(batcher.get_inputs([tf.int32]))
self.assertAllEqual([1], input0)
with self.assertRaisesRegexp(tf.errors.InvalidArgumentError,
'Invalid computation id'):
session.run(batcher.set_outputs([input0], 42))
def test_invalid_computation_id(self):
with self.test_session() as session:
batcher = dynamic_batching._Batcher(minimum_batch_size=1,
maximum_batch_size=1,
timeout_ms=None)
tp = pool.ThreadPool(10)
tp.apply_async(session.run, batcher.compute([[1]], [tf.int32]))
(input0,), _ = session.run(batcher.get_inputs([tf.int32]))
self.assertAllEqual([1], input0)
with self.assertRaisesRegexp(tf.errors.InvalidArgumentError,
'Invalid computation id'):
session.run(batcher.set_outputs([input0], 42))
def test_out_of_order_execution1(self):
with self.test_session() as session:
batcher = dynamic_batching._Batcher(minimum_batch_size=1,
maximum_batch_size=1,
timeout_ms=None)
tp = pool.ThreadPool(10)
r0 = tp.apply_async(session.run, batcher.compute([[1]], [tf.int32]))
(input0,), computation_id0 = session.run(batcher.get_inputs([tf.int32]))
r1 = tp.apply_async(session.run, batcher.compute([[2]], [tf.int32]))
(input1,), computation_id1 = session.run(batcher.get_inputs([tf.int32]))
self.assertAllEqual([1], input0)
self.assertAllEqual([2], input1)
session.run(batcher.set_outputs([input0 + 42], computation_id0))
session.run(batcher.set_outputs([input1 + 42], computation_id1))
self.assertAllEqual([43], r0.get())
self.assertAllEqual([44], r1.get())