def test_to_representation_for_tf_variable(self):
v = eager_executor.to_representation_for_type(
tf.Variable(10, dtype=tf.int32),
type_spec=computation_types.TensorType(tf.int32))
self.assertIsInstance(v, tf.Tensor)
self.assertEqual(v.numpy(), 10)
self.assertEqual(v.dtype, tf.int32)
def test_to_representation_for_type_succeeds_on_all_devices(self, device):
@computations.tf_computation(tf.int32)
def comp(x):
return tf.add(x, 1)
comp_proto = computation_impl.ComputationImpl.get_proto(comp)
fn = eager_executor.to_representation_for_type(
comp_proto, comp.type_signature, device='/{}'.format(device))
result = fn(tf.constant(20))
self.assertTrue(result.device.endswith(device))
def test_to_representation_for_type_with_int_on_specific_device(self):
v = eager_executor.to_representation_for_type(10, tf.int32, '/CPU:0')
self.assertIsInstance(v, tf.Tensor)
self.assertEqual(v.numpy(), 10)
self.assertEqual(v.dtype, tf.int32)
self.assertTrue(v.device.endswith('CPU:0'))
def test_to_representation_for_type_with_int(self):
v = eager_executor.to_representation_for_type(10, tf.int32)
self.assertIsInstance(v, tf.Tensor)
self.assertEqual(v.numpy(), 10)
self.assertEqual(v.dtype, tf.int32)
