def test_to_representation_for_tf_variable(self):
value = tf.Variable(10, dtype=tf.int32)
type_signature = computation_types.TensorType(tf.int32)
v = eager_tf_executor.to_representation_for_type(value, {}, type_signature)
self.assertIsInstance(v, tf.Tensor)
self.assertEqual(v, 10)
self.assertEqual(v.dtype, tf.int32)
def test_to_representation_for_type_with_int_on_specific_device(self):
v = eager_tf_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_tf_variable(self):
v = eager_tf_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_with_int(self):
value = 10
type_signature = computation_types.TensorType(tf.int32)
v = eager_tf_executor.to_representation_for_type(value, {}, type_signature)
self.assertIsInstance(v, tf.Tensor)
self.assertEqual(v.numpy(), 10)
self.assertEqual(v.dtype, tf.int32)
def test_eager_value_constructor_with_int_constant(self):
int_tensor_type = computation_types.TensorType(dtype=tf.int32, shape=[])
normalized_value = eager_tf_executor.to_representation_for_type(
10, {}, int_tensor_type)
v = eager_tf_executor.EagerValue(normalized_value, int_tensor_type)
self.assertEqual(str(v.type_signature), 'int32')
self.assertIsInstance(v.internal_representation, tf.Tensor)
self.assertEqual(v.internal_representation, 10)
def test_to_representation_for_type_with_int_on_specific_device(self):
value = 10
type_signature = computation_types.TensorType(tf.int32)
v = eager_tf_executor.to_representation_for_type(
value, {}, type_signature, '/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 _get_to_representation_for_type_succeeds_on_device(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_tf_executor.to_representation_for_type(
comp_proto, {}, comp.type_signature, device='/{}'.format(device))
result = fn(tf.constant(20))
return result
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_tf_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(self):
v = eager_tf_executor.to_representation_for_type(10, {}, tf.int32)
self.assertIsInstance(v, tf.Tensor)
self.assertEqual(v.numpy(), 10)
self.assertEqual(v.dtype, tf.int32)
