def test_raises_arg_does_not_match_param(self):
good_param = building_blocks.Reference('x', tf.int32)
good_body = building_blocks.Tuple(
[building_blocks.Reference('x', tf.int32)])
bad_arg_type = building_blocks.Data('y', tf.float32)
with self.assertRaises(TypeError):
compiler_transformations.construct_tensorflow_calling_lambda_on_concrete_arg(
good_param, good_body, bad_arg_type)
def test_constructs_called_tf_block_of_correct_type_signature(self):
param = building_blocks.Reference('x', tf.int32)
body = building_blocks.Tuple([building_blocks.Reference('x', tf.int32)])
arg = building_blocks.Reference('y', tf.int32)
tf_block = compiler_transformations.construct_tensorflow_calling_lambda_on_concrete_arg(
param, body, arg)
self.assertIsInstance(tf_block, building_blocks.Call)
self.assertIsInstance(tf_block.function,
building_blocks.CompiledComputation)
self.assertEqual(tf_block.type_signature, body.type_signature)
def test_generated_tensorflow_executes_correctly_sequence_parameter(self):
param = building_blocks.Reference('x',
computation_types.SequenceType(tf.int32))
body = building_blocks.Tuple([param])
sequence_ref = building_blocks.Reference(
'y', computation_types.SequenceType(tf.int32))
tf_block = compiler_transformations.construct_tensorflow_calling_lambda_on_concrete_arg(
param, body, sequence_ref)
result = test_utils.run_tensorflow(tf_block.function.proto, list(range(5)))
self.assertLen(result, 1)
self.assertAllEqual(result[0], list(range(5)))
def test_generated_tensorflow_executes_correctly_tuple_parameter(self):
param = building_blocks.Reference('x', [tf.int32, tf.float32])
body = building_blocks.Tuple([
building_blocks.Selection(param, index=1),
building_blocks.Selection(param, index=0)
])
int_constant = building_block_factory.create_tensorflow_constant(
[tf.int32, tf.float32], 1)
tf_block = compiler_transformations.construct_tensorflow_calling_lambda_on_concrete_arg(
param, body, int_constant)
result = test_utils.run_tensorflow(tf_block.function.proto)
self.assertLen(result, 2)
self.assertEqual(result[0], 1.)
self.assertEqual(result[1], 1)
def test_generated_tensorflow_executes_correctly_int_parameter(self):
param = building_blocks.Reference('x', tf.int32)
body = building_blocks.Tuple([
building_blocks.Reference('x', tf.int32),
building_blocks.Reference('x', tf.int32)
])
int_constant = building_block_factory.create_tensorflow_constant(
tf.int32, 0)
tf_block = transformations.construct_tensorflow_calling_lambda_on_concrete_arg(
param, body, int_constant)
result = test_utils.run_tensorflow(tf_block.function.proto)
self.assertLen(result, 2)
self.assertEqual(result[0], 0)
self.assertEqual(result[1], 0)
def test_raises_wrong_arguments(self):
good_param = building_blocks.Reference('x', tf.int32)
good_body = building_blocks.Tuple(
[building_blocks.Reference('x', tf.int32)])
good_arg = building_blocks.Data('y', tf.int32)
with self.assertRaises(TypeError):
compiler_transformations.construct_tensorflow_calling_lambda_on_concrete_arg(
good_body, good_body, good_arg)
with self.assertRaises(TypeError):
compiler_transformations.construct_tensorflow_calling_lambda_on_concrete_arg(
good_param, [good_param], good_arg)
with self.assertRaises(TypeError):
compiler_transformations.construct_tensorflow_calling_lambda_on_concrete_arg(
good_param, good_body, [good_arg])
