def _check_target_program(self, benchmark):
"""Checks that a benchmark's target program is consistent with its examples.
Args:
benchmark: A Benchmark to verify.
"""
self.assertIsNotNone(benchmark.target_program)
for example in benchmark.examples:
# Turn inputs into constant tensors and assign them to variables using a
# new global namespace.
global_namespace = {'tf': tf}
input_names_to_objects = value_search._input_names_to_objects(
example.inputs)
for input_name, input_object in input_names_to_objects.items():
input_value = value_module.InputValue(input_object,
name='dummy_name')
global_namespace[input_name] = input_value.value
# Evaluate the target program, which uses the canonical variables.
target_program_output = eval(benchmark.target_program,
global_namespace) # pylint: disable=eval-used
# Check that the two outputs have equal string representation.
expected_output = tf_coder_utils.convert_to_tensor(example.output)
self.assertEqual(
tf_coder_utils.object_to_string(expected_output),
tf_coder_utils.object_to_string(target_program_output))
def test_object_to_string_sequence(self):
# `Named` is a class and should be capitalized. It is only used in this test
# so it is declared here, not in the global scope.
Named = collections.namedtuple('Named', ('a', 'b')) # pylint: disable=invalid-name
sequence = [123, tf.constant([1, 2]), (), Named(a=False, b=1.5)]
self.assertEqual(tf_coder_utils.object_to_string(sequence),
'seq[123, tf.int32:[1, 2], seq[], seq[False, 1.5]]')
def __repr__(self):
"""Returns a string representation of the value.
Values are considered equal if and only if their string representations (as
computed by this function) are equal.
"""
if self._repr_cache is None:
self._repr_cache = tf_coder_utils.object_to_string(self.value)
return self._repr_cache
def test_object_to_string_raises_if_unsupported(self):
with self.assertRaises(ValueError):
tf_coder_utils.object_to_string({'key': 'value'})
def test_object_to_string_dtype(self):
self.assertEqual(tf_coder_utils.object_to_string(tf.int32), 'tf.int32')
def test_object_to_string_primitive(self, primitive, expected_result):
self.assertEqual(tf_coder_utils.object_to_string(primitive),
expected_result)
def test_object_to_string_tensor(self):
tensor = tf.constant([[1, 2], [3, 4]])
self.assertEqual(tf_coder_utils.object_to_string(tensor),
'tf.int32:[[1, 2], [3, 4]]')