def test_value_search_checks_bad_solutions(self):
inputs = {'tensor': [10, 20, 30], 'index': -2}
output = 20
constants = [1, 20]
results = value_search.run_value_search_from_example(
inputs=inputs,
output=output,
constants=constants,
settings=settings_module.from_dict(
{'require_all_inputs_used': True}))
self.assertLen(results.solutions, 1)
self.assertEqual(results.solutions[0].expression, 'tensor[index]')
results = value_search.run_value_search_from_example(
inputs=inputs,
output=output,
constants=constants,
settings=settings_module.from_dict({
'require_all_inputs_used': False,
'require_one_input_used': True
}))
self.assertLen(results.solutions, 1)
self.assertEqual(results.solutions[0].expression, 'tensor[1]')
results = value_search.run_value_search_from_example(
inputs=inputs,
output=output,
constants=constants,
settings=settings_module.from_dict({
'require_all_inputs_used': False,
'require_one_input_used': False
}))
self.assertLen(results.solutions, 1)
self.assertEqual(results.solutions[0].expression, 'tf.constant(20)')
def run_value_search_from_colab(
inputs: Dict[Text, Any],
output: Any,
constants: Optional[List[Any]] = None,
description: Optional[Text] = None,
settings: Optional[settings_module.Settings] = None
) -> value_search.ValueSearchResults:
"""Value search endpoint for the Colab interface.
Args:
inputs: A dict mapping input variable names to input tensors.
output: The corresponding desired output.
constants: An optional list of scalar constants.
description: An optional natural language description of the task.
settings: A Settings object containing settings for the search.
Returns:
A ValueSearchResults namedtuple.
"""
if not WARMED_UP:
warm_up()
return value_search.run_value_search_from_example(
inputs=inputs,
output=output,
settings=settings if settings is not None else DEFAULT_SETTINGS,
constants=constants,
description=description,
source='From TF-Coder Colab',
description_handler=DESCRIPTION_HANDLER,
tensor_model=TENSOR_MODEL,
tensor_config=TENSOR_CONFIG)
def test_run_value_search_from_example_with_constants(self):
results = value_search.run_value_search_from_example(
inputs=[
[10, 20, 30],
],
output=[54, 64, 74],
settings=self.settings,
constants=[44])
self.assertLen(results.solutions, 1)
self.assertEqual(results.solutions[0].expression,
'tf.add(in1, tf.constant(44))')
def test_run_value_search_from_example(self):
results = value_search.run_value_search_from_example(
inputs=[[1, 2, 3], [10, 20, 30]],
output=[11, 22, 33],
settings=settings_module.from_dict({
'timeout': 5,
'max_solutions': 2
}))
self.assertLen(results.solutions, 2)
self.assertEqual(results.solutions[0].expression, 'tf.add(in1, in2)')
self.assertEqual(results.solutions[1].expression, 'tf.add(in2, in1)')
# Linter suggests self.assertLess() but it's wrong.
self.assertTrue(0.0 < results.total_time < 5.0) # pylint: disable=g-generic-assert
