def test_runs(self):
problem_id = colab_logging.get_uuid()
colab_logging.log_problem(self.inputs,
self.output,
self.constants,
self.description,
self.settings,
include_in_dataset=True,
problem_id=problem_id)
results = colab_interface.run_value_search_from_colab(
self.inputs, self.output, self.constants, self.description,
self.settings)
colab_logging.log_result(results,
include_in_dataset=True,
problem_id=problem_id)
colab_logging._IPYTHON_MOCK.display.HTML.assert_called_once()
colab_logging._IPYTHON_MOCK.display.Javascript.assert_called()
js_strings = [
call_args[0] for call_args in (
colab_logging._IPYTHON_MOCK.display.Javascript.call_args_list)
]
self.assertTrue(all(js_strings)) # None of them are empty or None.
def test_too_large_logging_dict(self):
# Pretend that there are very few dimensions, so that the serialized logging
# dict is too large to send to GA.
old_num_dimensions = colab_logging.NUM_DIMENSIONS
colab_logging.NUM_DIMENSIONS = 5
problem_id = colab_logging.get_uuid()
colab_logging.log_problem(self.inputs,
self.output,
self.constants,
self.description,
self.settings,
include_in_dataset=True,
problem_id=problem_id)
results = colab_interface.run_value_search_from_colab(
self.inputs, self.output, self.constants, self.description,
self.settings)
colab_logging.log_result(results,
include_in_dataset=True,
problem_id=problem_id)
colab_logging._IPYTHON_MOCK.display.HTML.assert_called_once()
colab_logging._IPYTHON_MOCK.display.Javascript.assert_not_called()
colab_logging.NUM_DIMENSIONS = old_num_dimensions
def test_get_uuid_returns_different_results(self):
# This test will fail with probability 2^-64.
self.assertNotEqual(colab_logging.get_uuid(), colab_logging.get_uuid())