def test_no_floats(self):
want = "text ... text"
got = "text 1.0 1.2 1.9 text"
output_checker = keras_doctest_lib.KerasDoctestOutputChecker()
self.assertTrue(
output_checker.check_output(want=want,
got=got,
optionflags=doctest.ELLIPSIS))
def test_warning_messages(self, want, got):
output_checker = keras_doctest_lib.KerasDoctestOutputChecker()
output_checker.check_output(want=want,
got=got,
optionflags=doctest.ELLIPSIS)
example = doctest.Example("None", want=want)
result = output_checker.output_difference(example=example,
got=got,
optionflags=doctest.ELLIPSIS)
self.assertIn("doesn't work if *some* of the", result)
def test_fail_tolerences(self, text, expected_floats):
extract_floats = keras_doctest_lib._FloatExtractor()
output_checker = keras_doctest_lib.KerasDoctestOutputChecker()
(_, extracted_floats) = extract_floats(text)
# These floats should not match according to allclose
try:
self.assertFalse(
output_checker._allclose(expected_floats, extracted_floats))
except AssertionError as e:
msg = ("\n\nThese matched! They should not have.\n"
"\n\n Expected: {}\n found: {}".format(
expected_floats, extracted_floats))
e.args = (e.args[0] + msg, )
raise e
def test_extract_floats(self, text, expected_floats):
extract_floats = keras_doctest_lib._FloatExtractor()
output_checker = keras_doctest_lib.KerasDoctestOutputChecker()
(text_parts, extracted_floats) = extract_floats(text)
text_with_wildcards = "...".join(text_parts)
# Check that the lengths match before doing anything else.
try:
self.assertLen(extracted_floats, len(expected_floats))
except AssertionError as e:
msg = "\n\n expected: {}\n found: {}".format(
expected_floats, extracted_floats)
e.args = (e.args[0] + msg, )
raise e
# The floats should match according to allclose
try:
self.assertTrue(
output_checker._allclose(expected_floats, extracted_floats))
except AssertionError as e:
msg = "\n\nexpected: {}\nfound: {}".format(
expected_floats, extracted_floats)
e.args = (e.args[0] + msg, )
raise e
# The wildcard text should match the input text, according to the
# OutputChecker base class.
try:
self.assertTrue(doctest.OutputChecker().check_output(
want=text_with_wildcards,
got=text,
optionflags=doctest.ELLIPSIS,
))
except AssertionError as e:
msg = "\n\n expected: {}\n found: {}".format(
text_with_wildcards, text)
e.args = (e.args[0] + msg, )
raise e
def load_tests(unused_loader, tests, unused_ignore):
"""Loads all the tests in the docstrings and runs them."""
tf_modules = find_modules()
if FLAGS.module:
tf_modules = filter_on_submodules(tf_modules, FLAGS.module)
if FLAGS.list:
print("**************************************************")
for mod in tf_modules:
print(mod.__name__)
print("**************************************************")
return tests
if FLAGS.file:
tf_modules = get_module_and_inject_docstring(FLAGS.file)
for module in tf_modules:
testcase = TfTestCase()
tests.addTests(
doctest.DocTestSuite(
module,
test_finder=doctest.DocTestFinder(exclude_empty=False),
extraglobs={
"tf": tf,
"np": np,
"os": os
},
setUp=testcase.set_up,
tearDown=testcase.tear_down,
checker=keras_doctest_lib.KerasDoctestOutputChecker(),
optionflags=(doctest.ELLIPSIS
| doctest.NORMALIZE_WHITESPACE
| doctest.IGNORE_EXCEPTION_DETAIL
| doctest.DONT_ACCEPT_BLANKLINE),
))
return tests
def test_tf_tensor_numpy_output(self, string, expected_output):
output_checker = keras_doctest_lib.KerasDoctestOutputChecker()
output = output_checker._tf_tensor_numpy_output(string)
self.assertEqual(expected_output, output)