def testBadTBX(self):
config = {"b": (1, 2, 3)}
t = Trial(evaluated_params=config,
trial_id="tbx",
logdir=self.test_dir)
logger = TBXLoggerCallback()
logger.on_trial_result(0, [], t, result(0, 4))
logger.on_trial_result(1, [], t, result(1, 5))
logger.on_trial_result(
2, [], t, result(2, 6, score=[1, 2, 3], hello={"world": 1}))
with self.assertLogs("ray.tune.logger", level="INFO") as cm:
logger.on_trial_complete(3, [], t)
assert "INFO" in cm.output[0]
config = {"None": None}
t = Trial(evaluated_params=config,
trial_id="tbx",
logdir=self.test_dir)
logger = TBXLoggerCallback()
logger.on_trial_result(0, [], t, result(0, 4))
logger.on_trial_result(1, [], t, result(1, 5))
logger.on_trial_result(
2, [], t, result(2, 6, score=[1, 2, 3], hello={"world": 1}))
with self.assertLogs("ray.tune.logger", level="INFO") as cm:
logger.on_trial_complete(3, [], t)
assert "INFO" in cm.output[0]
def testTBX(self):
config = {
"a": 2,
"b": [1, 2],
"c": {
"c": {
"D": 123
}
},
"int32": np.int32(1),
"int64": np.int64(2),
"bool8": np.bool8(True),
"float32": np.float32(3),
"float64": np.float64(4),
"bad": np.float128(4),
}
t = Trial(
evaluated_params=config, trial_id="tbx", logdir=self.test_dir)
logger = TBXLoggerCallback()
logger.on_trial_result(0, [], t, result(0, 4))
logger.on_trial_result(1, [], t, result(1, 5))
logger.on_trial_result(
2, [], t, result(2, 6, score=[1, 2, 3], hello={"world": 1}))
logger.on_trial_complete(3, [], t)
self._validate_tbx_result(
params=(b"float32", b"float64", b"int32", b"int64", b"bool8"),
excluded_params=(b"bad", ))
def testTBX(self):
config = {
"a": 2,
"b": [1, 2],
"c": {
"c": {
"D": 123
}
},
"d": np.int64(1),
"e": np.bool8(True)
}
t = Trial(evaluated_params=config,
trial_id="tbx",
logdir=self.test_dir)
logger = TBXLoggerCallback()
logger.on_trial_result(0, [], t, result(0, 4))
logger.on_trial_result(1, [], t, result(1, 5))
logger.on_trial_result(
2, [], t, result(2, 6, score=[1, 2, 3], hello={"world": 1}))
logger.on_trial_complete(3, [], t)
self._validate_tbx_result()
