def on_epoch_start(self, state):
optimizer = state.get_key(key="optimizer",
inner_key=self.optimizer_key)
self._optimizer_wd = [
group.get("weight_decay", 0.0) for group in optimizer.param_groups
]
for i in range(len(optimizer.param_groups)):
safitty.set(optimizer.param_groups, i, "weight_decay", value=0.0)
def on_epoch_end(self, state):
if self.decouple_weight_decay:
optimizer = state.get_key(key="optimizer",
inner_key=self.optimizer_key)
for i, wd in enumerate(self._optimizer_wd):
safitty.set(optimizer.param_groups,
i,
"weight_decay",
value=wd)
def test_safe_set(config):
config = copy.deepcopy(config)
assert safitty.get(config, "numbers", transform=len) == 5
safitty.set(config, "numbers", 8, value=42)
assert safitty.get(config, "numbers", transform=len) == 9
assert safitty.get(config, "numbers", 8) == 42
assert safitty.set(config, "numbers2", "inner", value=[])
assert safitty.get(config, "numbers2", "inner", transform=len) == 0
assert safitty.set(config, "numbers", value=[])
assert safitty.get(config, "numbers", transform=len) == 0
def on_epoch_start(self, state):
"""On epoch start event"""
optimizer = state.get_key(
key="optimizer", inner_key=self.optimizer_key
)
if self.decouple_weight_decay:
self._optimizer_wd = [
group.get("weight_decay", 0.0)
for group in optimizer.param_groups
]
for i in range(len(optimizer.param_groups)):
safitty.set(
optimizer.param_groups, i, "weight_decay", value=0.0)
else:
self._optimizer_wd = [0.0] * len(optimizer.param_groups)
def set_optimizer_momentum(optimizer: Optimizer, value: float, index: int = 0):
"""
Set momentum of ``index``'th param group of optimizer to ``value``
Args:
optimizer: PyTorch optimizer
value (float): new value of momentum
index (int, optional): integer index of optimizer's param groups,
default is 0
"""
betas = safitty.get(optimizer.param_groups, index, "betas")
momentum = safitty.get(optimizer.param_groups, index, "momentum")
if betas is not None:
_, beta = betas
safitty.set(optimizer.param_groups,
index,
"betas",
value=(value, beta))
elif momentum is not None:
safitty.set(optimizer.param_groups, index, "momentum", value=value)
def test_safe_set_2(transforms):
transforms = copy.deepcopy(transforms)
safitty.set(transforms, 2, "name", value="BatchNorm2d")
assert safitty.get(transforms, 2, "name") == "BatchNorm2d"
safitty.set(transforms, 1, "params", value="add", strategy="on_none")
params1 = safitty.get(transforms, 1, "params")
assert params1 is not None
assert params1 != "add"
safitty.set(transforms, 0, "params", value="subtract", strategy="on_none")
params0 = safitty.get(transforms, 0, "params")
assert params0 is not None
assert params0 == "subtract"
def test_safe_set_strategies(config):
config = copy.deepcopy(config)
safitty.set(config,
"words",
"quadre",
value="four",
strategy="existing_key")
assert safitty.get(config, "words", "quadre") is None
safitty.set(config, "words", "one", value="four", strategy="existing_key")
assert safitty.get(config, "words", "one") is not None
assert safitty.get(config, "words", "one") == "four"
safitty.set(config, "words", "one", value="five", strategy="missing_key")
assert safitty.get(config, "words", "one") != "five"
safitty.set(config, "words", "five", value="five", strategy="missing_key")
assert safitty.get(config, "words", "five") == "five"
# cannot reset a reference
assert safitty.set(config, value="hi") == "hi"
assert config != "hi"
safitty.set(config, "numbers", 40, "hi", "", value="привет")
assert safitty.get(config, "numbers", 40, "hi", "") is not None
assert safitty.get(config, "numbers", 40, "hi", "") == "привет"
