Bases: BaseConditionHook
Returns True if the discriminator's
accuracy is higher than some threshold.
Source code in pytorch_adapt\hooks\conditions.py
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44 | class StrongDHook(BaseConditionHook):
"""
Returns ```True``` if the discriminator's
accuracy is higher than some threshold.
"""
def __init__(self, threshold: float = 0.6, **kwargs):
"""
Arguments:
threshold: The discriminator's accuracy must be higher
than this threshold for the hook to return ```True```.
"""
super().__init__(**kwargs)
self.accuracy_fn = SufficientAccuracy(
threshold=threshold, to_probs_func=torch.nn.Sigmoid()
)
self.hook = FeaturesChainHook(
FeaturesHook(detach=True), DLogitsHook(detach=True)
)
def call(self, inputs, losses):
""""""
with torch.no_grad():
outputs = self.hook(inputs, losses)[0]
[d_src_logits, d_target_logits] = c_f.extract(
[outputs, inputs],
c_f.filter(
self.hook.out_keys, "_dlogits_detached$", ["^src", "^target"]
),
)
[src_domain, target_domain] = c_f.extract(
inputs, ["src_domain", "target_domain"]
)
dlogits = torch.cat([d_src_logits, d_target_logits], dim=0)
domain_labels = torch.cat([src_domain, target_domain], dim=0)
return self.accuracy_fn(dlogits, domain_labels)
|
__init__(threshold=0.6, **kwargs)
Parameters:
| Name |
Type |
Description |
Default |
threshold |
float
|
The discriminator's accuracy must be higher
than this threshold for the hook to return True. |
0.6
|
Source code in pytorch_adapt\hooks\conditions.py
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27 | def __init__(self, threshold: float = 0.6, **kwargs):
"""
Arguments:
threshold: The discriminator's accuracy must be higher
than this threshold for the hook to return ```True```.
"""
super().__init__(**kwargs)
self.accuracy_fn = SufficientAccuracy(
threshold=threshold, to_probs_func=torch.nn.Sigmoid()
)
self.hook = FeaturesChainHook(
FeaturesHook(detach=True), DLogitsHook(detach=True)
)
|