pytorch_pfn_extras.training.extensions.fail_on_non_number.FailOnNonNumber#
- class pytorch_pfn_extras.training.extensions.fail_on_non_number.FailOnNonNumber(*, check_grad=True)#
Bases:
Extension
An extension to raise RuntimeError if parameters and its gradients contain NaN or Inf.
Although parameters including non-number such as NaN and Inf are unnecessary in most cases the training loop will continue to compute even if the parameters in a given optimizer diverge. This extension is aimed to reduce unnecessary computations by throwing
RuntimeError
if the parameters contain NaN or Inf.- Parameters:
check_grad (bool) – Set to False to skip checking gradients.
Methods
__init__
(*[, check_grad])finalize
(manager)Finalizes the extension.
initialize
(manager)Initializes up the manager state.
load_state_dict
(to_load)on_error
(manager, exc, tb)Handles the error raised during training before finalization.
state_dict
()Serializes the extension state.
Attributes
default_name
Default name of the extension.
is_async
name
priority
trigger
- __call__(manager)#
Invokes the extension.
Implementations should override this operator. This method is called at iterations which the corresponding trigger accepts.
- Parameters:
manager (ExtensionsManager) – Manager object to call this operator.
- Return type:
None
- __init__(*, check_grad=True)#
- Parameters:
check_grad (bool) –
- needs_model_state = True#