oneflow.set_grad_enabled¶
-
class
oneflow.
set_grad_enabled
(is_train=True)¶ Context-manager that enabled gradient calculation.
Enables gradient calculation, if it has been disabled via no_grad.
This context manager is thread local; it will not affect computation in other threads.
Also functions as a decorator. (Make sure to instantiate with parenthesis.)
- Parameters
mode (bool) – Flag whether to enable or disable gradient calculation. (default: True)
>>> import oneflow as flow >>> x = flow.ones(2, 3, requires_grad=True) >>> with flow.set_grad_enabled(True): ... y = x * x >>> y.requires_grad True >>> @flow.set_grad_enabled(False) ... def no_grad_func(x): ... return x * x >>> y = no_grad_func(x) >>> y.requires_grad False
-
__init__
(is_train=True)¶ Initialize self. See help(type(self)) for accurate signature.
Methods
__call__
(func)Call self as a function.
__delattr__
(name, /)Implement delattr(self, name).
__dir__
()Default dir() implementation.
__enter__
()__eq__
(value, /)Return self==value.
__exit__
(exc_type, exc_val, exc_tb)__format__
(format_spec, /)Default object formatter.
__ge__
(value, /)Return self>=value.
__getattribute__
(name, /)Return getattr(self, name).
__gt__
(value, /)Return self>value.
__hash__
()Return hash(self).
__init__
([is_train])Initialize self.
__init_subclass__
This method is called when a class is subclassed.
__le__
(value, /)Return self<=value.
__lt__
(value, /)Return self<value.
__ne__
(value, /)Return self!=value.
__new__
(**kwargs)Create and return a new object.
__reduce__
()Helper for pickle.
__reduce_ex__
(protocol, /)Helper for pickle.
__repr__
()Return repr(self).
__setattr__
(name, value, /)Implement setattr(self, name, value).
__sizeof__
()Size of object in memory, in bytes.
__str__
()Return str(self).
__subclasshook__
Abstract classes can override this to customize issubclass().