__call__The role of the method is to make the object can be called like a function. By defining methods in a class __call__, you can treat object instances as callable functions that perform specific actions when the object is called. __call__Methods are called when you call an object as a function. In Python, enclosing an object with parentheses triggers a __call__method on that object.
class MyClass:
def __call__(self, x):
print("Calling MyClass with argument:", x)
obj = MyClass()
# 触发__call__方法
obj(10)
output:
Calling MyClass with argument: 10
In the above example, we defined a class called MyClass and defined __call__the method in it. When we create MyClassan object of objand call it as a function, that is , the method of obj(10)will be triggered , and output . That is, the method provides a way to call an object as a function, allowing us to customize the behavior of the object when it is called. By defining methods in a class , we can represent an object as a callable function.obj__call__Calling MyClass with argument: 10__call____call__
We often use the network name directly during deep learning training. In fact, it is because the model we created inherits nn.Module. In , the PyTorchclass nn.Moduleoverrides __call__the method, so that when you call an inherited nn.Modulemodel object, actually is calling __call__the method of the model object. The purpose of this is to conveniently execute the forward propagation process of the model, and combine the calling method of the model object with the forward propagation logic.
To summarize, __call__methods are special methods that are called when an object is invoked as a function. By defining __call__methods, we can customize the behavior of the object when called. In PyTorch, nn.Modulethe class overrides __call__the method to trigger the forward pass process of the model when the model object is called.