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How objects are called in Keras
source link: https://adaickalavan.github.io/tensorflow/how-objects-are-called-in-keras/
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How objects are called in Keras
less than 1 minute read
This post elucidates how layers (for instance class MyLayer(Layer)) are called in Keras when we perform operations such as x_output = MyLayer( .... , ...)(x_input). In this example, the MyLayer class instance is called directly with input x_input. This action calls the def __call__() function, found in the parent of MyLayer which is class Layer(). The def __call__() function in the parent class, in-turn calls the def call() in MyLayer class which defines the logic of MyLayer layer.
I have given a simplified example below describing this operation flow.
class Layer():
def __init__(self,x):
print('Inside Layer -> __init__ :',x)
def __call__(self, y):
print('Inside Layer -> __call__ :',y)
self.call(y)
def call(self,z):
print('Inside Layer -> call :',z)
class MyLayer(Layer):
def __init__(self,k):
print('Inside MyLayer -> __init__ :',k)
super(MyLayer, self).__init__(k)
def call(self, m):
print('Inside MyLayer -> call :',m)
if __name__ == '__main__':
obj = MyLayer(3)
obj(4)
Upon running the above code, the output is as follows:
Inside MyLayer -> __init__ : 3
Inside Layer -> __init__ : 3
Inside Layer -> __call__ : 4
Inside MyLayer -> call : 4
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