pytorch에서forward의 용법과 해석 설명

앞말

forward의 사용

class Module(nn.Module):
 def __init__(self):
  super(Module, self).__init__()
  # ......
  
 def forward(self, x):
  # ......
  return x
data = ..... # 
#  
module = Module()
#  
module(data) 
#  
# module.forward(data) 

module(data) 

module.forward(data) 

forward 사용 설명

class A():
 def __call__(self):
  print('i can be called like a function')
 
a = A()
a()

class A():
 def __call__(self, param):
  
  print('i can called like a function')
  print(' ：{}  ： {}'.format(type(param), param))
 
  res = self.forward(param)
  return res
 
 def forward(self, input_):
  print('forward  ')
 
  print('in forward,  ：{}  : {}'.format( type(input_), input_))
  return input_ 
a = A() 
input_param = a('i')
print(" a ：", input_param)

class Module(nn.Module):
 def __init__(self):
  super(Module, self).__init__()
  # ......
 
 def forward(self, x):
  # ......
  return x
data = ..... # 
#  
module = Module()
#    
module(data) 
# module.forward(data) 

class A():
 def __call__(self):
  print('i can be called like a function')
 
a = A()
a()
>>>i can be called like a function

class A():
 def __call__(self, param):
  
  print(' __call__ ， ',param)
 
  res = self.forward(param)
  return res
 
 def forward(self, x):
  print(' forward ， : ',x)
  return x
 
a = A()
y = a('i')
 >>>  __call__ ，  i
 >>> forward ， : i
print(" ：", y)
 >>> ： i