(self, x)
return b, a
Arguments:
            x: a float tensor with shape [batch_size, 3, h, w].
        Returns:
            b: a float tensor with shape [batch_size, 4, h', w'].
            a: a float tensor with shape [batch_size, 2, h', w'].
Arguments:
            x: a float tensor with shape [batch_size, 3, h, w].
        Returns:
            b: a float tensor with shape [batch_size, 4, h', w'].
            a: a float tensor with shape [batch_size, 2, h', w'].
Arguments : x : a float tensor with shape [ batch_size 3 h w ] . Returns : b : a float tensor with shape [ batch_size 4 h w ] . a : a float tensor with shape [ batch_size 2 h w ] .
def forward(self, x):
        """
        Arguments:
            x: a float tensor with shape [batch_size, 3, h, w].
        Returns:
            b: a float tensor with shape [batch_size, 4, h', w'].
            a: a float tensor with shape [batch_size, 2, h', w'].
        """
        x = self.features(x)
        a = self.conv4_1(x)
        b = self.conv4_2(x)
        #print(a.shape)
        a = F.softmax(a,dim=1)
        return b, a
def forward ( self , x ) : x = self . features ( x ) a = self . conv4_1 ( x ) b = self . conv4_2 ( x ) #print(a.shape) a = F . softmax ( a , dim = 1 ) return b , a