(self, x)
return c, b, a
Arguments:
            x: a float tensor with shape [batch_size, 3, h, w].
        Returns:
            c: a float tensor with shape [batch_size, 10].
            b: a float tensor with shape [batch_size, 4].
            a: a float tensor with shape [batch_size, 2].
Arguments:
            x: a float tensor with shape [batch_size, 3, h, w].
        Returns:
            c: a float tensor with shape [batch_size, 10].
            b: a float tensor with shape [batch_size, 4].
            a: a float tensor with shape [batch_size, 2].
Arguments : x : a float tensor with shape [ batch_size 3 h w ] . Returns : c : a float tensor with shape [ batch_size 10 ] . b : a float tensor with shape [ batch_size 4 ] . a : a float tensor with shape [ batch_size 2 ] .
def forward(self, x):
        """
        Arguments:
            x: a float tensor with shape [batch_size, 3, h, w].
        Returns:
            c: a float tensor with shape [batch_size, 10].
            b: a float tensor with shape [batch_size, 4].
            a: a float tensor with shape [batch_size, 2].
        """
        x = self.features(x)
        a = self.conv6_1(x)
        b = self.conv6_2(x)
        c = self.conv6_3(x)
        a = F.softmax(a,dim=1)
        return c, b, a
def forward ( self , x ) : x = self . features ( x ) a = self . conv6_1 ( x ) b = self . conv6_2 ( x ) c = self . conv6_3 ( x ) a = F . softmax ( a , dim = 1 ) return c , b , a