text: # -*- coding: utf-8 -*-
  # @Author  : LG
  
  from tensor import Tensor
  import numpy as np
  from nn.functional import *
  
  
  class Module(object):
      def __init__(self):
          pass
  
      def forward(self, *inputs):
          raise NotImplementedError
  
  
  class Linear(Module):
      def __init__(self, in_features, out_features, bias=True):
          super(Linear, self).__init__()
          self.weight = Tensor(data=np.ones(shape=(in_features, out_features)))
          if bias:
              self.bias = Tensor(data=np.ones(shape=(out_features)))
          else:
              self.bias = None
  
      def forward(self, input):
          return linear(input,self.weight,self.bias)
  
  