Pytorch: TypeError: 'str' object 不能解释为 integer

Question

#Whatever I do, I encounter this error, what should I do?

class SearchCell(nn.Module):

  def __init__(self, steps, multiplier, prev_prev_C, prev_C, curr_C, reduction, prev_reduction):
    super(SearchCell, self).__init__()
    self.steps = steps
    self.multiplier = multiplier
    self.reduction = reduction
  
    if prev_reduction:
      self.prep0 = FactorizedReduce(prev_prev_C,curr_C, affine=False)
    else:
      self.prep0 = ReLUConvBN(prev_prev_C, curr_C, 1, 1, 0, affine=False)
    self.prep1 = ReLUConvBN(prev_C, curr_C, 1, 1, 0, affine=False)

    self.layers = nn.ModuleList()
 -->   for i in range(steps):
        for j in range(2+i):
            stride = 2 if reduction and j < 2 else 1
            op = MixedOp(curr_C, stride)
            self.layers.append(op)

  def forward(self, s0, s1, weights):
    s0 = self.prep0(s0)
    s1 = self.prep1(s1)
    states = [s0, s1]
    offset = 0
    for i in range(self.steps):
      s = sum([self.layers[offset + j](h, weights[offset + j]) for j, h in enumerate(states)])
      offset += len(states)
      states.append(s)

    return torch.cat(states[-self.multiplier:], dim=1)

TypeErrorTraceback (most recent call last) in init (self, steps, multiplier, prev_prev_C, prev_C, curr_C, reduction, prev_reduction) 36 37 self.layers = nn.ModuleList() 38 for i in range(steps): 39 for j in range(2+i): 40 stride = 2 if reduction and j < 2 else 1 TypeError: 'str' object cannot be interpreted as an integer

Answer 1

according to your error steps is a string while range(steps) means that steps must be an integer cause range iterates over an integer n ( from 0 to n-1). Check if steps integer or not using print(type(steps)) if it is a string try using this steps = int(steps) it will type convert it to integer. If there is an character in steps it will return another error can convert str to string . If that occours trace every occourance of steps and check where steps(int) is converted to str using print(type(steps))

class SearchCell(nn.Module):

  def __init__(self, steps, multiplier, prev_prev_C, prev_C, curr_C, reduction, prev_reduction):
    super(SearchCell, self).__init__()
    self.steps = int(steps)    # changed here 
    self.multiplier = multiplier
    self.reduction = reduction
  
    if prev_reduction:
      self.prep0 = FactorizedReduce(prev_prev_C,curr_C, affine=False)
    else:
      self.prep0 = ReLUConvBN(prev_prev_C, curr_C, 1, 1, 0, affine=False)
    self.prep1 = ReLUConvBN(prev_C, curr_C, 1, 1, 0, affine=False)

Or try this, hope it helps.