code: def sigmoid_cross_entropy_with_logits(
      input, label, ignore_index=-100, normalize=False
  ):
      output = F.binary_cross_entropy_with_logits(
          input, label, reduction="none"
      )
      mask_tensor = paddle.cast(label != ignore_index, "float32")
      output = paddle.multiply(output, mask_tensor)
      if normalize:
          sum_valid_mask = paddle.sum(mask_tensor)
          output = output / sum_valid_mask
      return output
  
imports: import paddle
  import paddle.nn.functional
  import paddle.nn
  from paddle import ParamAttr
  from paddle.regularizer import L2Decay
  from paddle import in_dynamic_mode
  from paddle.common_ops_import import Variable, LayerHelper, check_variable_and_dtype, check_type, check_dtype
label_desc: Use image node_id 14 for calling a global function with example usage: sigmoid_cross_entropy_with_logits(input, label, ignore_index, normalize) and returns: output