class_docstr: Encrypted tensor object that uses binary sharing to perform computations.
  
  Binary shares are computed by splitting each value of the input tensor
  into n separate random values that xor together to the input tensor value,
  where n is the number of parties present in the protocol (world_size).
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docstr: Writes all values from the tensor `src` into `self` at the indices
  specified in the `index` tensor. For each value in `src`, its output index
  is specified by its index in `src` for `dimension != dim` and by the
  corresponding value in `index` for `dimension = dim`.
docstr_tok: ["Writes","all","values","from","the","tensor","`","src","`","into","`","self","`","at","the","indices","specified","in","the","`","index","`","tensor",".","For","each","value","in","`","src","`",",","its","output","index","is","specified","by","its","index","in","`","src","`","for","`","dimension","!","=","dim","`","and","by","the","corresponding","value","in","`","index","`","for","`","dimension","=","dim","`","."]
code: def scatter(self, dim, index, src):
      """Writes all values from the tensor `src` into `self` at the indices
      specified in the `index` tensor. For each value in `src`, its output index
      is specified by its index in `src` for `dimension != dim` and by the
      corresponding value in `index` for `dimension = dim`.
      """
      result = self.clone()
      return result.scatter_(dim, index, src)
  
imports: import crypten.communicator
  import torch
  from crypten.common.functions import regular
  from crypten.common.rng import generate_kbit_random_tensor
  from crypten.common.tensor_types import is_tensor
  from crypten.common.util import torch_cat, torch_stack
  from crypten.cuda import CUDALongTensor
  from crypten.encoder import FixedPointEncoder
  from .None import beaver, circuit
label_desc: Use image node_id 48 for calling the BinarySharedTensor obj's underlying member method code with example usage: obj.scatter(dim, index, src) and returns: result