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).
docstr: Left shift elements by `value` bits
docstr_tok: ["Left","shift","elements","by","`","value","`","bits"]
code: def lshift_(self, value):
      """Left shift elements by `value` bits"""
      assert isinstance(
          value, int
      ), "lshift must take an integer argument."
      self.share <<= value
      return self
  
imports: import torch
  import fate.arch.protocol.mpc.communicator
  from fate.arch.protocol.mpc.common.rng import generate_kbit_random_tensor
  from fate.arch.protocol.mpc.common.tensor_types import is_tensor
  from fate.arch.protocol.mpc.common.util import torch_cat, torch_stack
  from fate.arch.protocol.mpc.cuda import CUDALongTensor
  from fate.arch.protocol.mpc.encoder import FixedPointEncoder
  from fate.arch.protocol.mpc.functions import regular
  from .None import beaver, circuit
label_desc: Use image node_id 27 for calling the BinarySharedTensor obj's underlying member method code with example usage: obj.lshift_(value) and returns: self