code: def uniform_(types, args=(), kwargs=None, pg=None):
      r"""
      Fills the Tensor in tensor.local_shards with values drawn from the uniform
      distribution :math:`\mathcal{U}(a, b)`.
      Args:
          tensor: tensor sharded across devices
          a: the lower bound of the uniform distribution
          b: the upper bound of the uniform distribution
      """
      validate_param(kwargs, "kwargs")
      sharded_tensor = kwargs["tensor"]
      validate_param(sharded_tensor, "tensor")
      a = kwargs["a"]
      validate_param(a, "a")
      b = kwargs["b"]
      validate_param(b, "b")
  
      for shard in sharded_tensor.local_shards():
          torch.nn.init.uniform_(shard.tensor, a=a, b=b)
      return sharded_tensor
  
file_path: pytorch/torch/distributed/_shard/sharded_tensor/_ops/init.py
imports: import torch
  import torch.distributed._shard.sharded_tensor
  from torch.distributed._shard.sharded_tensor import _sharded_op_impl
label_desc: Use image node_id 2 for calling a global function with example usage: uniform_(types, args, kwargs, pg) and returns: sharded_tensor