code: def xavier_uniform_(tensor, gain=1.0):
      """Drop-in replacement of `torch.nn.init.xavier_uniform_`.
      Note:
          -  if using this function, ensure `gain` does not depend on fan-in,
             fan-out, or other notions of width, e.g. if gain = 1.
          - `tensor` should have `infshape` attribute set by `set_base_shapes`.
      """
      fan_in, fan_out = _calculate_fan_in_and_fan_out(tensor)
      std = gain * math.sqrt(2.0 / float(fan_in + fan_out))
      std = _inf_fan_adjust_xavier(std, tensor)
      a = (
          math.sqrt(3.0) * std
      )  # Calculate uniform bounds from standard deviation
      return _no_grad_uniform_(tensor, -a, a)
  
file_path: NeMo/nemo/collections/nlp/modules/common/megatron/mup/init.py
imports: import math
  import warnings
  import torch
  from torch.nn.init import _calculate_correct_fan, _calculate_fan_in_and_fan_out, _no_grad_fill_, _no_grad_normal_, _no_grad_uniform_, calculate_gain
label_desc: Use image node_id 7 for calling a global function with example usage: xavier_uniform_(tensor, gain) and returns: _no_grad_uniform_