code: def _initialize_kaiming(x, initialization, d_sqrt_inv):
      if initialization == "kaiming_uniform":
          nn.init.uniform_(x, a=-d_sqrt_inv, b=d_sqrt_inv)
      elif initialization == "kaiming_normal":
          nn.init.normal_(x, std=d_sqrt_inv)
      elif initialization is None:
          pass
      else:
          raise NotImplementedError(
              "initialization should be either of `kaiming_normal`, `kaiming_uniform`,"
              " `None`"
          )
  
file_path: pytorch_tabular/src/pytorch_tabular/utils/nn_utils.py
imports: import torch
  import torch.nn
  from .logger import get_logger
label_desc: Use image node_id 6 for calling a global function with example usage: _initialize_kaiming(x, initialization, d_sqrt_inv) without return types