code: def reset_parameters(self):
      for i in range(self.n_models):
          nn.init.kaiming_uniform_(self.weight[i], a=math.sqrt(5))
          if self.bias is not None:
              fan_in, _ = nn.init._calculate_fan_in_and_fan_out(
                  self.weight[i]
              )
              bound = 1 / math.sqrt(fan_in)
              nn.init.uniform_(self.bias[i], -bound, bound)
  
imports: import math
  import os
  from dataclasses import dataclass
  from typing import Optional, Tuple
  import numpy
  import torch
  import torch.utils.checkpoint
  from torch import nn
  from torch.nn import functional
  from ...modeling_utils import PreTrainedModel
  from ...utils import ModelOutput, add_start_docstrings, add_start_docstrings_to_model_forward, logging, replace_return_docstrings
  from .configuration_trajectory_transformer import TrajectoryTransformerConfig
label_desc: Use image node_id 2 for calling the EinLinear obj's underlying member method code with example usage: obj.reset_parameters() without return types