class_docstr: Clip the range of possible GeLU outputs between [min, max]. This is especially useful for quantization purpose, as
  it allows mapping negatives values in the GeLU spectrum. For more information on this trick, please refer to
  https://arxiv.org/abs/2004.09602.
  
  Gaussian Error Linear Unit. Original Implementation of the gelu activation function in Google Bert repo when
  initially created.
  
  For information: OpenAI GPT's gelu is slightly different (and gives slightly different results): 0.5 * x * (1 +
  torch.tanh(math.sqrt(2 / math.pi) * (x + 0.044715 * torch.pow(x, 3)))). See https://arxiv.org/abs/1606.08415
code: def forward(self, x: Tensor) -> Tensor:
      return torch.clip(gelu(x), self.min, self.max)
  
imports: import math
  from collections import OrderedDict
  import torch
  from packaging import version
  from torch import Tensor, nn
  from .utils import logging
label_desc: Use image node_id 2 for calling the ClippedGELUActivation obj's underlying member method code with example usage: obj.forward(x) and returns: torch