old_contents: import logging
  import math
  
  import torch
  import torch.nn.functional as F
  
  
  logger = logging.getLogger(__name__)
  
  
  def swish(x):
      return x * torch.sigmoid(x)
  
  
  def _gelu_python(x):
      """ 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))))
          This is now written in C in torch.nn.functional
          Also see https://arxiv.org/abs/1606.08415
      """
      return x * 0.5 * (1.0 + torch.erf(x / math.sqrt(2.0)))
  
  
  def gelu_new(x):
      """ Implementation of the gelu activation function currently in Google Bert repo (identical to OpenAI GPT).
          Also see https://arxiv.org/abs/1606.08415
      """
      return 0.5 * x * (1 + torch.tanh(math.sqrt(2 / math.pi) * (x + 0.044715 * torch.pow(x, 3))))
  
  
  if torch.__version__ < "1.4.0":
      gelu = _gelu_python
  else:
      gelu = F.gelu
      try:
          import torch_xla  # noqa F401
  
          logger.warning(
              "The torch_xla package was detected in the python environment. PyTorch/XLA and JIT is untested,"
              " no activation function will be traced with JIT."
          )
      except ImportError:
          gelu_new = torch.jit.script(gelu_new)
  
  ACT2FN = {
      "relu": F.relu,
      "swish": swish,
      "gelu": gelu,
      "tanh": torch.tanh,
      "gelu_new": gelu_new,
  }
  
  
  def get_activation(activation_string):
      if activation_string in ACT2FN:
          return ACT2FN[activation_string]
      else:
          raise KeyError("function {} not found in ACT2FN mapping {}".format(activation_string, list(ACT2FN.keys())))
  
new_contents: import logging
  import math
  
  import torch
  import torch.nn.functional as F
  
  
  logger = logging.getLogger(__name__)
  
  
  def swish(x):
      return x * torch.sigmoid(x)
  
  
  def _gelu_python(x):
      """ 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))))
          This is now written in C in torch.nn.functional
          Also see https://arxiv.org/abs/1606.08415
      """
      return x * 0.5 * (1.0 + torch.erf(x / math.sqrt(2.0)))
  
  
  def gelu_new(x):
      """ Implementation of the gelu activation function currently in Google Bert repo (identical to OpenAI GPT).
          Also see https://arxiv.org/abs/1606.08415
      """
      return 0.5 * x * (1 + torch.tanh(math.sqrt(2 / math.pi) * (x + 0.044715 * torch.pow(x, 3.0))))
  
  
  if torch.__version__ < "1.4.0":
      gelu = _gelu_python
  else:
      gelu = F.gelu
      try:
          import torch_xla  # noqa F401
  
          logger.warning(
              "The torch_xla package was detected in the python environment. PyTorch/XLA and JIT is untested,"
              " no activation function will be traced with JIT."
          )
      except ImportError:
          gelu_new = torch.jit.script(gelu_new)
  
  ACT2FN = {
      "relu": F.relu,
      "swish": swish,
      "gelu": gelu,
      "tanh": torch.tanh,
      "gelu_new": gelu_new,
  }
  
  
  def get_activation(activation_string):
      if activation_string in ACT2FN:
          return ACT2FN[activation_string]
      else:
          raise KeyError("function {} not found in ACT2FN mapping {}".format(activation_string, list(ACT2FN.keys())))
  
subject: Fix for #3873 to change type of exponent parameter for torch.pow() call from int to float (#3924)