class_docstr: Version using (complex) diagonal state matrix (S4D).
class_docstr_tok: ["Version","using","(","complex",")","diagonal","state","matrix","(","S4D",")","."]
code: def _A_init(self, A_real):
      A_real = torch.clamp(A_real, max=-1e-4)
      if self.real_type == "none":
          return -A_real
      elif self.real_type == "exp":
          return torch.log(
              -A_real
          )  # Some of the HiPPO methods have real part 0
      elif self.real_type == "relu":
          return -A_real
      elif self.real_type == "sigmoid":
          return torch.logit(-A_real)
      elif self.real_type == "softplus":
          return torch.log(torch.exp(-A_real) - 1)
      else:
          raise NotImplementedError
  
imports: import logging
  import math
  import os
  from functools import wraps
  from typing import Any, Callable, Optional
  import numpy
  import opt_einsum
  import torch
  import torch.nn
  import torch.nn.functional
  from einops import rearrange, repeat
  from espnet2.asr.state_spaces.components import Activation, DropoutNd, LinearActivation
label_desc: Use image node_id 2 for calling the SSKernelDiag obj's underlying member method code with example usage: obj._A_init(A_real) and returns: unknown, torch, unknown, torch, torch