docstr: Forward pass.
  
  x: (B, L..., D)
code: def forward(self, x):
      """Forward pass.
  
      x: (B, L..., D)
      """
      if not self.transposed:
          x = rearrange(x, "b ... d -> b d ...")
      shape = x.shape[2:]
      x_f = torch.fft.ifftn(x, s=shape)
  
      for axis, l in enumerate(shape):
          assert (
              l % self.stride == 0
          ), "input length must be divisible by stride"
          new_l = l // self.stride
          idx = torch.cat(
              [
                  torch.arange(0, new_l - new_l // 2),
                  l + torch.arange(-new_l // 2, 0),
              ]
          ).to(x_f.device)
          x_f = torch.index_select(x_f, 2 + axis, idx)
      x = torch.fft.ifftn(
          x_f, s=[length // self.stride for length in shape]
      )
      x = x.real
  
      if self.expand > 1:
          x = repeat(x, "b d ... -> b (d e) ...", e=self.expand)
      if not self.transposed:
          x = rearrange(x, "b d ... -> b ... d")
      return x
  
imports: import torch
  import torch.nn.functional
  from einops import rearrange, reduce, repeat
  from torch import nn
  from espnet2.asr.state_spaces.base import SequenceModule
  from espnet2.asr.state_spaces.components import LinearActivation
label_desc: Use image node_id 2 for calling the DownSpectralPool obj's underlying member method code with example usage: obj.forward(x) and returns: x