class_docstr: Linear decoder for speaker diarization
docstr: Forward.
  
  Args:
      input (torch.Tensor): hidden_space [Batch, T, F]
      ilens (torch.Tensor): input lengths [Batch]
docstr_tok: ["Forward",".","Args",":","input","(","torch.Tensor",")",":","hidden_space","[","Batch",",","T",",","F","]","ilens","(","torch.Tensor",")",":","input","lengths","[","Batch","]"]
code: def forward(self, input: torch.Tensor, ilens: torch.Tensor):
      """Forward.
  
      Args:
          input (torch.Tensor): hidden_space [Batch, T, F]
          ilens (torch.Tensor): input lengths [Batch]
      """
  
      output = self.linear_decoder(input)
  
      return output
  
imports: import torch
  from espnet2.diar.decoder.abs_decoder import AbsDecoder
label_desc: Use image node_id 2 for calling the LinearDecoder obj's underlying member method code with example usage: obj.forward(input, ilens) and returns: output