docstr: Segmenting the signal into chunks with specific context.
  
  input:
      x: size (B, ch, T)
      window: int
      context: int
docstr_tok: ["Segmenting","the","signal","into","chunks","with","specific","context",".","input",":","x",":","size","(","B",",","ch",",","T",")","window",":","int","context",":","int"]
code: def seg_signal_context(self, x, window, context):
      """Segmenting the signal into chunks with specific context.
  
      input:
          x: size (B, ch, T)
          window: int
          context: int
      """
  
      # pad input accordingly
      # first pad according to window size
      input, rest = self.pad_input(x, window)
      batch_size, nmic, nsample = input.shape
      stride = window // 2
  
      # pad another context size
      pad_context = torch.zeros(batch_size, nmic, context).type(
          input.type()
      )
      input = torch.cat(
          [pad_context, input, pad_context], 2
      )  # B, ch, L
  
      # calculate index for each chunk
      nchunk = 2 * nsample // window - 1
      begin_idx = np.arange(nchunk) * stride
      begin_idx = (
          torch.from_numpy(begin_idx)
          .type(input.type())
          .long()
          .view(1, 1, -1)
      )  # 1, 1, nchunk
      begin_idx = begin_idx.expand(
          batch_size, nmic, nchunk
      )  # B, ch, nchunk
      # select entries from index
      chunks = [
          torch.gather(input, 2, begin_idx + i).unsqueeze(3)
          for i in range(2 * context + window)
      ]  # B, ch, nchunk, 1
      chunks = torch.cat(chunks, 3)  # B, ch, nchunk, chunk_size
  
      # center frame
      center_frame = chunks[:, :, :, context : context + window]
  
      return center_frame, chunks, rest
  
imports: import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from espnet2.enh.layers import dprnn
label_desc: Use image node_id 3 for calling the FaSNet_base obj's underlying member method code with example usage: obj.seg_signal_context(x, window, context) and returns: center_frame,  chunks,  rest