code: def get_timing_signal_1d(
      length, channels, min_timescale=1.0, max_timescale=1.0e4
  ):
      position = torch.arange(length, dtype=torch.float)
      num_timescales = channels // 2
      log_timescale_increment = math.log(
          float(max_timescale) / float(min_timescale)
      ) / (num_timescales - 1)
      inv_timescales = min_timescale * torch.exp(
          torch.arange(num_timescales, dtype=torch.float)
          * -log_timescale_increment
      )
      scaled_time = position.unsqueeze(0) * inv_timescales.unsqueeze(1)
      signal = torch.cat(
          [torch.sin(scaled_time), torch.cos(scaled_time)], 0
      )
      signal = F.pad(signal, [0, 0, 0, channels % 2])
      signal = signal.view(1, channels, length)
      return signal
  
imports: import math
  import numpy
  import torch
  from torch import nn
  from torch.nn import functional
label_desc: Use image node_id 11 for calling a global function with example usage: get_timing_signal_1d(length, channels, min_timescale, max_timescale) and returns: signal