class_docstr: Base class from which ticker tasks inherit.
docstr: Prepare data for delivery to device.
  
  Arguments:
      time_steps (int): Number of time steps in this minibatch.
      inputs (numpy array): Inputs numpy array
      outputs (numpy array): Outputs numpy array
      in_tensor (Tensor): Device buffer holding inputs
      out_tensor (Tensor): Device buffer holding outputs
      mask (numpy array): Device buffer for the output mask
docstr_tok: ["Prepare","data","for","delivery","to","device",".","Arguments",":","time_steps","(","int",")",":","Number","of","time","steps","in","this","minibatch",".","inputs","(","numpy","array",")",":","Inputs","numpy","array","outputs","(","numpy","array",")",":","Outputs","numpy","array","in_tensor","(","Tensor",")",":","Device","buffer","holding","inputs","out_tensor","(","Tensor",")",":","Device","buffer","holding","outputs","mask","(","numpy","array",")",":","Device","buffer","for","the","output","mask"]
code: def fill_buffers(
      self, time_steps, inputs, outputs, in_tensor, out_tensor, mask
  ):
      """
      Prepare data for delivery to device.
  
      Arguments:
          time_steps (int): Number of time steps in this minibatch.
          inputs (numpy array): Inputs numpy array
          outputs (numpy array): Outputs numpy array
          in_tensor (Tensor): Device buffer holding inputs
          out_tensor (Tensor): Device buffer holding outputs
          mask (numpy array): Device buffer for the output mask
      """
      # Put inputs and outputs, which are too small, into properly shaped arrays
      columns = time_steps * self.be.bsz
      inC = np.zeros((self.nin, self.max_columns))
      outC = np.zeros((self.nout, self.max_columns))
      inC[:, :columns] = inputs
      outC[:, :columns] = outputs
  
      # Copy those arrays to device
      in_tensor.set(inC)
      out_tensor.set(outC)
  
      # Set a mask over the unused part of the buffer
      mask[:, :columns] = 1
      mask[:, columns:] = 0
  
imports: import numpy
  from neon import NervanaObject
label_desc: Use image node_id 2 for calling the Task obj's underlying member method code with example usage: obj.fill_buffers(time_steps, inputs, outputs, in_tensor, out_tensor, mask) without return types