docstr: Returns underscore separated Path.
  A current timestamp is prepended if `self.save_date_time` is set.
  Sequence number left padded with 6 zeroes is appended if `save_every` is set.
  :rtype: Path
docstr_tok: ["Returns","underscore","separated","Path",".","A","current","timestamp","is","prepended","if","`","self.save_date_time","`","is","set",".","Sequence","number","left","padded","with","6","zeroes","is","appended","if","`","save_every","`","is","set",".",":","rtype",":","Path"]
code: def image_output_path(self, sequence_number=None):
      """
      Returns underscore separated Path.
      A current timestamp is prepended if `self.save_date_time` is set.
      Sequence number left padded with 6 zeroes is appended if `save_every` is set.
      :rtype: Path
      """
      output_path = self.textpath
      if sequence_number:
          sequence_number_left_padded = str(sequence_number).zfill(6)
          output_path = f"{output_path}.{sequence_number_left_padded}"
      if self.save_date_time:
          current_time = datetime.now().strftime("%y%m%d-%H%M%S_%f")
          output_path = f"{current_time}_{output_path}"
      return Path(f"{output_path}.jpg")
  
imports: import os
  import subprocess
  import sys
  import random
  from datetime import datetime
  from pathlib import Path
  import torch
  import torch.nn.functional
  from siren_pytorch import SirenNet, SirenWrapper
  from torch import nn
  from torch.cuda.amp import GradScaler, autocast
  from torch_optimizer import DiffGrad, AdamP
  import numpy
  from PIL import Image
  from imageio import imread, mimsave
  import torchvision.transforms
  from tqdm import trange, tqdm
  from .clip import load, tokenize
label_desc: Use image node_id 8 for calling the Imagine obj's underlying member method code with example usage: obj.image_output_path(sequence_number) and returns: Path