code: def rearrange_1(tensor):
      B, C, F, H, W = tensor.size()
      return torch.reshape(
          torch.permute(tensor, (0, 2, 1, 3, 4)), (B * F, C, H, W)
      )
  
imports: import copy
  import inspect
  from dataclasses import dataclass
  from typing import Callable, List, Optional, Union
  import numpy
  import PIL.Image
  import torch
  import torch.nn.functional
  from torch.nn.functional import grid_sample
  from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
  from ...image_processor import VaeImageProcessor
  from ...loaders import LoraLoaderMixin, TextualInversionLoaderMixin
  from ...models import AutoencoderKL, UNet2DConditionModel
  from ...models.lora import adjust_lora_scale_text_encoder
  from ...schedulers import KarrasDiffusionSchedulers
  from ...utils import USE_PEFT_BACKEND, BaseOutput, logging, scale_lora_layers, unscale_lora_layers
  from ...utils.torch_utils import randn_tensor
  from ..pipeline_utils import DiffusionPipeline
  from ..stable_diffusion import StableDiffusionSafetyChecker
label_desc: Use image node_id 2 for calling a global function with example usage: rearrange_1(tensor) and returns: torch