code: def time_embed_dim(self):
      return self.time_input_dim * 4
  
imports: import gc
  import random
  import unittest
  import numpy
  import torch
  from diffusers import DDIMScheduler, KandinskyV22ControlnetPipeline, KandinskyV22PriorPipeline, UNet2DConditionModel, VQModel
  from diffusers.utils.testing_utils import enable_full_determinism, floats_tensor, load_image, load_numpy, nightly, require_torch_gpu, torch_device
  from ..test_pipelines_common import PipelineTesterMixin, assert_mean_pixel_difference
label_desc: Use image node_id 4 for calling the KandinskyV22ControlnetPipelineFastTests obj's underlying member method code with example usage: obj.time_embed_dim() and returns: unknown