code: def test_timestep_flip_sin_cos(self):
      embedding_dim = 16
      timesteps = torch.arange(10)
  
      t1 = get_timestep_embedding(
          timesteps, embedding_dim, flip_sin_to_cos=True
      )
      t1 = torch.cat(
          [t1[:, embedding_dim // 2 :], t1[:, : embedding_dim // 2]],
          dim=-1,
      )
  
      t2 = get_timestep_embedding(
          timesteps, embedding_dim, flip_sin_to_cos=False
      )
  
      assert torch.allclose(t1.cpu(), t2.cpu(), 1e-3)
  
imports: import unittest
  import numpy
  import torch
  from torch import nn
  from diffusers.models.attention import GEGLU, AdaLayerNorm, ApproximateGELU
  from diffusers.models.embeddings import get_timestep_embedding
  from diffusers.models.lora import LoRACompatibleLinear
  from diffusers.models.resnet import Downsample2D, ResnetBlock2D, Upsample2D
  from diffusers.models.transformer_2d import Transformer2DModel
  from diffusers.utils.testing_utils import torch_device
label_desc: Use image node_id 3 for calling the EmbeddingsTests obj's underlying member method code with example usage: obj.test_timestep_flip_sin_cos() without return types