code: def test_timestep_defaults(self):
      embedding_dim = 16
      timesteps = torch.arange(10)
  
      t1 = get_timestep_embedding(timesteps, embedding_dim)
      t2 = get_timestep_embedding(
          timesteps,
          embedding_dim,
          flip_sin_to_cos=False,
          downscale_freq_shift=1,
          max_period=10_000,
      )
  
      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 backend_manual_seed, require_torch_accelerator_with_fp64, torch_device
label_desc: Use image node_id 2 for calling the EmbeddingsTests obj's underlying member method code with example usage: obj.test_timestep_defaults() without return types