code: def test_stable_diffusion_v1_4_bfloat_16_with_safety(self):
      pipeline, params = FlaxStableDiffusionPipeline.from_pretrained(
          "CompVis/stable-diffusion-v1-4",
          revision="bf16",
          dtype=jnp.bfloat16,
      )
  
      prompt = (
          "A cinematic film still of Morgan Freeman starring as Jimi Hendrix, portrait, 40mm lens, shallow depth of"
          " field, close up, split lighting, cinematic"
      )
  
      prng_seed = jax.random.PRNGKey(0)
      num_inference_steps = 50
  
      num_samples = jax.device_count()
      prompt = num_samples * [prompt]
      prompt_ids = pipeline.prepare_inputs(prompt)
  
      # shard inputs and rng
      params = replicate(params)
      prng_seed = jax.random.split(prng_seed, num_samples)
      prompt_ids = shard(prompt_ids)
  
      images = pipeline(
          prompt_ids, params, prng_seed, num_inference_steps, jit=True
      ).images
  
      assert images.shape == (num_samples, 1, 512, 512, 3)
      if jax.device_count() == 8:
          assert (
              np.abs(
                  (
                      np.abs(
                          images[0, 0, :2, :2, -2:], dtype=np.float32
                      ).sum()
                      - 0.04003906
                  )
              )
              < 5e-2
          )
          assert (
              np.abs(
                  (np.abs(images, dtype=np.float32).sum() - 2373516.75)
              )
              < 5e-1
          )
  
file_path: llmga/llmga/diffusers/tests/pipelines/test_pipelines_flax.py
imports: import os
  import tempfile
  import unittest
  import numpy
  from diffusers.utils import is_flax_available
  from diffusers.utils.testing_utils import require_flax, slow
label_desc: Use image node_id 4 for calling the FlaxPipelineTests obj's underlying member method code with example usage: obj.test_stable_diffusion_v1_4_bfloat_16_with_safety() without return types