class_docstr: Base class for Flax-based pipelines.
  
  [`FlaxDiffusionPipeline`] stores all components (models, schedulers, and processors) for diffusion pipelines and
  provides methods for loading, downloading and saving models. It also includes methods to:
  
      - enable/disable the progress bar for the denoising iteration
  
  Class attributes:
  
      - **config_name** ([`str`]) -- The configuration filename that stores the class and module names of all the
        diffusion pipeline's components.
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docstr: The `self.components` property can be useful to run different pipelines with the same weights and
  configurations to not have to re-allocate memory.
  
  Examples:
  
  ```py
  >>> from diffusers import (
  ...     FlaxStableDiffusionPipeline,
  ...     FlaxStableDiffusionImg2ImgPipeline,
  ... )
  
  >>> text2img = FlaxStableDiffusionPipeline.from_pretrained(
  ...     "runwayml/stable-diffusion-v1-5", revision="bf16", dtype=jnp.bfloat16
  ... )
  >>> img2img = FlaxStableDiffusionImg2ImgPipeline(**text2img.components)
  ```
  
  Returns:
      A dictionary containing all the modules needed to initialize the pipeline.
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code: def components(self) -> Dict[str, Any]:
      r"""
  
      The `self.components` property can be useful to run different pipelines with the same weights and
      configurations to not have to re-allocate memory.
  
      Examples:
  
      ```py
      >>> from diffusers import (
      ...     FlaxStableDiffusionPipeline,
      ...     FlaxStableDiffusionImg2ImgPipeline,
      ... )
  
      >>> text2img = FlaxStableDiffusionPipeline.from_pretrained(
      ...     "runwayml/stable-diffusion-v1-5", revision="bf16", dtype=jnp.bfloat16
      ... )
      >>> img2img = FlaxStableDiffusionImg2ImgPipeline(**text2img.components)
      ```
  
      Returns:
          A dictionary containing all the modules needed to initialize the pipeline.
      """
      expected_modules, optional_parameters = self._get_signature_keys(
          self
      )
      components = {
          k: getattr(self, k)
          for k in self.config.keys()
          if not k.startswith("_") and k not in optional_parameters
      }
  
      if set(components.keys()) != expected_modules:
          raise ValueError(
              f"{self} has been incorrectly initialized or {self.__class__} is incorrectly implemented. Expected"
              f" {expected_modules} to be defined, but {components} are defined."
          )
  
      return components
  
imports: import importlib
  import inspect
  import os
  from typing import Any, Dict, List, Optional, Union
  import flax
  import numpy
  import PIL.Image
  from flax.core.frozen_dict import FrozenDict
  from huggingface_hub import create_repo, snapshot_download
  from huggingface_hub.utils import validate_hf_hub_args
  from PIL import Image
  from tqdm.auto import tqdm
  from ..configuration_utils import ConfigMixin
  from ..models.modeling_flax_utils import FLAX_WEIGHTS_NAME, FlaxModelMixin
  from ..schedulers.scheduling_utils_flax import SCHEDULER_CONFIG_NAME, FlaxSchedulerMixin
  from ..utils import CONFIG_NAME, BaseOutput, PushToHubMixin, http_user_agent, is_transformers_available, logging
label_desc: Use image node_id 5 for calling the FlaxDiffusionPipeline obj's underlying member method code with example usage: obj.components() and returns: components