'''
    #################################################################################################################################################################################################
    # This code library is an adaptation of the original Transformers and was designed, developed and programmed by Sapiens Technology®.                                                            #
    # Any alteration and/or disclosure of this code without prior authorization is strictly prohibited and is subject to legal action that will be forwarded by the Sapiens Technology® legal team. #
    # This set of algorithms aims to download, train, fine-tune and/or infer large language models from various sources and slopes.                                                                 #
    #################################################################################################################################################################################################
'''
from typing import TYPE_CHECKING
from ...utils import DIFFUSERS_SLOW_IMPORT, OptionalDependencyNotAvailable, _LazyModule, get_objects_from_module, is_flax_available, is_torch_available, is_transformers_available
_dummy_objects = {}
_additional_imports = {}
_import_structure = {'pipeline_output': ['StableDiffusionXLPipelineOutput']}
if is_transformers_available() and is_flax_available(): _import_structure['pipeline_output'].extend(['FlaxStableDiffusionXLPipelineOutput'])
try:
    if not (is_transformers_available() and is_torch_available()): raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    from ...utils import dummy_torch_and_transformers_objects
    _dummy_objects.update(get_objects_from_module(dummy_torch_and_transformers_objects))
else:
    _import_structure['pipeline_stable_diffusion_xl'] = ['StableDiffusionXLPipeline']
    _import_structure['pipeline_stable_diffusion_xl_img2img'] = ['StableDiffusionXLImg2ImgPipeline']
    _import_structure['pipeline_stable_diffusion_xl_inpaint'] = ['StableDiffusionXLInpaintPipeline']
    _import_structure['pipeline_stable_diffusion_xl_instruct_pix2pix'] = ['StableDiffusionXLInstructPix2PixPipeline']
if is_transformers_available() and is_flax_available():
    from ...schedulers.scheduling_pndm_flax import PNDMSchedulerState
    _additional_imports.update({'PNDMSchedulerState': PNDMSchedulerState})
    _import_structure['pipeline_flax_stable_diffusion_xl'] = ['FlaxStableDiffusionXLPipeline']
if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
    try:
        if not (is_transformers_available() and is_torch_available()): raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable: from ...utils.dummy_torch_and_transformers_objects import *
    else:
        from .pipeline_stable_diffusion_xl import StableDiffusionXLPipeline
        from .pipeline_stable_diffusion_xl_img2img import StableDiffusionXLImg2ImgPipeline
        from .pipeline_stable_diffusion_xl_inpaint import StableDiffusionXLInpaintPipeline
        from .pipeline_stable_diffusion_xl_instruct_pix2pix import StableDiffusionXLInstructPix2PixPipeline
    try:
        if not (is_transformers_available() and is_flax_available()): raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable: from ...utils.dummy_flax_objects import *
    else:
        from .pipeline_flax_stable_diffusion_xl import FlaxStableDiffusionXLPipeline
        from .pipeline_output import FlaxStableDiffusionXLPipelineOutput
else:
    import sys
    sys.modules[__name__] = _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
    for name, value in _dummy_objects.items(): setattr(sys.modules[__name__], name, value)
    for name, value in _additional_imports.items(): setattr(sys.modules[__name__], name, value)
'''
    #################################################################################################################################################################################################
    # This code library is an adaptation of the original Transformers and was designed, developed and programmed by Sapiens Technology®.                                                            #
    # Any alteration and/or disclosure of this code without prior authorization is strictly prohibited and is subject to legal action that will be forwarded by the Sapiens Technology® legal team. #
    # This set of algorithms aims to download, train, fine-tune and/or infer large language models from various sources and slopes.                                                                 #
    #################################################################################################################################################################################################
'''
