

from argparse import ArgumentParser

from . import BaseTransformersCLICommand



def     __lowerCAmelCase						(							snake_case	:    Tuple )       ->							Tuple:
   return DownloadCommand(args.model						,      args.cache_dir						,      args.force						,      args.trust_remote_code )







class        a					(			__SCREAMING_SNAKE_CASE   ):





     @staticmethod
     def  SCREAMING_SNAKE_CASE__       (    SCREAMING_SNAKE_CASE_					:				ArgumentParser							):
        __lowerCamelCase:				Any     =	parser.add_parser("""download"""							)
        download_parser.add_argument(
            """--cache-dir"""    ,	type=_a    ,	default=_a    ,	help="""Path to location to store the models"""							)
        download_parser.add_argument(
            """--force"""    ,	action="""store_true"""    ,	help="""Force the model to be download even if already in cache-dir"""							)
        download_parser.add_argument(
            """--trust-remote-code"""    ,	action="""store_true"""    ,	help="""Whether or not to allow for custom models defined on the Hub in their own modeling files. Use only if you've reviewed the code as it will execute on your local machine"""    ,	)
        download_parser.add_argument("""model"""    ,	type=_a    ,	help="""Name of the model to download"""							)
        download_parser.set_defaults(func=_a							)





     def __init__(    self					:				List[str]    ,	SCREAMING_SNAKE_CASE_					:				str    ,	SCREAMING_SNAKE_CASE_					:				str    ,	SCREAMING_SNAKE_CASE_					:				bool    ,	SCREAMING_SNAKE_CASE_					:				bool							):
        __lowerCamelCase:				int     =	model
        __lowerCamelCase:				Tuple     =	cache
        __lowerCamelCase:				Tuple     =	force
        __lowerCamelCase:				str     =	trust_remote_code







     def  SCREAMING_SNAKE_CASE__       (    self					:				str							):
        from ..models.auto import AutoModel, AutoTokenizer

        AutoModel.from_pretrained(
            self._model    ,	cache_dir=self._cache    ,	force_download=self._force    ,	trust_remote_code=self._trust_remote_code							)
        AutoTokenizer.from_pretrained(
            self._model    ,	cache_dir=self._cache    ,	force_download=self._force    ,	trust_remote_code=self._trust_remote_code							)






from ..utils import (
    OptionalDependencyNotAvailable,
    is_flax_available,
    is_scipy_available,
    is_torch_available,
    is_torchsde_available,
)


try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   from ..utils.dummy_pt_objects import *  # noqa F403
else:
   from .scheduling_consistency_models import CMStochasticIterativeScheduler
   from .scheduling_ddim import DDIMScheduler
   from .scheduling_ddim_inverse import DDIMInverseScheduler
   from .scheduling_ddim_parallel import DDIMParallelScheduler
   from .scheduling_ddpm import DDPMScheduler
   from .scheduling_ddpm_parallel import DDPMParallelScheduler
   from .scheduling_deis_multistep import DEISMultistepScheduler
   from .scheduling_dpmsolver_multistep import DPMSolverMultistepScheduler
   from .scheduling_dpmsolver_multistep_inverse import DPMSolverMultistepInverseScheduler
   from .scheduling_dpmsolver_singlestep import DPMSolverSinglestepScheduler
   from .scheduling_euler_ancestral_discrete import EulerAncestralDiscreteScheduler
   from .scheduling_euler_discrete import EulerDiscreteScheduler
   from .scheduling_heun_discrete import HeunDiscreteScheduler
   from .scheduling_ipndm import IPNDMScheduler
   from .scheduling_k_dpm_2_ancestral_discrete import KDPMaAncestralDiscreteScheduler
   from .scheduling_k_dpm_2_discrete import KDPMaDiscreteScheduler
   from .scheduling_karras_ve import KarrasVeScheduler
   from .scheduling_pndm import PNDMScheduler
   from .scheduling_repaint import RePaintScheduler
   from .scheduling_sde_ve import ScoreSdeVeScheduler
   from .scheduling_sde_vp import ScoreSdeVpScheduler
   from .scheduling_unclip import UnCLIPScheduler
   from .scheduling_unipc_multistep import UniPCMultistepScheduler
   from .scheduling_utils import KarrasDiffusionSchedulers, SchedulerMixin
   from .scheduling_vq_diffusion import VQDiffusionScheduler

try:
   if not is_flax_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   from ..utils.dummy_flax_objects import *  # noqa F403
else:
   from .scheduling_ddim_flax import FlaxDDIMScheduler
   from .scheduling_ddpm_flax import FlaxDDPMScheduler
   from .scheduling_dpmsolver_multistep_flax import FlaxDPMSolverMultistepScheduler
   from .scheduling_karras_ve_flax import FlaxKarrasVeScheduler
   from .scheduling_lms_discrete_flax import FlaxLMSDiscreteScheduler
   from .scheduling_pndm_flax import FlaxPNDMScheduler
   from .scheduling_sde_ve_flax import FlaxScoreSdeVeScheduler
   from .scheduling_utils_flax import (
       FlaxKarrasDiffusionSchedulers,
       FlaxSchedulerMixin,
       FlaxSchedulerOutput,
       broadcast_to_shape_from_left,
   )


try:
   if not (is_torch_available() and is_scipy_available()):
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   from ..utils.dummy_torch_and_scipy_objects import *  # noqa F403
else:
   from .scheduling_lms_discrete import LMSDiscreteScheduler

try:
   if not (is_torch_available() and is_torchsde_available()):
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   from ..utils.dummy_torch_and_torchsde_objects import *  # noqa F403
else:
   from .scheduling_dpmsolver_sde import DPMSolverSDEScheduler


