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

'''simple docstring'''


from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tokenizers_available,
    is_torch_available,
)


__lowerCAmelCase	:       Optional[Any]						       =	{
    "configuration_llama": ["LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP", "LlamaConfig"],
}

try:
					if not is_sentencepiece_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__lowerCAmelCase	:       str						       =	["LlamaTokenizer"]

try:
					if not is_tokenizers_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__lowerCAmelCase	:       str						       =	["LlamaTokenizerFast"]

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__lowerCAmelCase	:       Union[str, Any]						       =	[
					    "LlamaForCausalLM",
					    "LlamaModel",
					    "LlamaPreTrainedModel",
					    "LlamaForSequenceClassification",
					]


if TYPE_CHECKING:
					from .configuration_llama import LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP, LlamaConfig

					try:
										if not is_sentencepiece_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_llama import LlamaTokenizer

					try:
										if not is_tokenizers_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_llama_fast import LlamaTokenizerFast

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_llama import LlamaForCausalLM, LlamaForSequenceClassification, LlamaModel, LlamaPreTrainedModel


else:
					import sys

					__lowerCAmelCase	:       Optional[Any]						       =	_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
