


import timeit

import numpy as np

import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD



def     __lowerCAmelCase						(							snake_case	:    Optional[int] )       ->							Dict:
   def wrapper(*snake_case	:    Union[str, Any]						,      **snake_case	:    Optional[int] ):
      __lowerCamelCase:				str     =	timeit.default_timer()
      __lowerCamelCase:				Any     =	func(*snake_case						,      **snake_case )
      __lowerCamelCase:				Tuple     =	timeit.default_timer() - starttime
      return delta

   __lowerCamelCase:				List[Any]     =	func.__name__

   return wrapper



def     __lowerCAmelCase						(							snake_case	:    dict						,      snake_case	:    int=100						,      snake_case	:    int=None )       ->							Union[str, Any]:
   __lowerCamelCase:				Optional[int]     =	[]
   __lowerCamelCase:				List[str]     =	seq_shapes or {}
   for i in range(snake_case ):
      __lowerCamelCase:				Any     =	{}
      for col_id, (k, v) in enumerate(features.items() ):
         if isinstance(snake_case						,      _ArrayXD ):
            __lowerCamelCase:				Dict     =	np.random.rand(*v.shape ).astype(v.dtype )
         elif isinstance(snake_case						,      datasets.Value ):
            if v.dtype == "string":
               __lowerCamelCase:				Optional[Any]     =	"""The small grey turtle was surprisingly fast when challenged."""
            else:
               __lowerCamelCase:				Any     =	np.random.randint(10						,      size=1 ).astype(v.dtype ).item()
         elif isinstance(snake_case						,      datasets.Sequence ):
            while isinstance(snake_case						,      datasets.Sequence ):
               __lowerCamelCase:				Optional[int]     =	v.feature
            __lowerCamelCase:				str     =	seq_shapes[k]
            __lowerCamelCase:				str     =	np.random.rand(*snake_case ).astype(v.dtype )
         __lowerCamelCase:				Optional[int]     =	data

      dummy_data.append((i, example) )

   return dummy_data







def     __lowerCAmelCase						(							snake_case	:    List[str]						,      snake_case	:    str						,      snake_case	:    Union[str, Any]=100						,      snake_case	:    Tuple=None )       ->							List[Any]:
   __lowerCamelCase:				int     =	generate_examples(snake_case						,      num_examples=snake_case						,      seq_shapes=snake_case )

   with ArrowWriter(features=snake_case						,      path=snake_case ) as writer:
      for key, record in dummy_data:
         __lowerCamelCase:				List[Any]     =	features.encode_example(snake_case )
         writer.write(snake_case )

      __lowerCamelCase   ,     __lowerCamelCase:				Optional[Any]     =	writer.finalize()

   if not num_final_examples == num_examples:
      raise ValueError(
          f'Error writing the dataset, wrote {num_final_examples} examples but should have written {num_examples}.' )

   __lowerCamelCase:				Any     =	datasets.Dataset.from_file(filename=snake_case						,      info=datasets.DatasetInfo(features=snake_case ) )

   return dataset






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


