


"""simple docstring"""






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"""






import os

from bleurt import score  # From: git+https://github.com/google-research/bleurt.git

import datasets


_lowerCamelCase     =  datasets.logging.get_logger(__name__)


_lowerCamelCase     =  '\\n@inproceedings{bleurt,\n  title={BLEURT: Learning Robust Metrics for Text Generation},\n  author={Thibault Sellam and Dipanjan Das and Ankur P. Parikh},\n  booktitle={ACL},\n  year={2020},\n  url={https://arxiv.org/abs/2004.04696}\n}\n'

_lowerCamelCase     =  '\\nBLEURT a learnt evaluation metric for Natural Language Generation. It is built using multiple phases of transfer learning starting from a pretrained BERT model (Devlin et al. 2018)\nand then employing another pre-training phrase using synthetic data. Finally it is trained on WMT human annotations. You may run BLEURT out-of-the-box or fine-tune\nit for your specific application (the latter is expected to perform better).\n\nSee the project\'s README at https://github.com/google-research/bleurt#readme for more information.\n'

_lowerCamelCase     =  '\nBLEURT score.\n\nArgs:\n    `predictions` (list of str): prediction/candidate sentences\n    `references` (list of str): reference sentences\n    `checkpoint` BLEURT checkpoint. Will default to BLEURT-tiny if None.\n\nReturns:\n    \'scores\': List of scores.\nExamples:\n\n    >>> predictions = ["hello there", "general kenobi"]\n    >>> references = ["hello there", "general kenobi"]\n    >>> bleurt = datasets.load_metric("bleurt")\n    >>> results = bleurt.compute(predictions=predictions, references=references)\n    >>> print([round(v, 2) for v in results["scores"]])\n    [1.03, 1.04]\n'

_lowerCamelCase     =  {
    'bleurt-tiny-128': 'https://storage.googleapis.com/bleurt-oss/bleurt-tiny-128.zip',
    'bleurt-tiny-512': 'https://storage.googleapis.com/bleurt-oss/bleurt-tiny-512.zip',
    'bleurt-base-128': 'https://storage.googleapis.com/bleurt-oss/bleurt-base-128.zip',
    'bleurt-base-512': 'https://storage.googleapis.com/bleurt-oss/bleurt-base-512.zip',
    'bleurt-large-128': 'https://storage.googleapis.com/bleurt-oss/bleurt-large-128.zip',
    'bleurt-large-512': 'https://storage.googleapis.com/bleurt-oss/bleurt-large-512.zip',
    'BLEURT-20-D3': 'https://storage.googleapis.com/bleurt-oss-21/BLEURT-20-D3.zip',
    'BLEURT-20-D6': 'https://storage.googleapis.com/bleurt-oss-21/BLEURT-20-D6.zip',
    'BLEURT-20-D12': 'https://storage.googleapis.com/bleurt-oss-21/BLEURT-20-D12.zip',
    'BLEURT-20': 'https://storage.googleapis.com/bleurt-oss-21/BLEURT-20.zip',
}


@datasets.utils.file_utils.add_start_docstrings(_DESCRIPTION       ,  _KWARGS_DESCRIPTION   )
class 			lowerCamelCase_		(			datasets.Metric   ):





				"""simple docstring"""







				def   lowerCAmelCase__		(						self     ):
								return datasets.MetricInfo(
								    description=_DESCRIPTION       ,		citation=_CITATION       ,		homepage="https://github.com/google-research/bleurt"       ,		inputs_description=_KWARGS_DESCRIPTION       ,		features=datasets.Features(
								        {
								            "predictions": datasets.Value("string"       ,		id="sequence"     ),
								            "references": datasets.Value("string"       ,		id="sequence"     ),
								        }     )       ,		codebase_urls=["https://github.com/google-research/bleurt"]       ,		reference_urls=["https://github.com/google-research/bleurt", "https://arxiv.org/abs/2004.04696"]       ,		)



				def   lowerCAmelCase__		(						self       ,		UpperCAmelCase__     ):
								# check that config name specifies a valid BLEURT model
								if self.config_name == "default":
												logger.warning(
												    "Using default BLEURT-Base checkpoint for sequence maximum length 128. "
												    "You can use a bigger model for better results with e.g.: datasets.load_metric('bleurt', 'bleurt-large-512')."     )
												SCREAMING_SNAKE_CASE__     							=				"bleurt-base-128"

								if self.config_name.lower() in CHECKPOINT_URLS:
												SCREAMING_SNAKE_CASE__     							=				self.config_name.lower()

								elif self.config_name.upper() in CHECKPOINT_URLS:
												SCREAMING_SNAKE_CASE__     							=				self.config_name.upper()

								else:
												raise KeyError(
												    f'''{self.config_name} model not found. You should supply the name of a model checkpoint for bleurt in {CHECKPOINT_URLS.keys()}'''     )

								# download the model checkpoint specified by self.config_name and set up the scorer
								SCREAMING_SNAKE_CASE__     							=				dl_manager.download_and_extract(CHECKPOINT_URLS[checkpoint_name]     )
								SCREAMING_SNAKE_CASE__     							=				score.BleurtScorer(os.path.join(UpperCAmelCase__       ,		UpperCAmelCase__     )     )






				def   lowerCAmelCase__		(						self       ,		UpperCAmelCase__       ,		UpperCAmelCase__     ):
								SCREAMING_SNAKE_CASE__     							=				self.scorer.score(references=UpperCAmelCase__       ,		candidates=UpperCAmelCase__     )
								return {"scores": scores}
