

"""simple docstring"""




import json
import os
from typing import Optional, Tuple

import regex as re

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


A_							:			str											= logging.get_logger(__name__)

A_							:			List[str]											= {
    "vocab_file": "vocab.json",
    "merges_file": "merges.txt",
}

A_							:			Optional[int]											= {
    "vocab_file": {"ctrl": "https://raw.githubusercontent.com/salesforce/ctrl/master/ctrl-vocab.json"},
    "merges_file": {"ctrl": "https://raw.githubusercontent.com/salesforce/ctrl/master/ctrl-merges.txt"},
}

A_							:			str											= {
    "ctrl": 256,
}

A_							:			int											= {
    "Pregnancy": 168_629,
    "Christianity": 7_675,
    "Explain": 106_423,
    "Fitness": 63_440,
    "Saving": 63_163,
    "Ask": 27_171,
    "Ass": 95_985,
    "Joke": 163_509,
    "Questions": 45_622,
    "Thoughts": 49_605,
    "Retail": 52_342,
    "Feminism": 164_338,
    "Writing": 11_992,
    "Atheism": 192_263,
    "Netflix": 48_616,
    "Computing": 39_639,
    "Opinion": 43_213,
    "Alone": 44_967,
    "Funny": 58_917,
    "Gaming": 40_358,
    "Human": 4_088,
    "India": 1_331,
    "Joker": 77_138,
    "Diet": 36_206,
    "Legal": 11_859,
    "Norman": 4_939,
    "Tip": 72_689,
    "Weight": 52_343,
    "Movies": 46_273,
    "Running": 23_425,
    "Science": 2_090,
    "Horror": 37_793,
    "Confession": 60_572,
    "Finance": 12_250,
    "Politics": 16_360,
    "Scary": 191_985,
    "Support": 12_654,
    "Technologies": 32_516,
    "Teenage": 66_160,
    "Event": 32_769,
    "Learned": 67_460,
    "Notion": 182_770,
    "Wikipedia": 37_583,
    "Books": 6_665,
    "Extract": 76_050,
    "Confessions": 102_701,
    "Conspiracy": 75_932,
    "Links": 63_674,
    "Narcissus": 150_425,
    "Relationship": 54_766,
    "Relationships": 134_796,
    "Reviews": 41_671,
    "News": 4_256,
    "Translation": 26_820,
    "multilingual": 128_406,
}

def 	A       (     snake_case__    ):




			'''simple docstring'''


			SCREAMING_SNAKE_CASE__								=      set()
			SCREAMING_SNAKE_CASE__								=      word[0]
			for char in word[1:]:
						pairs.add((prev_char, char)    )
						SCREAMING_SNAKE_CASE__								=      char

			SCREAMING_SNAKE_CASE__								=      set(snake_case__    )
			return pairs





class    lowerCamelCase						(a__			):
			lowerCamelCase__   :		List[Any]							=							VOCAB_FILES_NAMES
			lowerCamelCase__   :		Dict							=							PRETRAINED_VOCAB_FILES_MAP
			lowerCamelCase__   :		Tuple							=							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			lowerCamelCase__   :		Union[str, Any]							=							CONTROL_CODES

			def __init__(					self				:						Optional[int]    ,				__UpperCAmelCase				:						Dict    ,				__UpperCAmelCase				:						int    ,				__UpperCAmelCase				:						str="<unk>"    ,				**__UpperCAmelCase				:						Union[str, Any]       )   ->    List[str]:
						super().__init__(unk_token=lowerCamelCase_    ,				**lowerCamelCase_       )

						with open(lowerCamelCase_    ,				encoding="""utf-8"""       ) as vocab_handle:
									SCREAMING_SNAKE_CASE__								=      json.load(lowerCamelCase_       )
						SCREAMING_SNAKE_CASE__								=      {v: k for k, v in self.encoder.items()}
						with open(lowerCamelCase_    ,				encoding="""utf-8"""       ) as merges_handle:
									SCREAMING_SNAKE_CASE__								=      merges_handle.read().split("""\n"""       )[1:-1]
						SCREAMING_SNAKE_CASE__								=      [tuple(merge.split()       ) for merge in merges]
						SCREAMING_SNAKE_CASE__								=      dict(zip(lowerCamelCase_    ,				range(len(lowerCamelCase_       )       )       )       )
						SCREAMING_SNAKE_CASE__								=      {}

			@property
			def 					SCREAMING_SNAKE_CASE				(					self				:						str       )   ->    int:
						return len(self.encoder       )

			def 					SCREAMING_SNAKE_CASE				(					self				:						List[str]       )   ->    List[Any]:
						return dict(self.encoder    ,				**self.added_tokens_encoder       )

			def 					SCREAMING_SNAKE_CASE				(					self				:						str    ,				__UpperCAmelCase				:						Tuple       )   ->    List[str]:
						if token in self.cache:
									return self.cache[token]
						SCREAMING_SNAKE_CASE__								=      tuple(lowerCamelCase_       )
						SCREAMING_SNAKE_CASE__								=      tuple(list(word[:-1]       ) + [word[-1] + """</w>"""]       )
						SCREAMING_SNAKE_CASE__								=      get_pairs(lowerCamelCase_       )

						if not pairs:
									return token

						while True:
									SCREAMING_SNAKE_CASE__								=      min(lowerCamelCase_    ,				key=lambda __UpperCAmelCase       : self.bpe_ranks.get(lowerCamelCase_    ,				float("""inf"""       )       )       )
									if bigram not in self.bpe_ranks:
												break
									SCREAMING_SNAKE_CASE__							,		SCREAMING_SNAKE_CASE__								=      bigram
									SCREAMING_SNAKE_CASE__								=      []
									SCREAMING_SNAKE_CASE__								=      0
									while i < len(lowerCamelCase_       ):
												try:
															SCREAMING_SNAKE_CASE__								=      word.index(lowerCamelCase_    ,				lowerCamelCase_       )
												except ValueError:
															new_word.extend(word[i:]       )
															break
												else:
															new_word.extend(word[i:j]       )
															SCREAMING_SNAKE_CASE__								=      j

												if word[i] == first and i < len(lowerCamelCase_       ) - 1 and word[i + 1] == second:
															new_word.append(first + second       )
															i += 2
												else:
															new_word.append(word[i]       )
															i += 1
									SCREAMING_SNAKE_CASE__								=      tuple(lowerCamelCase_       )
									SCREAMING_SNAKE_CASE__								=      new_word
									if len(lowerCamelCase_       ) == 1:
												break
									else:
												SCREAMING_SNAKE_CASE__								=      get_pairs(lowerCamelCase_       )
						SCREAMING_SNAKE_CASE__								=      """@@ """.join(lowerCamelCase_       )
						SCREAMING_SNAKE_CASE__								=      word[:-4]
						SCREAMING_SNAKE_CASE__								=      word
						return word

			def 					SCREAMING_SNAKE_CASE				(					self				:						Any    ,				__UpperCAmelCase				:						List[Any]       )   ->    List[Any]:
						SCREAMING_SNAKE_CASE__								=      []

						SCREAMING_SNAKE_CASE__								=      re.findall(r"""\S+\n?"""    ,				lowerCamelCase_       )

						for token in words:
									split_tokens.extend(list(self.bpe(lowerCamelCase_       ).split(""" """       )       )       )
						return split_tokens

			def 					SCREAMING_SNAKE_CASE				(					self				:						Optional[int]    ,				__UpperCAmelCase				:						List[str]       )   ->    str:
						return self.encoder.get(lowerCamelCase_    ,				self.encoder.get(self.unk_token       )       )

			def 					SCREAMING_SNAKE_CASE				(					self				:						Optional[int]    ,				__UpperCAmelCase				:						Dict       )   ->    int:
						return self.decoder.get(lowerCamelCase_    ,				self.unk_token       )

			def 					SCREAMING_SNAKE_CASE				(					self				:						int    ,				__UpperCAmelCase				:						List[Any]       )   ->    Any:
						SCREAMING_SNAKE_CASE__								=      """ """.join(lowerCamelCase_       ).replace("""@@ """    ,				""""""       ).strip()
						return out_string





			def 					SCREAMING_SNAKE_CASE				(					self				:						List[str]    ,				__UpperCAmelCase				:						Optional[int]    ,				__UpperCAmelCase				:						Union[str, Any] = None       )   ->    Tuple[str]:
						if not os.path.isdir(lowerCamelCase_       ):
									logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""       )
									return
						SCREAMING_SNAKE_CASE__								=      os.path.join(
						    lowerCamelCase_    ,				(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]       )
						SCREAMING_SNAKE_CASE__								=      os.path.join(
						    lowerCamelCase_    ,				(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""merges_file"""]       )

						with open(lowerCamelCase_    ,				"""w"""    ,				encoding="""utf-8"""       ) as f:
									f.write(json.dumps(self.encoder    ,				indent=2    ,				sort_keys=lowerCamelCase_    ,				ensure_ascii=lowerCamelCase_       ) + """\n"""       )

						SCREAMING_SNAKE_CASE__								=      0
						with open(lowerCamelCase_    ,				"""w"""    ,				encoding="""utf-8"""       ) as writer:
									writer.write("""#version: 0.2\n"""       )
									for bpe_tokens, token_index in sorted(self.bpe_ranks.items()    ,				key=lambda __UpperCAmelCase       : kv[1]       ):
												if index != token_index:
															logger.warning(
															    F"""Saving vocabulary to {merge_file}: BPE merge indices are not consecutive."""
															    """ Please check that the tokenizer is not corrupted!"""       )
															SCREAMING_SNAKE_CASE__								=      token_index
												writer.write(""" """.join(lowerCamelCase_       ) + """\n"""       )
												index += 1

						return vocab_file, merge_file

			# def decode(self, token_ids, skip_special_tokens=False, clean_up_tokenization_spaces=True):
			#     filtered_tokens = ' '.join(self.convert_ids_to_tokens(token_ids, skip_special_tokens=skip_special_tokens))
			#     tokens_generated_so_far = re.sub('(@@ )', '', string=filtered_tokens)
			#     tokens_generated_so_far = re.sub('(@@ ?$)', '', string=tokens_generated_so_far)
			#     return ''.join(tokens_generated_so_far)





"""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


