



import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


A__  :  str								=					logging.get_logger(__name__)


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

A__  :  Union[str, Any]								=					{
    '''vocab_file''': {
        '''allenai/longformer-base-4096''': '''https://huggingface.co/allenai/longformer-base-4096/resolve/main/vocab.json''',
        '''allenai/longformer-large-4096''': (
            '''https://huggingface.co/allenai/longformer-large-4096/resolve/main/vocab.json'''
        ),
        '''allenai/longformer-large-4096-finetuned-triviaqa''': (
            '''https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/vocab.json'''
        ),
        '''allenai/longformer-base-4096-extra.pos.embd.only''': (
            '''https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/vocab.json'''
        ),
        '''allenai/longformer-large-4096-extra.pos.embd.only''': (
            '''https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/vocab.json'''
        ),
    },
    '''merges_file''': {
        '''allenai/longformer-base-4096''': '''https://huggingface.co/allenai/longformer-base-4096/resolve/main/merges.txt''',
        '''allenai/longformer-large-4096''': (
            '''https://huggingface.co/allenai/longformer-large-4096/resolve/main/merges.txt'''
        ),
        '''allenai/longformer-large-4096-finetuned-triviaqa''': (
            '''https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/merges.txt'''
        ),
        '''allenai/longformer-base-4096-extra.pos.embd.only''': (
            '''https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/merges.txt'''
        ),
        '''allenai/longformer-large-4096-extra.pos.embd.only''': (
            '''https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/merges.txt'''
        ),
    },
}

A__  :  List[Any]								=					{
    '''allenai/longformer-base-4096''': 4096,
    '''allenai/longformer-large-4096''': 4096,
    '''allenai/longformer-large-4096-finetuned-triviaqa''': 4096,
    '''allenai/longformer-base-4096-extra.pos.embd.only''': 4096,
    '''allenai/longformer-large-4096-extra.pos.embd.only''': 4096,
}


@lru_cache()
# Copied from transformers.models.roberta.tokenization_roberta.bytes_to_unicode
def 			UpperCamelCase(  ):
		lowerCAmelCase_			:     Optional[Any]									= (
		    list(range(ord('''!''' )     ,ord('''~''' ) + 1 ) ) + list(range(ord('''¡''' )     ,ord('''¬''' ) + 1 ) ) + list(range(ord('''®''' )     ,ord('''ÿ''' ) + 1 ) )
		)
		lowerCAmelCase_			:     Any									= bs[:]
		lowerCAmelCase_			:     Tuple									= 0
		for b in range(2**8 ):
				if b not in bs:
						bs.append(__UpperCamelCase )
						cs.append(2**8 + n )
						n += 1
		lowerCAmelCase_			:     Optional[int]									= [chr(__UpperCamelCase ) for n in cs]
		return dict(zip(__UpperCamelCase     ,__UpperCamelCase ) )


def 			UpperCamelCase(  __UpperCamelCase							:		Union[str, Any] ):
		lowerCAmelCase_			:     str									= set()
		lowerCAmelCase_			:     List[str]									= word[0]
		for char in word[1:]:
				pairs.add((prev_char, char) )
				lowerCAmelCase_			:     str									= char
		return pairs





class 				__snake_case						(     UpperCamelCase_						):
							_a			      = VOCAB_FILES_NAMES
							_a			      = PRETRAINED_VOCAB_FILES_MAP
							_a			      = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							_a			      = ['''input_ids''', '''attention_mask''']




							def __init__(       self     :       Any				,				A_     :       Dict				,				A_     :       Tuple				,				A_     :       List[str]="replace"				,				A_     :       str="<s>"				,				A_     :       int="</s>"				,				A_     :       Tuple="</s>"				,				A_     :       int="<s>"				,				A_     :       Any="<unk>"				,				A_     :       Optional[Any]="<pad>"				,				A_     :       List[str]="<mask>"				,				A_     :       Union[str, Any]=False				,				**A_     :       Optional[Any]				,				):
									lowerCAmelCase_			:     str									= AddedToken(A_				,				lstrip=A_				,				rstrip=A_) if isinstance(A_				,				A_) else bos_token
									lowerCAmelCase_			:     Any									= AddedToken(A_				,				lstrip=A_				,				rstrip=A_) if isinstance(A_				,				A_) else eos_token
									lowerCAmelCase_			:     List[Any]									= AddedToken(A_				,				lstrip=A_				,				rstrip=A_) if isinstance(A_				,				A_) else sep_token
									lowerCAmelCase_			:     Union[str, Any]									= AddedToken(A_				,				lstrip=A_				,				rstrip=A_) if isinstance(A_				,				A_) else cls_token
									lowerCAmelCase_			:     Any									= AddedToken(A_				,				lstrip=A_				,				rstrip=A_) if isinstance(A_				,				A_) else unk_token
									lowerCAmelCase_			:     int									= AddedToken(A_				,				lstrip=A_				,				rstrip=A_) if isinstance(A_				,				A_) else pad_token

									# Mask token behave like a normal word, i.e. include the space before it
									lowerCAmelCase_			:     Any									= AddedToken(A_				,				lstrip=A_				,				rstrip=A_) if isinstance(A_				,				A_) else mask_token

									super().__init__(
									    errors=A_				,				bos_token=A_				,				eos_token=A_				,				unk_token=A_				,				sep_token=A_				,				cls_token=A_				,				pad_token=A_				,				mask_token=A_				,				add_prefix_space=A_				,				**A_				,				)

									with open(A_				,				encoding='''utf-8''') as vocab_handle:
											lowerCAmelCase_			:     Any									= json.load(A_)
									lowerCAmelCase_			:     int									= {v: k for k, v in self.encoder.items()}
									lowerCAmelCase_			:     List[Any]									= errors  # how to handle errors in decoding
									lowerCAmelCase_			:     Dict									= bytes_to_unicode()
									lowerCAmelCase_			:     Optional[int]									= {v: k for k, v in self.byte_encoder.items()}
									with open(A_				,				encoding='''utf-8''') as merges_handle:
											lowerCAmelCase_			:     Any									= merges_handle.read().split('''\n''')[1:-1]
									lowerCAmelCase_			:     List[Any]									= [tuple(merge.split()) for merge in bpe_merges]
									lowerCAmelCase_			:     Union[str, Any]									= dict(zip(A_				,				range(len(A_))))
									lowerCAmelCase_			:     Optional[int]									= {}
									lowerCAmelCase_			:     Optional[int]									= add_prefix_space

									# Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
									lowerCAmelCase_			:     Union[str, Any]									= re.compile(r'''\'s|\'t|\'re|\'ve|\'m|\'ll|\'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+''')




							@property
							def    UpperCAmelCase__			(       self     :       Optional[Any]):
									return len(self.encoder)




							def    UpperCAmelCase__			(       self     :       List[str]):
									return dict(self.encoder				,				**self.added_tokens_encoder)




							def    UpperCAmelCase__			(       self     :       Dict				,				A_     :       List[str]):
									if token in self.cache:
											return self.cache[token]
									lowerCAmelCase_			:     List[Any]									= tuple(A_)
									lowerCAmelCase_			:     Optional[Any]									= get_pairs(A_)

									if not pairs:
											return token

									while True:
											lowerCAmelCase_			:     int									= min(A_				,				key=lambda A_: self.bpe_ranks.get(A_				,				float('''inf''')))
											if bigram not in self.bpe_ranks:
													break
											lowerCAmelCase_					,  lowerCAmelCase_			:     List[Any]									= bigram
											lowerCAmelCase_			:     Any									= []
											lowerCAmelCase_			:     Union[str, Any]									= 0
											while i < len(A_):
													try:
															lowerCAmelCase_			:     List[str]									= word.index(A_				,				A_)
													except ValueError:
															new_word.extend(word[i:])
															break
													else:
															new_word.extend(word[i:j])
															lowerCAmelCase_			:     Union[str, Any]									= j

													if word[i] == first and i < len(A_) - 1 and word[i + 1] == second:
															new_word.append(first + second)
															i += 2
													else:
															new_word.append(word[i])
															i += 1
											lowerCAmelCase_			:     Union[str, Any]									= tuple(A_)
											lowerCAmelCase_			:     List[Any]									= new_word
											if len(A_) == 1:
													break
											else:
													lowerCAmelCase_			:     List[Any]									= get_pairs(A_)
									lowerCAmelCase_			:     Any									= ''' '''.join(A_)
									lowerCAmelCase_			:     Any									= word
									return word




							def    UpperCAmelCase__			(       self     :       str				,				A_     :       Optional[Any]):
									lowerCAmelCase_			:     Optional[Any]									= []
									for token in re.findall(self.pat				,				A_):
											lowerCAmelCase_			:     List[Any]									= ''''''.join(
											    self.byte_encoder[b] for b in token.encode('''utf-8'''))  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
											bpe_tokens.extend(bpe_token for bpe_token in self.bpe(A_).split(''' '''))
									return bpe_tokens




							def    UpperCAmelCase__			(       self     :       Any				,				A_     :       str):
									return self.encoder.get(A_				,				self.encoder.get(self.unk_token))




							def    UpperCAmelCase__			(       self     :       str				,				A_     :       int):
									return self.decoder.get(A_)




							def    UpperCAmelCase__			(       self     :       Union[str, Any]				,				A_     :       Tuple):
									lowerCAmelCase_			:     Optional[int]									= ''''''.join(A_)
									lowerCAmelCase_			:     Optional[Any]									= bytearray([self.byte_decoder[c] for c in text]).decode('''utf-8'''				,				errors=self.errors)
									return text




							def    UpperCAmelCase__			(       self     :       List[Any]				,				A_     :       str				,				A_     :       Optional[str] = None):
									if not os.path.isdir(A_):
											logger.error(F"""Vocabulary path ({save_directory}) should be a directory""")
											return
									lowerCAmelCase_			:     Union[str, Any]									= os.path.join(
									    A_				,				(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file'''])
									lowerCAmelCase_			:     List[Any]									= os.path.join(
									    A_				,				(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''merges_file'''])

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

									lowerCAmelCase_			:     str									= 0
									with open(A_				,				'''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 A_: 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!''')
															lowerCAmelCase_			:     Any									= token_index
													writer.write(''' '''.join(A_) + '''\n''')
													index += 1

									return vocab_file, merge_file




							def    UpperCAmelCase__			(       self     :       List[str]				,				A_     :       List[int]				,				A_     :       Optional[List[int]] = None):
									if token_ids_a is None:
											return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
									lowerCAmelCase_			:     List[Any]									= [self.cls_token_id]
									lowerCAmelCase_			:     Tuple									= [self.sep_token_id]
									return cls + token_ids_a + sep + sep + token_ids_a + sep




							def    UpperCAmelCase__			(       self     :       int				,				A_     :       List[int]				,				A_     :       Optional[List[int]] = None				,				A_     :       bool = False):
									if already_has_special_tokens:
											return super().get_special_tokens_mask(
											    token_ids_a=A_				,				token_ids_a=A_				,				already_has_special_tokens=A_)

									if token_ids_a is None:
											return [1] + ([0] * len(A_)) + [1]
									return [1] + ([0] * len(A_)) + [1, 1] + ([0] * len(A_)) + [1]




							def    UpperCAmelCase__			(       self     :       str				,				A_     :       List[int]				,				A_     :       Optional[List[int]] = None):
									lowerCAmelCase_			:     Optional[Any]									= [self.sep_token_id]
									lowerCAmelCase_			:     str									= [self.cls_token_id]

									if token_ids_a is None:
											return len(cls + token_ids_a + sep) * [0]
									return len(cls + token_ids_a + sep + sep + token_ids_a + sep) * [0]







							def    UpperCAmelCase__			(       self     :       Dict				,				A_     :       Any				,				A_     :       str=False				,				**A_     :       Optional[int]):
									lowerCAmelCase_			:     Union[str, Any]									= kwargs.pop('''add_prefix_space'''				,				self.add_prefix_space)
									if (is_split_into_words or add_prefix_space) and (len(A_) > 0 and not text[0].isspace()):
											lowerCAmelCase_			:     str									= ''' ''' + text
									return (text, kwargs)










import darl  # noqa
import gym
import tqdm
from diffusers.experimental import ValueGuidedRLPipeline


A__  :  Union[str, Any]								=					{
    '''n_samples''': 64,
    '''horizon''': 32,
    '''num_inference_steps''': 20,
    '''n_guide_steps''': 2,  # can set to 0 for faster sampling, does not use value network
    '''scale_grad_by_std''': True,
    '''scale''': 0.1,
    '''eta''': 0.0,
    '''t_grad_cutoff''': 2,
    '''device''': '''cpu''',
}


if __name__ == "__main__":
						A__  :  Optional[int]								=					'''hopper-medium-v2'''
						A__  :  int								=					gym.make(env_name)

						A__  :  Optional[int]								=					ValueGuidedRLPipeline.from_pretrained(
						    '''bglick13/hopper-medium-v2-value-function-hor32''',
						    env=env,
						)

						env.seed(0)
						A__  :  int								=					env.reset()
						A__  :  Optional[int]								=					0
						A__  :  Union[str, Any]								=					0
						A__  :  Union[str, Any]								=					1000
						A__  :  Optional[Any]								=					[obs.copy()]
						try:
												for t in tqdm.tqdm(range(T)):
																		# call the policy
																		A__  :  Union[str, Any]								=					pipeline(obs, planning_horizon=32)

																		# execute action in environment
																		A__					,     A__					,     A__					,     A__  :  str								=					env.step(denorm_actions)
																		A__  :  Dict								=					env.get_normalized_score(total_reward)

																		# update return
																		total_reward += reward
																		total_score += score
																		print(
																		    F'''Step: {t}, Reward: {reward}, Total Reward: {total_reward}, Score: {score}, Total Score:'''
																		    F''' {total_score}'''
																		)

																		# save observations for rendering
																		rollout.append(next_observation.copy())

																		A__  :  List[str]								=					next_observation
						except KeyboardInterrupt:
												pass

						print(F'''Total reward: {total_reward}''')





