




'''simple docstring'''





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

import regex as re

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


if TYPE_CHECKING:
		from transformers.pipelines.conversational import Conversation

_SCREAMING_SNAKE_CASE							:       Union[str, Any]						=			logging.get_logger(__name__)


_SCREAMING_SNAKE_CASE							:       Any						=			{
    "vocab_file": "vocab.json",
    "merges_file": "merges.txt",
    "tokenizer_config_file": "tokenizer_config.json",
}

_SCREAMING_SNAKE_CASE							:       Tuple						=			{
    "vocab_file": {"facebook/blenderbot-3B": "https://huggingface.co/facebook/blenderbot-3B/resolve/main/vocab.json"},
    "merges_file": {"facebook/blenderbot-3B": "https://huggingface.co/facebook/blenderbot-3B/resolve/main/merges.txt"},
    "tokenizer_config_file": {
        "facebook/blenderbot-3B": "https://huggingface.co/facebook/blenderbot-3B/resolve/main/tokenizer_config.json"
    },
}

_SCREAMING_SNAKE_CASE							:       Dict						=			{"facebook/blenderbot-3B": 128}


@lru_cache()
# Copied from transformers.models.roberta.tokenization_roberta.bytes_to_unicode
def 					UpperCamelCase_(     ):

							'''simple docstring'''






							snake_case_      =				(
							    list(range(ord("!"					)							,    ord("~"					) + 1					)					) + list(range(ord("¡"					)							,    ord("¬"					) + 1					)					) + list(range(ord("®"					)							,    ord("ÿ"					) + 1					)					)
							)
							snake_case_      =				bs[:]
							snake_case_      =				0
							for b in range(2**8					):
														if b not in bs:
																					bs.append(snake_case					)
																					cs.append(2**8 + n					)
																					n += 1
							snake_case_      =				[chr(snake_case					) for n in cs]
							return dict(zip(snake_case							,    snake_case					)					)


def 					UpperCamelCase_(     snake_case							:	Any					):

							'''simple docstring'''






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




class 			_snake_case		(     lowercase_							):
			lowerCAmelCase_					:				Union[str, Any]							=   VOCAB_FILES_NAMES
			lowerCAmelCase_					:				int							=   PRETRAINED_VOCAB_FILES_MAP
			lowerCAmelCase_					:				List[Any]							=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			lowerCAmelCase_					:				Union[str, Any]							=   ["input_ids", "attention_mask"]




			def __init__( self    ,							a__    ,							a__    ,							a__="replace"    ,							a__="<s>"    ,							a__="</s>"    ,							a__="</s>"    ,							a__="<s>"    ,							a__="<unk>"    ,							a__="<pad>"    ,							a__="<mask>"    ,							a__=False    ,							**a__    ,							)    ->    Any:

										'''simple docstring'''




										snake_case_      =				AddedToken(a__    ,							lstrip=a__    ,							rstrip=a__							) if isinstance(a__    ,							a__							) else bos_token
										snake_case_      =				AddedToken(a__    ,							lstrip=a__    ,							rstrip=a__							) if isinstance(a__    ,							a__							) else eos_token
										snake_case_      =				AddedToken(a__    ,							lstrip=a__    ,							rstrip=a__							) if isinstance(a__    ,							a__							) else sep_token
										snake_case_      =				AddedToken(a__    ,							lstrip=a__    ,							rstrip=a__							) if isinstance(a__    ,							a__							) else cls_token
										snake_case_      =				AddedToken(a__    ,							lstrip=a__    ,							rstrip=a__							) if isinstance(a__    ,							a__							) else unk_token
										snake_case_      =				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
										snake_case_      =				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:
																	snake_case_      =				json.load(a__							)
										snake_case_      =				{v: k for k, v in self.encoder.items()}
										snake_case_      =				errors  # how to handle errors in decoding
										snake_case_      =				bytes_to_unicode()
										snake_case_      =				{v: k for k, v in self.byte_encoder.items()}
										with open(a__    ,							encoding="utf-8"							) as merges_handle:
																	snake_case_      =				merges_handle.read().split("\n"							)[1:-1]
										snake_case_      =				[tuple(merge.split()							) for merge in bpe_merges]
										snake_case_      =				dict(zip(a__    ,							range(len(a__							)							)							)							)
										snake_case_      =				{}
										snake_case_      =				add_prefix_space

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




			@property
			# Copied from transformers.models.roberta.tokenization_roberta.RobertaTokenizer.vocab_size with Roberta->Blenderbot, RoBERTa->Blenderbot
			def        lowerCAmelCase__    ( self							)    ->    Tuple:

										'''simple docstring'''




										return len(self.encoder							)




			def        lowerCAmelCase__    ( self							)    ->    str:

										'''simple docstring'''




										return dict(self.encoder    ,							**self.added_tokens_encoder							)




			def        lowerCAmelCase__    ( self    ,							a__							)    ->    Any:

										'''simple docstring'''




										if token in self.cache:
																	return self.cache[token]
										snake_case_      =				tuple(a__							)
										snake_case_      =				get_pairs(a__							)

										if not pairs:
																	return token

										while True:
																	snake_case_      =				min(a__    ,							key=lambda a__							: self.bpe_ranks.get(a__    ,							float("inf"							)							)							)
																	if bigram not in self.bpe_ranks:
																								break
																	snake_case_ ,				snake_case_      =				bigram
																	snake_case_      =				[]
																	snake_case_      =				0
																	while i < len(a__							):
																								try:
																															snake_case_      =				word.index(a__    ,							a__							)
																								except ValueError:
																															new_word.extend(word[i:]							)
																															break
																								else:
																															new_word.extend(word[i:j]							)
																															snake_case_      =				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
																	snake_case_      =				tuple(a__							)
																	snake_case_      =				new_word
																	if len(a__							) == 1:
																								break
																	else:
																								snake_case_      =				get_pairs(a__							)
										snake_case_      =				" ".join(a__							)
										snake_case_      =				word
										return word




			def        lowerCAmelCase__    ( self    ,							a__							)    ->    Optional[int]:

										'''simple docstring'''




										snake_case_      =				[]
										for token in re.findall(self.pat    ,							a__							):
																	snake_case_      =				"".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        lowerCAmelCase__    ( self    ,							a__							)    ->    Optional[Any]:

										'''simple docstring'''




										return self.encoder.get(a__    ,							self.encoder.get(self.unk_token							)							)




			def        lowerCAmelCase__    ( self    ,							a__							)    ->    Union[str, Any]:

										'''simple docstring'''




										return self.decoder.get(a__							)




			def        lowerCAmelCase__    ( self    ,							a__							)    ->    List[str]:

										'''simple docstring'''




										snake_case_      =				"".join(a__							)
										snake_case_      =				bytearray([self.byte_decoder[c] for c in text]							).decode("utf-8"    ,							errors=self.errors							)
										return text




			def        lowerCAmelCase__    ( self    ,							a__    ,							a__ = None							)    ->    Tuple[str]:

										'''simple docstring'''




										if not os.path.isdir(a__							):
																	logger.error(F'Vocabulary path ({save_directory}) should be a directory'							)
																	return
										snake_case_      =				os.path.join(
										    a__    ,							(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]							)
										snake_case_      =				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"							)

										snake_case_      =				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!"							)
																															snake_case_      =				token_index
																								writer.write(" ".join(a__							) + "\n"							)
																								index += 1

										return vocab_file, merge_file




			def        lowerCAmelCase__    ( self    ,							a__    ,							a__ = None    ,							a__ = False							)    ->    List[int]:

										'''simple docstring'''




										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        lowerCAmelCase__    ( self    ,							a__    ,							a__ = None							)    ->    List[int]:

										'''simple docstring'''




										snake_case_      =				[self.sep_token_id]
										snake_case_      =				[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        lowerCAmelCase__    ( self    ,							a__    ,							a__=False    ,							**a__							)    ->    Optional[Any]:

										'''simple docstring'''




										snake_case_      =				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()):
																	snake_case_      =				" " + text
										return (text, kwargs)




			def        lowerCAmelCase__    ( self    ,							a__    ,							a__ = None							)    ->    str:

										'''simple docstring'''




										return token_ids_a + [self.eos_token_id]




			def        lowerCAmelCase__    ( self    ,							a__							)    ->    List[int]:

										'''simple docstring'''




										snake_case_      =				[]
										for is_user, text in conversation.iter_texts():
																	if is_user:
																								# We need to space prefix as it's being done within blenderbot
																								inputs.append(" " + text							)
																	else:
																								# Generated responses should contain them already.
																								inputs.append(a__							)

										snake_case_      =				"  ".join(a__							)
										snake_case_      =				self.encode(a__							)
										if len(a__							) > self.model_max_length:
																	snake_case_      =				input_ids[-self.model_max_length :]
																	logger.warning(F'Trimmed input from conversation as it was longer than {self.model_max_length} tokens.'							)
										return input_ids










'''simple docstring'''





from ...configuration_utils import PretrainedConfig
from ...utils import logging


_SCREAMING_SNAKE_CASE							:       List[Any]						=			logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE							:       Optional[int]						=			{
    "edbeeching/decision-transformer-gym-hopper-medium": (
        "https://huggingface.co/edbeeching/decision-transformer-gym-hopper-medium/resolve/main/config.json"
    ),
    # See all DecisionTransformer models at https://huggingface.co/models?filter=decision_transformer
}




class 			_snake_case		(     lowercase_							):
			lowerCAmelCase_					:				Dict							=   "decision_transformer"
			lowerCAmelCase_					:				List[Any]							=   ["past_key_values"]
			lowerCAmelCase_					:				Tuple							=   {
			    "max_position_embeddings": "n_positions",
			    "num_attention_heads": "n_head",
			    "num_hidden_layers": "n_layer",
			}




			def __init__( self    ,							a__=17    ,							a__=4    ,							a__=128    ,							a__=4_096    ,							a__=True    ,							a__=1    ,							a__=1_024    ,							a__=3    ,							a__=1    ,							a__=None    ,							a__="relu"    ,							a__=0.1    ,							a__=0.1    ,							a__=0.1    ,							a__=1e-5    ,							a__=0.0_2    ,							a__=True    ,							a__=True    ,							a__=50_256    ,							a__=50_256    ,							a__=False    ,							a__=False    ,							**a__    ,							)    ->    Optional[int]:

										'''simple docstring'''




										snake_case_      =				state_dim
										snake_case_      =				act_dim
										snake_case_      =				hidden_size
										snake_case_      =				max_ep_len
										snake_case_      =				action_tanh
										snake_case_      =				vocab_size
										snake_case_      =				n_positions
										snake_case_      =				n_layer
										snake_case_      =				n_head
										snake_case_      =				n_inner
										snake_case_      =				activation_function
										snake_case_      =				resid_pdrop
										snake_case_      =				embd_pdrop
										snake_case_      =				attn_pdrop
										snake_case_      =				layer_norm_epsilon
										snake_case_      =				initializer_range
										snake_case_      =				scale_attn_weights
										snake_case_      =				use_cache
										snake_case_      =				scale_attn_by_inverse_layer_idx
										snake_case_      =				reorder_and_upcast_attn

										snake_case_      =				bos_token_id
										snake_case_      =				eos_token_id

										super().__init__(bos_token_id=a__    ,							eos_token_id=a__    ,							**a__							)




