import uuid
from typing import Any, Dict, List, Optional, Union

from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline


if is_tf_available():
						import tensorflow as tf

if is_torch_available():
						import torch


A_      =      logging.get_logger(__name__)






class      __lowercase					:

						def __init__(	self				:      str							,							__lowerCamelCase				:      str = None							,							__lowerCamelCase				:      uuid.UUID = None							,							__lowerCamelCase				:      Any=None							,							__lowerCamelCase				:      List[Any]=None   )							->		Dict:


									'''simple docstring'''

									if not conversation_id:
												lowercase							=		uuid.uuida()
									if past_user_inputs is None:
												lowercase							=		[]
									if generated_responses is None:
												lowercase							=		[]

									lowercase							=		conversation_id
									lowercase							=		past_user_inputs
									lowercase							=		generated_responses
									lowercase							=		text

						def __eq__(	self				:      List[str]							,							__lowerCamelCase				:      Optional[Any]   )							->		List[Any]:


									'''simple docstring'''

									if not isinstance(__lowerCamelCase							,							__lowerCamelCase   ):
												return False
									if self.uuid == other.uuid:
												return True
									return (
									    self.new_user_input == other.new_user_input
									    and self.past_user_inputs == other.past_user_inputs
									    and self.generated_responses == other.generated_responses
									)

						def        __a		(	self				:      List[str]							,							__lowerCamelCase				:      str							,							__lowerCamelCase				:      bool = False   )							->		List[Any]:


									'''simple docstring'''

									if self.new_user_input:
												if overwrite:
															logger.warning(
															    f'User input added while unprocessed input was existing: "{self.new_user_input}" was overwritten '
															    f'with: "{text}".'   )
															lowercase							=		text
												else:
															logger.warning(
															    f'User input added while unprocessed input was existing: "{self.new_user_input}" new input '
															    f'ignored: "{text}". Set `overwrite` to True to overwrite unprocessed user input'   )
									else:
												lowercase							=		text

						def        __a		(	self				:      List[Any]   )							->		List[str]:


									'''simple docstring'''

									if self.new_user_input:
												self.past_user_inputs.append(self.new_user_input   )
									lowercase							=		None

						def        __a		(	self				:      str							,							__lowerCamelCase				:      str   )							->		Optional[Any]:


									'''simple docstring'''

									self.generated_responses.append(__lowerCamelCase   )

						def        __a		(	self				:      Optional[Any]   )							->		List[str]:


									'''simple docstring'''

									for user_input, generated_response in zip(self.past_user_inputs							,							self.generated_responses   ):
												yield True, user_input
												yield False, generated_response
									if self.new_user_input:
												yield True, self.new_user_input



						def __repr__(	self				:      Any   )							->		Any:


									'''simple docstring'''

									lowercase							=		f'Conversation id: {self.uuid} \n'
									for is_user, text in self.iter_texts():
												lowercase							=		'''user''' if is_user else '''bot'''
												output += f'{name} >> {text} \n'
									return output






@add_end_docstrings(
    _A       ,     R'\n        min_length_for_response (`int`, *optional*, defaults to 32):\n            The minimum length (in number of tokens) for a response.\n        minimum_tokens (`int`, *optional*, defaults to 10):\n            The minimum length of tokens to leave for a response.\n    '       ,     )
class      __lowercase					(    _A    ):

						def __init__(	self				:      Dict							,							*__lowerCamelCase				:      List[Any]							,							**__lowerCamelCase				:      Optional[Any]   )							->		Optional[int]:


									'''simple docstring'''

									super().__init__(*__lowerCamelCase							,							**__lowerCamelCase   )
									if self.tokenizer.pad_token_id is None:
												lowercase							=		self.tokenizer.eos_token

						def        __a		(	self				:      str							,							__lowerCamelCase				:      int=None							,							__lowerCamelCase				:      Tuple=None							,							__lowerCamelCase				:      str=None							,							**__lowerCamelCase				:      Optional[Any]   )							->		Optional[Any]:


									'''simple docstring'''

									lowercase							=		{}
									lowercase							=		{}
									lowercase							=		{}

									if min_length_for_response is not None:
												lowercase							=		min_length_for_response
									if minimum_tokens is not None:
												lowercase							=		minimum_tokens

									if "max_length" in generate_kwargs:
												lowercase							=		generate_kwargs['''max_length''']
												# self.max_length = generate_kwargs.get("max_length", self.model.config.max_length)
									if clean_up_tokenization_spaces is not None:
												lowercase							=		clean_up_tokenization_spaces

									if generate_kwargs:
												forward_params.update(__lowerCamelCase   )
									return preprocess_params, forward_params, postprocess_params

						def __call__(	self				:      Union[str, Any]							,							__lowerCamelCase				:      Union[Conversation, List[Conversation]]							,							__lowerCamelCase				:      List[Any]=0							,							**__lowerCamelCase				:      Dict   )							->		str:


									'''simple docstring'''

									lowercase							=		super().__call__(__lowerCamelCase							,							num_workers=__lowerCamelCase							,							**__lowerCamelCase   )
									if isinstance(__lowerCamelCase							,							__lowerCamelCase   ) and len(__lowerCamelCase   ) == 1:
												return outputs[0]
									return outputs

						def        __a		(	self				:      Dict							,							__lowerCamelCase				:      Conversation							,							__lowerCamelCase				:      Optional[int]=32   )							->		Dict[str, Any]:


									'''simple docstring'''

									if not isinstance(__lowerCamelCase							,							__lowerCamelCase   ):
												raise ValueError('''ConversationalPipeline, expects Conversation as inputs'''   )
									if conversation.new_user_input is None:
												raise ValueError(
												    f'Conversation with UUID {type(conversation.uuid   )} does not contain new user input to process. '
												    '''Add user inputs with the conversation\'s `add_user_input` method'''   )
									if hasattr(self.tokenizer							,							'''_build_conversation_input_ids'''   ):
												lowercase							=		self.tokenizer._build_conversation_input_ids(__lowerCamelCase   )
									else:
												# If the tokenizer cannot handle conversations, we default to only the old version
												lowercase							=		self._legacy_parse_and_tokenize(__lowerCamelCase   )

									if self.framework == "pt":
												lowercase							=		torch.LongTensor([input_ids]   )
									elif self.framework == "tf":
												lowercase							=		tf.constant([input_ids]   )
									return {"input_ids": input_ids, "conversation": conversation}

						def        __a		(	self				:      Optional[Any]							,							__lowerCamelCase				:      Union[str, Any]							,							__lowerCamelCase				:      Union[str, Any]=10							,							**__lowerCamelCase				:      int   )							->		Any:


									'''simple docstring'''

									lowercase							=		generate_kwargs.get('''max_length'''							,							self.model.config.max_length   )

									lowercase							=		model_inputs['''input_ids'''].shape[1]
									if max_length - minimum_tokens < n:
												logger.warning(f'Conversation input is to long ({n}), trimming it to ({max_length} - {minimum_tokens})'   )
												lowercase							=		max_length - minimum_tokens
												lowercase							=		model_inputs['''input_ids'''][:, -trim:]
												if "attention_mask" in model_inputs:
															lowercase							=		model_inputs['''attention_mask'''][:, -trim:]
									lowercase							=		model_inputs.pop('''conversation'''   )
									lowercase							=		max_length
									lowercase							=		self.model.generate(**__lowerCamelCase							,							**__lowerCamelCase   )
									if self.model.config.is_encoder_decoder:
												lowercase							=		1
									else:
												lowercase							=		n
									return {"output_ids": output_ids[:, start_position:], "conversation": conversation}

						def        __a		(	self				:      Dict							,							__lowerCamelCase				:      List[str]							,							__lowerCamelCase				:      int=True   )							->		str:


									'''simple docstring'''

									lowercase							=		model_outputs['''output_ids''']
									lowercase							=		self.tokenizer.decode(
									    output_ids[0]							,							skip_special_tokens=__lowerCamelCase							,							clean_up_tokenization_spaces=__lowerCamelCase							,							)
									lowercase							=		model_outputs['''conversation''']
									conversation.mark_processed()
									conversation.append_response(__lowerCamelCase   )
									return conversation



						def        __a		(	self				:      Dict							,							__lowerCamelCase				:      Conversation   )							->		Dict:


									'''simple docstring'''

									lowercase							=		self.tokenizer.eos_token_id
									lowercase							=		[]
									for is_user, text in conversation.iter_texts():
												if eos_token_id is not None:
															input_ids.extend(self.tokenizer.encode(__lowerCamelCase							,							add_special_tokens=__lowerCamelCase   ) + [eos_token_id]   )
												else:
															input_ids.extend(self.tokenizer.encode(__lowerCamelCase							,							add_special_tokens=__lowerCamelCase   )   )

									if len(__lowerCamelCase   ) > self.tokenizer.model_max_length:
												lowercase							=		input_ids[-self.tokenizer.model_max_length :]
									return input_ids






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_      =      logging.get_logger(__name__)


A_      =      {"vocab_file": "vocab.json", "merges_file": "merges.txt"}

# See all BART models at https://huggingface.co/models?filter=bart
A_      =      {
    "vocab_file": {
        "facebook/bart-base": "https://huggingface.co/facebook/bart-base/resolve/main/vocab.json",
        "facebook/bart-large": "https://huggingface.co/facebook/bart-large/resolve/main/vocab.json",
        "facebook/bart-large-mnli": "https://huggingface.co/facebook/bart-large-mnli/resolve/main/vocab.json",
        "facebook/bart-large-cnn": "https://huggingface.co/facebook/bart-large-cnn/resolve/main/vocab.json",
        "facebook/bart-large-xsum": "https://huggingface.co/facebook/bart-large-xsum/resolve/main/vocab.json",
        "yjernite/bart_eli5": "https://huggingface.co/yjernite/bart_eli5/resolve/main/vocab.json",
    },
    "merges_file": {
        "facebook/bart-base": "https://huggingface.co/facebook/bart-base/resolve/main/merges.txt",
        "facebook/bart-large": "https://huggingface.co/facebook/bart-large/resolve/main/merges.txt",
        "facebook/bart-large-mnli": "https://huggingface.co/facebook/bart-large-mnli/resolve/main/merges.txt",
        "facebook/bart-large-cnn": "https://huggingface.co/facebook/bart-large-cnn/resolve/main/merges.txt",
        "facebook/bart-large-xsum": "https://huggingface.co/facebook/bart-large-xsum/resolve/main/merges.txt",
        "yjernite/bart_eli5": "https://huggingface.co/yjernite/bart_eli5/resolve/main/merges.txt",
    },
}

A_      =      {
    "facebook/bart-base": 1024,
    "facebook/bart-large": 1024,
    "facebook/bart-large-mnli": 1024,
    "facebook/bart-large-cnn": 1024,
    "facebook/bart-large-xsum": 1024,
    "yjernite/bart_eli5": 1024,
}






@lru_cache()
def        __UpperCAmelCase    (       )->       Optional[int]:



			"""simple docstring"""







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






def        __UpperCAmelCase    (       UpperCAmelCase       )->       str:



			"""simple docstring"""







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






class      __lowercase					(    _A    ):
						lowercase					 =     VOCAB_FILES_NAMES
						lowercase					 =     PRETRAINED_VOCAB_FILES_MAP
						lowercase					 =     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						lowercase					 =     ['input_ids', 'attention_mask']

						def __init__(	self				:      Optional[int]							,							__lowerCamelCase				:      List[str]							,							__lowerCamelCase				:      str							,							__lowerCamelCase				:      Union[str, Any]="replace"							,							__lowerCamelCase				:      Optional[Any]="<s>"							,							__lowerCamelCase				:      int="</s>"							,							__lowerCamelCase				:      int="</s>"							,							__lowerCamelCase				:      Optional[Any]="<s>"							,							__lowerCamelCase				:      Optional[int]="<unk>"							,							__lowerCamelCase				:      List[str]="<pad>"							,							__lowerCamelCase				:      Union[str, Any]="<mask>"							,							__lowerCamelCase				:      str=False							,							**__lowerCamelCase				:      List[str]							,							)							->		Dict:


									'''simple docstring'''

									lowercase							=		AddedToken(__lowerCamelCase							,							lstrip=__lowerCamelCase							,							rstrip=__lowerCamelCase   ) if isinstance(__lowerCamelCase							,							__lowerCamelCase   ) else bos_token
									lowercase							=		AddedToken(__lowerCamelCase							,							lstrip=__lowerCamelCase							,							rstrip=__lowerCamelCase   ) if isinstance(__lowerCamelCase							,							__lowerCamelCase   ) else eos_token
									lowercase							=		AddedToken(__lowerCamelCase							,							lstrip=__lowerCamelCase							,							rstrip=__lowerCamelCase   ) if isinstance(__lowerCamelCase							,							__lowerCamelCase   ) else sep_token
									lowercase							=		AddedToken(__lowerCamelCase							,							lstrip=__lowerCamelCase							,							rstrip=__lowerCamelCase   ) if isinstance(__lowerCamelCase							,							__lowerCamelCase   ) else cls_token
									lowercase							=		AddedToken(__lowerCamelCase							,							lstrip=__lowerCamelCase							,							rstrip=__lowerCamelCase   ) if isinstance(__lowerCamelCase							,							__lowerCamelCase   ) else unk_token
									lowercase							=		AddedToken(__lowerCamelCase							,							lstrip=__lowerCamelCase							,							rstrip=__lowerCamelCase   ) if isinstance(__lowerCamelCase							,							__lowerCamelCase   ) else pad_token

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

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

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

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

						@property
						def        __a		(	self				:      int   )							->		Any:


									'''simple docstring'''

									return len(self.encoder   )

						def        __a		(	self				:      List[str]   )							->		Any:


									'''simple docstring'''

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

						def        __a		(	self				:      List[str]							,							__lowerCamelCase				:      Any   )							->		List[str]:


									'''simple docstring'''

									if token in self.cache:
												return self.cache[token]
									lowercase							=		tuple(__lowerCamelCase   )
									lowercase							=		get_pairs(__lowerCamelCase   )

									if not pairs:
												return token

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

						def        __a		(	self				:      List[str]							,							__lowerCamelCase				:      Union[str, Any]   )							->		List[str]:


									'''simple docstring'''

									lowercase							=		[]
									for token in re.findall(self.pat							,							__lowerCamelCase   ):
												lowercase							=		''''''.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(__lowerCamelCase   ).split(''' '''   )   )
									return bpe_tokens

						def        __a		(	self				:      Optional[Any]							,							__lowerCamelCase				:      Optional[int]   )							->		List[str]:


									'''simple docstring'''

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

						def        __a		(	self				:      List[str]							,							__lowerCamelCase				:      Union[str, Any]   )							->		Any:


									'''simple docstring'''

									return self.decoder.get(__lowerCamelCase   )

						def        __a		(	self				:      str							,							__lowerCamelCase				:      List[Any]   )							->		Any:


									'''simple docstring'''

									lowercase							=		''''''.join(__lowerCamelCase   )
									lowercase							=		bytearray([self.byte_decoder[c] for c in text]   ).decode('''utf-8'''							,							errors=self.errors   )
									return text

						def        __a		(	self				:      Dict							,							__lowerCamelCase				:      str							,							__lowerCamelCase				:      Optional[str] = None   )							->		Tuple[str]:


									'''simple docstring'''

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

									lowercase							=		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 __lowerCamelCase   : 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!'''   )
																		lowercase							=		token_index
															writer.write(''' '''.join(__lowerCamelCase   ) + '''\n'''   )
															index += 1

									return vocab_file, merge_file

						def        __a		(	self				:      List[Any]							,							__lowerCamelCase				:      List[int]							,							__lowerCamelCase				:      Optional[List[int]] = None   )							->		List[int]:


									'''simple docstring'''

									if token_ids_a is None:
												return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
									lowercase							=		[self.cls_token_id]
									lowercase							=		[self.sep_token_id]
									return cls + token_ids_a + sep + sep + token_ids_a + sep

						def        __a		(	self				:      str							,							__lowerCamelCase				:      List[int]							,							__lowerCamelCase				:      Optional[List[int]] = None							,							__lowerCamelCase				:      bool = False   )							->		List[int]:


									'''simple docstring'''

									if already_has_special_tokens:
												return super().get_special_tokens_mask(
												    token_ids_a=__lowerCamelCase							,							token_ids_a=__lowerCamelCase							,							already_has_special_tokens=__lowerCamelCase   )

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

						def        __a		(	self				:      Optional[Any]							,							__lowerCamelCase				:      List[int]							,							__lowerCamelCase				:      Optional[List[int]] = None   )							->		List[int]:


									'''simple docstring'''

									lowercase							=		[self.sep_token_id]
									lowercase							=		[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        __a		(	self				:      Union[str, Any]							,							__lowerCamelCase				:      List[Any]							,							__lowerCamelCase				:      Optional[Any]=False							,							**__lowerCamelCase				:      List[str]   )							->		int:


									'''simple docstring'''

									lowercase							=		kwargs.pop('''add_prefix_space'''							,							self.add_prefix_space   )
									if (is_split_into_words or add_prefix_space) and (len(__lowerCamelCase   ) > 0 and not text[0].isspace()):
												lowercase							=		''' ''' + text
									return (text, kwargs)





