
"""simple docstring"""
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


SCREAMING_SNAKE_CASE_					     =	logging.get_logger(__name__)
class       lowerCAmelCase_		:



							'''simple docstring'''





							def __init__( self    ,				snake_case_ = None    ,				snake_case_ = None    ,				snake_case_=None    ,				snake_case_=None				)       ->  Optional[int]:
													if not conversation_id:
																			__lowerCAmelCase     =  uuid.uuida()
													if past_user_inputs is None:
																			__lowerCAmelCase     =  []
													if generated_responses is None:
																			__lowerCAmelCase     =  []

													__lowerCAmelCase     =  conversation_id
													__lowerCAmelCase     =  past_user_inputs
													__lowerCAmelCase     =  generated_responses
													__lowerCAmelCase     =  text




							def __eq__( self    ,				snake_case_				)       ->  Union[str, Any]:
													if not isinstance(__UpperCamelCase    ,				__UpperCamelCase				):
																			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    ,				snake_case_    ,				snake_case_ = False				)       ->  Union[str, Any]:
													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}\"."""				)
																									__lowerCAmelCase     =  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:
																			__lowerCAmelCase     =  text




							def    A__						( self				)       ->  List[Any]:
													if self.new_user_input:
																			self.past_user_inputs.append(self.new_user_input				)
													__lowerCAmelCase     =  None




							def    A__						( self    ,				snake_case_				)       ->  List[Any]:
													self.generated_responses.append(__UpperCamelCase				)




							def    A__						( self				)       ->  Union[str, Any]:
													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				)       ->  Dict:
													__lowerCAmelCase     =  f"""Conversation id: {self.uuid} \n"""
													for is_user, text in self.iter_texts():
																			__lowerCAmelCase     =  """user""" if is_user else """bot"""
																			output += f"""{name} >> {text} \n"""
													return output
@add_end_docstrings(
    _lowerCamelCase				,				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       lowerCAmelCase_		(				_lowerCamelCase ):



							'''simple docstring'''





							def __init__( self    ,				*snake_case_    ,				**snake_case_				)       ->  str:
													super().__init__(*__UpperCamelCase    ,				**__UpperCamelCase				)
													if self.tokenizer.pad_token_id is None:
																			__lowerCAmelCase     =  self.tokenizer.eos_token




							def    A__						( self    ,				snake_case_=None    ,				snake_case_=None    ,				snake_case_=None    ,				**snake_case_				)       ->  Optional[Any]:
													__lowerCAmelCase     =  {}
													__lowerCAmelCase     =  {}
													__lowerCAmelCase     =  {}

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

													if "max_length" in generate_kwargs:
																			__lowerCAmelCase     =  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:
																			__lowerCAmelCase     =  clean_up_tokenization_spaces

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




							def __call__( self    ,				snake_case_    ,				snake_case_=0    ,				**snake_case_				)       ->  Any:
													__lowerCAmelCase     =  super().__call__(__UpperCamelCase    ,				num_workers=__UpperCamelCase    ,				**__UpperCamelCase				)
													if isinstance(__UpperCamelCase    ,				__UpperCamelCase				) and len(__UpperCamelCase				) == 1:
																			return outputs[0]
													return outputs




							def    A__						( self    ,				snake_case_    ,				snake_case_=32				)       ->  Dict[str, Any]:
													if not isinstance(__UpperCamelCase    ,				__UpperCamelCase				):
																			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"""				):
																			__lowerCAmelCase     =  self.tokenizer._build_conversation_input_ids(__UpperCamelCase				)
													else:
																			# If the tokenizer cannot handle conversations, we default to only the old version
																			__lowerCAmelCase     =  self._legacy_parse_and_tokenize(__UpperCamelCase				)

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




							def    A__						( self    ,				snake_case_    ,				snake_case_=10    ,				**snake_case_				)       ->  Any:
													__lowerCAmelCase     =  generate_kwargs.get("""max_length"""    ,				self.model.config.max_length				)

													__lowerCAmelCase     =  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})"""				)
																			__lowerCAmelCase     =  max_length - minimum_tokens
																			__lowerCAmelCase     =  model_inputs["""input_ids"""][:, -trim:]
																			if "attention_mask" in model_inputs:
																									__lowerCAmelCase     =  model_inputs["""attention_mask"""][:, -trim:]
													__lowerCAmelCase     =  model_inputs.pop("""conversation"""				)
													__lowerCAmelCase     =  max_length
													__lowerCAmelCase     =  self.model.generate(**__UpperCamelCase    ,				**__UpperCamelCase				)
													if self.model.config.is_encoder_decoder:
																			__lowerCAmelCase     =  1
													else:
																			__lowerCAmelCase     =  n
													return {"output_ids": output_ids[:, start_position:], "conversation": conversation}




							def    A__						( self    ,				snake_case_    ,				snake_case_=True				)       ->  int:
													__lowerCAmelCase     =  model_outputs["""output_ids"""]
													__lowerCAmelCase     =  self.tokenizer.decode(
													    output_ids[0]    ,				skip_special_tokens=__UpperCamelCase    ,				clean_up_tokenization_spaces=__UpperCamelCase    ,				)
													__lowerCAmelCase     =  model_outputs["""conversation"""]
													conversation.mark_processed()
													conversation.append_response(__UpperCamelCase				)
													return conversation




							def    A__						( self    ,				snake_case_				)       ->  Dict:
													__lowerCAmelCase     =  self.tokenizer.eos_token_id
													__lowerCAmelCase     =  []
													for is_user, text in conversation.iter_texts():
																			if eos_token_id is not None:
																									input_ids.extend(self.tokenizer.encode(__UpperCamelCase    ,				add_special_tokens=__UpperCamelCase				) + [eos_token_id]				)
																			else:
																									input_ids.extend(self.tokenizer.encode(__UpperCamelCase    ,				add_special_tokens=__UpperCamelCase				)				)

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





import math
import sys






def  lowerCamelCase_	(      lowerCAmelCase__	:	str				)       ->							str:

							'''simple docstring'''






							A      						=    ''
							try:
														with open(lowerCAmelCase__			,	'rb'				) as binary_file:
																					A      						=    binary_file.read()
														for dat in data:
																					A      						=    F'''{dat:08b}'''
																					result += curr_byte
														return result
							except OSError:
														print('File not accessible'				)
														sys.exit()






def  lowerCamelCase_	(      lowerCAmelCase__	:	str				)       ->							str:

							'''simple docstring'''






							A      						=    {'0': '0', '1': '1'}
							A						,   A      						=    '', ''
							A      						=    len(lowerCAmelCase__				)

							for i in range(len(lowerCAmelCase__				)				):
														curr_string += data_bits[i]
														if curr_string not in lexicon:
																					continue

														A      						=    lexicon[curr_string]
														result += last_match_id
														A      						=    last_match_id + '0'

														if math.loga(lowerCAmelCase__				).is_integer():
																					A      						=    {}
																					for curr_key in list(lowerCAmelCase__				):
																												A      						=    lexicon.pop(lowerCAmelCase__				)
																					A      						=    new_lex

														A      						=    last_match_id + '1'
														index += 1
														A      						=    ''
							return result






def  lowerCamelCase_	(      lowerCAmelCase__	:	str			,	lowerCAmelCase__	:	str				)       ->							None:

							'''simple docstring'''






							A      						=    8
							try:
														with open(lowerCAmelCase__			,	'wb'				) as opened_file:
																					A      						=    [
																					    to_write[i : i + byte_length]
																					    for i in range(0			,	len(lowerCAmelCase__				)			,	lowerCAmelCase__				)
																					]

																					if len(result_byte_array[-1]				) % byte_length == 0:
																												result_byte_array.append('10000000'				)
																					else:
																												result_byte_array[-1] += "1" + "0" * (
																												    byte_length - len(result_byte_array[-1]				) - 1
																												)

																					for elem in result_byte_array[:-1]:
																												opened_file.write(int(lowerCAmelCase__			,	2				).to_bytes(1			,	byteorder='big'				)				)
							except OSError:
														print('File not accessible'				)
														sys.exit()






def  lowerCamelCase_	(      lowerCAmelCase__	:	str				)       ->							str:

							'''simple docstring'''






							A      						=    0
							for letter in data_bits:
														if letter == "1":
																					break
														counter += 1

							A      						=    data_bits[counter:]
							A      						=    data_bits[counter + 1 :]
							return data_bits






def  lowerCamelCase_	(      lowerCAmelCase__	:	str			,	lowerCAmelCase__	:	str				)       ->							None:

							'''simple docstring'''






							A      						=    read_file_binary(lowerCAmelCase__				)
							A      						=    remove_prefix(lowerCAmelCase__				)
							A      						=    decompress_data(lowerCAmelCase__				)
							write_file_binary(lowerCAmelCase__			,	lowerCAmelCase__				)


if __name__ == "__main__":
				compress(sys.argv[1], sys.argv[2])