


'''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


UpperCAmelCase_ :     str								=      logging.get_logger(__name__)




class 						_lowerCamelCase					:




 '''simple docstring'''


 def __init__(      self      ,      __lowercase = None      ,      __lowercase = None      ,      __lowercase=None      ,      __lowercase=None						):

  """simple docstring"""







  if not conversation_id:
   __A  :		Optional[Any]       =			uuid.uuida()
  if past_user_inputs is None:
   __A  :		Tuple       =			[]
  if generated_responses is None:
   __A  :		Any       =			[]

  __A  :		uuid.UUID       =			conversation_id
  __A  :		List[str]       =			past_user_inputs
  __A  :		List[str]       =			generated_responses
  __A  :		Optional[str]       =			text


 def __eq__(      self      ,      __lowercase						):

  """simple docstring"""







  if not isinstance(__lowercase      ,      __lowercase						):
   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  snake_case__   (      self      ,      __lowercase      ,      __lowercase = False						):

  """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}\"."""						)
    __A  :		Optional[int]       =			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:
   __A  :		int       =			text


 def  snake_case__   (      self						):

  """simple docstring"""







  if self.new_user_input:
   self.past_user_inputs.append(self.new_user_input						)
  __A  :		Optional[int]       =			None


 def  snake_case__   (      self      ,      __lowercase						):

  """simple docstring"""







  self.generated_responses.append(__lowercase						)


 def  snake_case__   (      self						):

  """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						):

  """simple docstring"""







  __A  :		Dict       =			F"""Conversation id: {self.uuid} \n"""
  for is_user, text in self.iter_texts():
   __A  :		List[Any]       =			"""user""" if is_user else """bot"""
   output += F"""{name} >> {text} \n"""
  return output




@add_end_docstrings(
    UpperCAmelCase__    ,		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					(    UpperCAmelCase__				):




 '''simple docstring'''


 def __init__(      self      ,      *__lowercase      ,      **__lowercase						):

  """simple docstring"""







  super().__init__(*__lowercase      ,      **__lowercase						)
  if self.tokenizer.pad_token_id is None:
   __A  :		Tuple       =			self.tokenizer.eos_token


 def  snake_case__   (      self      ,      __lowercase=None      ,      __lowercase=None      ,      __lowercase=None      ,      **__lowercase						):

  """simple docstring"""







  __A  :		Tuple       =			{}
  __A  :		str       =			{}
  __A  :		str       =			{}

  if min_length_for_response is not None:
   __A  :		List[Any]       =			min_length_for_response
  if minimum_tokens is not None:
   __A  :		str       =			minimum_tokens

  if "max_length" in generate_kwargs:
   __A  :		Optional[Any]       =			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:
   __A  :		Dict       =			clean_up_tokenization_spaces

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


 def __call__(      self      ,      __lowercase      ,      __lowercase=0      ,      **__lowercase						):

  """simple docstring"""







  __A  :		Union[str, Any]       =			super().__call__(__lowercase      ,      num_workers=__lowercase      ,      **__lowercase						)
  if isinstance(__lowercase      ,      __lowercase						) and len(__lowercase						) == 1:
   return outputs[0]
  return outputs


 def  snake_case__   (      self      ,      __lowercase      ,      __lowercase=32						):

  """simple docstring"""







  if not isinstance(__lowercase      ,      __lowercase						):
   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'						):
   __A  :		List[Any]       =			self.tokenizer._build_conversation_input_ids(__lowercase						)
  else:
   # If the tokenizer cannot handle conversations, we default to only the old version
   __A  :		List[Any]       =			self._legacy_parse_and_tokenize(__lowercase						)

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


 def  snake_case__   (      self      ,      __lowercase      ,      __lowercase=10      ,      **__lowercase						):

  """simple docstring"""







  __A  :		Optional[int]       =			generate_kwargs.get('max_length'      ,      self.model.config.max_length						)

  __A  :		str       =			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})"""						)
   __A  :		Tuple       =			max_length - minimum_tokens
   __A  :		int       =			model_inputs["""input_ids"""][:, -trim:]
   if "attention_mask" in model_inputs:
    __A  :		Optional[Any]       =			model_inputs["""attention_mask"""][:, -trim:]
  __A  :		Union[str, Any]       =			model_inputs.pop('conversation'						)
  __A  :		List[Any]       =			max_length
  __A  :		Union[str, Any]       =			self.model.generate(**__lowercase      ,      **__lowercase						)
  if self.model.config.is_encoder_decoder:
   __A  :		List[str]       =			1
  else:
   __A  :		Tuple       =			n
  return {"output_ids": output_ids[:, start_position:], "conversation": conversation}


 def  snake_case__   (      self      ,      __lowercase      ,      __lowercase=True						):

  """simple docstring"""







  __A  :		str       =			model_outputs["""output_ids"""]
  __A  :		List[str]       =			self.tokenizer.decode(
      output_ids[0]      ,      skip_special_tokens=__lowercase      ,      clean_up_tokenization_spaces=__lowercase      ,      )
  __A  :		Optional[Any]       =			model_outputs["""conversation"""]
  conversation.mark_processed()
  conversation.append_response(__lowercase						)
  return conversation







 def  snake_case__   (      self      ,      __lowercase						):

  """simple docstring"""







  __A  :		Optional[Any]       =			self.tokenizer.eos_token_id
  __A  :		List[Any]       =			[]
  for is_user, text in conversation.iter_texts():
   if eos_token_id is not None:
    input_ids.extend(self.tokenizer.encode(__lowercase      ,      add_special_tokens=__lowercase						) + [eos_token_id]						)
   else:
    input_ids.extend(self.tokenizer.encode(__lowercase      ,      add_special_tokens=__lowercase						)						)

  if len(__lowercase						) > self.tokenizer.model_max_length:
   __A  :		List[Any]       =			input_ids[-self.tokenizer.model_max_length :]
  return input_ids










'''simple docstring'''
from __future__ import annotations

import math
import random
from collections.abc import Collection
from typing import overload

class 						_lowerCamelCase					:




 '''simple docstring'''


 def __init__(      self      ,      __lowercase = None						):

  """simple docstring"""







  if components is None:
   __A  :		Optional[int]       =			[]
  __A  :		Dict       =			list(__lowercase						)


 def __len__(      self						):

  """simple docstring"""







  return len(self.__components						)


 def __str__(      self						):

  """simple docstring"""







  return "(" + ",".join(map(__lowercase      ,      self.__components						)						) + ")"


 def __add__(      self      ,      __lowercase						):

  """simple docstring"""







  __A  :		Union[str, Any]       =			len(self						)
  if size == len(__lowercase						):
   __A  :		Dict       =			[self.__components[i] + other.component(__lowercase						) for i in range(__lowercase						)]
   return Vector(__lowercase						)
  else:
   raise Exception('must have the same size'						)


 def __sub__(      self      ,      __lowercase						):

  """simple docstring"""







  __A  :		int       =			len(self						)
  if size == len(__lowercase						):
   __A  :		str       =			[self.__components[i] - other.component(__lowercase						) for i in range(__lowercase						)]
   return Vector(__lowercase						)
  else:  # error case
   raise Exception('must have the same size'						)


 @overload
 def __mul__(      self      ,      __lowercase						):

  """simple docstring"""







  ...


 @overload
 def __mul__(      self      ,      __lowercase						):

  """simple docstring"""







  ...


 def __mul__(      self      ,      __lowercase						):

  """simple docstring"""







  if isinstance(__lowercase      ,      (float, int)						):
   __A  :		Dict       =			[c * other for c in self.__components]
   return Vector(__lowercase						)
  elif isinstance(__lowercase      ,      __lowercase						) and len(self						) == len(__lowercase						):
   __A  :		Optional[Any]       =			len(self						)
   __A  :		Optional[int]       =			[self.__components[i] * other.component(__lowercase						) for i in range(__lowercase						)]
   return sum(__lowercase						)
  else:  # error case
   raise Exception('invalid operand!'						)


 def  snake_case__   (      self						):

  """simple docstring"""







  return Vector(self.__components						)


 def  snake_case__   (      self      ,      __lowercase						):

  """simple docstring"""







  if isinstance(__lowercase      ,      __lowercase						) and -len(self.__components						) <= i < len(self.__components						):
   return self.__components[i]
  else:
   raise Exception('index out of range'						)


 def  snake_case__   (      self      ,      __lowercase      ,      __lowercase						):

  """simple docstring"""







  assert -len(self.__components						) <= pos < len(self.__components						)
  __A  :		str       =			value


 def  snake_case__   (      self						):

  """simple docstring"""







  if len(self.__components						) == 0:
   raise Exception('Vector is empty'						)
  __A  :		List[Any]       =			[c**2 for c in self.__components]
  return math.sqrt(sum(__lowercase						)						)







 def  snake_case__   (      self      ,      __lowercase      ,      __lowercase = False						):

  """simple docstring"""







  __A  :		List[Any]       =			self * other
  __A  :		Any       =			self.euclidean_length() * other.euclidean_length()
  if deg:
   return math.degrees(math.acos(num / den						)						)
  else:
   return math.acos(num / den						)


def 			_lowercase       (				UpperCamelCase__       :					int			):
 assert isinstance(UpperCamelCase__,				UpperCamelCase__			)
 return Vector([0] * dimension			)


def 			_lowercase       (				UpperCamelCase__       :					int,				UpperCamelCase__       :					int			):
 assert isinstance(UpperCamelCase__,				UpperCamelCase__			) and (isinstance(UpperCamelCase__,				UpperCamelCase__			))
 __A  :		List[str]       =			[0] * dimension
 __A  :		Tuple       =			1
 return Vector(UpperCamelCase__			)


def 			_lowercase       (				UpperCamelCase__       :					float,				UpperCamelCase__       :					Vector,				UpperCamelCase__       :					Vector			):
 assert (
     isinstance(UpperCamelCase__,				UpperCamelCase__			)
     and isinstance(UpperCamelCase__,				UpperCamelCase__			)
     and (isinstance(UpperCamelCase__,				(int, float)			))
 )
 return x * scalar + y


def 			_lowercase       (				UpperCamelCase__       :					int,				UpperCamelCase__       :					int,				UpperCamelCase__       :					int			):
 random.seed(UpperCamelCase__			)
 __A  :		Any       =			[random.randint(UpperCamelCase__,				UpperCamelCase__			) for _ in range(UpperCamelCase__			)]
 return Vector(UpperCamelCase__			)

class 						_lowerCamelCase					:




 '''simple docstring'''


 def __init__(      self      ,      __lowercase      ,      __lowercase      ,      __lowercase						):

  """simple docstring"""







  __A  :		str       =			matrix
  __A  :		str       =			w
  __A  :		Dict       =			h


 def __str__(      self						):

  """simple docstring"""







  __A  :		Tuple       =			''
  for i in range(self.__height						):
   ans += "|"
   for j in range(self.__width						):
    if j < self.__width - 1:
     ans += str(self.__matrix[i][j]						) + ","
    else:
     ans += str(self.__matrix[i][j]						) + "|\n"
  return ans


 def __add__(      self      ,      __lowercase						):

  """simple docstring"""







  if self.__width == other.width() and self.__height == other.height():
   __A  :		Union[str, Any]       =			[]
   for i in range(self.__height						):
    __A  :		List[Any]       =			[
        self.__matrix[i][j] + other.component(__lowercase      ,      __lowercase						)
        for j in range(self.__width						)
    ]
    matrix.append(__lowercase						)
   return Matrix(__lowercase      ,      self.__width      ,      self.__height						)
  else:
   raise Exception('matrix must have the same dimension!'						)


 def __sub__(      self      ,      __lowercase						):

  """simple docstring"""







  if self.__width == other.width() and self.__height == other.height():
   __A  :		Dict       =			[]
   for i in range(self.__height						):
    __A  :		str       =			[
        self.__matrix[i][j] - other.component(__lowercase      ,      __lowercase						)
        for j in range(self.__width						)
    ]
    matrix.append(__lowercase						)
   return Matrix(__lowercase      ,      self.__width      ,      self.__height						)
  else:
   raise Exception('matrices must have the same dimension!'						)


 @overload
 def __mul__(      self      ,      __lowercase						):

  """simple docstring"""







  ...


 @overload
 def __mul__(      self      ,      __lowercase						):

  """simple docstring"""







  ...


 def __mul__(      self      ,      __lowercase						):

  """simple docstring"""







  if isinstance(__lowercase      ,      __lowercase						):  # matrix-vector
   if len(__lowercase						) == self.__width:
    __A  :		Tuple       =			zero_vector(self.__height						)
    for i in range(self.__height						):
     __A  :		Any       =			[
         self.__matrix[i][j] * other.component(__lowercase						)
         for j in range(self.__width						)
     ]
     ans.change_component(__lowercase      ,      sum(__lowercase						)						)
    return ans
   else:
    raise Exception(
        'vector must have the same size as the '
        'number of columns of the matrix!'						)
  elif isinstance(__lowercase      ,      (int, float)						):  # matrix-scalar
   __A  :		Optional[Any]       =			[
       [self.__matrix[i][j] * other for j in range(self.__width						)]
       for i in range(self.__height						)
   ]
   return Matrix(__lowercase      ,      self.__width      ,      self.__height						)
  return None


 def  snake_case__   (      self						):

  """simple docstring"""







  return self.__height


 def  snake_case__   (      self						):

  """simple docstring"""







  return self.__width


 def  snake_case__   (      self      ,      __lowercase      ,      __lowercase						):

  """simple docstring"""







  if 0 <= x < self.__height and 0 <= y < self.__width:
   return self.__matrix[x][y]
  else:
   raise Exception('change_component: indices out of bounds'						)


 def  snake_case__   (      self      ,      __lowercase      ,      __lowercase      ,      __lowercase						):

  """simple docstring"""







  if 0 <= x < self.__height and 0 <= y < self.__width:
   __A  :		Dict       =			value
  else:
   raise Exception('change_component: indices out of bounds'						)


 def  snake_case__   (      self      ,      __lowercase      ,      __lowercase						):

  """simple docstring"""







  if self.__height != self.__width:
   raise Exception('Matrix is not square'						)
  __A  :		Union[str, Any]       =			self.__matrix[:x] + self.__matrix[x + 1 :]
  for i in range(len(__lowercase						)						):
   __A  :		Dict       =			minor[i][:y] + minor[i][y + 1 :]
  return Matrix(__lowercase      ,      self.__width - 1      ,      self.__height - 1						).determinant()


 def  snake_case__   (      self      ,      __lowercase      ,      __lowercase						):

  """simple docstring"""







  if self.__height != self.__width:
   raise Exception('Matrix is not square'						)
  if 0 <= x < self.__height and 0 <= y < self.__width:
   return (-1) ** (x + y) * self.minor(__lowercase      ,      __lowercase						)
  else:
   raise Exception('Indices out of bounds'						)







 def  snake_case__   (      self						):

  """simple docstring"""







  if self.__height != self.__width:
   raise Exception('Matrix is not square'						)
  if self.__height < 1:
   raise Exception('Matrix has no element'						)
  elif self.__height == 1:
   return self.__matrix[0][0]
  elif self.__height == 2:
   return (
       self.__matrix[0][0] * self.__matrix[1][1]
       - self.__matrix[0][1] * self.__matrix[1][0]
   )
  else:
   __A  :		List[str]       =			[
       self.__matrix[0][y] * self.cofactor(0      ,      __lowercase						) for y in range(self.__width						)
   ]
   return sum(__lowercase						)


def 			_lowercase       (				UpperCamelCase__       :					int			):
 __A  :		list[list[float]]       =			[[0] * n for _ in range(UpperCamelCase__			)]
 return Matrix(UpperCamelCase__,				UpperCamelCase__,				UpperCamelCase__			)


def 			_lowercase       (				UpperCamelCase__       :					int,				UpperCamelCase__       :					int,				UpperCamelCase__       :					int,				UpperCamelCase__       :					int			):
 random.seed(UpperCamelCase__			)
 __A  :		list[list[float]]       =			[
     [random.randint(UpperCamelCase__,				UpperCamelCase__			) for _ in range(UpperCamelCase__			)] for _ in range(UpperCamelCase__			)
 ]
 return Matrix(UpperCamelCase__,				UpperCamelCase__,				UpperCamelCase__			)






