



import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List

import git
import torch
from torch.utils.data import Dataset

from transformers import BartTokenizer, RagTokenizer, TaTokenizer



def    snake_case_				(    _SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE=True  ,	_SCREAMING_SNAKE_CASE="pt"   ):
	__lowercase		       =			{"add_prefix_space": True} if isinstance(_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE   ) and not line.startswith(" "   ) else {}
	__lowercase		       =			padding_side
	return tokenizer(
	    [line]  ,	max_length=_SCREAMING_SNAKE_CASE  ,	padding="max_length" if pad_to_max_length else None  ,	truncation=_SCREAMING_SNAKE_CASE  ,	return_tensors=_SCREAMING_SNAKE_CASE  ,	add_special_tokens=_SCREAMING_SNAKE_CASE  ,	**_SCREAMING_SNAKE_CASE  ,	)



def    snake_case_				(    _SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE=None  ,	):
	__lowercase		       =			input_ids.ne(_SCREAMING_SNAKE_CASE   ).any(dim=0   )
	if attention_mask is None:
		return input_ids[:, keep_column_mask]
	else:
		return (input_ids[:, keep_column_mask], attention_mask[:, keep_column_mask])

class   _A   ( _lowercase	):


						'''simple docstring'''





						def __init__(	self	:							Tuple							,      lowerCamelCase	:							Dict							,      lowerCamelCase	:							int							,      lowerCamelCase	:							Optional[int]							,      lowerCamelCase	:							Any							,      lowerCamelCase	:							int="train"							,      lowerCamelCase	:							List[str]=None							,      lowerCamelCase	:							Dict=None							,      lowerCamelCase	:							Optional[Any]=None							,      lowerCamelCase	:							List[Any]=""							,      ):






							'''simple docstring'''



							super().__init__()
							__lowercase		       =			Path(lowerCamelCase	).joinpath(type_path + ".source"	)
							__lowercase		       =			Path(lowerCamelCase	).joinpath(type_path + ".target"	)
							__lowercase		       =			self.get_char_lens(self.src_file	)
							__lowercase		       =			max_source_length
							__lowercase		       =			max_target_length
							assert min(self.src_lens	) > 0, f"""found empty line in {self.src_file}"""
							__lowercase		       =			tokenizer
							__lowercase		       =			prefix
							if n_obs is not None:
								__lowercase		       =			self.src_lens[:n_obs]
							__lowercase		       =			src_lang
							__lowercase		       =			tgt_lang



						def __len__(	self	:							Dict	):






							'''simple docstring'''



							return len(self.src_lens	)



						def __getitem__(	self	:							Optional[int]							,      lowerCamelCase	:							Tuple	):






							'''simple docstring'''



							__lowercase		       =			index + 1  # linecache starts at 1
							__lowercase		       =			self.prefix + linecache.getline(str(self.src_file	)							,      lowerCamelCase	).rstrip("\n"	)
							__lowercase		       =			linecache.getline(str(self.tgt_file	)							,      lowerCamelCase	).rstrip("\n"	)
							assert source_line, f"""empty source line for index {index}"""
							assert tgt_line, f"""empty tgt line for index {index}"""

							# Need to add eos token manually for T5
							if isinstance(self.tokenizer							,      lowerCamelCase	):
								source_line += self.tokenizer.eos_token
								tgt_line += self.tokenizer.eos_token

							# Pad source and target to the right
							__lowercase		       =			(
							    self.tokenizer.question_encoder if isinstance(self.tokenizer							,      lowerCamelCase	) else self.tokenizer
							)
							__lowercase		       =			self.tokenizer.generator if isinstance(self.tokenizer							,      lowerCamelCase	) else self.tokenizer

							__lowercase		       =			encode_line(lowerCamelCase							,      lowerCamelCase							,      self.max_source_length							,      "right"	)
							__lowercase		       =			encode_line(lowerCamelCase							,      lowerCamelCase							,      self.max_target_length							,      "right"	)

							__lowercase		       =			source_inputs["input_ids"].squeeze()
							__lowercase		       =			target_inputs["input_ids"].squeeze()
							__lowercase		       =			source_inputs["attention_mask"].squeeze()
							return {
							    "input_ids": source_ids,
							    "attention_mask": src_mask,
							    "decoder_input_ids": target_ids,
							}



						@staticmethod
						def     _snake_case	(	lowerCamelCase	:							Union[str, Any]	):






							'''simple docstring'''



							return [len(lowerCamelCase	) for x in Path(lowerCamelCase	).open().readlines()]



						def     _snake_case	(	self	:							Optional[int]							,      lowerCamelCase	:							Dict	):






							'''simple docstring'''



							__lowercase		       =			torch.stack([x["input_ids"] for x in batch]	)
							__lowercase		       =			torch.stack([x["attention_mask"] for x in batch]	)
							__lowercase		       =			torch.stack([x["decoder_input_ids"] for x in batch]	)
							__lowercase		       =			(
							    self.tokenizer.generator.pad_token_id
							    if isinstance(self.tokenizer							,      lowerCamelCase	)
							    else self.tokenizer.pad_token_id
							)
							__lowercase		       =			(
							    self.tokenizer.question_encoder.pad_token_id
							    if isinstance(self.tokenizer							,      lowerCamelCase	)
							    else self.tokenizer.pad_token_id
							)
							__lowercase		       =			trim_batch(lowerCamelCase							,      lowerCamelCase	)
							__lowercase       ,    __lowercase		       =			trim_batch(lowerCamelCase							,      lowerCamelCase							,      attention_mask=lowerCamelCase	)
							__lowercase		       =			{
							    "input_ids": source_ids,
							    "attention_mask": source_mask,
							    "decoder_input_ids": y,
							}
							return batch

snake_case__					:     List[Any]    		=   getLogger(__name__)



def    snake_case_				(    _SCREAMING_SNAKE_CASE   ):
	return list(itertools.chain.from_iterable(_SCREAMING_SNAKE_CASE   )   )



def    snake_case_				(    _SCREAMING_SNAKE_CASE   ):
	__lowercase		       =			get_git_info()
	save_json(_SCREAMING_SNAKE_CASE  ,	os.path.join(_SCREAMING_SNAKE_CASE  ,	"git_log.json"   )   )



def    snake_case_				(    _SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE=4  ,	**_SCREAMING_SNAKE_CASE   ):
	with open(_SCREAMING_SNAKE_CASE  ,	"w"   ) as f:
		json.dump(_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE  ,	indent=_SCREAMING_SNAKE_CASE  ,	**_SCREAMING_SNAKE_CASE   )



def    snake_case_				(    _SCREAMING_SNAKE_CASE   ):
	with open(_SCREAMING_SNAKE_CASE   ) as f:
		return json.load(_SCREAMING_SNAKE_CASE   )



def    snake_case_				(    ):
	__lowercase		       =			git.Repo(search_parent_directories=_SCREAMING_SNAKE_CASE   )
	__lowercase		       =			{
	    "repo_id": str(_SCREAMING_SNAKE_CASE   ),
	    "repo_sha": str(repo.head.object.hexsha   ),
	    "repo_branch": str(repo.active_branch   ),
	    "hostname": str(socket.gethostname()   ),
	}
	return repo_infos



def    snake_case_				(    _SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE   ):
	return list(map(_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE   )   )



def    snake_case_				(    _SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE   ):
	with open(_SCREAMING_SNAKE_CASE  ,	"wb"   ) as f:
		return pickle.dump(_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE   )



def    snake_case_				(    _SCREAMING_SNAKE_CASE   ):

	def remove_articles(_SCREAMING_SNAKE_CASE   ):
		return re.sub(R"\b(a|an|the)\b"  ,	" "  ,	_SCREAMING_SNAKE_CASE   )

	def white_space_fix(_SCREAMING_SNAKE_CASE   ):
		return " ".join(text.split()   )

	def remove_punc(_SCREAMING_SNAKE_CASE   ):
		__lowercase		       =			set(string.punctuation   )
		return "".join(ch for ch in text if ch not in exclude   )

	def lower(_SCREAMING_SNAKE_CASE   ):
		return text.lower()

	return white_space_fix(remove_articles(remove_punc(lower(_SCREAMING_SNAKE_CASE   )   )   )   )



def    snake_case_				(    _SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE   ):
	__lowercase		       =			normalize_answer(_SCREAMING_SNAKE_CASE   ).split()
	__lowercase		       =			normalize_answer(_SCREAMING_SNAKE_CASE   ).split()
	__lowercase		       =			Counter(_SCREAMING_SNAKE_CASE   ) & Counter(_SCREAMING_SNAKE_CASE   )
	__lowercase		       =			sum(common.values()   )
	if num_same == 0:
		return 0
	__lowercase		       =			1.0 * num_same / len(_SCREAMING_SNAKE_CASE   )
	__lowercase		       =			1.0 * num_same / len(_SCREAMING_SNAKE_CASE   )
	__lowercase		       =			(2 * precision * recall) / (precision + recall)
	return fa



def    snake_case_				(    _SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE   ):
	return normalize_answer(_SCREAMING_SNAKE_CASE   ) == normalize_answer(_SCREAMING_SNAKE_CASE   )



def    snake_case_				(    _SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE   ):
	assert len(_SCREAMING_SNAKE_CASE   ) == len(_SCREAMING_SNAKE_CASE   )
	__lowercase		       =			0
	for hypo, pred in zip(_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE   ):
		em += exact_match_score(_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE   )
	if len(_SCREAMING_SNAKE_CASE   ) > 0:
		em /= len(_SCREAMING_SNAKE_CASE   )
	return {"em": em}



def    snake_case_				(    _SCREAMING_SNAKE_CASE   ):
	return model_prefix.startswith("rag"   )



def    snake_case_				(    _SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE   ):
	__lowercase		       =			{p: p for p in extra_params}
	# T5 models don't have `dropout` param, they have `dropout_rate` instead
	__lowercase		       =			"dropout_rate"
	for p in extra_params:
		if getattr(_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE   ):
			if not hasattr(_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE   ) and not hasattr(_SCREAMING_SNAKE_CASE  ,	equivalent_param[p]   ):
				logger.info("config doesn't have a `{}` attribute".format(_SCREAMING_SNAKE_CASE   )   )
				delattr(_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE   )
				continue
			__lowercase		       =			p if hasattr(_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE   ) else equivalent_param[p]
			setattr(_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE  ,	getattr(_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE   )   )
			delattr(_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE   )
	return hparams, config








from __future__ import annotations

from typing import Any

class   _A   :


						'''simple docstring'''





						def __init__(	self	:							Union[str, Any]							,      lowerCamelCase	:							int	):






							'''simple docstring'''



							__lowercase		       =			num_of_nodes
							__lowercase		       =			[]
							__lowercase		       =			{}



						def     _snake_case	(	self	:							Dict							,      lowerCamelCase	:							int							,      lowerCamelCase	:							int							,      lowerCamelCase	:							int	):






							'''simple docstring'''



							self.m_edges.append([u_node, v_node, weight]	)



						def     _snake_case	(	self	:							List[Any]							,      lowerCamelCase	:							int	):






							'''simple docstring'''



							if self.m_component[u_node] == u_node:
								return u_node
							return self.find_component(self.m_component[u_node]	)



						def     _snake_case	(	self	:							Union[str, Any]							,      lowerCamelCase	:							int	):






							'''simple docstring'''



							if self.m_component[u_node] != u_node:
								for k in self.m_component:
									__lowercase		       =			self.find_component(lowerCamelCase	)



						def     _snake_case	(	self	:							Union[str, Any]							,      lowerCamelCase	:							list[int]							,      lowerCamelCase	:							int							,      lowerCamelCase	:							int	):






							'''simple docstring'''



							if component_size[u_node] <= component_size[v_node]:
								__lowercase		       =			v_node
								component_size[v_node] += component_size[u_node]
								self.set_component(lowerCamelCase	)

							elif component_size[u_node] >= component_size[v_node]:
								__lowercase		       =			self.find_component(lowerCamelCase	)
								component_size[u_node] += component_size[v_node]
								self.set_component(lowerCamelCase	)



						def     _snake_case	(	self	:							Any	):






							'''simple docstring'''



							__lowercase		       =			[]
							__lowercase		       =			0

							__lowercase		       =			[-1] * self.m_num_of_nodes

							# A list of components (initialized to all of the nodes)
							for node in range(self.m_num_of_nodes	):
								self.m_component.update({node: node}	)
								component_size.append(1	)

							__lowercase		       =			self.m_num_of_nodes

							while num_of_components > 1:
								for edge in self.m_edges:
									__lowercase       ,    __lowercase       ,    __lowercase		       =			edge

									__lowercase		       =			self.m_component[u]
									__lowercase		       =			self.m_component[v]

									if u_component != v_component:

										for component in (u_component, v_component):
											if (
											    minimum_weight_edge[component] == -1
											    or minimum_weight_edge[component][2] > w
											):
												__lowercase		       =			[u, v, w]

								for edge in minimum_weight_edge:
									if isinstance(lowerCamelCase							,      lowerCamelCase	):
										__lowercase       ,    __lowercase       ,    __lowercase		       =			edge

										__lowercase		       =			self.m_component[u]
										__lowercase		       =			self.m_component[v]

										if u_component != v_component:
											mst_weight += w
											self.union(lowerCamelCase							,      lowerCamelCase							,      lowerCamelCase	)
											print(f"""Added edge [{u} - {v}]\nAdded weight: {w}\n"""	)
											num_of_components -= 1

								__lowercase		       =			[-1] * self.m_num_of_nodes
							print(f"""The total weight of the minimal spanning tree is: {mst_weight}"""	)



def    snake_case_				(    ):
	pass


if __name__ == "__main__":
	import doctest

	doctest.testmod()



