

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     __SCREAMING_SNAKE_CASE   (SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__=True    ,						SCREAMING_SNAKE_CASE__="pt"			):
						snake_case_  =      {'''add_prefix_space''': True} if isinstance(SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__			) and not line.startswith(''' '''			) else {}
						snake_case_  =      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     __SCREAMING_SNAKE_CASE   (SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__=None    ,						):
						snake_case_  =      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       snake_case_  (						__A   ):







			'''simple docstring'''

			def __init__(	self					:							Optional[int]				,  _UpperCamelCase					:							Dict				,  _UpperCamelCase					:							int				,  _UpperCamelCase					:							Tuple				,  _UpperCamelCase					:							int				,  _UpperCamelCase					:							Tuple="train"				,  _UpperCamelCase					:							Dict=None				,  _UpperCamelCase					:							Optional[int]=None				,  _UpperCamelCase					:							List[str]=None				,  _UpperCamelCase					:							int=""				,  ) ->Tuple:
									super().__init__()
									snake_case_  =      Path(_UpperCamelCase				).joinpath(type_path + '''.source'''				)
									snake_case_  =      Path(_UpperCamelCase				).joinpath(type_path + '''.target'''				)
									snake_case_  =      self.get_char_lens(self.src_file				)
									snake_case_  =      max_source_length
									snake_case_  =      max_target_length
									assert min(self.src_lens				) > 0, f'''found empty line in {self.src_file}'''
									snake_case_  =      tokenizer
									snake_case_  =      prefix
									if n_obs is not None:
															snake_case_  =      self.src_lens[:n_obs]
									snake_case_  =      src_lang
									snake_case_  =      tgt_lang







			def __len__(	self					:							List[str]				) ->Dict:
									return len(self.src_lens				)







			def __getitem__(	self					:							Tuple				,  _UpperCamelCase					:							Tuple				) ->Dict[str, torch.Tensor]:
									snake_case_  =      index + 1  # linecache starts at 1
									snake_case_  =      self.prefix + linecache.getline(str(self.src_file				)				,  _UpperCamelCase				).rstrip('''\n'''				)
									snake_case_  =      linecache.getline(str(self.tgt_file				)				,  _UpperCamelCase				).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				,  _UpperCamelCase				):
															source_line += self.tokenizer.eos_token
															tgt_line += self.tokenizer.eos_token

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

									snake_case_  =      encode_line(_UpperCamelCase				,  _UpperCamelCase				,  self.max_source_length				,  '''right'''				)
									snake_case_  =      encode_line(_UpperCamelCase				,  _UpperCamelCase				,  self.max_target_length				,  '''right'''				)

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







			@staticmethod
			def 							snake_case__(	_UpperCamelCase					:							Tuple				) ->Any:
									return [len(_UpperCamelCase				) for x in Path(_UpperCamelCase				).open().readlines()]







			def 							snake_case__(	self					:							Tuple				,  _UpperCamelCase					:							Optional[Any]				) ->Dict[str, torch.Tensor]:
									snake_case_  =      torch.stack([x['''input_ids'''] for x in batch]				)
									snake_case_  =      torch.stack([x['''attention_mask'''] for x in batch]				)
									snake_case_  =      torch.stack([x['''decoder_input_ids'''] for x in batch]				)
									snake_case_  =      (
									    self.tokenizer.generator.pad_token_id
									    if isinstance(self.tokenizer				,  _UpperCamelCase				)
									    else self.tokenizer.pad_token_id
									)
									snake_case_  =      (
									    self.tokenizer.question_encoder.pad_token_id
									    if isinstance(self.tokenizer				,  _UpperCamelCase				)
									    else self.tokenizer.pad_token_id
									)
									snake_case_  =      trim_batch(_UpperCamelCase				,  _UpperCamelCase				)
									snake_case_,       snake_case_  =      trim_batch(_UpperCamelCase				,  _UpperCamelCase				,  attention_mask=_UpperCamelCase				)
									snake_case_  =      {
									    '''input_ids''': source_ids,
									    '''attention_mask''': source_mask,
									    '''decoder_input_ids''': y,
									}
									return batch






lowerCAmelCase_			      =      getLogger(__name__)


def     __SCREAMING_SNAKE_CASE   (SCREAMING_SNAKE_CASE__			):
						return list(itertools.chain.from_iterable(SCREAMING_SNAKE_CASE__			)			)


def     __SCREAMING_SNAKE_CASE   (SCREAMING_SNAKE_CASE__			):
						snake_case_  =      get_git_info()
						save_json(SCREAMING_SNAKE_CASE__    ,						os.path.join(SCREAMING_SNAKE_CASE__    ,						'''git_log.json'''			)			)


def     __SCREAMING_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     __SCREAMING_SNAKE_CASE   (SCREAMING_SNAKE_CASE__			):
						with open(SCREAMING_SNAKE_CASE__			) as f:
												return json.load(SCREAMING_SNAKE_CASE__			)


def     __SCREAMING_SNAKE_CASE   ():
						snake_case_  =      git.Repo(search_parent_directories=SCREAMING_SNAKE_CASE__			)
						snake_case_  =      {
						    '''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     __SCREAMING_SNAKE_CASE   (SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__			):
						return list(map(SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__			)			)


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


def     __SCREAMING_SNAKE_CASE   (SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__			):
						return normalize_answer(SCREAMING_SNAKE_CASE__			) == normalize_answer(SCREAMING_SNAKE_CASE__			)


def     __SCREAMING_SNAKE_CASE   (SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__			):
						assert len(SCREAMING_SNAKE_CASE__			) == len(SCREAMING_SNAKE_CASE__			)
						snake_case_  =      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     __SCREAMING_SNAKE_CASE   (SCREAMING_SNAKE_CASE__			):
						return model_prefix.startswith('''rag'''			)


def     __SCREAMING_SNAKE_CASE   (SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__			):
						snake_case_  =      {p: p for p in extra_params}
						# T5 models don't have `dropout` param, they have `dropout_rate` instead
						snake_case_  =      '''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
																		snake_case_  =      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






# this script reports modified .py files under the desired list of top-level sub-dirs passed as a list of arguments, e.g.:
#   python ./utils/get_modified_files.py utils src tests examples
#
# it uses git to find the forking point and which files were modified - i.e. files not under git won't be considered
# since the output of this script is fed into Makefile commands it doesn't print a newline after the results

import re
import subprocess
import sys


UpperCamelCase__           =			subprocess.check_output("git merge-base main HEAD".split()).decode("utf-8")
UpperCamelCase__           =			subprocess.check_output(f"""git diff --name-only {fork_point_sha}""".split()).decode("utf-8").split()

UpperCamelCase__           =			"|".join(sys.argv[1:])
UpperCamelCase__           =			re.compile(rf"""^({joined_dirs}).*?\.py$""")

UpperCamelCase__           =			[x for x in modified_files if regex.match(x)]
print(" ".join(relevant_modified_files), end="")




