



from collections import defaultdict
from pathlib import Path

import pandas as pd
from rouge_cli import calculate_rouge_path

from utils import calculate_rouge


SCREAMING_SNAKE_CASE__   			=   [
    '''Prosecutor: "No videos were used in the crash investigation" German papers say they saw a cell phone video of the'''
    ''' final seconds on board Flight 9525. The Germanwings co-pilot says he had a "previous episode of severe'''
    ''' depression\" German airline confirms it knew of Andreas Lubitz\'s depression years before he took control.''',
    '''The Palestinian Authority officially becomes the 123rd member of the International Criminal Court. The formal'''
    ''' accession was marked with a ceremony at The Hague, in the Netherlands. The Palestinians signed the ICC\'s'''
    ''' founding Rome Statute in January. Israel and the United States opposed the Palestinians\' efforts to join the'''
    ''' body.''',
    '''Amnesty International releases its annual report on the death penalty. The report catalogs the use of'''
    ''' state-sanctioned killing as a punitive measure across the globe. At least 607 people were executed around the'''
    ''' world in 2014, compared to 778 in 2013. The U.S. remains one of the worst offenders for imposing capital'''
    ''' punishment.''',
]

SCREAMING_SNAKE_CASE__   			=   [
    '''Marseille prosecutor says "so far no videos were used in the crash investigation" despite media reports .'''
    ''' Journalists at Bild and Paris Match are "very confident" the video clip is real, an editor says . Andreas Lubitz'''
    ''' had informed his Lufthansa training school of an episode of severe depression, airline says .''',
    '''Membership gives the ICC jurisdiction over alleged crimes committed in Palestinian territories since last June .'''
    ''' Israel and the United States opposed the move, which could open the door to war crimes investigations against'''
    ''' Israelis .''',
    '''Amnesty\'s annual death penalty report catalogs encouraging signs, but setbacks in numbers of those sentenced to'''
    ''' death . Organization claims that governments around the world are using the threat of terrorism to advance'''
    ''' executions . The number of executions worldwide has gone down by almost 22% compared with 2013, but death'''
    ''' sentences up by 28% .''',
]


def A    (							)    ->   Optional[int]:
			A__	  =     calculate_rouge(__UpperCamelCase			,						__UpperCamelCase			,						bootstrap_aggregation=__UpperCamelCase			,						rouge_keys=['rouge2', 'rougeL']       )
			assert isinstance(__UpperCamelCase			,						__UpperCamelCase       )
			A__	  =     calculate_rouge(__UpperCamelCase			,						__UpperCamelCase			,						bootstrap_aggregation=__UpperCamelCase			,						rouge_keys=['rouge2']       )
			assert (
			    pd.DataFrame(no_aggregation['rouge2']       ).fmeasure.mean()
			    == pd.DataFrame(no_aggregation_just_ra['rouge2']       ).fmeasure.mean()
			)


def A    (							)    ->   Optional[Any]:
			A__	  =     'rougeLsum'
			A__	  =     calculate_rouge(__UpperCamelCase			,						__UpperCamelCase			,						newline_sep=__UpperCamelCase			,						rouge_keys=[k]       )[k]
			A__	  =     calculate_rouge(__UpperCamelCase			,						__UpperCamelCase			,						newline_sep=__UpperCamelCase			,						rouge_keys=[k]       )[k]
			assert score > score_no_sep


def A    (							)    ->   Optional[Any]:
			A__	  =     ['rouge1', 'rouge2', 'rougeL']
			A__	  =     calculate_rouge(__UpperCamelCase			,						__UpperCamelCase			,						newline_sep=__UpperCamelCase			,						rouge_keys=__UpperCamelCase       )
			A__	  =     calculate_rouge(__UpperCamelCase			,						__UpperCamelCase			,						newline_sep=__UpperCamelCase			,						rouge_keys=__UpperCamelCase       )
			assert score_sep == score_no_sep


def A    (							)    ->   Optional[Any]:
			A__	  =     [
			    'Her older sister, Margot Frank, died in 1945, a month earlier than previously thought.',
			    'Marseille prosecutor says "so far no videos were used in the crash investigation" despite media reports .',
			]
			A__	  =     [
			    'Margot Frank, died in 1945, a month earlier than previously thought.',
			    'Prosecutor: "No videos were used in the crash investigation" German papers say they saw a cell phone video of'
			    ' the final seconds on board Flight 9525.',
			]
			assert calculate_rouge(__UpperCamelCase			,						__UpperCamelCase			,						newline_sep=__UpperCamelCase       ) == calculate_rouge(__UpperCamelCase			,						__UpperCamelCase			,						newline_sep=__UpperCamelCase       )


def A    (							)    ->   Tuple:
			A__	  =     [
			    '" "a person who has such a video needs to immediately give it to the investigators," prosecutor says .<n> "it is a very disturbing scene," editor-in-chief of bild online tells "erin burnett: outfront" '
			]
			A__	  =     [
			    ' Marseille prosecutor says "so far no videos were used in the crash investigation" despite media reports . Journalists at Bild and Paris Match are "very confident" the video clip is real, an editor says . Andreas Lubitz had informed his Lufthansa training school of an episode of severe depression, airline says .'
			]

			A__	  =     calculate_rouge(__UpperCamelCase			,						__UpperCamelCase			,						rouge_keys=['rougeLsum']			,						newline_sep=__UpperCamelCase       )['rougeLsum']
			A__	  =     calculate_rouge(__UpperCamelCase			,						__UpperCamelCase			,						rouge_keys=['rougeLsum']       )['rougeLsum']
			assert new_score > prev_score






def A    (							)    ->   str:
			A__	  =     Path('examples/seq2seq/test_data/wmt_en_ro'       )
			A__	  =     calculate_rouge_path(data_dir.joinpath('test.source'       )			,						data_dir.joinpath('test.target'       )       )
			assert isinstance(__UpperCamelCase			,						__UpperCamelCase       )
			A__	  =     calculate_rouge_path(
			    data_dir.joinpath('test.source'       )			,						data_dir.joinpath('test.target'       )			,						bootstrap_aggregation=__UpperCamelCase       )
			assert isinstance(__UpperCamelCase			,						__UpperCamelCase       )












"""simple docstring"""
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       __UpperCamelCase						(		snake_case__ , snake_case__ , snake_case__ , snake_case__ , snake_case__=True , snake_case__="pt"       ):
	A_		:    Dict						     = {"""add_prefix_space""": True} if isinstance(snake_case__ , snake_case__       ) and not line.startswith(""" """       ) else {}
	A_		:    int						     = padding_side
	return tokenizer(
	    [line] , max_length=snake_case__ , padding="""max_length""" if pad_to_max_length else None , truncation=snake_case__ , return_tensors=snake_case__ , add_special_tokens=snake_case__ , **snake_case__ , )






def       __UpperCamelCase						(		snake_case__ , snake_case__ , snake_case__=None , ):
	A_		:    int						     = input_ids.ne(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   SCREAMING_SNAKE_CASE	(					_SCREAMING_SNAKE_CASE    ):





	"""simple docstring"""




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





	def __len__(self				):
		return len(self.src_lens				)





	def __getitem__(self  ,  lowerCAmelCase_				):
		A_		:    Optional[Any]						     = index + 1  # linecache starts at 1
		A_		:    int						     = self.prefix + linecache.getline(str(self.src_file				)  ,  lowerCAmelCase_				).rstrip("""\n"""				)
		A_		:    Any						     = 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
		A_		:    Optional[Any]						     = (
		    self.tokenizer.question_encoder if isinstance(self.tokenizer  ,  lowerCAmelCase_				) else self.tokenizer
		)
		A_		:    Optional[int]						     = self.tokenizer.generator if isinstance(self.tokenizer  ,  lowerCAmelCase_				) else self.tokenizer

		A_		:    str						     = encode_line(lowerCAmelCase_  ,  lowerCAmelCase_  ,  self.max_source_length  ,  """right"""				)
		A_		:    Optional[Any]						     = encode_line(lowerCAmelCase_  ,  lowerCAmelCase_  ,  self.max_target_length  ,  """right"""				)

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





	@staticmethod
	def  lowerCamelCase(lowerCAmelCase_				):
		return [len(lowerCAmelCase_				) for x in Path(lowerCAmelCase_				).open().readlines()]





	def  lowerCamelCase(self  ,  lowerCAmelCase_				):
		A_		:    List[str]						     = torch.stack([x["""input_ids"""] for x in batch]				)
		A_		:    Optional[int]						     = torch.stack([x["""attention_mask"""] for x in batch]				)
		A_		:    Any						     = torch.stack([x["""decoder_input_ids"""] for x in batch]				)
		A_		:    Optional[Any]						     = (
		    self.tokenizer.generator.pad_token_id
		    if isinstance(self.tokenizer  ,  lowerCAmelCase_				)
		    else self.tokenizer.pad_token_id
		)
		A_		:    int						     = (
		    self.tokenizer.question_encoder.pad_token_id
		    if isinstance(self.tokenizer  ,  lowerCAmelCase_				)
		    else self.tokenizer.pad_token_id
		)
		A_		:    List[str]						     = trim_batch(lowerCAmelCase_  ,  lowerCAmelCase_				)
		A_     ,  A_		:    Dict						     = trim_batch(lowerCAmelCase_  ,  lowerCAmelCase_  ,  attention_mask=lowerCAmelCase_				)
		A_		:    Optional[Any]						     = {
		    """input_ids""": source_ids,
		    """attention_mask""": source_mask,
		    """decoder_input_ids""": y,
		}
		return batch






_lowerCAmelCase       =				getLogger(__name__)






def       __UpperCamelCase						(		snake_case__       ):
	return list(itertools.chain.from_iterable(snake_case__       )       )






def       __UpperCamelCase						(		snake_case__       ):
	A_		:    List[str]						     = get_git_info()
	save_json(snake_case__ , os.path.join(snake_case__ , """git_log.json"""       )       )






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






def       __UpperCamelCase						(		snake_case__       ):
	with open(snake_case__       ) as f:
		return json.load(snake_case__       )






def       __UpperCamelCase						(		):
	A_		:    Optional[int]						     = git.Repo(search_parent_directories=snake_case__       )
	A_		:    Union[str, Any]						     = {
	    """repo_id""": str(snake_case__       ),
	    """repo_sha""": str(repo.head.object.hexsha       ),
	    """repo_branch""": str(repo.active_branch       ),
	    """hostname""": str(socket.gethostname()       ),
	}
	return repo_infos






def       __UpperCamelCase						(		snake_case__ , snake_case__       ):
	return list(map(snake_case__ , snake_case__       )       )






def       __UpperCamelCase						(		snake_case__ , snake_case__       ):
	with open(snake_case__ , """wb"""       ) as f:
		return pickle.dump(snake_case__ , snake_case__       )






def       __UpperCamelCase						(		snake_case__       ):

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

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

	def remove_punc(snake_case__       ):
		A_		:    Optional[Any]						     = set(string.punctuation       )
		return "".join(ch for ch in text if ch not in exclude       )

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

	return white_space_fix(remove_articles(remove_punc(lower(snake_case__       )       )       )       )






def       __UpperCamelCase						(		snake_case__ , snake_case__       ):
	A_		:    Tuple						     = normalize_answer(snake_case__       ).split()
	A_		:    Dict						     = normalize_answer(snake_case__       ).split()
	A_		:    int						     = Counter(snake_case__       ) & Counter(snake_case__       )
	A_		:    Dict						     = sum(common.values()       )
	if num_same == 0:
		return 0
	A_		:    str						     = 1.0 * num_same / len(snake_case__       )
	A_		:    Any						     = 1.0 * num_same / len(snake_case__       )
	A_		:    Union[str, Any]						     = (2 * precision * recall) / (precision + recall)
	return fa






def       __UpperCamelCase						(		snake_case__ , snake_case__       ):
	return normalize_answer(snake_case__       ) == normalize_answer(snake_case__       )






def       __UpperCamelCase						(		snake_case__ , snake_case__       ):
	assert len(snake_case__       ) == len(snake_case__       )
	A_		:    Optional[Any]						     = 0
	for hypo, pred in zip(snake_case__ , snake_case__       ):
		em += exact_match_score(snake_case__ , snake_case__       )
	if len(snake_case__       ) > 0:
		em /= len(snake_case__       )
	return {"em": em}






def       __UpperCamelCase						(		snake_case__       ):
	return model_prefix.startswith("""rag"""       )






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

