


'''simple docstring'''
import asyncio
import os
import re
import sys
import tempfile
import unittest
from contextlib import contextmanager
from copy import deepcopy
from distutils.util import strtobool
from enum import Enum
from importlib.util import find_spec
from pathlib import Path
from unittest.mock import patch

import pyarrow as pa
import pytest
import requests
from packaging import version

from datasets import config


if config.PY_VERSION < version.parse('3.8'):
 import importlib_metadata
else:
 import importlib.metadata as importlib_metadata


def 			_lowercase       (				UpperCamelCase__       :					Tuple,				UpperCamelCase__       :					Any=False			):
 try:
  __A  :		int       =			os.environ[key]
 except KeyError:
  # KEY isn't set, default to `default`.
  __A  :		Any       =			default
 else:
  # KEY is set, convert it to True or False.
  try:
   __A  :		Union[str, Any]       =			strtobool(UpperCamelCase__			)
  except ValueError:
   # More values are supported, but let's keep the message simple.
   raise ValueError(f"""If set, {key} must be yes or no."""			)
 return _value


UpperCAmelCase_ :     str								=      parse_flag_from_env('RUN_SLOW', default=False)
UpperCAmelCase_ :     Tuple								=      parse_flag_from_env('RUN_REMOTE', default=False)
UpperCAmelCase_ :     Tuple								=      parse_flag_from_env('RUN_LOCAL', default=True)
UpperCAmelCase_ :     int								=      parse_flag_from_env('RUN_PACKAGED', default=True)

# Compression
UpperCAmelCase_ :     Optional[int]								=      pytest.mark.skipif(not config.LZ4_AVAILABLE, reason='test requires lz4')
UpperCAmelCase_ :     List[str]								=      pytest.mark.skipif(not config.PY7ZR_AVAILABLE, reason='test requires py7zr')
UpperCAmelCase_ :     Tuple								=      pytest.mark.skipif(not config.ZSTANDARD_AVAILABLE, reason='test requires zstandard')

# Audio
UpperCAmelCase_ :     Dict								=      pytest.mark.skipif(
    # On Windows and OS X, soundfile installs sndfile
    find_spec('soundfile') is None or version.parse(importlib_metadata.version('soundfile')) < version.parse('0.12.0'),
    reason='test requires sndfile>=0.12.1: \'pip install \"soundfile>=0.12.1\"\'; ',
)

# Beam
UpperCAmelCase_ :     Optional[Any]								=      pytest.mark.skipif(
    not config.BEAM_AVAILABLE or config.DILL_VERSION >= version.parse('0.3.2'),
    reason='test requires apache-beam and a compatible dill version',
)

# Dill-cloudpickle compatibility
UpperCAmelCase_ :     Tuple								=      pytest.mark.skipif(
    config.DILL_VERSION <= version.parse('0.3.2'),
    reason='test requires dill>0.3.2 for cloudpickle compatibility',
)

# Windows
UpperCAmelCase_ :     Optional[Any]								=      pytest.mark.skipif(
    sys.platform == 'win32',
    reason='test should not be run on Windows',
)


def 			_lowercase       (				UpperCamelCase__       :					Union[str, Any]			):
 try:
  import faiss  # noqa
 except ImportError:
  __A  :		List[Any]       =			unittest.skip('test requires faiss'			)(UpperCamelCase__			)
 return test_case


def 			_lowercase       (				UpperCamelCase__       :					int			):
 try:
  import regex  # noqa
 except ImportError:
  __A  :		List[str]       =			unittest.skip('test requires regex'			)(UpperCamelCase__			)
 return test_case


def 			_lowercase       (				UpperCamelCase__       :					Optional[int]			):
 try:
  import elasticsearch  # noqa
 except ImportError:
  __A  :		List[str]       =			unittest.skip('test requires elasticsearch'			)(UpperCamelCase__			)
 return test_case


def 			_lowercase       (				UpperCamelCase__       :					str			):
 try:
  import sqlalchemy  # noqa
 except ImportError:
  __A  :		Any       =			unittest.skip('test requires sqlalchemy'			)(UpperCamelCase__			)
 return test_case


def 			_lowercase       (				UpperCamelCase__       :					Union[str, Any]			):
 if not config.TORCH_AVAILABLE:
  __A  :		int       =			unittest.skip('test requires PyTorch'			)(UpperCamelCase__			)
 return test_case


def 			_lowercase       (				UpperCamelCase__       :					Dict			):
 if not config.TF_AVAILABLE:
  __A  :		Optional[Any]       =			unittest.skip('test requires TensorFlow'			)(UpperCamelCase__			)
 return test_case


def 			_lowercase       (				UpperCamelCase__       :					Optional[int]			):
 if not config.JAX_AVAILABLE:
  __A  :		int       =			unittest.skip('test requires JAX'			)(UpperCamelCase__			)
 return test_case


def 			_lowercase       (				UpperCamelCase__       :					Tuple			):
 if not config.PIL_AVAILABLE:
  __A  :		List[Any]       =			unittest.skip('test requires Pillow'			)(UpperCamelCase__			)
 return test_case


def 			_lowercase       (				UpperCamelCase__       :					int			):
 try:
  import transformers  # noqa F401
 except ImportError:
  return unittest.skip('test requires transformers'			)(UpperCamelCase__			)
 else:
  return test_case


def 			_lowercase       (				UpperCamelCase__       :					Any			):
 try:
  import tiktoken  # noqa F401
 except ImportError:
  return unittest.skip('test requires tiktoken'			)(UpperCamelCase__			)
 else:
  return test_case


def 			_lowercase       (				UpperCamelCase__       :					Dict			):
 try:
  import spacy  # noqa F401
 except ImportError:
  return unittest.skip('test requires spacy'			)(UpperCamelCase__			)
 else:
  return test_case


def 			_lowercase       (				UpperCamelCase__       :					Tuple			):

 def _require_spacy_model(UpperCamelCase__       :					Union[str, Any]			):
  try:
   import spacy  # noqa F401

   spacy.load(UpperCamelCase__			)
  except ImportError:
   return unittest.skip('test requires spacy'			)(UpperCamelCase__			)
  except OSError:
   return unittest.skip('test requires spacy model \'{}\''.format(UpperCamelCase__			)			)(UpperCamelCase__			)
  else:
   return test_case

 return _require_spacy_model


def 			_lowercase       (				UpperCamelCase__       :					Any			):
 try:
  import pyspark  # noqa F401
 except ImportError:
  return unittest.skip('test requires pyspark'			)(UpperCamelCase__			)
 else:
  return test_case


def 			_lowercase       (				UpperCamelCase__       :					Any			):
 try:
  import joblibspark  # noqa F401
 except ImportError:
  return unittest.skip('test requires joblibspark'			)(UpperCamelCase__			)
 else:
  return test_case


def 			_lowercase       (				UpperCamelCase__       :					Optional[Any]			):
 if not _run_slow_tests or _run_slow_tests == 0:
  __A  :		Any       =			unittest.skip('test is slow'			)(UpperCamelCase__			)
 return test_case


def 			_lowercase       (				UpperCamelCase__       :					Union[str, Any]			):
 if not _run_local_tests or _run_local_tests == 0:
  __A  :		str       =			unittest.skip('test is local'			)(UpperCamelCase__			)
 return test_case


def 			_lowercase       (				UpperCamelCase__       :					Optional[Any]			):
 if not _run_packaged_tests or _run_packaged_tests == 0:
  __A  :		Any       =			unittest.skip('test is packaged'			)(UpperCamelCase__			)
 return test_case


def 			_lowercase       (				UpperCamelCase__       :					Tuple			):
 if not _run_remote_tests or _run_remote_tests == 0:
  __A  :		Optional[Any]       =			unittest.skip('test requires remote'			)(UpperCamelCase__			)
 return test_case


def 			_lowercase       (				*UpperCamelCase__       :					Tuple			):
 def decorate(cls       :					Tuple			):
  for name, fn in cls.__dict__.items():
   if callable(UpperCamelCase__			) and name.startswith('test'			):
    for decorator in decorators:
     __A  :		Union[str, Any]       =			decorator(UpperCamelCase__			)
    setattr(cls,				UpperCamelCase__,				UpperCamelCase__			)
  return cls

 return decorate

class 						_lowerCamelCase					(    snake_case_				):




 '''simple docstring'''
 pass


class 						_lowerCamelCase					(    snake_case_				):




 '''simple docstring'''
 __lowercase				:		str    							=						0
 __lowercase				:		Union[str, Any]    							=						1
 __lowercase				:		str    							=						2


@contextmanager
def 			_lowercase       (				UpperCamelCase__       :					int=OfflineSimulationMode.CONNECTION_FAILS,				UpperCamelCase__       :					Optional[int]=1E-16			):
 __A  :		List[str]       =			requests.Session().request

 def timeout_request(UpperCamelCase__       :					Dict,				UpperCamelCase__       :					str,				UpperCamelCase__       :					int,				**UpperCamelCase__       :					Optional[Any]			):
  # Change the url to an invalid url so that the connection hangs
  __A  :		List[Any]       =			'https://10.255.255.1'
  if kwargs.get('timeout'			) is None:
   raise RequestWouldHangIndefinitelyError(
       f"""Tried a call to {url} in offline mode with no timeout set. Please set a timeout."""			)
  __A  :		Dict       =			timeout
  try:
   return online_request(UpperCamelCase__,				UpperCamelCase__,				**UpperCamelCase__			)
  except Exception as e:
   # The following changes in the error are just here to make the offline timeout error prettier
   __A  :		Tuple       =			url
   __A  :		List[str]       =			e.args[0]
   __A  :		str       =			(max_retry_error.args[0].replace('10.255.255.1',				f"""OfflineMock[{url}]"""			),)
   __A  :		Union[str, Any]       =			(max_retry_error,)
   raise

 def raise_connection_error(UpperCamelCase__       :					Any,				UpperCamelCase__       :					str,				**UpperCamelCase__       :					List[str]			):
  raise requests.ConnectionError('Offline mode is enabled.',				request=UpperCamelCase__			)

 if mode is OfflineSimulationMode.CONNECTION_FAILS:
  with patch('requests.Session.send',				UpperCamelCase__			):
   yield
 elif mode is OfflineSimulationMode.CONNECTION_TIMES_OUT:
  # inspired from https://stackoverflow.com/a/904609
  with patch('requests.Session.request',				UpperCamelCase__			):
   yield
 elif mode is OfflineSimulationMode.HF_DATASETS_OFFLINE_SET_TO_1:
  with patch('datasets.config.HF_DATASETS_OFFLINE',				UpperCamelCase__			):
   yield
 else:
  raise ValueError('Please use a value from the OfflineSimulationMode enum.'			)


@contextmanager
def 			_lowercase       (				*UpperCamelCase__       :					Optional[int],				**UpperCamelCase__       :					Optional[Any]			):
 __A  :		Union[str, Any]       =			str(Path().resolve()			)
 with tempfile.TemporaryDirectory(*UpperCamelCase__,				**UpperCamelCase__			) as tmp_dir:
  try:
   os.chdir(UpperCamelCase__			)
   yield
  finally:
   os.chdir(UpperCamelCase__			)


@contextmanager
def 			_lowercase       (				):
 import gc

 gc.collect()
 __A  :		Dict       =			pa.total_allocated_bytes()
 yield
 assert pa.total_allocated_bytes() - previous_allocated_memory > 0, "Arrow memory didn't increase."


@contextmanager
def 			_lowercase       (				):
 import gc

 gc.collect()
 __A  :		List[Any]       =			pa.total_allocated_bytes()
 yield
 assert pa.total_allocated_bytes() - previous_allocated_memory <= 0, "Arrow memory wasn't expected to increase."


def 			_lowercase       (				UpperCamelCase__       :					int,				UpperCamelCase__       :					Union[str, Any]			):
 return deepcopy(UpperCamelCase__			).integers(0,				100,				10			).tolist() == deepcopy(UpperCamelCase__			).integers(0,				100,				10			).tolist()


def 			_lowercase       (				UpperCamelCase__       :					str			):
 import decorator
 from requests.exceptions import HTTPError

 def _wrapper(UpperCamelCase__       :					Dict,				*UpperCamelCase__       :					List[str],				**UpperCamelCase__       :					int			):
  try:
   return func(*UpperCamelCase__,				**UpperCamelCase__			)
  except HTTPError as err:
   if str(UpperCamelCase__			).startswith('500'			) or str(UpperCamelCase__			).startswith('502'			):
    pytest.xfail(str(UpperCamelCase__			)			)
   raise err

 return decorator.decorator(_wrapper,				UpperCamelCase__			)

class 						_lowerCamelCase					:




 '''simple docstring'''


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

  """simple docstring"""







  __A  :		Any       =			returncode
  __A  :		Union[str, Any]       =			stdout
  __A  :		Optional[Any]       =			stderr


async def 			_lowercase       (				UpperCamelCase__       :					List[str],				UpperCamelCase__       :					Any			):
 while True:
  __A  :		Dict       =			await stream.readline()
  if line:
   callback(UpperCamelCase__			)
  else:
   break


async def 			_lowercase       (				UpperCamelCase__       :					Union[str, Any],				UpperCamelCase__       :					Union[str, Any]=None,				UpperCamelCase__       :					int=None,				UpperCamelCase__       :					List[str]=None,				UpperCamelCase__       :					Union[str, Any]=False,				UpperCamelCase__       :					Any=False			):
 if echo:
  print('\nRunning: ',				' '.join(UpperCamelCase__			)			)

 __A  :		int       =			await asyncio.create_subprocess_exec(
     cmd[0],				*cmd[1:],				stdin=UpperCamelCase__,				stdout=asyncio.subprocess.PIPE,				stderr=asyncio.subprocess.PIPE,				env=UpperCamelCase__,				)

 # note: there is a warning for a possible deadlock when using `wait` with huge amounts of data in the pipe
 # https://docs.python.org/3/library/asyncio-subprocess.html#asyncio.asyncio.subprocess.Process.wait
 #
 # If it starts hanging, will need to switch to the following code. The problem is that no data
 # will be seen until it's done and if it hangs for example there will be no debug info.
 # out, err = await p.communicate()
 # return _RunOutput(p.returncode, out, err)

 __A  :		int       =			[]
 __A  :		int       =			[]

 def tee(UpperCamelCase__       :					Optional[Any],				UpperCamelCase__       :					int,				UpperCamelCase__       :					Any,				UpperCamelCase__       :					str=""			):
  __A  :		str       =			line.decode('utf-8'			).rstrip()
  sink.append(UpperCamelCase__			)
  if not quiet:
   print(UpperCamelCase__,				UpperCamelCase__,				file=UpperCamelCase__			)

    # XXX: the timeout doesn't seem to make any difference here
 await asyncio.wait(
     [
         _read_stream(p.stdout,				lambda UpperCamelCase__			: tee(UpperCamelCase__,				UpperCamelCase__,				sys.stdout,				label='stdout:'			)			),
         _read_stream(p.stderr,				lambda UpperCamelCase__			: tee(UpperCamelCase__,				UpperCamelCase__,				sys.stderr,				label='stderr:'			)			),
     ],				timeout=UpperCamelCase__,				)
 return _RunOutput(await p.wait(),				UpperCamelCase__,				UpperCamelCase__			)


def 			_lowercase       (				UpperCamelCase__       :					str,				UpperCamelCase__       :					Optional[Any]=None,				UpperCamelCase__       :					int=None,				UpperCamelCase__       :					Optional[Any]=180,				UpperCamelCase__       :					Dict=False,				UpperCamelCase__       :					int=True			):
 __A  :		List[str]       =			asyncio.get_event_loop()
 __A  :		Optional[int]       =			loop.run_until_complete(
     _stream_subprocess(UpperCamelCase__,				env=UpperCamelCase__,				stdin=UpperCamelCase__,				timeout=UpperCamelCase__,				quiet=UpperCamelCase__,				echo=UpperCamelCase__			)			)

 __A  :		List[Any]       =			' '.join(UpperCamelCase__			)
 if result.returncode > 0:
  __A  :		Dict       =			'\n'.join(result.stderr			)
  raise RuntimeError(
      f"""'{cmd_str}' failed with returncode {result.returncode}\n\n"""
      f"""The combined stderr from workers follows:\n{stderr}"""			)

 # check that the subprocess actually did run and produced some output, should the test rely on
 # the remote side to do the testing
 if not result.stdout and not result.stderr:
  raise RuntimeError(f"""'{cmd_str}' produced no output."""			)

 return result


def 			_lowercase       (				):
 __A  :		List[Any]       =			os.environ.get('PYTEST_XDIST_WORKER',				'gw0'			)
 __A  :		Dict       =			re.sub(r'^gw',				'',				UpperCamelCase__,				0,				re.M			)
 return int(UpperCamelCase__			)


def 			_lowercase       (				):
 __A  :		Any       =			29500
 __A  :		Optional[Any]       =			pytest_xdist_worker_id()
 return port + uniq_delta










'''simple docstring'''
import argparse
import shutil
import time
from json import JSONDecodeError
from logging import getLogger
from pathlib import Path
from typing import Dict, List

import torch
from torch.utils.data import DataLoader
from tqdm import tqdm

from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from utils import (
    SeqaSeqDataset,
    calculate_bleu,
    calculate_rouge,
    chunks,
    lmap,
    load_json,
    parse_numeric_n_bool_cl_kwargs,
    save_json,
    use_task_specific_params,
    write_txt_file,
)


UpperCAmelCase_ :     Dict								=      getLogger(__name__)


def 			_lowercase       (				UpperCamelCase__       :					List[Any],				UpperCamelCase__       :					str,				UpperCamelCase__       :					str,				UpperCamelCase__       :					int = 8,				UpperCamelCase__       :					int = 1024,				UpperCamelCase__       :					List[Any]="val",				UpperCamelCase__       :					int=None,				UpperCamelCase__       :					str=False,				UpperCamelCase__       :					int="summarization",				UpperCamelCase__       :					List[Any]=None,				UpperCamelCase__       :					List[Any]=1,				UpperCamelCase__       :					Dict = None,				UpperCamelCase__       :					Optional[int]="",				**UpperCamelCase__       :					str,				):
 __A  :		Dict       =			str(UpperCamelCase__			)
 assert local_rank is not None
 torch.distributed.init_process_group(backend='nccl',				rank=UpperCamelCase__			)

 __A  :		Union[str, Any]       =			Path(UpperCamelCase__			)
 __A  :		Optional[int]       =			save_dir.joinpath(f"""rank_{local_rank}_output.json"""			)
 torch.cuda.set_device(UpperCamelCase__			)
 __A  :		Dict       =			AutoModelForSeqaSeqLM.from_pretrained(UpperCamelCase__			).cuda()
 if fpaa:
  __A  :		Optional[Any]       =			model.half()
 # determine if we need to increase num_beams
 use_task_specific_params(UpperCamelCase__,				UpperCamelCase__			)  # update config with task specific params
 __A  :		Any       =			generate_kwargs.pop('num_beams',				model.config.num_beams			)  # AttributeError risk?
 if num_return_sequences > num_beams:
  __A  :		int       =			num_return_sequences

 __A  :		Optional[Any]       =			AutoTokenizer.from_pretrained(UpperCamelCase__			)
 logger.info(f"""Inferred tokenizer type: {tokenizer.__class__}"""			)  # if this is wrong, check config.model_type.

 if max_source_length is None:
  __A  :		Union[str, Any]       =			tokenizer.model_max_length
 if prefix is None:
  __A  :		List[Any]       =			prefix or getattr(model.config,				'prefix',				''			) or ''
 __A  :		Tuple       =			SeqaSeqDataset(
     UpperCamelCase__,				UpperCamelCase__,				UpperCamelCase__,				max_target_length=1024,				type_path=UpperCamelCase__,				n_obs=UpperCamelCase__,				prefix=UpperCamelCase__,				**UpperCamelCase__,				)
 # I set shuffle=True for a more accurate progress bar.
 # If all the longest samples are first, the prog bar estimate is too high at the beginning.
 __A  :		Any       =			ds.make_sortish_sampler(UpperCamelCase__,				distributed=UpperCamelCase__,				add_extra_examples=UpperCamelCase__,				shuffle=UpperCamelCase__			)
 __A  :		Union[str, Any]       =			DataLoader(UpperCamelCase__,				sampler=UpperCamelCase__,				batch_size=UpperCamelCase__,				collate_fn=ds.collate_fn			)
 __A  :		Tuple       =			[]
 for batch in tqdm(UpperCamelCase__			):
  __A  :		Any       =			model.generate(
      input_ids=batch['input_ids'].to(model.device			),				attention_mask=batch['attention_mask'].to(model.device			),				num_return_sequences=UpperCamelCase__,				num_beams=UpperCamelCase__,				**UpperCamelCase__,				)
  __A  :		Dict       =			tokenizer.batch_decode(UpperCamelCase__,				skip_special_tokens=UpperCamelCase__,				clean_up_tokenization_spaces=UpperCamelCase__			)
  __A  :		List[str]       =			batch['ids']
  if num_return_sequences > 1:
   __A  :		str       =			chunks(UpperCamelCase__,				UpperCamelCase__			)  # batch size chunks, each of size num_return_seq
  for i, pred in enumerate(UpperCamelCase__			):
   results.append({'pred': pred, 'id': ids[i].item()}			)
 save_json(UpperCamelCase__,				UpperCamelCase__			)
 return results, sampler.num_replicas


def 			_lowercase       (				):
 __A  :		Optional[Any]       =			argparse.ArgumentParser(
     epilog='Unspecified args like --num_beams=2 --decoder_start_token_id=4 are passed to model.generate'			)
 parser.add_argument('--data_dir',				type=UpperCamelCase__,				help='like cnn_dm/test.source'			)
 parser.add_argument(
     '--model_name',				type=UpperCamelCase__,				help='like facebook/bart-large-cnn,t5-base, etc.',				default='sshleifer/distilbart-xsum-12-3',				)
 parser.add_argument('--save_dir',				type=UpperCamelCase__,				help='where to save',				default='tmp_gen'			)
 parser.add_argument('--max_source_length',				type=UpperCamelCase__,				default=UpperCamelCase__			)
 parser.add_argument(
     '--type_path',				type=UpperCamelCase__,				default='test',				help='which subset to evaluate typically train/val/test'			)
 parser.add_argument('--task',				type=UpperCamelCase__,				default='summarization',				help='used for task_specific_params + metrics'			)
 parser.add_argument('--bs',				type=UpperCamelCase__,				default=8,				required=UpperCamelCase__,				help='batch size'			)
 parser.add_argument(
     '--local_rank',				type=UpperCamelCase__,				default=-1,				required=UpperCamelCase__,				help='should be passed by distributed.launch'			)

 parser.add_argument(
     '--n_obs',				type=UpperCamelCase__,				default=UpperCamelCase__,				required=UpperCamelCase__,				help='How many observations. Defaults to all.'			)
 parser.add_argument(
     '--num_return_sequences',				type=UpperCamelCase__,				default=1,				required=UpperCamelCase__,				help='How many sequences to return'			)
 parser.add_argument(
     '--sync_timeout',				type=UpperCamelCase__,				default=600,				required=UpperCamelCase__,				help='How long should master process wait for other processes to finish.',				)
 parser.add_argument('--src_lang',				type=UpperCamelCase__,				default=UpperCamelCase__,				required=UpperCamelCase__			)
 parser.add_argument('--tgt_lang',				type=UpperCamelCase__,				default=UpperCamelCase__,				required=UpperCamelCase__			)
 parser.add_argument(
     '--prefix',				type=UpperCamelCase__,				required=UpperCamelCase__,				default=UpperCamelCase__,				help='will be added to the begininng of src examples'			)
 parser.add_argument('--fp16',				action='store_true'			)
 parser.add_argument('--debug',				action='store_true'			)
 __A  :		int       =			time.time()
 __A     ,__A  :		int       =			parser.parse_known_args()
 __A  :		List[str]       =			parse_numeric_n_bool_cl_kwargs(UpperCamelCase__			)
 if generate_kwargs and args.local_rank <= 0:
  print(f"""parsed the following generate kwargs: {generate_kwargs}"""			)
 __A  :		List[str]       =			Path(args.save_dir + '_tmp'			)
 Path(UpperCamelCase__			).mkdir(exist_ok=UpperCamelCase__			)  # this handles locking.
 __A  :		Optional[Any]       =			list(json_save_dir.glob('rank_*.json'			)			)
 if intermediate_files:
  raise ValueError(f"""Found files at {json_save_dir} please move or remove them."""			)
  # In theory, a node could finish and save before another node hits this. If this happens, we can address later.
 __A  :		List[str]       =			{}
 if args.src_lang is not None:
  __A  :		Dict       =			args.src_lang
 if args.tgt_lang is not None:
  __A  :		Optional[Any]       =			args.tgt_lang

 Path(args.save_dir			).mkdir(exist_ok=UpperCamelCase__			)
 __A     ,__A  :		List[Any]       =			eval_data_dir(
     args.data_dir,				UpperCamelCase__,				args.model_name,				type_path=args.type_path,				bs=args.bs,				fpaa=args.fpaa,				task=args.task,				local_rank=args.local_rank,				n_obs=args.n_obs,				max_source_length=args.max_source_length,				num_return_sequences=args.num_return_sequences,				prefix=args.prefix,				dataset_kwargs=UpperCamelCase__,				**UpperCamelCase__,				)

 if args.local_rank <= 0:
  __A  :		Tuple       =			Path(args.save_dir			)
  save_dir.mkdir(exist_ok=UpperCamelCase__			)
  __A  :		Dict       =			gather_results_from_each_node(UpperCamelCase__,				UpperCamelCase__,				args.sync_timeout			)
  __A  :		Union[str, Any]       =			combine_partial_results(UpperCamelCase__			)
  if args.num_return_sequences > 1:
   __A  :		Any       =			save_dir.joinpath('pseudolabel_results.json'			)
   print(f"""Saving aggregated results at {save_path}, intermediate in {json_save_dir}/"""			)
   save_json(UpperCamelCase__,				UpperCamelCase__			)
   return
  __A  :		int       =			Path(args.data_dir			).joinpath(args.type_path + '.target'			)
  with open(UpperCamelCase__			) as f:
   __A  :		str       =			[x.rstrip() for x in f.readlines()][: len(UpperCamelCase__			)]

  # Calculate metrics, save metrics,  and save _generations.txt
  __A  :		Tuple       =			'translation' in args.task
  __A  :		Union[str, Any]       =			calculate_bleu if calc_bleu else calculate_rouge
  __A  :		Optional[Any]       =			'bleu' if calc_bleu else 'rouge'
  __A  :		Dict       =			score_fn(UpperCamelCase__,				UpperCamelCase__			)
  __A  :		Any       =			len(UpperCamelCase__			)
  __A  :		Tuple       =			time.time() - start_time
  __A  :		Tuple       =			round(runtime / metrics['n_obs'],				4			)
  __A  :		int       =			num_replicas
  # TODO(@stas00): add whatever metadata to metrics
  __A  :		List[Any]       =			save_dir.joinpath(f"""{args.type_path}_{metric_name}.json"""			)
  save_json(UpperCamelCase__,				UpperCamelCase__,				indent=UpperCamelCase__			)
  print(UpperCamelCase__			)
  write_txt_file(UpperCamelCase__,				save_dir.joinpath(f"""{args.type_path}_generations.txt"""			)			)
  if args.debug:
   write_txt_file(UpperCamelCase__,				save_dir.joinpath(f"""{args.type_path}.target"""			)			)
  else:
   shutil.rmtree(UpperCamelCase__			)


def 			_lowercase       (				UpperCamelCase__       :					List[str]			):
 __A  :		List[str]       =			[]
 for partial_result in partial_results:
  records.extend(UpperCamelCase__			)
 __A  :		List[Any]       =			sorted(UpperCamelCase__,				key=lambda UpperCamelCase__			: x["id"]			)
 __A  :		Dict       =			[x['pred'] for x in records]
 return preds


def 			_lowercase       (				UpperCamelCase__       :					Dict,				UpperCamelCase__       :					List[Any],				UpperCamelCase__       :					int			):
 # WAIT FOR lots of .json files
 __A  :		Dict       =			time.time()
 logger.info('waiting for all nodes to finish'			)
 __A  :		int       =			None
 while (time.time() - start_wait) < timeout:
  __A  :		List[Any]       =			list(save_dir.glob('rank_*.json'			)			)
  if len(UpperCamelCase__			) < num_replicas:
   continue
  try:
   # make sure all json files are fully saved
   __A  :		List[Any]       =			lmap(UpperCamelCase__,				UpperCamelCase__			)
   return json_data
  except JSONDecodeError:
   continue
 else:
  raise TimeoutError('Rank 0 gave up on waiting for other processes'			)
 # Unreachable


if __name__ == "__main__":
 # Usage for MT:
 run_generate()






