





from transformers import BertTokenizer, EncoderDecoderModel, SeqaSeqTrainer, SeqaSeqTrainingArguments
from transformers.testing_utils import TestCasePlus, require_torch, slow
from transformers.utils import is_datasets_available


if is_datasets_available():
							import datasets

class  __A       (  a      ):






				"""simple docstring"""




				@slow
				@require_torch
				def _snake_case    (						self							):
								lowerCamelCase			=EncoderDecoderModel.from_encoder_decoder_pretrained("""prajjwal1/bert-tiny"""				,	"""prajjwal1/bert-tiny"""							)
								lowerCamelCase			=BertTokenizer.from_pretrained("""bert-base-uncased"""							)

								lowerCamelCase			=bertabert.config.encoder.vocab_size
								lowerCamelCase			=tokenizer.sep_token_id
								lowerCamelCase			=tokenizer.cls_token_id
								lowerCamelCase			=128

								lowerCamelCase			=datasets.load_dataset("""cnn_dailymail"""				,	"""3.0.0"""				,	split="""train[:1%]"""							)
								lowerCamelCase			=datasets.load_dataset("""cnn_dailymail"""				,	"""3.0.0"""				,	split="""validation[:1%]"""							)

								lowerCamelCase			=train_dataset.select(range(32							)							)
								lowerCamelCase			=val_dataset.select(range(16							)							)

								lowerCamelCase			=4

								def _map_to_encoder_decoder_inputs(UpperCAmelCase_							):
												# Tokenizer will automatically set [BOS] <text> [EOS]
												lowerCamelCase			=tokenizer(batch["""article"""]				,	padding="""max_length"""				,	truncation=UpperCAmelCase_				,	max_length=512							)
												lowerCamelCase			=tokenizer(batch["""highlights"""]				,	padding="""max_length"""				,	truncation=UpperCAmelCase_				,	max_length=128							)
												lowerCamelCase			=inputs.input_ids
												lowerCamelCase			=inputs.attention_mask

												lowerCamelCase			=outputs.input_ids
												lowerCamelCase			=outputs.input_ids.copy()
												lowerCamelCase			=[
												    [-100 if token == tokenizer.pad_token_id else token for token in labels] for labels in batch["""labels"""]
												]
												lowerCamelCase			=outputs.attention_mask

												assert all(len(UpperCAmelCase_							) == 512 for x in inputs.input_ids							)
												assert all(len(UpperCAmelCase_							) == 128 for x in outputs.input_ids							)

												return batch

								def _compute_metrics(UpperCAmelCase_							):
												lowerCamelCase			=pred.label_ids
												lowerCamelCase			=pred.predictions

												# all unnecessary tokens are removed
												lowerCamelCase			=tokenizer.batch_decode(UpperCAmelCase_				,	skip_special_tokens=UpperCAmelCase_							)
												lowerCamelCase			=tokenizer.batch_decode(UpperCAmelCase_				,	skip_special_tokens=UpperCAmelCase_							)

												lowerCamelCase			=sum([int(pred_str[i] == label_str[i]							) for i in range(len(UpperCAmelCase_							)							)]							) / len(UpperCAmelCase_							)

												return {"accuracy": accuracy}

								# map train dataset
								lowerCamelCase			=train_dataset.map(
								    _map_to_encoder_decoder_inputs				,	batched=UpperCAmelCase_				,	batch_size=UpperCAmelCase_				,	remove_columns=["""article""", """highlights"""]				,	)
								train_dataset.set_format(
								    type="""torch"""				,	columns=["""input_ids""", """attention_mask""", """decoder_input_ids""", """decoder_attention_mask""", """labels"""]				,	)

								# same for validation dataset
								lowerCamelCase			=val_dataset.map(
								    _map_to_encoder_decoder_inputs				,	batched=UpperCAmelCase_				,	batch_size=UpperCAmelCase_				,	remove_columns=["""article""", """highlights"""]				,	)
								val_dataset.set_format(
								    type="""torch"""				,	columns=["""input_ids""", """attention_mask""", """decoder_input_ids""", """decoder_attention_mask""", """labels"""]				,	)

								lowerCamelCase			=self.get_auto_remove_tmp_dir()

								lowerCamelCase			=SeqaSeqTrainingArguments(
								    output_dir=UpperCAmelCase_				,	per_device_train_batch_size=UpperCAmelCase_				,	per_device_eval_batch_size=UpperCAmelCase_				,	predict_with_generate=UpperCAmelCase_				,	evaluation_strategy="""steps"""				,	do_train=UpperCAmelCase_				,	do_eval=UpperCAmelCase_				,	warmup_steps=0				,	eval_steps=2				,	logging_steps=2				,	)

								# instantiate trainer
								lowerCamelCase			=SeqaSeqTrainer(
								    model=UpperCAmelCase_				,	args=UpperCAmelCase_				,	compute_metrics=_compute_metrics				,	train_dataset=UpperCAmelCase_				,	eval_dataset=UpperCAmelCase_				,	tokenizer=UpperCAmelCase_				,	)

								# start training
								trainer.train()












import dataclasses
import json
import sys
import types
from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, ArgumentTypeError
from copy import copy
from enum import Enum
from inspect import isclass
from pathlib import Path
from typing import Any, Callable, Dict, Iterable, List, Literal, NewType, Optional, Tuple, Union, get_type_hints

import yaml


UpperCAmelCase__  :     Dict   			=NewType('''DataClass''', Any)
UpperCAmelCase__  :     int   			=NewType('''DataClassType''', Any)





def        _lowercase   (  _UpperCAmelCase			)  ->					List[Any]:
				if isinstance(_UpperCAmelCase     , _UpperCAmelCase			):
								return v
				if v.lower() in ("yes", "true", "t", "y", "1"):
								return True
				elif v.lower() in ("no", "false", "f", "n", "0"):
								return False
				else:
								raise ArgumentTypeError(
								    F"""Truthy value expected: got {v} but expected one of yes/no, true/false, t/f, y/n, 1/0 (case insensitive)."""			)





def        _lowercase   (  _UpperCAmelCase			)  ->					Callable[[str], Any]:
				lowerCamelCase			={str(_UpperCAmelCase			): choice for choice in choices}
				return lambda _UpperCAmelCase			: str_to_choice.get(_UpperCAmelCase     , _UpperCAmelCase			)





def        _lowercase   (  *,
    _UpperCAmelCase = None     , _UpperCAmelCase = None     , _UpperCAmelCase = dataclasses.MISSING     , _UpperCAmelCase = dataclasses.MISSING     , _UpperCAmelCase = None     , **_UpperCAmelCase     , )  ->					dataclasses.Field:
				if metadata is None:
								# Important, don't use as default param in function signature because dict is mutable and shared across function calls
								lowerCamelCase			={}
				if aliases is not None:
								lowerCamelCase			=aliases
				if help is not None:
								lowerCamelCase			=help

				return dataclasses.field(metadata=_UpperCAmelCase     , default=_UpperCAmelCase     , default_factory=_UpperCAmelCase     , **_UpperCAmelCase			)




class  __A       (  a      ):
				__A								=			42


				def __init__(						self				,	UpperCAmelCase_				,	**UpperCAmelCase_							):
								# To make the default appear when using --help
								if "formatter_class" not in kwargs:
												lowerCamelCase			=ArgumentDefaultsHelpFormatter
								super().__init__(**UpperCAmelCase_							)
								if dataclasses.is_dataclass(UpperCAmelCase_							):
												lowerCamelCase			=[dataclass_types]
								lowerCamelCase			=list(UpperCAmelCase_							)
								for dtype in self.dataclass_types:
												self._add_dataclass_arguments(UpperCAmelCase_							)


				@staticmethod
				def _snake_case    (						UpperCAmelCase_				,	UpperCAmelCase_							):
								lowerCamelCase			=f"""--{field.name}"""
								lowerCamelCase			=field.metadata.copy()
								# field.metadata is not used at all by Data Classes,
								# it is provided as a third-party extension mechanism.
								if isinstance(field.type				,	UpperCAmelCase_							):
												raise RuntimeError(
												    """Unresolved type detected, which should have been done with the help of """
												    """`typing.get_type_hints` method by default"""							)

								lowerCamelCase			=kwargs.pop("""aliases"""				,	[]							)
								if isinstance(UpperCAmelCase_				,	UpperCAmelCase_							):
												lowerCamelCase			=[aliases]

								lowerCamelCase			=getattr(field.type				,	"""__origin__"""				,	field.type							)
								if origin_type is Union or (hasattr(UpperCAmelCase_				,	"""UnionType"""							) and isinstance(UpperCAmelCase_				,	types.UnionType							)):
												if str not in field.type.__args__ and (
												    len(field.type.__args__							) != 2 or type(UpperCAmelCase_							) not in field.type.__args__
												):
																raise ValueError(
																    """Only `Union[X, NoneType]` (i.e., `Optional[X]`) is allowed for `Union` because"""
																    """ the argument parser only supports one type per argument."""
																    f""" Problem encountered in field '{field.name}'."""							)
												if type(UpperCAmelCase_							) not in field.type.__args__:
																# filter `str` in Union
																lowerCamelCase			=field.type.__args__[0] if field.type.__args__[1] == str else field.type.__args__[1]
																lowerCamelCase			=getattr(field.type				,	"""__origin__"""				,	field.type							)
												elif bool not in field.type.__args__:
																# filter `NoneType` in Union (except for `Union[bool, NoneType]`)
																lowerCamelCase			=(
																    field.type.__args__[0] if isinstance(UpperCAmelCase_				,	field.type.__args__[1]							) else field.type.__args__[1]
																)
																lowerCamelCase			=getattr(field.type				,	"""__origin__"""				,	field.type							)

        # A variable to store kwargs for a boolean field, if needed
        # so that we can init a `no_*` complement argument (see below)
								lowerCamelCase			={}
								if origin_type is Literal or (isinstance(field.type				,	UpperCAmelCase_							) and issubclass(field.type				,	UpperCAmelCase_							)):
												if origin_type is Literal:
																lowerCamelCase			=field.type.__args__
												else:
																lowerCamelCase			=[x.value for x in field.type]

												lowerCamelCase			=make_choice_type_function(kwargs["""choices"""]							)

												if field.default is not dataclasses.MISSING:
																lowerCamelCase			=field.default
												else:
																lowerCamelCase			=True
								elif field.type is bool or field.type == Optional[bool]:
												# Copy the currect kwargs to use to instantiate a `no_*` complement argument below.
												# We do not initialize it here because the `no_*` alternative must be instantiated after the real argument
												lowerCamelCase			=copy(UpperCAmelCase_							)

												# Hack because type=bool in argparse does not behave as we want.
												lowerCamelCase			=string_to_bool
												if field.type is bool or (field.default is not None and field.default is not dataclasses.MISSING):
																# Default value is False if we have no default when of type bool.
																lowerCamelCase			=False if field.default is dataclasses.MISSING else field.default
																# This is the value that will get picked if we don't include --field_name in any way
																lowerCamelCase			=default
																# This tells argparse we accept 0 or 1 value after --field_name
																lowerCamelCase			="""?"""
																# This is the value that will get picked if we do --field_name (without value)
																lowerCamelCase			=True
								elif isclass(UpperCAmelCase_							) and issubclass(UpperCAmelCase_				,	UpperCAmelCase_							):
												lowerCamelCase			=field.type.__args__[0]
												lowerCamelCase			="""+"""
												if field.default_factory is not dataclasses.MISSING:
																lowerCamelCase			=field.default_factory()
												elif field.default is dataclasses.MISSING:
																lowerCamelCase			=True
								else:
												lowerCamelCase			=field.type
												if field.default is not dataclasses.MISSING:
																lowerCamelCase			=field.default
												elif field.default_factory is not dataclasses.MISSING:
																lowerCamelCase			=field.default_factory()
												else:
																lowerCamelCase			=True
								parser.add_argument(UpperCAmelCase_				,	*UpperCAmelCase_				,	**UpperCAmelCase_							)

								# Add a complement `no_*` argument for a boolean field AFTER the initial field has already been added.
								# Order is important for arguments with the same destination!
								# We use a copy of earlier kwargs because the original kwargs have changed a lot before reaching down
								# here and we do not need those changes/additional keys.
								if field.default is True and (field.type is bool or field.type == Optional[bool]):
												lowerCamelCase			=False
												parser.add_argument(f"""--no_{field.name}"""				,	action="""store_false"""				,	dest=field.name				,	**UpperCAmelCase_							)


				def _snake_case    (						self				,	UpperCAmelCase_							):
								if hasattr(UpperCAmelCase_				,	"""_argument_group_name"""							):
												lowerCamelCase			=self.add_argument_group(dtype._argument_group_name							)
								else:
												lowerCamelCase			=self

								try:
												lowerCamelCase			=get_type_hints(UpperCAmelCase_							)
								except NameError:
												raise RuntimeError(
												    f"""Type resolution failed for {dtype}. Try declaring the class in global scope or """
												    """removing line of `from __future__ import annotations` which opts in Postponed """
												    """Evaluation of Annotations (PEP 563)"""							)
								except TypeError as ex:
												# Remove this block when we drop Python 3.9 support
												if sys.version_info[:2] < (3, 10) and "unsupported operand type(s) for |" in str(UpperCAmelCase_							):
																lowerCamelCase			=""".""".join(map(UpperCAmelCase_				,	sys.version_info[:3]							)							)
																raise RuntimeError(
																    f"""Type resolution failed for {dtype} on Python {python_version}. Try removing """
																    """line of `from __future__ import annotations` which opts in union types as """
																    """`X | Y` (PEP 604) via Postponed Evaluation of Annotations (PEP 563). To """
																    """support Python versions that lower than 3.10, you need to use """
																    """`typing.Union[X, Y]` instead of `X | Y` and `typing.Optional[X]` instead of """
																    """`X | None`."""							) from ex
												raise

								for field in dataclasses.fields(UpperCAmelCase_							):
												if not field.init:
																continue
												lowerCamelCase			=type_hints[field.name]
												self._parse_dataclass_field(UpperCAmelCase_				,	UpperCAmelCase_							)


				def _snake_case    (						self				,	UpperCAmelCase_=None				,	UpperCAmelCase_=False				,	UpperCAmelCase_=True				,	UpperCAmelCase_=None				,	UpperCAmelCase_=None				,	):

								if args_file_flag or args_filename or (look_for_args_file and len(sys.argv							)):
												lowerCamelCase			=[]

												if args_filename:
																args_files.append(Path(UpperCAmelCase_							)							)
												elif look_for_args_file and len(sys.argv							):
																args_files.append(Path(sys.argv[0]							).with_suffix(""".args"""							)							)

												# args files specified via command line flag should overwrite default args files so we add them last
												if args_file_flag:
																# Create special parser just to extract the args_file_flag values
																lowerCamelCase			=ArgumentParser()
																args_file_parser.add_argument(UpperCAmelCase_				,	type=UpperCAmelCase_				,	action="""append"""							)

																# Use only remaining args for further parsing (remove the args_file_flag)
																lowerCamelCase	,					lowerCamelCase			=args_file_parser.parse_known_args(args=UpperCAmelCase_							)
																lowerCamelCase			=vars(UpperCAmelCase_							).get(args_file_flag.lstrip("""-"""							)				,	UpperCAmelCase_							)

																if cmd_args_file_paths:
																				args_files.extend([Path(UpperCAmelCase_							) for p in cmd_args_file_paths]							)

												lowerCamelCase			=[]
												for args_file in args_files:
																if args_file.exists():
																				file_args += args_file.read_text().split()

            # in case of duplicate arguments the last one has precedence
            # args specified via the command line should overwrite args from files, so we add them last
												lowerCamelCase			=file_args + args if args is not None else file_args + sys.argv[1:]
								lowerCamelCase	,					lowerCamelCase			=self.parse_known_args(args=UpperCAmelCase_							)
								lowerCamelCase			=[]
								for dtype in self.dataclass_types:
												lowerCamelCase			={f.name for f in dataclasses.fields(UpperCAmelCase_							) if f.init}
												lowerCamelCase			={k: v for k, v in vars(UpperCAmelCase_							).items() if k in keys}
												for k in keys:
																delattr(UpperCAmelCase_				,	UpperCAmelCase_							)
												lowerCamelCase			=dtype(**UpperCAmelCase_							)
												outputs.append(UpperCAmelCase_							)
								if len(namespace.__dict__							) > 0:
												# additional namespace.
												outputs.append(UpperCAmelCase_							)
								if return_remaining_strings:
												return (*outputs, remaining_args)
								else:
												if remaining_args:
																raise ValueError(f"""Some specified arguments are not used by the HfArgumentParser: {remaining_args}"""							)

												return (*outputs,)


				def _snake_case    (						self				,	UpperCAmelCase_				,	UpperCAmelCase_ = False							):
								lowerCamelCase			=set(args.keys()							)
								lowerCamelCase			=[]
								for dtype in self.dataclass_types:
												lowerCamelCase			={f.name for f in dataclasses.fields(UpperCAmelCase_							) if f.init}
												lowerCamelCase			={k: v for k, v in args.items() if k in keys}
												unused_keys.difference_update(inputs.keys()							)
												lowerCamelCase			=dtype(**UpperCAmelCase_							)
												outputs.append(UpperCAmelCase_							)
								if not allow_extra_keys and unused_keys:
												raise ValueError(f"""Some keys are not used by the HfArgumentParser: {sorted(UpperCAmelCase_							)}"""							)
								return tuple(UpperCAmelCase_							)


				def _snake_case    (						self				,	UpperCAmelCase_				,	UpperCAmelCase_ = False							):
								with open(Path(UpperCAmelCase_							)				,	encoding="""utf-8"""							) as open_json_file:
												lowerCamelCase			=json.loads(open_json_file.read()							)
								lowerCamelCase			=self.parse_dict(UpperCAmelCase_				,	allow_extra_keys=UpperCAmelCase_							)
								return tuple(UpperCAmelCase_							)


				def _snake_case    (						self				,	UpperCAmelCase_				,	UpperCAmelCase_ = False							):
								lowerCamelCase			=self.parse_dict(yaml.safe_load(Path(UpperCAmelCase_							).read_text()							)				,	allow_extra_keys=UpperCAmelCase_							)
								return tuple(UpperCAmelCase_							)





