


import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional

import yaml

from transformers import HfArgumentParser, TrainingArguments
from transformers.hf_argparser import make_choice_type_function, string_to_bool


# Since Python 3.10, we can use the builtin `|` operator for Union types
# See PEP 604: https://peps.python.org/pep-0604
lowerCamelCase		   =			sys.version_info >= (3, 10)




def       a_ (       SCREAMING_SNAKE_CASE__   : Union[str, Any]=None						,     SCREAMING_SNAKE_CASE__   : List[str]=None	):
       '''simple docstring'''





       return field(default_factory=lambda: default						,     metadata=SCREAMING_SNAKE_CASE__	)




@dataclass
class A    :
      UpperCamelCase__				:    int
      UpperCamelCase__				:    float
      UpperCamelCase__				:    str
      UpperCamelCase__				:    bool




@dataclass
class A    :
      UpperCamelCase__				:    int =42
      UpperCamelCase__				:    str =field(default='toto'       ,				metadata={'help': 'help message'}	)




@dataclass
class A    :
      UpperCamelCase__				:    bool =False
      UpperCamelCase__				:    bool =True
      UpperCamelCase__				:    Optional[bool] =None




class A    (  UpperCamelCase_	):
      UpperCamelCase__				:    Dict ='titi'
      UpperCamelCase__				:    Dict ='toto'




class A    (  UpperCamelCase_	):
      UpperCamelCase__				:    Optional[int] ='titi'
      UpperCamelCase__				:    int ='toto'
      UpperCamelCase__				:    List[str] =42




@dataclass
class A    :
      UpperCamelCase__				:    BasicEnum ="toto"






      def 			lowerCamelCase			(   self		:	int					)   ->		List[Any]:
             """simple docstring"""




             _lowerCamelCase			:						Any            =BasicEnum(self.foo					)




@dataclass
class A    :
      UpperCamelCase__				:    MixedTypeEnum ="toto"






      def 			lowerCamelCase			(   self		:	Dict					)   ->		str:
             """simple docstring"""




             _lowerCamelCase			:						List[str]            =MixedTypeEnum(self.foo					)




@dataclass
class A    :
      UpperCamelCase__				:    Optional[int] =None
      UpperCamelCase__				:    Optional[float] =field(default=UpperCamelCase_       ,				metadata={'help': 'help message'}	)
      UpperCamelCase__				:    Optional[str] =None
      UpperCamelCase__				:    Optional[List[str]] =list_field(default=[]	)
      UpperCamelCase__				:    Optional[List[int]] =list_field(default=[]	)




@dataclass
class A    :
      UpperCamelCase__				:    List[int] =list_field(default=[]	)
      UpperCamelCase__				:    List[int] =list_field(default=[1, 2, 3]	)
      UpperCamelCase__				:    List[str] =list_field(default=['Hallo', 'Bonjour', 'Hello']	)
      UpperCamelCase__				:    List[float] =list_field(default=[0.1, 0.2, 0.3]	)




@dataclass
class A    :
      UpperCamelCase__				:    List[int] =field()
      UpperCamelCase__				:    str =field()
      UpperCamelCase__				:    BasicEnum =field()






      def 			lowerCamelCase			(   self		:	Tuple					)   ->		Tuple:
             """simple docstring"""




             _lowerCamelCase			:						Any            =BasicEnum(self.required_enum					)




@dataclass
class A    :
      UpperCamelCase__				:    int
      UpperCamelCase__				:    "BasicEnum" =field()
      UpperCamelCase__				:    "Optional[bool]" =None
      UpperCamelCase__				:    "str" =field(default='toto'       ,				metadata={'help': 'help message'}	)
      UpperCamelCase__				:    "List[str]" =list_field(default=['Hallo', 'Bonjour', 'Hello']	)


if is_python_no_less_than_3_10:




 @dataclass
 class A    :
       UpperCamelCase__				:    bool =False
       UpperCamelCase__				:    bool =True
       UpperCamelCase__				:    bool | None =None




 @dataclass
 class A    :
       UpperCamelCase__				:    int | None =None
       UpperCamelCase__				:    float | None =field(default=UpperCamelCase_       ,				metadata={'help': 'help message'}	)
       UpperCamelCase__				:    str | None =None
       UpperCamelCase__				:    list[str] | None =list_field(default=[]	)
       UpperCamelCase__				:    list[int] | None =list_field(default=[]	)




class A    (  unittest.TestCase	):






      def 			lowerCamelCase			(   self		:	Union[str, Any]     ,  lowercase_		:	argparse.ArgumentParser     ,  lowercase_		:	argparse.ArgumentParser					)   ->		Union[str, Any]:
             """simple docstring"""




             self.assertEqual(len(a._actions					)     ,  len(b._actions					)					)
             for x, y in zip(a._actions     ,  b._actions					):
                    _lowerCamelCase			:						List[Any]            ={k: v for k, v in vars(lowercase_					).items() if k != 'container'}
                    _lowerCamelCase			:						Optional[int]            ={k: v for k, v in vars(lowercase_					).items() if k != 'container'}

                    # Choices with mixed type have custom function as "type"
                    # So we need to compare results directly for equality
                    if xx.get('choices'     ,  lowercase_					) and yy.get('choices'     ,  lowercase_					):
                           for expected_choice in yy["choices"] + xx["choices"]:
                                  self.assertEqual(xx['type'](lowercase_					)     ,  yy['type'](lowercase_					)					)
                           del xx["type"], yy["type"]

                    self.assertEqual(lowercase_     ,  lowercase_					)






      def 			lowerCamelCase			(   self		:	Union[str, Any]					)   ->		str:
             """simple docstring"""




             _lowerCamelCase			:						List[Any]            =HfArgumentParser(lowercase_					)

             _lowerCamelCase			:						Optional[Any]            =argparse.ArgumentParser()
             expected.add_argument('--foo'     ,  type=lowercase_     ,  required=lowercase_					)
             expected.add_argument('--bar'     ,  type=lowercase_     ,  required=lowercase_					)
             expected.add_argument('--baz'     ,  type=lowercase_     ,  required=lowercase_					)
             expected.add_argument('--flag'     ,  type=lowercase_     ,  default=lowercase_     ,  const=lowercase_     ,  nargs='?'					)
             self.argparsersEqual(lowercase_     ,  lowercase_					)

             _lowerCamelCase			:						Dict            =['--foo', '1', '--baz', 'quux', '--bar', '0.5']
             ((_lowerCamelCase)      ,	)			:						Optional[int]            =parser.parse_args_into_dataclasses(lowercase_     ,  look_for_args_file=lowercase_					)
             self.assertFalse(example.flag					)






      def 			lowerCamelCase			(   self		:	str					)   ->		Union[str, Any]:
             """simple docstring"""




             _lowerCamelCase			:						Union[str, Any]            =HfArgumentParser(lowercase_					)

             _lowerCamelCase			:						Union[str, Any]            =argparse.ArgumentParser()
             expected.add_argument('--foo'     ,  default=42     ,  type=lowercase_					)
             expected.add_argument('--baz'     ,  default='toto'     ,  type=lowercase_     ,  help='help message'					)
             self.argparsersEqual(lowercase_     ,  lowercase_					)






      def 			lowerCamelCase			(   self		:	Union[str, Any]					)   ->		int:
             """simple docstring"""




             _lowerCamelCase			:						Tuple            =argparse.ArgumentParser()
             expected.add_argument('--foo'     ,  type=lowercase_     ,  default=lowercase_     ,  const=lowercase_     ,  nargs='?'					)
             expected.add_argument('--baz'     ,  type=lowercase_     ,  default=lowercase_     ,  const=lowercase_     ,  nargs='?'					)
             # A boolean no_* argument always has to come after its "default: True" regular counter-part
             # and its default must be set to False
             expected.add_argument('--no_baz'     ,  action='store_false'     ,  default=lowercase_     ,  dest='baz'					)
             expected.add_argument('--opt'     ,  type=lowercase_     ,  default=lowercase_					)

             _lowerCamelCase			:						Union[str, Any]            =[WithDefaultBoolExample]
             if is_python_no_less_than_3_10:
                    dataclass_types.append(lowercase_					)

             for dataclass_type in dataclass_types:
                    _lowerCamelCase			:						str            =HfArgumentParser(lowercase_					)
                    self.argparsersEqual(lowercase_     ,  lowercase_					)

                    _lowerCamelCase			:						Dict            =parser.parse_args([]					)
                    self.assertEqual(lowercase_     ,  Namespace(foo=lowercase_     ,  baz=lowercase_     ,  opt=lowercase_					)					)

                    _lowerCamelCase			:						List[str]            =parser.parse_args(['--foo', '--no_baz']					)
                    self.assertEqual(lowercase_     ,  Namespace(foo=lowercase_     ,  baz=lowercase_     ,  opt=lowercase_					)					)

                    _lowerCamelCase			:						Union[str, Any]            =parser.parse_args(['--foo', '--baz']					)
                    self.assertEqual(lowercase_     ,  Namespace(foo=lowercase_     ,  baz=lowercase_     ,  opt=lowercase_					)					)

                    _lowerCamelCase			:						List[str]            =parser.parse_args(['--foo', 'True', '--baz', 'True', '--opt', 'True']					)
                    self.assertEqual(lowercase_     ,  Namespace(foo=lowercase_     ,  baz=lowercase_     ,  opt=lowercase_					)					)

                    _lowerCamelCase			:						Optional[Any]            =parser.parse_args(['--foo', 'False', '--baz', 'False', '--opt', 'False']					)
                    self.assertEqual(lowercase_     ,  Namespace(foo=lowercase_     ,  baz=lowercase_     ,  opt=lowercase_					)					)






      def 			lowerCamelCase			(   self		:	Optional[Any]					)   ->		Tuple:
             """simple docstring"""




             _lowerCamelCase			:						Union[str, Any]            =HfArgumentParser(lowercase_					)

             _lowerCamelCase			:						str            =argparse.ArgumentParser()
             expected.add_argument(
                 '--foo'     ,  default='toto'     ,  choices=['titi', 'toto', 42]     ,  type=make_choice_type_function(['titi', 'toto', 42]					)     ,  )
             self.argparsersEqual(lowercase_     ,  lowercase_					)

             _lowerCamelCase			:						List[Any]            =parser.parse_args([]					)
             self.assertEqual(args.foo     ,  'toto'					)
             _lowerCamelCase			:						Optional[Any]            =parser.parse_args_into_dataclasses([]					)[0]
             self.assertEqual(enum_ex.foo     ,  MixedTypeEnum.toto					)

             _lowerCamelCase			:						int            =parser.parse_args(['--foo', 'titi']					)
             self.assertEqual(args.foo     ,  'titi'					)
             _lowerCamelCase			:						Optional[Any]            =parser.parse_args_into_dataclasses(['--foo', 'titi']					)[0]
             self.assertEqual(enum_ex.foo     ,  MixedTypeEnum.titi					)

             _lowerCamelCase			:						Any            =parser.parse_args(['--foo', '42']					)
             self.assertEqual(args.foo     ,  42					)
             _lowerCamelCase			:						str            =parser.parse_args_into_dataclasses(['--foo', '42']					)[0]
             self.assertEqual(enum_ex.foo     ,  MixedTypeEnum.fourtytwo					)






      def 			lowerCamelCase			(   self		:	Any					)   ->		Optional[int]:
             """simple docstring"""




             @dataclass
             class A    :
                   UpperCamelCase__				:    Literal["titi", "toto", 42] ="toto"




             _lowerCamelCase			:						List[Any]            =HfArgumentParser(lowercase_					)

             _lowerCamelCase			:						Any            =argparse.ArgumentParser()
             expected.add_argument(
                 '--foo'     ,  default='toto'     ,  choices=('titi', 'toto', 42)     ,  type=make_choice_type_function(['titi', 'toto', 42]					)     ,  )
             self.argparsersEqual(lowercase_     ,  lowercase_					)

             _lowerCamelCase			:						int            =parser.parse_args([]					)
             self.assertEqual(args.foo     ,  'toto'					)

             _lowerCamelCase			:						Dict            =parser.parse_args(['--foo', 'titi']					)
             self.assertEqual(args.foo     ,  'titi'					)

             _lowerCamelCase			:						List[str]            =parser.parse_args(['--foo', '42']					)
             self.assertEqual(args.foo     ,  42					)






      def 			lowerCamelCase			(   self		:	Optional[Any]					)   ->		str:
             """simple docstring"""




             _lowerCamelCase			:						Tuple            =HfArgumentParser(lowercase_					)

             _lowerCamelCase			:						Optional[Any]            =argparse.ArgumentParser()
             expected.add_argument('--foo_int'     ,  nargs='+'     ,  default=[]     ,  type=lowercase_					)
             expected.add_argument('--bar_int'     ,  nargs='+'     ,  default=[1, 2, 3]     ,  type=lowercase_					)
             expected.add_argument('--foo_str'     ,  nargs='+'     ,  default=['Hallo', 'Bonjour', 'Hello']     ,  type=lowercase_					)
             expected.add_argument('--foo_float'     ,  nargs='+'     ,  default=[0.1, 0.2, 0.3]     ,  type=lowercase_					)

             self.argparsersEqual(lowercase_     ,  lowercase_					)

             _lowerCamelCase			:						Dict            =parser.parse_args([]					)
             self.assertEqual(
                 lowercase_     ,  Namespace(foo_int=[]     ,  bar_int=[1, 2, 3]     ,  foo_str=['Hallo', 'Bonjour', 'Hello']     ,  foo_float=[0.1, 0.2, 0.3]					)     ,  )

             _lowerCamelCase			:						List[str]            =parser.parse_args('--foo_int 1 --bar_int 2 3 --foo_str a b c --foo_float 0.1 0.7'.split()					)
             self.assertEqual(lowercase_     ,  Namespace(foo_int=[1]     ,  bar_int=[2, 3]     ,  foo_str=['a', 'b', 'c']     ,  foo_float=[0.1, 0.7]					)					)






      def 			lowerCamelCase			(   self		:	List[str]					)   ->		Dict:
             """simple docstring"""




             _lowerCamelCase			:						Dict            =argparse.ArgumentParser()
             expected.add_argument('--foo'     ,  default=lowercase_     ,  type=lowercase_					)
             expected.add_argument('--bar'     ,  default=lowercase_     ,  type=lowercase_     ,  help='help message'					)
             expected.add_argument('--baz'     ,  default=lowercase_     ,  type=lowercase_					)
             expected.add_argument('--ces'     ,  nargs='+'     ,  default=[]     ,  type=lowercase_					)
             expected.add_argument('--des'     ,  nargs='+'     ,  default=[]     ,  type=lowercase_					)

             _lowerCamelCase			:						Any            =[OptionalExample]
             if is_python_no_less_than_3_10:
                    dataclass_types.append(lowercase_					)

             for dataclass_type in dataclass_types:
                    _lowerCamelCase			:						Tuple            =HfArgumentParser(lowercase_					)

                    self.argparsersEqual(lowercase_     ,  lowercase_					)

                    _lowerCamelCase			:						List[str]            =parser.parse_args([]					)
                    self.assertEqual(lowercase_     ,  Namespace(foo=lowercase_     ,  bar=lowercase_     ,  baz=lowercase_     ,  ces=[]     ,  des=[]					)					)

                    _lowerCamelCase			:						List[Any]            =parser.parse_args('--foo 12 --bar 3.14 --baz 42 --ces a b c --des 1 2 3'.split()					)
                    self.assertEqual(lowercase_     ,  Namespace(foo=12     ,  bar=3.14     ,  baz='42'     ,  ces=['a', 'b', 'c']     ,  des=[1, 2, 3]					)					)






      def 			lowerCamelCase			(   self		:	Any					)   ->		str:
             """simple docstring"""




             _lowerCamelCase			:						Union[str, Any]            =HfArgumentParser(lowercase_					)

             _lowerCamelCase			:						str            =argparse.ArgumentParser()
             expected.add_argument('--required_list'     ,  nargs='+'     ,  type=lowercase_     ,  required=lowercase_					)
             expected.add_argument('--required_str'     ,  type=lowercase_     ,  required=lowercase_					)
             expected.add_argument(
                 '--required_enum'     ,  type=make_choice_type_function(['titi', 'toto']					)     ,  choices=['titi', 'toto']     ,  required=lowercase_     ,  )
             self.argparsersEqual(lowercase_     ,  lowercase_					)






      def 			lowerCamelCase			(   self		:	Union[str, Any]					)   ->		str:
             """simple docstring"""




             _lowerCamelCase			:						Any            =HfArgumentParser(lowercase_					)

             _lowerCamelCase			:						Optional[int]            =argparse.ArgumentParser()
             expected.add_argument('--foo'     ,  type=lowercase_     ,  required=lowercase_					)
             expected.add_argument(
                 '--required_enum'     ,  type=make_choice_type_function(['titi', 'toto']					)     ,  choices=['titi', 'toto']     ,  required=lowercase_     ,  )
             expected.add_argument('--opt'     ,  type=lowercase_     ,  default=lowercase_					)
             expected.add_argument('--baz'     ,  default='toto'     ,  type=lowercase_     ,  help='help message'					)
             expected.add_argument('--foo_str'     ,  nargs='+'     ,  default=['Hallo', 'Bonjour', 'Hello']     ,  type=lowercase_					)
             self.argparsersEqual(lowercase_     ,  lowercase_					)






      def 			lowerCamelCase			(   self		:	Dict					)   ->		Tuple:
             """simple docstring"""




             _lowerCamelCase			:						List[Any]            =HfArgumentParser(lowercase_					)

             _lowerCamelCase			:						Any            ={
                 'foo': 12,
                 'bar': 3.14,
                 'baz': '42',
                 'flag': True,
             }

             _lowerCamelCase			:						int            =parser.parse_dict(lowercase_					)[0]
             _lowerCamelCase			:						List[str]            =BasicExample(**lowercase_					)
             self.assertEqual(lowercase_     ,  lowercase_					)






      def 			lowerCamelCase			(   self		:	Tuple					)   ->		Union[str, Any]:
             """simple docstring"""




             _lowerCamelCase			:						Optional[int]            =HfArgumentParser(lowercase_					)

             _lowerCamelCase			:						Union[str, Any]            ={
                 'foo': 12,
                 'bar': 3.14,
                 'baz': '42',
                 'flag': True,
                 'extra': 42,
             }

             self.assertRaises(lowercase_     ,  parser.parse_dict     ,  lowercase_     ,  allow_extra_keys=lowercase_					)






      def 			lowerCamelCase			(   self		:	str					)   ->		int:
             """simple docstring"""




             _lowerCamelCase			:						int            =HfArgumentParser(lowercase_					)

             _lowerCamelCase			:						List[Any]            ={
                 'foo': 12,
                 'bar': 3.14,
                 'baz': '42',
                 'flag': True,
             }
             with tempfile.TemporaryDirectory() as tmp_dir:
                    _lowerCamelCase			:						int            =os.path.join(lowercase_     ,  'temp_json'					)
                    os.mkdir(lowercase_					)
                    with open(temp_local_path + '.json'     ,  'w+'					) as f:
                           json.dump(lowercase_     ,  lowercase_					)
                    _lowerCamelCase			:						Tuple            =parser.parse_yaml_file(Path(temp_local_path + '.json'					)					)[0]

             _lowerCamelCase			:						Optional[Any]            =BasicExample(**lowercase_					)
             self.assertEqual(lowercase_     ,  lowercase_					)






      def 			lowerCamelCase			(   self		:	Optional[Any]					)   ->		Any:
             """simple docstring"""




             _lowerCamelCase			:						Optional[Any]            =HfArgumentParser(lowercase_					)

             _lowerCamelCase			:						str            ={
                 'foo': 12,
                 'bar': 3.14,
                 'baz': '42',
                 'flag': True,
             }
             with tempfile.TemporaryDirectory() as tmp_dir:
                    _lowerCamelCase			:						Any            =os.path.join(lowercase_     ,  'temp_yaml'					)
                    os.mkdir(lowercase_					)
                    with open(temp_local_path + '.yaml'     ,  'w+'					) as f:
                           yaml.dump(lowercase_     ,  lowercase_					)
                    _lowerCamelCase			:						str            =parser.parse_yaml_file(Path(temp_local_path + '.yaml'					)					)[0]
             _lowerCamelCase			:						Tuple            =BasicExample(**lowercase_					)
             self.assertEqual(lowercase_     ,  lowercase_					)






      def 			lowerCamelCase			(   self		:	Dict					)   ->		List[str]:
             """simple docstring"""




             _lowerCamelCase			:						Dict            =HfArgumentParser(lowercase_					)
             self.assertIsNotNone(lowercase_					)






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    (  UpperCamelCase_	):






      @slow
      @require_torch
      def 			lowerCamelCase			(   self		:	Any					)   ->		Any:
             """simple docstring"""




             _lowerCamelCase			:						int            =EncoderDecoderModel.from_encoder_decoder_pretrained('prajjwal1/bert-tiny'     ,  'prajjwal1/bert-tiny'					)
             _lowerCamelCase			:						Dict            =BertTokenizer.from_pretrained('bert-base-uncased'					)

             _lowerCamelCase			:						Union[str, Any]            =bertabert.config.encoder.vocab_size
             _lowerCamelCase			:						Dict            =tokenizer.sep_token_id
             _lowerCamelCase			:						List[Any]            =tokenizer.cls_token_id
             _lowerCamelCase			:						Optional[int]            =128

             _lowerCamelCase			:						int            =datasets.load_dataset('cnn_dailymail'     ,  '3.0.0'     ,  split='train[:1%]'					)
             _lowerCamelCase			:						int            =datasets.load_dataset('cnn_dailymail'     ,  '3.0.0'     ,  split='validation[:1%]'					)

             _lowerCamelCase			:						Optional[int]            =train_dataset.select(range(32					)					)
             _lowerCamelCase			:						Optional[int]            =val_dataset.select(range(16					)					)

             _lowerCamelCase			:						Optional[int]            =4

             def _map_to_encoder_decoder_inputs(lowercase_		:	Tuple					):
                    # Tokenizer will automatically set [BOS] <text> [EOS]
                    _lowerCamelCase			:						Optional[int]            =tokenizer(batch['article']     ,  padding='max_length'     ,  truncation=lowercase_     ,  max_length=512					)
                    _lowerCamelCase			:						List[str]            =tokenizer(batch['highlights']     ,  padding='max_length'     ,  truncation=lowercase_     ,  max_length=128					)
                    _lowerCamelCase			:						List[str]            =inputs.input_ids
                    _lowerCamelCase			:						Any            =inputs.attention_mask

                    _lowerCamelCase			:						List[str]            =outputs.input_ids
                    _lowerCamelCase			:						int            =outputs.input_ids.copy()
                    _lowerCamelCase			:						List[str]            =[
                        [-100 if token == tokenizer.pad_token_id else token for token in labels] for labels in batch['labels']
                    ]
                    _lowerCamelCase			:						Dict            =outputs.attention_mask

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

                    return batch

             def _compute_metrics(lowercase_		:	str					):
                    _lowerCamelCase			:						List[Any]            =pred.label_ids
                    _lowerCamelCase			:						List[Any]            =pred.predictions

                    # all unnecessary tokens are removed
                    _lowerCamelCase			:						str            =tokenizer.batch_decode(lowercase_     ,  skip_special_tokens=lowercase_					)
                    _lowerCamelCase			:						Tuple            =tokenizer.batch_decode(lowercase_     ,  skip_special_tokens=lowercase_					)

                    _lowerCamelCase			:						List[str]            =sum([int(pred_str[i] == label_str[i]					) for i in range(len(lowercase_					)					)]					) / len(lowercase_					)

                    return {"accuracy": accuracy}

             # map train dataset
             _lowerCamelCase			:						Tuple            =train_dataset.map(
                 _map_to_encoder_decoder_inputs     ,  batched=lowercase_     ,  batch_size=lowercase_     ,  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			:						Tuple            =val_dataset.map(
                 _map_to_encoder_decoder_inputs     ,  batched=lowercase_     ,  batch_size=lowercase_     ,  remove_columns=['article', 'highlights']     ,  )
             val_dataset.set_format(
                 type='torch'     ,  columns=['input_ids', 'attention_mask', 'decoder_input_ids', 'decoder_attention_mask', 'labels']     ,  )

             _lowerCamelCase			:						Dict            =self.get_auto_remove_tmp_dir()

             _lowerCamelCase			:						Optional[int]            =SeqaSeqTrainingArguments(
                 output_dir=lowercase_     ,  per_device_train_batch_size=lowercase_     ,  per_device_eval_batch_size=lowercase_     ,  predict_with_generate=lowercase_     ,  evaluation_strategy='steps'     ,  do_train=lowercase_     ,  do_eval=lowercase_     ,  warmup_steps=0     ,  eval_steps=2     ,  logging_steps=2     ,  )

             # instantiate trainer
             _lowerCamelCase			:						Optional[Any]            =SeqaSeqTrainer(
                 model=lowercase_     ,  args=lowercase_     ,  compute_metrics=_compute_metrics     ,  train_dataset=lowercase_     ,  eval_dataset=lowercase_     ,  tokenizer=lowercase_     ,  )

             # start training
             trainer.train()


