






import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartaaTokenizer, MBartaaTokenizerFast, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
    slow,
)

from ...test_tokenization_common import TokenizerTesterMixin


lowerCamelCase__       		=  get_tests_dir("""fixtures/test_sentencepiece.model""")

if is_torch_available():
     from transformers.models.mbart.modeling_mbart import shift_tokens_right

lowerCamelCase__       		=  25_0004
lowerCamelCase__       		=  25_0020




@require_sentencepiece
@require_tokenizers
class       snake_case__ (				a__						,     unittest.TestCase):

       '''simple docstring'''
       lowerCamelCase				:					List[str]								=			MBartaaTokenizer
       lowerCamelCase				:					Union[str, Any]								=			MBartaaTokenizerFast
       lowerCamelCase				:					Tuple								=			True
       lowerCamelCase				:					Optional[Any]								=			True



       def        __lowercase    (				self     )			->   Any:






            '''simple docstring'''





            super().setUp()

            # We have a SentencePiece fixture for testing
            __snake_case      :Tuple 							=    MBartaaTokenizer(lowerCamelCase_      ,    src_lang="""en_XX"""      ,    tgt_lang="""ro_RO"""      ,    keep_accents=lowerCamelCase_     )
            tokenizer.save_pretrained(self.tmpdirname     )



       def        __lowercase    (				self     )			->   Optional[Any]:






            '''simple docstring'''





            __snake_case      :int 							=    """<s>"""
            __snake_case      :List[Any] 							=    0

            self.assertEqual(self.get_tokenizer()._convert_token_to_id(lowerCamelCase_     )      ,    lowerCamelCase_     )
            self.assertEqual(self.get_tokenizer()._convert_id_to_token(lowerCamelCase_     )      ,    lowerCamelCase_     )



       def        __lowercase    (				self     )			->   Union[str, Any]:






            '''simple docstring'''





            __snake_case      :Dict 							=    list(self.get_tokenizer().get_vocab().keys()     )

            self.assertEqual(vocab_keys[0]      ,    """<s>"""     )
            self.assertEqual(vocab_keys[1]      ,    """<pad>"""     )
            self.assertEqual(vocab_keys[-1]      ,    """<mask>"""     )
            self.assertEqual(len(lowerCamelCase_     )      ,    10_54     )



       def        __lowercase    (				self     )			->   Any:






            '''simple docstring'''





            self.assertEqual(self.get_tokenizer().vocab_size      ,    10_54     )



       def        __lowercase    (				self     )			->   Optional[int]:






            '''simple docstring'''





            __snake_case      :str 							=    MBartaaTokenizer(lowerCamelCase_      ,    src_lang="""en_XX"""      ,    tgt_lang="""ro_RO"""      ,    keep_accents=lowerCamelCase_     )

            __snake_case      :Union[str, Any] 							=    tokenizer.tokenize("""This is a test"""     )
            self.assertListEqual(lowerCamelCase_      ,    ["""▁This""", """▁is""", """▁a""", """▁t""", """est"""]     )

            self.assertListEqual(
                tokenizer.convert_tokens_to_ids(lowerCamelCase_     )      ,    [value + tokenizer.fairseq_offset for value in [2_85, 46, 10, 1_70, 3_82]]      ,    )

            __snake_case      :List[Any] 							=    tokenizer.tokenize("""I was born in 92000, and this is falsé."""     )
            self.assertListEqual(
                lowerCamelCase_      ,    [SPIECE_UNDERLINE + """I""", SPIECE_UNDERLINE + """was""", SPIECE_UNDERLINE + """b""", """or""", """n""", SPIECE_UNDERLINE + """in""", SPIECE_UNDERLINE + """""", """9""", """2""", """0""", """0""", """0""", """,""", SPIECE_UNDERLINE + """and""", SPIECE_UNDERLINE + """this""", SPIECE_UNDERLINE + """is""", SPIECE_UNDERLINE + """f""", """al""", """s""", """é""", """."""]      ,    )
            __snake_case      :List[Any] 							=    tokenizer.convert_tokens_to_ids(lowerCamelCase_     )
            self.assertListEqual(
                lowerCamelCase_      ,    [
                    value + tokenizer.fairseq_offset
                    for value in [8, 21, 84, 55, 24, 19, 7, 2, 6_02, 3_47, 3_47, 3_47, 3, 12, 66, 46, 72, 80, 6, 2, 4]
                ]      ,    )

            __snake_case      :List[Any] 							=    tokenizer.convert_ids_to_tokens(lowerCamelCase_     )
            self.assertListEqual(
                lowerCamelCase_      ,    [SPIECE_UNDERLINE + """I""", SPIECE_UNDERLINE + """was""", SPIECE_UNDERLINE + """b""", """or""", """n""", SPIECE_UNDERLINE + """in""", SPIECE_UNDERLINE + """""", """<unk>""", """2""", """0""", """0""", """0""", """,""", SPIECE_UNDERLINE + """and""", SPIECE_UNDERLINE + """this""", SPIECE_UNDERLINE + """is""", SPIECE_UNDERLINE + """f""", """al""", """s""", """<unk>""", """."""]      ,    )



       @slow
       def        __lowercase    (				self     )			->   int:






            '''simple docstring'''





            __snake_case      :Any 							=    {"""input_ids""": [[25_00_04, 1_10_62, 8_27_72, 7, 15, 8_27_72, 5_38, 5_15_29, 2_37, 1_71_98, 12_90, 2_06, 9, 21_51_75, 13_14, 1_36, 1_71_98, 12_90, 2_06, 9, 5_63_59, 42, 12_20_09, 9, 1_64_66, 16, 8_73_44, 45_37, 9, 47_17, 7_83_81, 6, 15_99_58, 7, 15, 2_44_80, 6_18, 4, 5_27, 2_26_93, 54_28, 4, 27_77, 2_44_80, 98_74, 4, 4_35_23, 5_94, 4, 8_03, 1_83_92, 3_31_89, 18, 4, 4_35_23, 2_44_47, 1_23_99, 1_00, 2_49_55, 8_36_58, 96_26, 14_40_57, 15, 8_39, 2_23_35, 16, 1_36, 2_49_55, 8_36_58, 8_34_79, 15, 3_91_02, 7_24, 16, 6_78, 6_45, 27_89, 13_28, 45_89, 42, 12_20_09, 11_57_74, 23, 8_05, 13_28, 4_68_76, 7, 1_36, 5_38_94, 19_40, 4_22_27, 4_11_59, 1_77_21, 8_23, 4_25, 4, 2_75_12, 9_87_22, 2_06, 1_36, 55_31, 49_70, 9_19, 1_73_36, 5, 2], [25_00_04, 2_00_80, 6_18, 83, 8_27_75, 47, 4_79, 9, 15_17, 73, 5_38_94, 3_33, 8_05_81, 11_01_17, 1_88_11, 52_56, 12_95, 51, 15_25_26, 2_97, 79_86, 3_90, 12_44_16, 5_38, 3_54_31, 2_14, 98, 1_50_44, 2_57_37, 1_36, 71_08, 4_37_01, 23, 7_56, 13_53_55, 7, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [25_00_04, 5_81, 6_37_73, 11_94_55, 6, 14_77_97, 8_82_03, 7, 6_45, 70, 21, 32_85, 1_02_69, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]], """attention_mask""": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
            # fmt: on

            self.tokenizer_integration_test_util(
                expected_encoding=lowerCamelCase_      ,    model_name="""facebook/mbart-large-50"""      ,    revision="""d3913889c59cd5c9e456b269c376325eabad57e2"""      ,    )



       def        __lowercase    (				self     )			->   str:






            '''simple docstring'''





            if not self.test_slow_tokenizer:
                 # as we don't have a slow version, we can't compare the outputs between slow and fast versions
                 return

            __snake_case      :Optional[int] 							=    (self.rust_tokenizer_class, """hf-internal-testing/tiny-random-mbart50""", {})
            for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
                 with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''     ):
                      __snake_case      :List[Any] 							=    self.rust_tokenizer_class.from_pretrained(lowerCamelCase_      ,    **lowerCamelCase_     )
                      __snake_case      :Optional[int] 							=    self.tokenizer_class.from_pretrained(lowerCamelCase_      ,    **lowerCamelCase_     )

                      __snake_case      :Optional[int] 							=    tempfile.mkdtemp()

                      __snake_case      :List[str] 							=    tokenizer_r.save_pretrained(lowerCamelCase_     )
                      __snake_case      :List[str] 							=    tokenizer_p.save_pretrained(lowerCamelCase_     )

                      # Checks it save with the same files + the tokenizer.json file for the fast one
                      self.assertTrue(any("""tokenizer.json""" in f for f in tokenizer_r_files     )     )
                      __snake_case      :List[str] 							=    tuple(f for f in tokenizer_r_files if """tokenizer.json""" not in f     )
                      self.assertSequenceEqual(lowerCamelCase_      ,    lowerCamelCase_     )

                      # Checks everything loads correctly in the same way
                      __snake_case      :List[Any] 							=    tokenizer_r.from_pretrained(lowerCamelCase_     )
                      __snake_case      :Dict 							=    tokenizer_p.from_pretrained(lowerCamelCase_     )

                      # Check special tokens are set accordingly on Rust and Python
                      for key in tokenizer_pp.special_tokens_map:
                           self.assertTrue(hasattr(lowerCamelCase_      ,    lowerCamelCase_     )     )
                           # self.assertEqual(getattr(tokenizer_rp, key), getattr(tokenizer_pp, key))
                           # self.assertEqual(getattr(tokenizer_rp, key + "_id"), getattr(tokenizer_pp, key + "_id"))

                      shutil.rmtree(lowerCamelCase_     )

                      # Save tokenizer rust, legacy_format=True
                      __snake_case      :Optional[int] 							=    tempfile.mkdtemp()

                      __snake_case      :Any 							=    tokenizer_r.save_pretrained(lowerCamelCase_      ,    legacy_format=lowerCamelCase_     )
                      __snake_case      :Any 							=    tokenizer_p.save_pretrained(lowerCamelCase_     )

                      # Checks it save with the same files
                      self.assertSequenceEqual(lowerCamelCase_      ,    lowerCamelCase_     )

                      # Checks everything loads correctly in the same way
                      __snake_case      :List[Any] 							=    tokenizer_r.from_pretrained(lowerCamelCase_     )
                      __snake_case      :Tuple 							=    tokenizer_p.from_pretrained(lowerCamelCase_     )

                      # Check special tokens are set accordingly on Rust and Python
                      for key in tokenizer_pp.special_tokens_map:
                           self.assertTrue(hasattr(lowerCamelCase_      ,    lowerCamelCase_     )     )

                      shutil.rmtree(lowerCamelCase_     )

                      # Save tokenizer rust, legacy_format=False
                      __snake_case      :str 							=    tempfile.mkdtemp()

                      __snake_case      :Tuple 							=    tokenizer_r.save_pretrained(lowerCamelCase_      ,    legacy_format=lowerCamelCase_     )
                      __snake_case      :int 							=    tokenizer_p.save_pretrained(lowerCamelCase_     )

                      # Checks it saved the tokenizer.json file
                      self.assertTrue(any("""tokenizer.json""" in f for f in tokenizer_r_files     )     )

                      # Checks everything loads correctly in the same way
                      __snake_case      :List[Any] 							=    tokenizer_r.from_pretrained(lowerCamelCase_     )
                      __snake_case      :str 							=    tokenizer_p.from_pretrained(lowerCamelCase_     )

                      # Check special tokens are set accordingly on Rust and Python
                      for key in tokenizer_pp.special_tokens_map:
                           self.assertTrue(hasattr(lowerCamelCase_      ,    lowerCamelCase_     )     )

                      shutil.rmtree(lowerCamelCase_     )




@require_torch
@require_sentencepiece
@require_tokenizers
class       snake_case__ (				unittest.TestCase):

       '''simple docstring'''
       lowerCamelCase				:					Union[str, Any]								=			"facebook/mbart-large-50-one-to-many-mmt"
       lowerCamelCase				:					List[Any]								=			[
           " UN Chief Says There Is No Military Solution in Syria",
           " Secretary-General Ban Ki-moon says his response to Russia's stepped up military support for Syria is that \"there is no military solution\" to the nearly five-year conflict and more weapons will only worsen the violence and misery for millions of people.",
       ]
       lowerCamelCase				:					int								=			[
           "Şeful ONU declară că nu există o soluţie militară în Siria",
           "Secretarul General Ban Ki-moon declară că răspunsul său la intensificarea sprijinului militar al Rusiei"
           " pentru Siria este că \"nu există o soluţie militară\" la conflictul de aproape cinci ani şi că noi arme nu vor"
           " face decât să înrăutăţească violenţele şi mizeria pentru milioane de oameni.",
       ]
       lowerCamelCase				:					Tuple								=			[EN_CODE, 8274, 12_7873, 2_5916, 7, 8622, 2071, 438, 6_7485, 53, 18_7895, 23, 5_1712, 2]



       @classmethod
       def        __lowercase    (				cls     )			->   int:






            '''simple docstring'''





            __snake_case      :Any 							=    MBartaaTokenizer.from_pretrained(
                cls.checkpoint_name      ,    src_lang="""en_XX"""      ,    tgt_lang="""ro_RO"""     )
            __snake_case      :Any 							=    1
            return cls



       def        __lowercase    (				self     )			->   Optional[Any]:






            '''simple docstring'''





            self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""ar_AR"""]      ,    25_00_01     )
            self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""en_EN"""]      ,    25_00_04     )
            self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""ro_RO"""]      ,    25_00_20     )
            self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""mr_IN"""]      ,    25_00_38     )



       def        __lowercase    (				self     )			->   int:






            '''simple docstring'''





            __snake_case      :List[Any] 							=    self.tokenizer.batch_encode_plus(self.src_text     ).input_ids[0]
            self.assertListEqual(self.expected_src_tokens      ,    lowerCamelCase_     )



       def        __lowercase    (				self     )			->   List[str]:






            '''simple docstring'''





            self.assertIn(lowerCamelCase_      ,    self.tokenizer.all_special_ids     )
            __snake_case      :Tuple 							=    [RO_CODE, 8_84, 90_19, 96, 9, 9_16, 8_67_92, 36, 1_87_43, 1_55_96, 5, 2]
            __snake_case      :Dict 							=    self.tokenizer.decode(lowerCamelCase_      ,    skip_special_tokens=lowerCamelCase_     )
            __snake_case      :str 							=    self.tokenizer.decode(generated_ids[1:]      ,    skip_special_tokens=lowerCamelCase_     )
            self.assertEqual(lowerCamelCase_      ,    lowerCamelCase_     )
            self.assertNotIn(self.tokenizer.eos_token      ,    lowerCamelCase_     )



       def        __lowercase    (				self     )			->   Optional[int]:






            '''simple docstring'''





            __snake_case      :List[str] 							=    ["""this is gunna be a long sentence """ * 20]
            assert isinstance(src_text[0]      ,    lowerCamelCase_     )
            __snake_case      :Optional[int] 							=    10
            __snake_case      :List[Any] 							=    self.tokenizer(lowerCamelCase_      ,    max_length=lowerCamelCase_      ,    truncation=lowerCamelCase_     ).input_ids[0]
            self.assertEqual(ids[0]      ,    lowerCamelCase_     )
            self.assertEqual(ids[-1]      ,    2     )
            self.assertEqual(len(lowerCamelCase_     )      ,    lowerCamelCase_     )



       def        __lowercase    (				self     )			->   Any:






            '''simple docstring'''





            self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["""<mask>""", """ar_AR"""]     )      ,    [25_00_53, 25_00_01]     )



       def        __lowercase    (				self     )			->   Optional[Any]:






            '''simple docstring'''





            __snake_case      :Union[str, Any] 							=    tempfile.mkdtemp()
            __snake_case      :Tuple 							=    self.tokenizer.fairseq_tokens_to_ids
            self.tokenizer.save_pretrained(lowerCamelCase_     )
            __snake_case      :str 							=    MBartaaTokenizer.from_pretrained(lowerCamelCase_     )
            self.assertDictEqual(new_tok.fairseq_tokens_to_ids      ,    lowerCamelCase_     )



       @require_torch
       def        __lowercase    (				self     )			->   Union[str, Any]:






            '''simple docstring'''





            __snake_case      :Optional[Any] 							=    self.tokenizer(self.src_text      ,    text_target=self.tgt_text      ,    padding=lowerCamelCase_      ,    return_tensors="""pt"""     )
            __snake_case      :Optional[int] 							=    shift_tokens_right(batch["""labels"""]      ,    self.tokenizer.pad_token_id     )

            # fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
            assert batch.input_ids[1][0] == EN_CODE
            assert batch.input_ids[1][-1] == 2
            assert batch.labels[1][0] == RO_CODE
            assert batch.labels[1][-1] == 2
            assert batch.decoder_input_ids[1][:2].tolist() == [2, RO_CODE]



       @require_torch
       def        __lowercase    (				self     )			->   List[str]:






            '''simple docstring'''





            __snake_case      :int 							=    self.tokenizer(
                self.src_text      ,    text_target=self.tgt_text      ,    padding=lowerCamelCase_      ,    truncation=lowerCamelCase_      ,    max_length=len(self.expected_src_tokens     )      ,    return_tensors="""pt"""      ,    )
            __snake_case      :Dict 							=    shift_tokens_right(batch["""labels"""]      ,    self.tokenizer.pad_token_id     )

            self.assertIsInstance(lowerCamelCase_      ,    lowerCamelCase_     )

            self.assertEqual((2, 14)      ,    batch.input_ids.shape     )
            self.assertEqual((2, 14)      ,    batch.attention_mask.shape     )
            __snake_case      :Union[str, Any] 							=    batch.input_ids.tolist()[0]
            self.assertListEqual(self.expected_src_tokens      ,    lowerCamelCase_     )
            self.assertEqual(2      ,    batch.decoder_input_ids[0, 0]     )  # decoder_start_token_id
            # Test that special tokens are reset
            self.assertEqual(self.tokenizer.prefix_tokens      ,    [EN_CODE]     )
            self.assertEqual(self.tokenizer.suffix_tokens      ,    [self.tokenizer.eos_token_id]     )



       def        __lowercase    (				self     )			->   List[str]:






            '''simple docstring'''





            __snake_case      :Optional[Any] 							=    self.tokenizer(self.src_text      ,    padding=lowerCamelCase_      ,    truncation=lowerCamelCase_      ,    max_length=3      ,    return_tensors="""pt"""     )
            __snake_case      :List[str] 							=    self.tokenizer(
                text_target=self.tgt_text      ,    padding=lowerCamelCase_      ,    truncation=lowerCamelCase_      ,    max_length=10      ,    return_tensors="""pt"""     )
            __snake_case      :Optional[int] 							=    targets["""input_ids"""]
            __snake_case      :Tuple 							=    shift_tokens_right(lowerCamelCase_      ,    self.tokenizer.pad_token_id     )

            self.assertEqual(batch.input_ids.shape[1]      ,    3     )
            self.assertEqual(batch.decoder_input_ids.shape[1]      ,    10     )



       @require_torch
       def        __lowercase    (				self     )			->   Union[str, Any]:






            '''simple docstring'''





            __snake_case      :List[str] 							=    self.tokenizer._build_translation_inputs(
                """A test"""      ,    return_tensors="""pt"""      ,    src_lang="""en_XX"""      ,    tgt_lang="""ar_AR"""     )

            self.assertEqual(
                nested_simplify(lowerCamelCase_     )      ,    {
                    # en_XX, A, test, EOS
                    """input_ids""": [[25_00_04, 62, 30_34, 2]],
                    """attention_mask""": [[1, 1, 1, 1]],
                    # ar_AR
                    """forced_bos_token_id""": 25_00_01,
                }      ,    )






'''simple docstring'''






import logging
from dataclasses import dataclass, field
from pathlib import Path
from typing import Optional, Union

from .generation.configuration_utils import GenerationConfig
from .training_args import TrainingArguments
from .utils import add_start_docstrings


__UpperCAmelCase       							=				logging.getLogger(__name__)




@dataclass
@add_start_docstrings(TrainingArguments.__doc__    )
class 						a__							(				a__    ):





							'''simple docstring'''






							lowercase__     :  bool      		= field(default=a__							,							metadata={"help": "Whether to use SortishSampler or not."}    )
							lowercase__     :  bool      		= field(
							    default=a__							,							metadata={"help": "Whether to use generate to calculate generative metrics (ROUGE, BLEU)."}    )
							lowercase__     :  Optional[int]      		= field(
							    default=a__							,							metadata={
							        "help": (
							            "The `max_length` to use on each evaluation loop when `predict_with_generate=True`. Will default "
							            "to the `max_length` value of the model configuration."
							        )
							    }							,							)
							lowercase__     :  Optional[int]      		= field(
							    default=a__							,							metadata={
							        "help": (
							            "The `num_beams` to use on each evaluation loop when `predict_with_generate=True`. Will default "
							            "to the `num_beams` value of the model configuration."
							        )
							    }							,							)
							lowercase__     :  Optional[Union[str, Path, GenerationConfig]]      		= field(
							    default=a__							,							metadata={
							        "help": "Model id, file path or url pointing to a GenerationConfig json file, to use during prediction."
							    }							,							)







							def     __SCREAMING_SNAKE_CASE				(						self  )			->				Dict:
														lowerCAmelCase__			  =      super().to_dict()
														for k, v in d.items():
																					if isinstance(lowerCamelCase_   ,       lowerCamelCase_  ):
																												lowerCAmelCase__			  =      v.to_dict()
														return d