





'''simple docstring'''





import unittest

from transformers import ErnieMTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


_A				:							Dict							= get_tests_dir("""fixtures/spiece.model""")



@require_sentencepiece
@require_tokenizers
class 				__snake_case  (     lowerCamelCase__ ,    unittest.TestCase						):


    '''simple docstring'''







    lowerCamelCase__						:		Optional[Any]							=  ErnieMTokenizer
    lowerCamelCase__						:		Dict							=  False
    lowerCamelCase__						:		int							=  True
    lowerCamelCase__						:		List[Any]							=  False
    lowerCamelCase__						:		Optional[int]							=  False



    def    lowercase_				(					self    ):





        '''simple docstring'''

        super().setUp()

        # We have a SentencePiece fixture for testing
        SCREAMING_SNAKE_CASE__       							= ErnieMTokenizer(lowercase_      ,							unk_token='''<unk>'''      ,							pad_token='''<pad>'''    )
        tokenizer.save_pretrained(self.tmpdirname    )



    def    lowercase_				(					self      ,							A_    ):





        '''simple docstring'''

        SCREAMING_SNAKE_CASE__       							= '''this is a test'''
        SCREAMING_SNAKE_CASE__       							= '''this is a test'''
        return input_text, output_text



    def    lowercase_				(					self    ):





        '''simple docstring'''

        SCREAMING_SNAKE_CASE__       							= '''<pad>'''
        SCREAMING_SNAKE_CASE__       							= 0

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



    def    lowercase_				(					self    ):





        '''simple docstring'''

        SCREAMING_SNAKE_CASE__       							= list(self.get_tokenizer().get_vocab().keys()    )

        self.assertEqual(vocab_keys[0]      ,							'''<pad>'''    )
        self.assertEqual(vocab_keys[1]      ,							'''<unk>'''    )
        self.assertEqual(vocab_keys[-1]      ,							'''▁eloquent'''    )
        self.assertEqual(len(lowercase_    )      ,							3_00_00    )



    def    lowercase_				(					self    ):





        '''simple docstring'''

        self.assertEqual(self.get_tokenizer().vocab_size      ,							3_00_00    )



    def    lowercase_				(					self    ):





        '''simple docstring'''

        if not self.test_rust_tokenizer:
            return

        SCREAMING_SNAKE_CASE__       							= self.get_tokenizer()
        SCREAMING_SNAKE_CASE__       							= self.get_rust_tokenizer()

        SCREAMING_SNAKE_CASE__       							= '''I was born in 92000, and this is falsé.'''

        SCREAMING_SNAKE_CASE__       							= tokenizer.tokenize(lowercase_    )
        SCREAMING_SNAKE_CASE__       							= rust_tokenizer.tokenize(lowercase_    )
        self.assertListEqual(lowercase_      ,							lowercase_    )

        SCREAMING_SNAKE_CASE__       							= tokenizer.encode(lowercase_      ,							add_special_tokens=lowercase_    )
        SCREAMING_SNAKE_CASE__       							= rust_tokenizer.encode(lowercase_      ,							add_special_tokens=lowercase_    )
        self.assertListEqual(lowercase_      ,							lowercase_    )

        SCREAMING_SNAKE_CASE__       							= self.get_rust_tokenizer()
        SCREAMING_SNAKE_CASE__       							= tokenizer.encode(lowercase_    )
        SCREAMING_SNAKE_CASE__       							= rust_tokenizer.encode(lowercase_    )
        self.assertListEqual(lowercase_      ,							lowercase_    )



    def    lowercase_				(					self    ):





        '''simple docstring'''

        SCREAMING_SNAKE_CASE__       							= ErnieMTokenizer(lowercase_      ,							do_lower_case=lowercase_      ,							unk_token='''<unk>'''      ,							pad_token='''<pad>'''    )

        SCREAMING_SNAKE_CASE__       							= tokenizer.tokenize('''This is a test'''    )
        self.assertListEqual(lowercase_      ,							['''▁this''', '''▁is''', '''▁a''', '''▁test''']    )

        self.assertListEqual(tokenizer.convert_tokens_to_ids(lowercase_    )      ,							[48, 25, 21, 12_89]    )

        SCREAMING_SNAKE_CASE__       							= tokenizer.tokenize('''I was born in 92000, and this is falsé.'''    )
        # ErnieMTokenizer(paddlenlp implementation) outputs '9' instead of '_9' so to mimic that '_9' is changed to '9'
        self.assertListEqual(
            lowercase_      ,							['''▁i''', '''▁was''', '''▁born''', '''▁in''', '''9''', '''2000''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''é''', '''.''']    )
        SCREAMING_SNAKE_CASE__       							= tokenizer.convert_tokens_to_ids(lowercase_    )
        self.assertListEqual(lowercase_      ,							[31, 23, 3_86, 19, 5_18, 30_50, 15, 17, 48, 25, 82_56, 18, 1, 9]    )

        SCREAMING_SNAKE_CASE__       							= tokenizer.convert_ids_to_tokens(lowercase_    )
        self.assertListEqual(
            lowercase_      ,							['''▁i''', '''▁was''', '''▁born''', '''▁in''', '''9''', '''2000''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''<unk>''', '''.''']      ,							)



    def    lowercase_				(					self    ):





        '''simple docstring'''

        SCREAMING_SNAKE_CASE__       							= ErnieMTokenizer(lowercase_      ,							unk_token='''<unk>'''      ,							pad_token='''<pad>'''    )

        SCREAMING_SNAKE_CASE__       							= tokenizer.encode('''sequence builders'''    )
        SCREAMING_SNAKE_CASE__       							= tokenizer.encode('''multi-sequence build'''    )

        SCREAMING_SNAKE_CASE__       							= tokenizer.build_inputs_with_special_tokens(lowercase_    )
        SCREAMING_SNAKE_CASE__       							= tokenizer.build_inputs_with_special_tokens(lowercase_      ,							lowercase_    )

        assert encoded_sentence == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]
        assert encoded_pair == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + [
            tokenizer.sep_token_id
        ] + text_a + [tokenizer.sep_token_id]




    @slow
    def    lowercase_				(					self    ):





        '''simple docstring'''

        SCREAMING_SNAKE_CASE__       							= {'''input_ids''': [[0, 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, 9, 3_04, 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, 5, 5, 5, 16, 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, 64_60, 13_28, 45_89, 42, 12_20_09, 11_57_74, 23, 35_59, 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], [0, 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, 1, 1, 1, 1], [0, 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, 1, 1, 1, 1]]}
        # fmt: on

        self.tokenizer_integration_test_util(
            expected_encoding=lowercase_      ,							model_name='''susnato/ernie-m-base_pytorch'''      ,							sequences=[
                '''Transformers (formerly known as pytorch-transformers and pytorch-pretrained-bert) provides '''
                '''general-purpose architectures (BERT, GPT-2, RoBERTa, XLM, DistilBert, XLNet...) for Natural '''
                '''Language Understanding (NLU) and Natural Language Generation (NLG) with over32+ pretrained '''
                '''models in100+ languages and deep interoperability between Jax, PyTorch and TensorFlow.''',
                '''BERT is designed to pre-train deep bidirectional representations from unlabeled text by jointly '''
                '''conditioning on both left and right context in all layers.''',
                '''The quick brown fox jumps over the lazy dog.''',
            ]      ,							)







import os
from pathlib import Path
from typing import Dict, List

import fire
import torch

from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from transformers.utils.logging import get_logger


_A				:							Any							= get_logger(__name__)


def        __snake_case       (						lowerCAmelCase_   ,       lowerCAmelCase_  )							->	str:
    if text.startswith(lowerCAmelCase_  ):
        return text[len(lowerCAmelCase_  ) :]
    return text  # or whatever


def        __snake_case       (						lowerCAmelCase_  )							->	Union[str, Any]:
    return {remove_prefix(lowerCAmelCase_   ,       '''model.'''  ): v for k, v in sd.items()}


def        __snake_case       (						lowerCAmelCase_  )							->	Optional[int]:
    SCREAMING_SNAKE_CASE__       							= {}
    for k in state_dicts[0].keys():
        SCREAMING_SNAKE_CASE__       							= [sd[k] for sd in state_dicts]
        SCREAMING_SNAKE_CASE__       							= sum(lowerCAmelCase_  ) / len(lowerCAmelCase_  )
        assert isinstance(lowerCAmelCase_   ,       torch.Tensor  )
        SCREAMING_SNAKE_CASE__       							= new_t
    return new_sd


def        __snake_case       (						lowerCAmelCase_   ,       lowerCAmelCase_   ,       lowerCAmelCase_  )							->	None:
    SCREAMING_SNAKE_CASE__       							= AutoModelForSeqaSeqLM.from_pretrained(lowerCAmelCase_  )
    if os.path.isfile(lowerCAmelCase_  ):
        SCREAMING_SNAKE_CASE__       							= [pl_ckpt_path]
    else:
        assert os.path.isdir(lowerCAmelCase_  )
        SCREAMING_SNAKE_CASE__       							= list(Path(lowerCAmelCase_  ).glob('''*.ckpt'''  )  )
        assert ckpt_files, f'''could not find any ckpt files inside the {pl_ckpt_path} directory'''

    if len(lowerCAmelCase_  ) > 1:
        logger.info(f'''averaging the weights of {ckpt_files}'''  )

    SCREAMING_SNAKE_CASE__       							= [sanitize(torch.load(lowerCAmelCase_   ,       map_location='''cpu'''  )['''state_dict''']  ) for x in ckpt_files]
    SCREAMING_SNAKE_CASE__       							= average_state_dicts(lowerCAmelCase_  )

    SCREAMING_SNAKE_CASE__							,		SCREAMING_SNAKE_CASE__       							= hf_model.load_state_dict(lowerCAmelCase_   ,       strict=lowerCAmelCase_  )
    assert not missing, f'''missing keys: {missing}'''
    hf_model.save_pretrained(lowerCAmelCase_  )
    try:
        SCREAMING_SNAKE_CASE__       							= AutoTokenizer.from_pretrained(lowerCAmelCase_  )
        tok.save_pretrained(lowerCAmelCase_  )
    except Exception:
        pass
        # dont copy tokenizer if cant


if __name__ == "__main__":
  fire.Fire(convert_pl_to_hf)
