


import argparse

import torch

from transformers import FunnelBaseModel, FunnelConfig, FunnelModel, load_tf_weights_in_funnel
from transformers.utils import logging


logging.set_verbosity_info()




def 	a_      (    SCREAMING_SNAKE_CASE__					:      Union[str, Any]		,			SCREAMING_SNAKE_CASE__					:      str		,			SCREAMING_SNAKE_CASE__					:      Any		,			SCREAMING_SNAKE_CASE__					:      Any     ):
       '''simple docstring'''





       _lowerCamelCase       :		Tuple		=FunnelConfig.from_json_file(SCREAMING_SNAKE_CASE__     )
       print(F'''Building PyTorch model from configuration: {config}'''     )
       _lowerCamelCase       :		int		=FunnelBaseModel(SCREAMING_SNAKE_CASE__     ) if base_model else FunnelModel(SCREAMING_SNAKE_CASE__     )

       # Load weights from tf checkpoint
       load_tf_weights_in_funnel(SCREAMING_SNAKE_CASE__		,			SCREAMING_SNAKE_CASE__		,			SCREAMING_SNAKE_CASE__     )

       # Save pytorch-model
       print(F'''Save PyTorch model to {pytorch_dump_path}'''     )
       torch.save(model.state_dict()		,			SCREAMING_SNAKE_CASE__     )


if __name__ == "__main__":
 lowerCamelCase											=       argparse.ArgumentParser()
 # Required parameters
 parser.add_argument(
     '--tf_checkpoint_path', default=None, type=str, required=True, help='Path to the TensorFlow checkpoint path.'
 )
 parser.add_argument(
     '--config_file',
     default=None,
     type=str,
     required=True,
     help='The config json file corresponding to the pre-trained model. \nThis specifies the model architecture.',
 )
 parser.add_argument(
     '--pytorch_dump_path', default=None, type=str, required=True, help='Path to the output PyTorch model.'
 )
 parser.add_argument(
     '--base_model', action='store_true', help='Whether you want just the base model (no decoder) or not.'
 )
 lowerCamelCase											=       parser.parse_args()
 convert_tf_checkpoint_to_pytorch(
     args.tf_checkpoint_path, args.config_file, args.pytorch_dump_path, args.base_model
 )






import unittest

from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


lowerCamelCase											=       get_tests_dir('fixtures/test_sentencepiece.model')




@require_sentencepiece
class A  (   UpperCamelCase_    ,							unittest.TestCase     ):
      UpperCamelCase__							:  str      =XLMProphetNetTokenizer
      UpperCamelCase__							:  Any      =False
      UpperCamelCase__							:  Optional[Any]      =True






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




             super().setUp()

             # We have a SentencePiece fixture for testing
             _lowerCamelCase       :		Union[str, Any]		=XLMProphetNetTokenizer(lowercase_			,   keep_accents=lowercase_ )
             tokenizer.save_pretrained(self.tmpdirname )






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




             _lowerCamelCase       :		Tuple		='[PAD]'
             _lowerCamelCase       :		Dict		=0

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






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




             _lowerCamelCase       :		int		=list(self.get_tokenizer().get_vocab().keys() )

             self.assertEqual(vocab_keys[0]			,   '[PAD]' )
             self.assertEqual(vocab_keys[1]			,   '[CLS]' )
             self.assertEqual(vocab_keys[-1]			,   'j' )
             self.assertEqual(len(lowercase_ )			,   1012 )






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




             self.assertEqual(self.get_tokenizer().vocab_size			,   1012 )






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




             _lowerCamelCase       :		List[Any]		=XLMProphetNetTokenizer(lowercase_			,   keep_accents=lowercase_ )

             _lowerCamelCase       :		Any		=tokenizer.tokenize('This is a test' )
             self.assertListEqual(lowercase_			,   ['▁This', '▁is', '▁a', '▁t', 'est'] )

             self.assertListEqual(
                 tokenizer.convert_tokens_to_ids(lowercase_ )			,   [value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]]			,   )

             _lowerCamelCase       :		Dict		=tokenizer.tokenize('I was born in 92000, and this is falsé.' )
             self.assertListEqual(
                 lowercase_			,   [
                     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',
                     '.',
                 ]			,   )
             _lowerCamelCase       :		Union[str, Any]		=tokenizer.convert_tokens_to_ids(lowercase_ )
             self.assertListEqual(
                 lowercase_			,   [
                     value + tokenizer.fairseq_offset
                     for value in [8, 21, 84, 55, 24, 19, 7, -9, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, -9, 4]
                 ]			,   )

             _lowerCamelCase       :		int		=tokenizer.convert_ids_to_tokens(lowercase_ )
             self.assertListEqual(
                 lowercase_			,   [
                     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]',
                     '.',
                 ]			,   )






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




             return XLMProphetNetTokenizer.from_pretrained('microsoft/xprophetnet-large-wiki100-cased' )






      @slow
      def        lowerCamelCase       (					self						:     List[str] )					->						Any:
             """simple docstring"""




             _lowerCamelCase       :		Optional[int]		='Hello World!'
             _lowerCamelCase       :		Optional[int]		=[3_5389, 6672, 49, 2]
             self.assertListEqual(lowercase_			,   self.big_tokenizer.encode(lowercase_ ) )






      @slow
      def        lowerCamelCase       (					self						:     Optional[int] )					->						Dict:
             """simple docstring"""




             _lowerCamelCase       :		Dict		={'input_ids': [[1_1073, 8_2783, 18, 26, 8_2783, 549, 5_1540, 248, 1_7209, 1301, 217, 20, 21_5186, 1325, 147, 1_7209, 1301, 217, 20, 5_6370, 53, 12_2020, 20, 1_6477, 27, 8_7355, 4548, 20, 4728, 7_8392, 17, 15_9969, 18, 26, 2_4491, 629, 15, 538, 2_2704, 5439, 15, 2788, 2_4491, 9885, 15, 4_3534, 605, 15, 814, 1_8403, 3_3200, 29, 15, 4_3534, 2_4458, 1_2410, 111, 2_4966, 8_3669, 9637, 14_4068, 26, 850, 2_2346, 27, 147, 2_4966, 8_3669, 8_3490, 26, 3_9113, 735, 27, 689, 656, 2800, 1339, 4600, 53, 12_2020, 11_5785, 34, 816, 1339, 4_6887, 18, 147, 5_3905, 1951, 4_2238, 4_1170, 1_7732, 834, 436, 15, 2_7523, 9_8733, 217, 147, 5542, 4981, 930, 1_7347, 16, 2], [2_0091, 629, 94, 8_2786, 58, 490, 20, 1528, 84, 5_3905, 344, 8_0592, 11_0128, 1_8822, 5267, 1306, 62, 15_2537, 308, 7997, 401, 12_4427, 549, 3_5442, 225, 109, 1_5055, 2_5748, 147, 7119, 4_3712, 34, 767, 13_5366, 18, 16, 2, 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], [592, 6_3784, 11_9466, 17, 14_7808, 8_8214, 18, 656, 81, 32, 3296, 1_0280, 16, 2, 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]], '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, 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, 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=lowercase_			,   model_name='microsoft/xprophetnet-large-wiki100-cased'			,   revision='1acad1643ddd54a44df6a1b797ada8373685d90e'			,   )


