
"""simple docstring"""

import unittest

from transformers import SPIECE_UNDERLINE, XLNetTokenizer, XLNetTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


UpperCamelCase     :    List[str]       =			get_tests_dir("fixtures/test_sentencepiece.model")

@require_sentencepiece
@require_tokenizers
class __lowerCAmelCase		(				__SCREAMING_SNAKE_CASE      ,  unittest.TestCase      ):
     lowercase						       =						XLNetTokenizer
     lowercase						       =						XLNetTokenizerFast
     lowercase						       =						True
     lowercase						       =						True





     def 						UpperCAmelCase (     self				):

      '''simple docstring'''




      super().setUp()

      # We have a SentencePiece fixture for testing
      __UpperCamelCase      =	XLNetTokenizer(__UpperCAmelCase     ,					keep_accents=__UpperCAmelCase				)
      tokenizer.sanitize_special_tokens()
      tokenizer.save_pretrained(self.tmpdirname				)





     def 						UpperCAmelCase (     self				):

      '''simple docstring'''




      __UpperCamelCase      =	'<s>'
      __UpperCamelCase      =	1

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





     def 						UpperCAmelCase (     self				):

      '''simple docstring'''




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

      self.assertEqual(vocab_keys[0]     ,					'<unk>'				)
      self.assertEqual(vocab_keys[1]     ,					'<s>'				)
      self.assertEqual(vocab_keys[-1]     ,					'<eod>'				)
      self.assertEqual(len(__UpperCAmelCase				)     ,					1006				)





     def 						UpperCAmelCase (     self				):

      '''simple docstring'''




      self.assertEqual(self.get_tokenizer().vocab_size     ,					1000				)





     def 						UpperCAmelCase (     self				):

      '''simple docstring'''




      __UpperCamelCase      =	XLNetTokenizer(__UpperCAmelCase     ,					keep_accents=__UpperCAmelCase				)

      __UpperCamelCase      =	tokenizer.tokenize('This is a test'				)
      self.assertListEqual(__UpperCAmelCase     ,					['▁This', '▁is', '▁a', '▁t', 'est']				)

      self.assertListEqual(tokenizer.convert_tokens_to_ids(__UpperCAmelCase				)     ,					[285, 46, 10, 170, 382]				)

      __UpperCamelCase      =	tokenizer.tokenize('I was born in 92000, and this is falsé.'				)
      self.assertListEqual(
          __UpperCAmelCase     ,					[
              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',
              '.',
          ]     ,					)
      __UpperCamelCase      =	tokenizer.convert_tokens_to_ids(__UpperCAmelCase				)
      self.assertListEqual(__UpperCAmelCase     ,					[8, 21, 84, 55, 24, 19, 7, 0, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 0, 4]				)

      __UpperCamelCase      =	tokenizer.convert_ids_to_tokens(__UpperCAmelCase				)
      self.assertListEqual(
          __UpperCAmelCase     ,					[
              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>',
              '.',
          ]     ,					)





     def 						UpperCAmelCase (     self				):

      '''simple docstring'''




      __UpperCamelCase      =	XLNetTokenizer(__UpperCAmelCase     ,					do_lower_case=__UpperCAmelCase				)
      __UpperCamelCase      =	tokenizer.tokenize('I was born in 92000, and this is falsé.'				)
      self.assertListEqual(
          __UpperCAmelCase     ,					[
              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',
              'se',
              '.',
          ]     ,					)
      self.assertListEqual(tokenizer.tokenize('H\u00E9llo'				)     ,					['▁he', 'll', 'o']				)





     def 						UpperCAmelCase (     self				):

      '''simple docstring'''




      __UpperCamelCase      =	XLNetTokenizer(__UpperCAmelCase     ,					do_lower_case=__UpperCAmelCase				)
      __UpperCamelCase      =	tokenizer.tokenize('I was born in 92000, and this is falsé.'				)
      self.assertListEqual(
          __UpperCAmelCase     ,					[
              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',
              'se',
              '.',
          ]     ,					)





     @slow
     def 						UpperCAmelCase (     self				):

      '''simple docstring'''




      __UpperCamelCase      =	XLNetTokenizer.from_pretrained('xlnet-base-cased'				)

      __UpperCamelCase      =	tokenizer.encode('sequence builders'     ,					add_special_tokens=__UpperCAmelCase				)
      __UpperCamelCase      =	tokenizer.encode('multi-sequence build'     ,					add_special_tokens=__UpperCAmelCase				)

      __UpperCamelCase      =	tokenizer.build_inputs_with_special_tokens(__UpperCAmelCase				)
      __UpperCamelCase      =	tokenizer.build_inputs_with_special_tokens(__UpperCAmelCase     ,					__UpperCAmelCase				)

      assert encoded_sentence == text + [4, 3]
      assert encoded_pair == text + [4] + text_a + [4, 3]







     @slow
     def 						UpperCAmelCase (     self				):

      '''simple docstring'''




      __UpperCamelCase      =	{'input_ids': [[17, 2_1442, 270, 17, 10, 1_4645, 318, 34, 17, 4546, 3145, 787, 13, 7752, 2_2018, 23, 21, 17, 4546, 3145, 787, 13, 3352, 1_4431, 13, 5500, 11, 1176, 580, 13, 1_6819, 4797, 23, 17, 10, 1_7135, 658, 19, 457, 7932, 13, 184, 19, 3154, 1_7135, 6468, 19, 1404, 1_2269, 19, 4229, 5356, 1_6264, 46, 19, 17, 2_0545, 1_0395, 9, 9, 9, 11, 28, 6421, 9531, 2_0729, 17, 10, 353, 1_7022, 11, 21, 6421, 9531, 1_6949, 17, 10, 1_1509, 753, 11, 33, 95, 2421, 7385, 956, 1_4431, 2626, 25, 842, 7385, 4836, 21, 1429, 2272, 9855, 3120, 161, 2_4738, 19, 1_3203, 658, 218, 787, 21, 430, 1_8482, 847, 2637, 9, 4, 3], [5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 322, 2_2178, 27, 1064, 22, 956, 13, 1_1101, 1429, 5854, 2_4313, 1_8953, 40, 422, 2_4366, 68, 1758, 37, 1_0483, 1_4257, 31, 207, 263, 21, 203, 3773, 25, 71, 9735, 9, 4, 3], [5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 32, 2049, 3442, 17, 1_3894, 3380, 23, 95, 18, 1_7634, 2288, 9, 4, 3]], 'token_type_ids': [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2], [3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2], [3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2]], '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], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 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, 0, 0, 0, 0, 0, 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]]}  # noqa: E501
      # fmt: on

      self.tokenizer_integration_test_util(
          expected_encoding=__UpperCAmelCase     ,					model_name='xlnet-base-cased'     ,					revision='c841166438c31ec7ca9a106dee7bb312b73ae511'     ,					)





"""simple docstring"""

import argparse

import OmegaConf
import torch

from diffusers import DDIMScheduler, LDMPipeline, UNetLDMModel, VQModel






def 							A						(    snake_case				:Dict    , snake_case				:Optional[Any]    , snake_case				:List[Any]		)				->     Optional[Any]:
 __UpperCamelCase      =	OmegaConf.load(snake_case		)
 __UpperCamelCase      =	torch.load(snake_case    , map_location='cpu'		)['model']
 __UpperCamelCase      =	list(state_dict.keys()		)

 # extract state_dict for VQVAE
 __UpperCamelCase      =	{}
 __UpperCamelCase      =	'first_stage_model.'
 for key in keys:
  if key.startswith(snake_case		):
   __UpperCamelCase      =	state_dict[key]

    # extract state_dict for UNetLDM
 __UpperCamelCase      =	{}
 __UpperCamelCase      =	'model.diffusion_model.'
 for key in keys:
  if key.startswith(snake_case		):
   __UpperCamelCase      =	state_dict[key]

 __UpperCamelCase      =	config.model.params.first_stage_config.params
 __UpperCamelCase      =	config.model.params.unet_config.params

 __UpperCamelCase      =	VQModel(**snake_case		).eval()
 vqvae.load_state_dict(snake_case		)

 __UpperCamelCase      =	UNetLDMModel(**snake_case		).eval()
 unet.load_state_dict(snake_case		)

 __UpperCamelCase      =	DDIMScheduler(
     timesteps=config.model.params.timesteps    , beta_schedule='scaled_linear'    , beta_start=config.model.params.linear_start    , beta_end=config.model.params.linear_end    , clip_sample=snake_case    , )

 __UpperCamelCase      =	LDMPipeline(snake_case    , snake_case    , snake_case		)
 pipeline.save_pretrained(snake_case		)


if __name__ == "__main__":
      UpperCamelCase     :    Dict       =			argparse.ArgumentParser()
      parser.add_argument("--checkpoint_path", type=str, required=True)
      parser.add_argument("--config_path", type=str, required=True)
      parser.add_argument("--output_path", type=str, required=True)
      UpperCamelCase     :    Optional[int]       =			parser.parse_args()

      convert_ldm_original(args.checkpoint_path, args.config_path, args.output_path)



