

import os
import unittest

from transformers import BatchEncoding
from transformers.models.bert.tokenization_bert import (
    BasicTokenizer,
    WordpieceTokenizer,
    _is_control,
    _is_punctuation,
    _is_whitespace,
)
from transformers.models.prophetnet.tokenization_prophetnet import VOCAB_FILES_NAMES, ProphetNetTokenizer
from transformers.testing_utils import require_torch, slow

from ...test_tokenization_common import TokenizerTesterMixin





class        lowerCAmelCase__  (					__magic_name__				,							unittest.TestCase			):



       '''simple docstring'''







       lowercase_						=    ProphetNetTokenizer
       lowercase_						=    False

       def     __UpperCamelCase     (							self     ):







             '''simple docstring'''



             super().setUp()

             __A    =[
                 '''[UNK]''',
                 '''[CLS]''',
                 '''[SEP]''',
                 '''[PAD]''',
                 '''[MASK]''',
                 '''want''',
                 '''##want''',
                 '''##ed''',
                 '''wa''',
                 '''un''',
                 '''runn''',
                 '''##ing''',
                 ''',''',
                 '''low''',
                 '''lowest''',
             ]
             __A    =os.path.join(self.tmpdirname ,   VOCAB_FILES_NAMES['''vocab_file''']     )
             with open(self.vocab_file ,   '''w''' ,   encoding='''utf-8'''     ) as vocab_writer:
                   vocab_writer.write(''''''.join([x + '''\n''' for x in vocab_tokens]     )     )

       def     __UpperCamelCase     (							self ,   lowercase__     ):







             '''simple docstring'''



             __A    ='''UNwant\u00E9d,running'''
             __A    ='''unwanted, running'''
             return input_text, output_text

       def     __UpperCamelCase     (							self     ):







             '''simple docstring'''



             __A    =self.tokenizer_class(self.vocab_file     )

             __A    =tokenizer.tokenize('''UNwant\u00E9d,running'''     )
             self.assertListEqual(lowercase__ ,   ['''un''', '''##want''', '''##ed''', ''',''', '''runn''', '''##ing''']     )
             self.assertListEqual(tokenizer.convert_tokens_to_ids(lowercase__     ) ,   [9, 6, 7, 1_2, 1_0, 1_1]     )

       def     __UpperCamelCase     (							self     ):







             '''simple docstring'''



             __A    =BasicTokenizer()

             self.assertListEqual(tokenizer.tokenize('''ah\u535A\u63A8zz'''     ) ,   ['''ah''', '''\u535A''', '''\u63A8''', '''zz''']     )

       def     __UpperCamelCase     (							self     ):







             '''simple docstring'''



             __A    =BasicTokenizer(do_lower_case=lowercase__     )

             self.assertListEqual(
                 tokenizer.tokenize(''' \tHeLLo!how  \n Are yoU?  '''     ) ,   ['''hello''', '''!''', '''how''', '''are''', '''you''', '''?''']     )
             self.assertListEqual(tokenizer.tokenize('''H\u00E9llo'''     ) ,   ['''hello''']     )

       def     __UpperCamelCase     (							self     ):







             '''simple docstring'''



             __A    =BasicTokenizer(do_lower_case=lowercase__ ,   strip_accents=lowercase__     )

             self.assertListEqual(
                 tokenizer.tokenize(''' \tHäLLo!how  \n Are yoU?  '''     ) ,   ['''hällo''', '''!''', '''how''', '''are''', '''you''', '''?''']     )
             self.assertListEqual(tokenizer.tokenize('''H\u00E9llo'''     ) ,   ['''h\u00E9llo''']     )

       def     __UpperCamelCase     (							self     ):







             '''simple docstring'''



             __A    =BasicTokenizer(do_lower_case=lowercase__ ,   strip_accents=lowercase__     )

             self.assertListEqual(
                 tokenizer.tokenize(''' \tHäLLo!how  \n Are yoU?  '''     ) ,   ['''hallo''', '''!''', '''how''', '''are''', '''you''', '''?''']     )
             self.assertListEqual(tokenizer.tokenize('''H\u00E9llo'''     ) ,   ['''hello''']     )

       def     __UpperCamelCase     (							self     ):







             '''simple docstring'''



             __A    =BasicTokenizer(do_lower_case=lowercase__     )

             self.assertListEqual(
                 tokenizer.tokenize(''' \tHäLLo!how  \n Are yoU?  '''     ) ,   ['''hallo''', '''!''', '''how''', '''are''', '''you''', '''?''']     )
             self.assertListEqual(tokenizer.tokenize('''H\u00E9llo'''     ) ,   ['''hello''']     )

       def     __UpperCamelCase     (							self     ):







             '''simple docstring'''



             __A    =BasicTokenizer(do_lower_case=lowercase__     )

             self.assertListEqual(
                 tokenizer.tokenize(''' \tHeLLo!how  \n Are yoU?  '''     ) ,   ['''HeLLo''', '''!''', '''how''', '''Are''', '''yoU''', '''?''']     )

       def     __UpperCamelCase     (							self     ):







             '''simple docstring'''



             __A    =BasicTokenizer(do_lower_case=lowercase__ ,   strip_accents=lowercase__     )

             self.assertListEqual(
                 tokenizer.tokenize(''' \tHäLLo!how  \n Are yoU?  '''     ) ,   ['''HäLLo''', '''!''', '''how''', '''Are''', '''yoU''', '''?''']     )

       def     __UpperCamelCase     (							self     ):







             '''simple docstring'''



             __A    =BasicTokenizer(do_lower_case=lowercase__ ,   strip_accents=lowercase__     )

             self.assertListEqual(
                 tokenizer.tokenize(''' \tHäLLo!how  \n Are yoU?  '''     ) ,   ['''HaLLo''', '''!''', '''how''', '''Are''', '''yoU''', '''?''']     )

       def     __UpperCamelCase     (							self     ):







             '''simple docstring'''



             __A    =BasicTokenizer(do_lower_case=lowercase__ ,   never_split=['''[UNK]''']     )

             self.assertListEqual(
                 tokenizer.tokenize(''' \tHeLLo!how  \n Are yoU? [UNK]'''     ) ,   ['''HeLLo''', '''!''', '''how''', '''Are''', '''yoU''', '''?''', '''[UNK]''']     )

       def     __UpperCamelCase     (							self     ):







             '''simple docstring'''



             __A    =['''[UNK]''', '''[CLS]''', '''[SEP]''', '''want''', '''##want''', '''##ed''', '''wa''', '''un''', '''runn''', '''##ing''']

             __A    ={}
             for i, token in enumerate(lowercase__     ):
                   __A    =i
             __A    =WordpieceTokenizer(vocab=lowercase__ ,   unk_token='''[UNK]'''     )

             self.assertListEqual(tokenizer.tokenize(''''''     ) ,   []     )

             self.assertListEqual(tokenizer.tokenize('''unwanted running'''     ) ,   ['''un''', '''##want''', '''##ed''', '''runn''', '''##ing''']     )

             self.assertListEqual(tokenizer.tokenize('''unwantedX running'''     ) ,   ['''[UNK]''', '''runn''', '''##ing''']     )

       @require_torch
       def     __UpperCamelCase     (							self     ):







             '''simple docstring'''



             __A    =self.tokenizer_class.from_pretrained('''microsoft/prophetnet-large-uncased'''     )

             __A    =['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
             __A    =[1_0_3_7, 2_1_4_6, 2_0_4_2_3, 2_0_0_5, 7_6_8_0, 7_8_4_9, 3_9_8_9, 1_0_1_2, 1_0_2]
             __A    =tokenizer(lowercase__ ,   padding=lowercase__ ,   return_tensors='''pt'''     )
             self.assertIsInstance(lowercase__ ,   lowercase__     )
             __A    =list(batch.input_ids.numpy()[0]     )
             self.assertListEqual(lowercase__ ,   lowercase__     )

             self.assertEqual((2, 9) ,   batch.input_ids.shape     )
             self.assertEqual((2, 9) ,   batch.attention_mask.shape     )

       def     __UpperCamelCase     (							self     ):







             '''simple docstring'''



             self.assertTrue(_is_whitespace(''' '''     )     )
             self.assertTrue(_is_whitespace('''\t'''     )     )
             self.assertTrue(_is_whitespace('''\r'''     )     )
             self.assertTrue(_is_whitespace('''\n'''     )     )
             self.assertTrue(_is_whitespace('''\u00A0'''     )     )

             self.assertFalse(_is_whitespace('''A'''     )     )
             self.assertFalse(_is_whitespace('''-'''     )     )

       def     __UpperCamelCase     (							self     ):







             '''simple docstring'''



             self.assertTrue(_is_control('''\u0005'''     )     )

             self.assertFalse(_is_control('''A'''     )     )
             self.assertFalse(_is_control(''' '''     )     )
             self.assertFalse(_is_control('''\t'''     )     )
             self.assertFalse(_is_control('''\r'''     )     )

       def     __UpperCamelCase     (							self     ):







             '''simple docstring'''



             self.assertTrue(_is_punctuation('''-'''     )     )
             self.assertTrue(_is_punctuation('''$'''     )     )
             self.assertTrue(_is_punctuation('''`'''     )     )
             self.assertTrue(_is_punctuation('''.'''     )     )

             self.assertFalse(_is_punctuation('''A'''     )     )
             self.assertFalse(_is_punctuation(''' '''     )     )


       @slow
       def     __UpperCamelCase     (							self     ):







             '''simple docstring'''



             __A    =self.tokenizer_class.from_pretrained('''microsoft/prophetnet-large-uncased'''     )

             __A    =tokenizer.encode('''sequence builders''' ,   add_special_tokens=lowercase__     )
             __A    =tokenizer.encode('''multi-sequence build''' ,   add_special_tokens=lowercase__     )

             __A    =tokenizer.build_inputs_with_special_tokens(lowercase__     )
             __A    =tokenizer.build_inputs_with_special_tokens(lowercase__ ,   lowercase__     )

             assert encoded_sentence == text + [1_0_2]
             assert encoded_pair == text + [1_0_2] + text_a + [1_0_2]





import argparse
import json
import os

import torch
from transformers.file_utils import has_file

from diffusers import UNetaDConditionModel, UNetaDModel


lowercase_   							=  False
lowercase_   							=  True
lowercase_   							=  False


if __name__ == "__main__":
  lowercase_   							=  argparse.ArgumentParser()

  parser.add_argument(
      '--repo_path',
      default=None,
      type=str,
      required=True,
      help='The config json file corresponding to the architecture.',
  )

  parser.add_argument('--dump_path', default=None, type=str, required=True, help='Path to the output model.')

  lowercase_   							=  parser.parse_args()

  lowercase_   							=  {
      'image_size': 'sample_size',
      'num_res_blocks': 'layers_per_block',
      'block_channels': 'block_out_channels',
      'down_blocks': 'down_block_types',
      'up_blocks': 'up_block_types',
      'downscale_freq_shift': 'freq_shift',
      'resnet_num_groups': 'norm_num_groups',
      'resnet_act_fn': 'act_fn',
      'resnet_eps': 'norm_eps',
      'num_head_channels': 'attention_head_dim',
  }

  lowercase_   							=  {
      'time_steps': 'time_proj',
      'mid': 'mid_block',
      'downsample_blocks': 'down_blocks',
      'upsample_blocks': 'up_blocks',
  }

  lowercase_   							=  '' if has_file(args.repo_path, 'config.json') else 'unet'

  with open(os.path.join(args.repo_path, subfolder, 'config.json'), 'r', encoding='utf-8') as reader:
    lowercase_   							=  reader.read()
    lowercase_   							=  json.loads(text)

  if do_only_config:
    for key in config_parameters_to_change.keys():
      config.pop(key, None)

  if has_file(args.repo_path, 'config.json'):
    lowercase_   							=  UNetaDModel(**config)
  else:
    lowercase_   							=  UNetaDConditionModel if 'ldm-text2im-large-256' in args.repo_path else UNetaDModel
    lowercase_   							=  class_name(**config)

  if do_only_config:
    model.save_config(os.path.join(args.repo_path, subfolder))

  lowercase_   							=  dict(model.config)

  if do_only_renaming:
    for key, value in config_parameters_to_change.items():
      if key in config:
        lowercase_   							=  config[key]
        del config[key]

    lowercase_   							=  [k.replace('UNetRes', '') for k in config['down_block_types']]
    lowercase_   							=  [k.replace('UNetRes', '') for k in config['up_block_types']]

  if do_only_weights:
    lowercase_   							=  torch.load(os.path.join(args.repo_path, subfolder, 'diffusion_pytorch_model.bin'))

    lowercase_   							=  {}
    for param_key, param_value in state_dict.items():
      if param_key.endswith('.op.bias') or param_key.endswith('.op.weight'):
        continue
      lowercase_   							=  False
      for key, new_key in key_parameters_to_change.items():
        if not has_changed and param_key.split('.')[0] == key:
          lowercase_   							=  param_value
          lowercase_   							=  True
      if not has_changed:
        lowercase_   							=  param_value

    model.load_state_dict(new_state_dict)
    model.save_pretrained(os.path.join(args.repo_path, subfolder))


