
"""simple docstring"""



import argparse
from collections import defaultdict

import yaml


UpperCAmelCase__          = 'docs/source/en/_toctree.yml'
def 					_UpperCAmelCase      ( __lowerCamelCase   :       str		)     ->					str:
  _snake_case					     =       defaultdict(__lowerCamelCase		)
  _snake_case					     =       []
  _snake_case					     =       []
  for doc in doc_list:
    if "local" in doc:
      counts[doc["local"]] += 1

    if doc["title"].lower() == "overview":
      overview_doc.append({'''local''': doc['''local'''], '''title''': doc['''title''']}		)
    else:
      new_doc_list.append(__lowerCamelCase		)

  _snake_case					     =       new_doc_list
  _snake_case					     =       [key for key, value in counts.items() if value > 1]

  _snake_case					     =       []
  for duplicate_key in duplicates:
    _snake_case					     =       list({doc['''title'''] for doc in doc_list if doc['''local'''] == duplicate_key}		)
    if len(__lowerCamelCase		) > 1:
      raise ValueError(
          f'''{duplicate_key} is present several times in the documentation table of content at '''
          '''`docs/source/en/_toctree.yml` with different *Title* values. Choose one of those and remove the '''
          '''others.'''		)
    # Only add this once
    new_doc.append({'''local''': duplicate_key, '''title''': titles[0]}		)

  # Add none duplicate-keys
  new_doc.extend([doc for doc in doc_list if '''local''' not in counts or counts[doc['''local''']] == 1]		)
  _snake_case					     =       sorted(__lowerCamelCase ,					key=lambda __lowerCamelCase		: s["title"].lower()		)

  # "overview" gets special treatment and is always first
  if len(__lowerCamelCase		) > 1:
    raise ValueError('''{doc_list} has two \'overview\' docs which is not allowed.'''		)

  overview_doc.extend(__lowerCamelCase		)

  # Sort
  return overview_doc
def 					_UpperCAmelCase      ( __lowerCamelCase   :       List[str]=False		)     ->					Union[str, Any]:
  with open(__lowerCamelCase ,					encoding='''utf-8'''		) as f:
    _snake_case					     =       yaml.safe_load(f.read()		)

  # Get to the API doc
  _snake_case					     =       0
  while content[api_idx]["title"] != "API":
    api_idx += 1
  _snake_case					     =       content[api_idx]['''sections''']

  # Then to the model doc
  _snake_case					     =       0
  while api_doc[scheduler_idx]["title"] != "Schedulers":
    scheduler_idx += 1

  _snake_case					     =       api_doc[scheduler_idx]['''sections''']
  _snake_case					     =       clean_doc_toc(__lowerCamelCase		)

  _snake_case					     =       False
  if new_scheduler_doc != scheduler_doc:
    _snake_case					     =       True
    if overwrite:
      _snake_case					     =       new_scheduler_doc

  if diff:
    if overwrite:
      _snake_case					     =       api_doc
      with open(__lowerCamelCase ,					'''w''' ,					encoding='''utf-8'''		) as f:
        f.write(yaml.dump(__lowerCamelCase ,					allow_unicode=__lowerCamelCase		)		)
    else:
      raise ValueError(
          '''The model doc part of the table of content is not properly sorted, run `make style` to fix this.'''		)
def 					_UpperCAmelCase      ( __lowerCamelCase   :       int=False		)     ->					Any:
  with open(__lowerCamelCase ,					encoding='''utf-8'''		) as f:
    _snake_case					     =       yaml.safe_load(f.read()		)

  # Get to the API doc
  _snake_case					     =       0
  while content[api_idx]["title"] != "API":
    api_idx += 1
  _snake_case					     =       content[api_idx]['''sections''']

  # Then to the model doc
  _snake_case					     =       0
  while api_doc[pipeline_idx]["title"] != "Pipelines":
    pipeline_idx += 1

  _snake_case					     =       False
  _snake_case					     =       api_doc[pipeline_idx]['''sections''']
  _snake_case					     =       []

  # sort sub pipeline docs
  for pipeline_doc in pipeline_docs:
    if "section" in pipeline_doc:
      _snake_case					     =       pipeline_doc['''section''']
      _snake_case					     =       clean_doc_toc(__lowerCamelCase		)
      if overwrite:
        _snake_case					     =       new_sub_pipeline_doc
    new_pipeline_docs.append(__lowerCamelCase		)

  # sort overall pipeline doc
  _snake_case					     =       clean_doc_toc(__lowerCamelCase		)

  if new_pipeline_docs != pipeline_docs:
    _snake_case					     =       True
    if overwrite:
      _snake_case					     =       new_pipeline_docs

  if diff:
    if overwrite:
      _snake_case					     =       api_doc
      with open(__lowerCamelCase ,					'''w''' ,					encoding='''utf-8'''		) as f:
        f.write(yaml.dump(__lowerCamelCase ,					allow_unicode=__lowerCamelCase		)		)
    else:
      raise ValueError(
          '''The model doc part of the table of content is not properly sorted, run `make style` to fix this.'''		)


if __name__ == "__main__":
 UpperCAmelCase__          = argparse.ArgumentParser()
 parser.add_argument('--fix_and_overwrite', action='store_true', help='Whether to fix inconsistencies.')
 UpperCAmelCase__          = parser.parse_args()

 check_scheduler_doc(args.fix_and_overwrite)
 check_pipeline_doc(args.fix_and_overwrite)





"""simple docstring"""



import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils import IMAGE_PROCESSOR_NAME, is_vision_available


if is_vision_available():
 from PIL import Image

 from transformers import CLIPImageProcessor, CLIPProcessor

@require_vision
class       lowerCAmelCase__				(						unittest.TestCase	):







     def      lowercase	(							self			:			Any			):
       _snake_case					     =       tempfile.mkdtemp()

       # fmt: off
       _snake_case					     =       ['''l''', '''o''', '''w''', '''e''', '''r''', '''s''', '''t''', '''i''', '''d''', '''n''', '''lo''', '''l</w>''', '''w</w>''', '''r</w>''', '''t</w>''', '''low</w>''', '''er</w>''', '''lowest</w>''', '''newer</w>''', '''wider''', '''<unk>''', '''<|startoftext|>''', '''<|endoftext|>''']
       # fmt: on
       _snake_case					     =       dict(zip(_lowerCamelCase    ,      range(len(_lowerCamelCase			)			)			)			)
       _snake_case					     =       ['''#version: 0.2''', '''l o''', '''lo w</w>''', '''e r</w>''', '''''']
       _snake_case					     =       {'''unk_token''': '''<unk>'''}

       _snake_case					     =       os.path.join(self.tmpdirname    ,      VOCAB_FILES_NAMES['''vocab_file''']			)
       _snake_case					     =       os.path.join(self.tmpdirname    ,      VOCAB_FILES_NAMES['''merges_file''']			)
       with open(self.vocab_file    ,      '''w'''    ,      encoding='''utf-8'''			) as fp:
         fp.write(json.dumps(_lowerCamelCase			) + '''\n'''			)
       with open(self.merges_file    ,      '''w'''    ,      encoding='''utf-8'''			) as fp:
         fp.write('''\n'''.join(_lowerCamelCase			)			)

       _snake_case					     =       {
           '''do_resize''': True,
           '''size''': 20,
           '''do_center_crop''': True,
           '''crop_size''': 18,
           '''do_normalize''': True,
           '''image_mean''': [0.4_8_1_4_5_4_6_6, 0.4_5_7_8_2_7_5, 0.4_0_8_2_1_0_7_3],
           '''image_std''': [0.2_6_8_6_2_9_5_4, 0.2_6_1_3_0_2_5_8, 0.2_7_5_7_7_7_1_1],
       }
       _snake_case					     =       os.path.join(self.tmpdirname    ,      _lowerCamelCase			)
       with open(self.image_processor_file    ,      '''w'''    ,      encoding='''utf-8'''			) as fp:
         json.dump(_lowerCamelCase    ,      _lowerCamelCase			)







     def      lowercase	(							self			:			Tuple    ,      **_lowerCamelCase			:			Any			):
       return CLIPTokenizer.from_pretrained(self.tmpdirname    ,      **_lowerCamelCase			)







     def      lowercase	(							self			:			str    ,      **_lowerCamelCase			:			Any			):
       return CLIPTokenizerFast.from_pretrained(self.tmpdirname    ,      **_lowerCamelCase			)







     def      lowercase	(							self			:			int    ,      **_lowerCamelCase			:			Optional[int]			):
       return CLIPImageProcessor.from_pretrained(self.tmpdirname    ,      **_lowerCamelCase			)







     def      lowercase	(							self			:			Union[str, Any]			):
       shutil.rmtree(self.tmpdirname			)







     def      lowercase	(							self			:			Any			):
       _snake_case					     =       [np.random.randint(255    ,      size=(3, 30, 400)    ,      dtype=np.uinta			)]

       _snake_case					     =       [Image.fromarray(np.moveaxis(_lowerCamelCase    ,      0    ,      -1			)			) for x in image_inputs]

       return image_inputs







     def      lowercase	(							self			:			Optional[Any]			):
       _snake_case					     =       self.get_tokenizer()
       _snake_case					     =       self.get_rust_tokenizer()
       _snake_case					     =       self.get_image_processor()

       _snake_case					     =       CLIPProcessor(tokenizer=_lowerCamelCase    ,      image_processor=_lowerCamelCase			)
       processor_slow.save_pretrained(self.tmpdirname			)
       _snake_case					     =       CLIPProcessor.from_pretrained(self.tmpdirname    ,      use_fast=_lowerCamelCase			)

       _snake_case					     =       CLIPProcessor(tokenizer=_lowerCamelCase    ,      image_processor=_lowerCamelCase			)
       processor_fast.save_pretrained(self.tmpdirname			)
       _snake_case					     =       CLIPProcessor.from_pretrained(self.tmpdirname			)

       self.assertEqual(processor_slow.tokenizer.get_vocab()    ,      tokenizer_slow.get_vocab()			)
       self.assertEqual(processor_fast.tokenizer.get_vocab()    ,      tokenizer_fast.get_vocab()			)
       self.assertEqual(tokenizer_slow.get_vocab()    ,      tokenizer_fast.get_vocab()			)
       self.assertIsInstance(processor_slow.tokenizer    ,      _lowerCamelCase			)
       self.assertIsInstance(processor_fast.tokenizer    ,      _lowerCamelCase			)

       self.assertEqual(processor_slow.image_processor.to_json_string()    ,      image_processor.to_json_string()			)
       self.assertEqual(processor_fast.image_processor.to_json_string()    ,      image_processor.to_json_string()			)
       self.assertIsInstance(processor_slow.image_processor    ,      _lowerCamelCase			)
       self.assertIsInstance(processor_fast.image_processor    ,      _lowerCamelCase			)







     def      lowercase	(							self			:			List[Any]			):
       _snake_case					     =       CLIPProcessor(tokenizer=self.get_tokenizer()    ,      image_processor=self.get_image_processor()			)
       processor.save_pretrained(self.tmpdirname			)

       _snake_case					     =       self.get_tokenizer(bos_token='''(BOS)'''    ,      eos_token='''(EOS)'''			)
       _snake_case					     =       self.get_image_processor(do_normalize=_lowerCamelCase    ,      padding_value=1.0			)

       _snake_case					     =       CLIPProcessor.from_pretrained(
           self.tmpdirname    ,      bos_token='''(BOS)'''    ,      eos_token='''(EOS)'''    ,      do_normalize=_lowerCamelCase    ,      padding_value=1.0			)

       self.assertEqual(processor.tokenizer.get_vocab()    ,      tokenizer_add_kwargs.get_vocab()			)
       self.assertIsInstance(processor.tokenizer    ,      _lowerCamelCase			)

       self.assertEqual(processor.image_processor.to_json_string()    ,      image_processor_add_kwargs.to_json_string()			)
       self.assertIsInstance(processor.image_processor    ,      _lowerCamelCase			)







     def      lowercase	(							self			:			int			):
       _snake_case					     =       self.get_image_processor()
       _snake_case					     =       self.get_tokenizer()

       _snake_case					     =       CLIPProcessor(tokenizer=_lowerCamelCase    ,      image_processor=_lowerCamelCase			)

       _snake_case					     =       self.prepare_image_inputs()

       _snake_case					     =       image_processor(_lowerCamelCase    ,      return_tensors='''np'''			)
       _snake_case					     =       processor(images=_lowerCamelCase    ,      return_tensors='''np'''			)

       for key in input_image_proc.keys():
         self.assertAlmostEqual(input_image_proc[key].sum()    ,      input_processor[key].sum()    ,      delta=1e-2			)







     def      lowercase	(							self			:			Any			):
       _snake_case					     =       self.get_image_processor()
       _snake_case					     =       self.get_tokenizer()

       _snake_case					     =       CLIPProcessor(tokenizer=_lowerCamelCase    ,      image_processor=_lowerCamelCase			)

       _snake_case					     =       '''lower newer'''

       _snake_case					     =       processor(text=_lowerCamelCase			)

       _snake_case					     =       tokenizer(_lowerCamelCase			)

       for key in encoded_tok.keys():
         self.assertListEqual(encoded_tok[key]    ,      encoded_processor[key]			)







     def      lowercase	(							self			:			Any			):
       _snake_case					     =       self.get_image_processor()
       _snake_case					     =       self.get_tokenizer()

       _snake_case					     =       CLIPProcessor(tokenizer=_lowerCamelCase    ,      image_processor=_lowerCamelCase			)

       _snake_case					     =       '''lower newer'''
       _snake_case					     =       self.prepare_image_inputs()

       _snake_case					     =       processor(text=_lowerCamelCase    ,      images=_lowerCamelCase			)

       self.assertListEqual(list(inputs.keys()			)    ,      ['''input_ids''', '''attention_mask''', '''pixel_values''']			)

       # test if it raises when no input is passed
       with pytest.raises(_lowerCamelCase			):
         processor()







     def      lowercase	(							self			:			List[str]			):
       _snake_case					     =       self.get_image_processor()
       _snake_case					     =       self.get_tokenizer()

       _snake_case					     =       CLIPProcessor(tokenizer=_lowerCamelCase    ,      image_processor=_lowerCamelCase			)

       _snake_case					     =       [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

       _snake_case					     =       processor.batch_decode(_lowerCamelCase			)
       _snake_case					     =       tokenizer.batch_decode(_lowerCamelCase			)

       self.assertListEqual(_lowerCamelCase    ,      _lowerCamelCase			)







     def      lowercase	(							self			:			List[Any]			):
       _snake_case					     =       self.get_image_processor()
       _snake_case					     =       self.get_tokenizer()

       _snake_case					     =       CLIPProcessor(tokenizer=_lowerCamelCase    ,      image_processor=_lowerCamelCase			)

       _snake_case					     =       '''lower newer'''
       _snake_case					     =       self.prepare_image_inputs()

       _snake_case					     =       processor(text=_lowerCamelCase    ,      images=_lowerCamelCase			)

       self.assertListEqual(list(inputs.keys()			)    ,      processor.model_input_names			)



