"""simple docstring"""


import json
import os
import random
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert 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 FlavaImageProcessor, FlavaProcessor
  from transformers.models.flava.image_processing_flava import (
      FLAVA_CODEBOOK_MEAN,
      FLAVA_CODEBOOK_STD,
      FLAVA_IMAGE_MEAN,
      FLAVA_IMAGE_STD,
  )
@require_vision
class   UpperCAmelCase_	(				unittest.TestCase   ):
    def 		_lowerCamelCase      (	self			:       int		)						->    List[str]:
       _lowercase							     =       tempfile.mkdtemp()

       # fmt: off
       _lowercase							     =       ["[UNK]", "[CLS]", "[SEP]", "[PAD]", "[MASK]", "want", "##want", "##ed", "wa", "un", "runn", "##ing", ",", "low", "lowest"]
       # fmt: on
       _lowercase							     =       os.path.join(self.tmpdirname   ,						VOCAB_FILES_NAMES["vocab_file"]		)

       with open(self.vocab_file   ,						"w"   ,						encoding="utf-8"		) as fp:
          fp.write("".join([x + "\n" for x in vocab_tokens]		)		)

       _lowercase							     =       {
           "image_mean": FLAVA_IMAGE_MEAN,
           "image_std": FLAVA_IMAGE_STD,
           "do_normalize": True,
           "do_resize": True,
           "size": 2_2_4,
           "do_center_crop": True,
           "crop_size": 2_2_4,
           "input_size_patches": 1_4,
           "total_mask_patches": 7_5,
           "mask_group_max_patches": None,
           "mask_group_min_patches": 1_6,
           "mask_group_min_aspect_ratio": 0.3,
           "mask_group_max_aspect_ratio": None,
           "codebook_do_resize": True,
           "codebook_size": 1_1_2,
           "codebook_do_center_crop": True,
           "codebook_crop_size": 1_1_2,
           "codebook_do_map_pixels": True,
           "codebook_do_normalize": True,
           "codebook_image_mean": FLAVA_CODEBOOK_MEAN,
           "codebook_image_std": FLAVA_CODEBOOK_STD,
       }

       _lowercase							     =       os.path.join(self.tmpdirname   ,						_lowercase		)
       with open(self.image_processor_file   ,						"w"   ,						encoding="utf-8"		) as fp:
          json.dump(_lowercase   ,						_lowercase		)
    def 		_lowerCamelCase      (	self			:       int   ,						**_lowercase			:       Tuple		)						->    Any:
       return BertTokenizer.from_pretrained(self.tmpdirname   ,						**_lowercase		)
    def 		_lowerCamelCase      (	self			:       Tuple   ,						**_lowercase			:       int		)						->    Tuple:
       return BertTokenizerFast.from_pretrained(self.tmpdirname   ,						**_lowercase		)
    def 		_lowerCamelCase      (	self			:       Optional[int]   ,						**_lowercase			:       int		)						->    Dict:
       return FlavaImageProcessor.from_pretrained(self.tmpdirname   ,						**_lowercase		)
    def 		_lowerCamelCase      (	self			:       Optional[Any]		)						->    Union[str, Any]:
       shutil.rmtree(self.tmpdirname		)
    def 		_lowerCamelCase      (	self			:       Dict		)						->    int:
       _lowercase							     =       [np.random.randint(2_5_5   ,						size=(3, 3_0, 4_0_0)   ,						dtype=np.uinta		)]

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

       return image_inputs
    def 		_lowerCamelCase      (	self			:       int		)						->    Any:
       _lowercase							     =       self.get_tokenizer()
       _lowercase							     =       self.get_rust_tokenizer()
       _lowercase							     =       self.get_image_processor()

       _lowercase							     =       FlavaProcessor(tokenizer=_lowercase   ,						image_processor=_lowercase		)
       processor_slow.save_pretrained(self.tmpdirname		)
       _lowercase							     =       FlavaProcessor.from_pretrained(self.tmpdirname   ,						use_fast=_lowercase		)

       _lowercase							     =       FlavaProcessor(tokenizer=_lowercase   ,						image_processor=_lowercase		)
       processor_fast.save_pretrained(self.tmpdirname		)
       _lowercase							     =       FlavaProcessor.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   ,						_lowercase		)
       self.assertIsInstance(processor_fast.tokenizer   ,						_lowercase		)

       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   ,						_lowercase		)
       self.assertIsInstance(processor_fast.image_processor   ,						_lowercase		)
    def 		_lowerCamelCase      (	self			:       Dict		)						->    Optional[int]:
       _lowercase							     =       FlavaProcessor(tokenizer=self.get_tokenizer()   ,						image_processor=self.get_image_processor()		)
       processor.save_pretrained(self.tmpdirname		)

       _lowercase							     =       self.get_tokenizer(bos_token="(BOS)"   ,						eos_token="(EOS)"		)
       _lowercase							     =       self.get_image_processor(do_normalize=_lowercase   ,						padding_value=1.0		)

       _lowercase							     =       FlavaProcessor.from_pretrained(
           self.tmpdirname   ,						bos_token="(BOS)"   ,						eos_token="(EOS)"   ,						do_normalize=_lowercase   ,						padding_value=1.0		)

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

       self.assertEqual(processor.image_processor.to_json_string()   ,						image_processor_add_kwargs.to_json_string()		)
       self.assertIsInstance(processor.image_processor   ,						_lowercase		)
    def 		_lowerCamelCase      (	self			:       Dict		)						->    Dict:
       _lowercase							     =       self.get_image_processor()
       _lowercase							     =       self.get_tokenizer()

       _lowercase							     =       FlavaProcessor(tokenizer=_lowercase   ,						image_processor=_lowercase		)

       _lowercase							     =       self.prepare_image_inputs()

       _lowercase							     =       image_processor(_lowercase   ,						return_tensors="np"		)
       _lowercase							     =       processor(images=_lowercase   ,						return_tensors="np"		)

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

       # With rest of the args
       random.seed(1_2_3_4		)
       _lowercase							     =       image_processor(
           _lowercase   ,						return_image_mask=_lowercase   ,						return_codebook_pixels=_lowercase   ,						return_tensors="np"		)
       random.seed(1_2_3_4		)
       _lowercase							     =       processor(
           images=_lowercase   ,						return_image_mask=_lowercase   ,						return_codebook_pixels=_lowercase   ,						return_tensors="np"		)

       for key in input_feat_extract.keys():
          self.assertAlmostEqual(input_feat_extract[key].sum()   ,						input_processor[key].sum()   ,						delta=1e-2		)
    def 		_lowerCamelCase      (	self			:       List[str]		)						->    int:
       _lowercase							     =       self.get_image_processor()
       _lowercase							     =       self.get_tokenizer()

       _lowercase							     =       FlavaProcessor(tokenizer=_lowercase   ,						image_processor=_lowercase		)

       _lowercase							     =       "lower newer"

       _lowercase							     =       processor(text=_lowercase		)

       _lowercase							     =       tokenizer(_lowercase		)

       for key in encoded_tok.keys():
          self.assertListEqual(encoded_tok[key]   ,						encoded_processor[key]		)
    def 		_lowerCamelCase      (	self			:       Tuple		)						->    Optional[int]:
       _lowercase							     =       self.get_image_processor()
       _lowercase							     =       self.get_tokenizer()

       _lowercase							     =       FlavaProcessor(tokenizer=_lowercase   ,						image_processor=_lowercase		)

       _lowercase							     =       "lower newer"
       _lowercase							     =       self.prepare_image_inputs()

       _lowercase							     =       processor(text=_lowercase   ,						images=_lowercase		)

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

       # add extra args
       _lowercase							     =       processor(text=_lowercase   ,						images=_lowercase   ,						return_codebook_pixels=_lowercase   ,						return_image_mask=_lowercase		)

       self.assertListEqual(
           list(inputs.keys()		)   ,						[
               "input_ids",
               "token_type_ids",
               "attention_mask",
               "pixel_values",
               "codebook_pixel_values",
               "bool_masked_pos",
           ]   ,						)

       # test if it raises when no input is passed
       with pytest.raises(_lowercase		):
          processor()
    def 		_lowerCamelCase      (	self			:       Any		)						->    List[Any]:
       _lowercase							     =       self.get_image_processor()
       _lowercase							     =       self.get_tokenizer()

       _lowercase							     =       FlavaProcessor(tokenizer=_lowercase   ,						image_processor=_lowercase		)

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

       _lowercase							     =       processor.batch_decode(_lowercase		)
       _lowercase							     =       tokenizer.batch_decode(_lowercase		)

       self.assertListEqual(_lowercase   ,						_lowercase		)




    def 		_lowerCamelCase      (	self			:       Union[str, Any]		)						->    List[Any]:
       _lowercase							     =       self.get_image_processor()
       _lowercase							     =       self.get_tokenizer()

       _lowercase							     =       FlavaProcessor(tokenizer=_lowercase   ,						image_processor=_lowercase		)

       _lowercase							     =       "lower newer"
       _lowercase							     =       self.prepare_image_inputs()

       _lowercase							     =       processor(text=_lowercase   ,						images=_lowercase		)

       self.assertListEqual(list(inputs.keys()		)   ,						processor.model_input_names		)
"""simple docstring"""


__UpperCamelCase       :    List[Any]         =		"\n# Diffusers installation\n! pip install diffusers transformers datasets accelerate\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/diffusers.git\n"

__UpperCamelCase       :    Any         =		[{"type": "code", "content": INSTALL_CONTENT}]