



"""simple docstring"""






import json
import os
import shutil
import tempfile
import unittest

import numpy as np

from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES, BertTokenizer
from transformers.testing_utils import require_tokenizers, require_vision
from transformers.utils import IMAGE_PROCESSOR_NAME, is_vision_available


if is_vision_available():
	from PIL import Image

	from transformers import VisionTextDualEncoderProcessor, ViTImageProcessor



@require_tokenizers
@require_vision
class      A__  (    unittest.TestCase				):




	'''simple docstring'''





	def 				_SCREAMING_SNAKE_CASE  (	self:						Union[str, Any])							->			str:

				"""simple docstring"""

				__lowerCAmelCase :    Optional[Any]				=			tempfile.mkdtemp()

				# fmt: off
				__lowerCAmelCase :    Tuple				=			["[UNK]", "[CLS]", "[SEP]", "[PAD]", "[MASK]", "want", "##want", "##ed", "wa", "un", "runn", "##ing", ",", "low", "lowest"]
				# fmt: on
				__lowerCAmelCase :    Dict				=			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]))

				__lowerCAmelCase :    Dict				=			{
				    "do_resize": True,
				    "size": {"height": 18, "width": 18},
				    "do_normalize": True,
				    "image_mean": [0.5, 0.5, 0.5],
				    "image_std": [0.5, 0.5, 0.5],
				}
				__lowerCAmelCase :    int				=			os.path.join(self.tmpdirname			,     _SCREAMING_SNAKE_CASE)
				with open(self.image_processor_file			,     "w"			,     encoding="utf-8") as fp:
							json.dump(_SCREAMING_SNAKE_CASE			,     _SCREAMING_SNAKE_CASE)

	def 				_SCREAMING_SNAKE_CASE  (	self:						List[str]			,     **_SCREAMING_SNAKE_CASE:						List[str])							->			Dict:

				"""simple docstring"""

				return BertTokenizer.from_pretrained(self.tmpdirname			,     **_SCREAMING_SNAKE_CASE)

	def 				_SCREAMING_SNAKE_CASE  (	self:						Dict			,     **_SCREAMING_SNAKE_CASE:						List[Any])							->			Optional[Any]:

				"""simple docstring"""

				return ViTImageProcessor.from_pretrained(self.tmpdirname			,     **_SCREAMING_SNAKE_CASE)

	def 				_SCREAMING_SNAKE_CASE  (	self:						Any)							->			Dict:

				"""simple docstring"""

				shutil.rmtree(self.tmpdirname)

	def 				_SCREAMING_SNAKE_CASE  (	self:						Optional[int])							->			Dict:

				"""simple docstring"""

				__lowerCAmelCase :    List[str]				=			[np.random.randint(255			,     size=(3, 30, 400)			,     dtype=np.uinta)]

				__lowerCAmelCase :    str				=			[Image.fromarray(np.moveaxis(_SCREAMING_SNAKE_CASE			,     0			,     -1)) for x in image_inputs]

				return image_inputs

	def 				_SCREAMING_SNAKE_CASE  (	self:						str)							->			Dict:

				"""simple docstring"""

				__lowerCAmelCase :    Tuple				=			self.get_tokenizer()
				__lowerCAmelCase :    Any				=			self.get_image_processor()

				__lowerCAmelCase :    str				=			VisionTextDualEncoderProcessor(tokenizer=_SCREAMING_SNAKE_CASE			,     image_processor=_SCREAMING_SNAKE_CASE)

				processor.save_pretrained(self.tmpdirname)
				__lowerCAmelCase :    List[Any]				=			VisionTextDualEncoderProcessor.from_pretrained(self.tmpdirname)

				self.assertEqual(processor.tokenizer.get_vocab()			,     tokenizer.get_vocab())
				self.assertIsInstance(processor.tokenizer			,     (BertTokenizer, BertTokenizerFast))

				self.assertEqual(processor.image_processor.to_json_string()			,     image_processor.to_json_string())
				self.assertIsInstance(processor.image_processor			,     _SCREAMING_SNAKE_CASE)

	def 				_SCREAMING_SNAKE_CASE  (	self:						Optional[int])							->			str:

				"""simple docstring"""

				__lowerCAmelCase :    Optional[int]				=			VisionTextDualEncoderProcessor(
				    tokenizer=self.get_tokenizer()			,     image_processor=self.get_image_processor())
				processor.save_pretrained(self.tmpdirname)

				__lowerCAmelCase :    int				=			self.get_tokenizer(bos_token="(BOS)"			,     eos_token="(EOS)")
				__lowerCAmelCase :    List[Any]				=			self.get_image_processor(do_normalize=_SCREAMING_SNAKE_CASE			,     padding_value=1.0)

				__lowerCAmelCase :    int				=			VisionTextDualEncoderProcessor.from_pretrained(
				    self.tmpdirname			,     bos_token="(BOS)"			,     eos_token="(EOS)"			,     do_normalize=_SCREAMING_SNAKE_CASE			,     padding_value=1.0)

				self.assertEqual(processor.tokenizer.get_vocab()			,     tokenizer_add_kwargs.get_vocab())
				self.assertIsInstance(processor.tokenizer			,     (BertTokenizer, BertTokenizerFast))

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

	def 				_SCREAMING_SNAKE_CASE  (	self:						List[str])							->			int:

				"""simple docstring"""

				__lowerCAmelCase :    Tuple				=			self.get_image_processor()
				__lowerCAmelCase :    str				=			self.get_tokenizer()

				__lowerCAmelCase :    Optional[int]				=			VisionTextDualEncoderProcessor(tokenizer=_SCREAMING_SNAKE_CASE			,     image_processor=_SCREAMING_SNAKE_CASE)

				__lowerCAmelCase :    List[str]				=			self.prepare_image_inputs()

				__lowerCAmelCase :    str				=			image_processor(_SCREAMING_SNAKE_CASE			,     return_tensors="np")
				__lowerCAmelCase :    Any				=			processor(images=_SCREAMING_SNAKE_CASE			,     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 				_SCREAMING_SNAKE_CASE  (	self:						List[Any])							->			Optional[Any]:

				"""simple docstring"""

				__lowerCAmelCase :    Dict				=			self.get_image_processor()
				__lowerCAmelCase :    List[str]				=			self.get_tokenizer()

				__lowerCAmelCase :    Optional[int]				=			VisionTextDualEncoderProcessor(tokenizer=_SCREAMING_SNAKE_CASE			,     image_processor=_SCREAMING_SNAKE_CASE)

				__lowerCAmelCase :    Optional[int]				=			"lower newer"

				__lowerCAmelCase :    int				=			processor(text=_SCREAMING_SNAKE_CASE)

				__lowerCAmelCase :    str				=			tokenizer(_SCREAMING_SNAKE_CASE)

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

	def 				_SCREAMING_SNAKE_CASE  (	self:						Union[str, Any])							->			int:

				"""simple docstring"""

				__lowerCAmelCase :    Optional[int]				=			self.get_image_processor()
				__lowerCAmelCase :    List[str]				=			self.get_tokenizer()

				__lowerCAmelCase :    str				=			VisionTextDualEncoderProcessor(tokenizer=_SCREAMING_SNAKE_CASE			,     image_processor=_SCREAMING_SNAKE_CASE)

				__lowerCAmelCase :    Optional[Any]				=			"lower newer"
				__lowerCAmelCase :    Optional[Any]				=			self.prepare_image_inputs()

				__lowerCAmelCase :    Optional[Any]				=			processor(text=_SCREAMING_SNAKE_CASE			,     images=_SCREAMING_SNAKE_CASE)

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

				# test if it raises when no input is passed
				with self.assertRaises(_SCREAMING_SNAKE_CASE):
							processor()

	def 				_SCREAMING_SNAKE_CASE  (	self:						Tuple)							->			Dict:

				"""simple docstring"""

				__lowerCAmelCase :    Dict				=			self.get_image_processor()
				__lowerCAmelCase :    List[Any]				=			self.get_tokenizer()

				__lowerCAmelCase :    List[str]				=			VisionTextDualEncoderProcessor(tokenizer=_SCREAMING_SNAKE_CASE			,     image_processor=_SCREAMING_SNAKE_CASE)

				__lowerCAmelCase :    List[Any]				=			[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

				__lowerCAmelCase :    List[Any]				=			processor.batch_decode(_SCREAMING_SNAKE_CASE)
				__lowerCAmelCase :    List[str]				=			tokenizer.batch_decode(_SCREAMING_SNAKE_CASE)

				self.assertListEqual(_SCREAMING_SNAKE_CASE			,     _SCREAMING_SNAKE_CASE)







	def 				_SCREAMING_SNAKE_CASE  (	self:						int)							->			Optional[Any]:

				"""simple docstring"""

				__lowerCAmelCase :    Optional[Any]				=			self.get_image_processor()
				__lowerCAmelCase :    str				=			self.get_tokenizer()

				__lowerCAmelCase :    int				=			VisionTextDualEncoderProcessor(tokenizer=_SCREAMING_SNAKE_CASE			,     image_processor=_SCREAMING_SNAKE_CASE)

				__lowerCAmelCase :    List[Any]				=			"lower newer"
				__lowerCAmelCase :    List[Any]				=			self.prepare_image_inputs()

				__lowerCAmelCase :    List[Any]				=			processor(text=_SCREAMING_SNAKE_CASE			,     images=_SCREAMING_SNAKE_CASE)

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




"""simple docstring"""






# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works

from ...utils import deprecate
from ..controlnet.pipeline_flax_controlnet import FlaxStableDiffusionControlNetPipeline  # noqa: F401


deprecate(
    'stable diffusion controlnet',
    '0.22.0',
    'Importing `FlaxStableDiffusionControlNetPipeline` from diffusers.pipelines.stable_diffusion.flax_pipeline_stable_diffusion_controlnet is deprecated. Please import `from diffusers import FlaxStableDiffusionControlNetPipeline` instead.',
    standard_warn=False,
    stacklevel=3,
)