

'''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 					_snake_case		(unittest.TestCase):






			def 		UpperCamelCase__							(  self     ):
				UpperCAmelCase_     :      Dict						=  tempfile.mkdtemp()

				# fmt: off
				UpperCAmelCase_     :      List[str]						=  ["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
				UpperCAmelCase_     :      List[str]						=  dict(zip(_snake_case			,range(len(_snake_case     )     )     )     )
				UpperCAmelCase_     :      List[Any]						=  ["#version: 0.2", "l o", "lo w</w>", "e r</w>", ""]
				UpperCAmelCase_     :      Dict						=  {"unk_token": "<unk>"}

				UpperCAmelCase_     :      Optional[int]						=  os.path.join(self.tmpdirname			,VOCAB_FILES_NAMES["vocab_file"]     )
				UpperCAmelCase_     :      str						=  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(_snake_case     ) + "\n"     )
				with open(self.merges_file			,"w"			,encoding="utf-8"     ) as fp:
					fp.write("\n".join(_snake_case     )     )

				UpperCAmelCase_     :      Optional[Any]						=  {
				    "do_resize": True,
				    "size": 20,
				    "do_center_crop": True,
				    "crop_size": 18,
				    "do_normalize": True,
				    "image_mean": [0.48145466, 0.4578275, 0.40821073],
				    "image_std": [0.26862954, 0.26130258, 0.27577711],
				}
				UpperCAmelCase_     :      str						=  os.path.join(self.tmpdirname			,_snake_case     )
				with open(self.image_processor_file			,"w"			,encoding="utf-8"     ) as fp:
					json.dump(_snake_case			,_snake_case     )






			def 		UpperCamelCase__							(  self			,**_snake_case     ):
				return CLIPTokenizer.from_pretrained(self.tmpdirname			,**_snake_case     )






			def 		UpperCamelCase__							(  self			,**_snake_case     ):
				return CLIPTokenizerFast.from_pretrained(self.tmpdirname			,**_snake_case     )






			def 		UpperCamelCase__							(  self			,**_snake_case     ):
				return CLIPImageProcessor.from_pretrained(self.tmpdirname			,**_snake_case     )






			def 		UpperCamelCase__							(  self     ):
				shutil.rmtree(self.tmpdirname     )






			def 		UpperCamelCase__							(  self     ):
				UpperCAmelCase_     :      Optional[Any]						=  [np.random.randint(2_55			,size=(3, 30, 4_00)			,dtype=np.uinta     )]

				UpperCAmelCase_     :      Union[str, Any]						=  [Image.fromarray(np.moveaxis(_snake_case			,0			,-1     )     ) for x in image_inputs]

				return image_inputs






			def 		UpperCamelCase__							(  self     ):
				UpperCAmelCase_     :      Tuple						=  self.get_tokenizer()
				UpperCAmelCase_     :      str						=  self.get_rust_tokenizer()
				UpperCAmelCase_     :      List[str]						=  self.get_image_processor()

				UpperCAmelCase_     :      Tuple						=  CLIPProcessor(tokenizer=_snake_case			,image_processor=_snake_case     )
				processor_slow.save_pretrained(self.tmpdirname     )
				UpperCAmelCase_     :      int						=  CLIPProcessor.from_pretrained(self.tmpdirname			,use_fast=_snake_case     )

				UpperCAmelCase_     :      str						=  CLIPProcessor(tokenizer=_snake_case			,image_processor=_snake_case     )
				processor_fast.save_pretrained(self.tmpdirname     )
				UpperCAmelCase_     :      str						=  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			,_snake_case     )
				self.assertIsInstance(processor_fast.tokenizer			,_snake_case     )

				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			,_snake_case     )
				self.assertIsInstance(processor_fast.image_processor			,_snake_case     )






			def 		UpperCamelCase__							(  self     ):
				UpperCAmelCase_     :      List[str]						=  CLIPProcessor(tokenizer=self.get_tokenizer()			,image_processor=self.get_image_processor()     )
				processor.save_pretrained(self.tmpdirname     )

				UpperCAmelCase_     :      Union[str, Any]						=  self.get_tokenizer(bos_token="(BOS)"			,eos_token="(EOS)"     )
				UpperCAmelCase_     :      Tuple						=  self.get_image_processor(do_normalize=_snake_case			,padding_value=1.0     )

				UpperCAmelCase_     :      int						=  CLIPProcessor.from_pretrained(
				    self.tmpdirname			,bos_token="(BOS)"			,eos_token="(EOS)"			,do_normalize=_snake_case			,padding_value=1.0     )

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

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






			def 		UpperCamelCase__							(  self     ):
				UpperCAmelCase_     :      List[str]						=  self.get_image_processor()
				UpperCAmelCase_     :      Dict						=  self.get_tokenizer()

				UpperCAmelCase_     :      Dict						=  CLIPProcessor(tokenizer=_snake_case			,image_processor=_snake_case     )

				UpperCAmelCase_     :      Any						=  self.prepare_image_inputs()

				UpperCAmelCase_     :      Optional[int]						=  image_processor(_snake_case			,return_tensors="np"     )
				UpperCAmelCase_     :      Any						=  processor(images=_snake_case			,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 		UpperCamelCase__							(  self     ):
				UpperCAmelCase_     :      Optional[Any]						=  self.get_image_processor()
				UpperCAmelCase_     :      Union[str, Any]						=  self.get_tokenizer()

				UpperCAmelCase_     :      Optional[int]						=  CLIPProcessor(tokenizer=_snake_case			,image_processor=_snake_case     )

				UpperCAmelCase_     :      Tuple						=  "lower newer"

				UpperCAmelCase_     :      Any						=  processor(text=_snake_case     )

				UpperCAmelCase_     :      List[Any]						=  tokenizer(_snake_case     )

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






			def 		UpperCamelCase__							(  self     ):
				UpperCAmelCase_     :      str						=  self.get_image_processor()
				UpperCAmelCase_     :      Union[str, Any]						=  self.get_tokenizer()

				UpperCAmelCase_     :      Tuple						=  CLIPProcessor(tokenizer=_snake_case			,image_processor=_snake_case     )

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

				UpperCAmelCase_     :      str						=  processor(text=_snake_case			,images=_snake_case     )

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

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






			def 		UpperCamelCase__							(  self     ):
				UpperCAmelCase_     :      str						=  self.get_image_processor()
				UpperCAmelCase_     :      Dict						=  self.get_tokenizer()

				UpperCAmelCase_     :      Optional[int]						=  CLIPProcessor(tokenizer=_snake_case			,image_processor=_snake_case     )

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

				UpperCAmelCase_     :      int						=  processor.batch_decode(_snake_case     )
				UpperCAmelCase_     :      int						=  tokenizer.batch_decode(_snake_case     )

				self.assertListEqual(_snake_case			,_snake_case     )






			def 		UpperCamelCase__							(  self     ):
				UpperCAmelCase_     :      Dict						=  self.get_image_processor()
				UpperCAmelCase_     :      int						=  self.get_tokenizer()

				UpperCAmelCase_     :      Tuple						=  CLIPProcessor(tokenizer=_snake_case			,image_processor=_snake_case     )

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

				UpperCAmelCase_     :      Dict						=  processor(text=_snake_case			,images=_snake_case     )

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










'''simple docstring'''



from typing import Optional

import pyspark

from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader





class      lowerCAmelCase (			__lowerCAmelCase):


       def __init__( self     ,	__SCREAMING_SNAKE_CASE     ,	__SCREAMING_SNAKE_CASE = None     ,	__SCREAMING_SNAKE_CASE = None     ,	__SCREAMING_SNAKE_CASE = True     ,	__SCREAMING_SNAKE_CASE = None     ,	__SCREAMING_SNAKE_CASE = False     ,	__SCREAMING_SNAKE_CASE = None     ,	__SCREAMING_SNAKE_CASE = True     ,	__SCREAMING_SNAKE_CASE = "arrow"     ,	**__SCREAMING_SNAKE_CASE     ,	)   ->	Union[str, Any]:



            '''simple docstring'''




            super().__init__(
                split=__SCREAMING_SNAKE_CASE     ,	features=__SCREAMING_SNAKE_CASE     ,	cache_dir=__SCREAMING_SNAKE_CASE     ,	keep_in_memory=__SCREAMING_SNAKE_CASE     ,	streaming=__SCREAMING_SNAKE_CASE     ,	**__SCREAMING_SNAKE_CASE     ,	)
            __snake_case            =	load_from_cache_file
            __snake_case            =	file_format
            __snake_case            =	Spark(
                df=__SCREAMING_SNAKE_CASE     ,	features=__SCREAMING_SNAKE_CASE     ,	cache_dir=__SCREAMING_SNAKE_CASE     ,	working_dir=__SCREAMING_SNAKE_CASE     ,	**__SCREAMING_SNAKE_CASE     ,	)




       def    lowerCAmelCase   ( self	)   ->	str:



            '''simple docstring'''




            if self.streaming:
                 return self.builder.as_streaming_dataset(split=self.split	)
            __snake_case            =	None if self._load_from_cache_file else DownloadMode.FORCE_REDOWNLOAD
            self.builder.download_and_prepare(
                download_mode=__SCREAMING_SNAKE_CASE     ,	file_format=self._file_format     ,	)
            return self.builder.as_dataset(split=self.split	)






