






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 CLIPSegProcessor, ViTImageProcessor
@require_vision
class     lowerCamelCase_					(   unittest.TestCase			):







				def       A						(    self  ):
								"""simple docstring"""
								__magic_name__		:Optional[int]   =   tempfile.mkdtemp()

								# fmt: off
								__magic_name__		:int   =   ['''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
								__magic_name__		:Any   =   dict(zip(__lowerCAmelCase							,       range(len(__lowerCAmelCase  )  )  )  )
								__magic_name__		:Tuple   =   ['''#version: 0.2''', '''l o''', '''lo w</w>''', '''e r</w>''', '''''']
								__magic_name__		:int   =   {'''unk_token''': '''<unk>'''}

								__magic_name__		:Optional[int]   =   os.path.join(self.tmpdirname							,       VOCAB_FILES_NAMES['''vocab_file''']  )
								__magic_name__		:Any   =   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  )  )

								__magic_name__		:Any   =   {
								    '''do_resize''': True,
								    '''size''': 2_0,
								    '''do_center_crop''': True,
								    '''crop_size''': 1_8,
								    '''do_normalize''': True,
								    '''image_mean''': [0.48145466, 0.4578275, 0.40821073],
								    '''image_std''': [0.26862954, 0.26130258, 0.27577711],
								}
								__magic_name__		:int   =   os.path.join(self.tmpdirname							,       __lowerCAmelCase  )
								with open(self.image_processor_file							,       '''w'''							,       encoding='''utf-8'''  ) as fp:
												json.dump(__lowerCAmelCase							,       __lowerCAmelCase  )







				def       A						(    self							,       **__lowerCAmelCase  ):
								"""simple docstring"""
								return CLIPTokenizer.from_pretrained(self.tmpdirname							,       **__lowerCAmelCase  )







				def       A						(    self							,       **__lowerCAmelCase  ):
								"""simple docstring"""
								return CLIPTokenizerFast.from_pretrained(self.tmpdirname							,       **__lowerCAmelCase  )







				def       A						(    self							,       **__lowerCAmelCase  ):
								"""simple docstring"""
								return ViTImageProcessor.from_pretrained(self.tmpdirname							,       **__lowerCAmelCase  )







				def       A						(    self  ):
								"""simple docstring"""
								shutil.rmtree(self.tmpdirname  )







				def       A						(    self  ):
								"""simple docstring"""
								__magic_name__		:Any   =   [np.random.randint(2_5_5							,       size=(3, 3_0, 4_0_0)							,       dtype=np.uinta  )]

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

								return image_inputs







				def       A						(    self  ):
								"""simple docstring"""
								__magic_name__		:Tuple   =   self.get_tokenizer()
								__magic_name__		:Union[str, Any]   =   self.get_rust_tokenizer()
								__magic_name__		:Any   =   self.get_image_processor()

								__magic_name__		:Optional[int]   =   CLIPSegProcessor(tokenizer=__lowerCAmelCase							,       image_processor=__lowerCAmelCase  )
								processor_slow.save_pretrained(self.tmpdirname  )
								__magic_name__		:List[Any]   =   CLIPSegProcessor.from_pretrained(self.tmpdirname							,       use_fast=__lowerCAmelCase  )

								__magic_name__		:Tuple   =   CLIPSegProcessor(tokenizer=__lowerCAmelCase							,       image_processor=__lowerCAmelCase  )
								processor_fast.save_pretrained(self.tmpdirname  )
								__magic_name__		:Dict   =   CLIPSegProcessor.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       A						(    self  ):
								"""simple docstring"""
								__magic_name__		:Dict   =   CLIPSegProcessor(tokenizer=self.get_tokenizer()							,       image_processor=self.get_image_processor()  )
								processor.save_pretrained(self.tmpdirname  )

								__magic_name__		:Optional[Any]   =   self.get_tokenizer(bos_token='''(BOS)'''							,       eos_token='''(EOS)'''  )
								__magic_name__		:int   =   self.get_image_processor(do_normalize=__lowerCAmelCase							,       padding_value=1.0  )

								__magic_name__		:Union[str, Any]   =   CLIPSegProcessor.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       A						(    self  ):
								"""simple docstring"""
								__magic_name__		:Dict   =   self.get_image_processor()
								__magic_name__		:Dict   =   self.get_tokenizer()

								__magic_name__		:int   =   CLIPSegProcessor(tokenizer=__lowerCAmelCase							,       image_processor=__lowerCAmelCase  )

								__magic_name__		:List[Any]   =   self.prepare_image_inputs()

								__magic_name__		:str   =   image_processor(__lowerCAmelCase							,       return_tensors='''np'''  )
								__magic_name__		:List[str]   =   processor(images=__lowerCAmelCase							,       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       A						(    self  ):
								"""simple docstring"""
								__magic_name__		:Optional[Any]   =   self.get_image_processor()
								__magic_name__		:int   =   self.get_tokenizer()

								__magic_name__		:List[Any]   =   CLIPSegProcessor(tokenizer=__lowerCAmelCase							,       image_processor=__lowerCAmelCase  )

								__magic_name__		:Optional[int]   =   '''lower newer'''

								__magic_name__		:Dict   =   processor(text=__lowerCAmelCase  )

								__magic_name__		:Optional[Any]   =   tokenizer(__lowerCAmelCase  )

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







				def       A						(    self  ):
								"""simple docstring"""
								__magic_name__		:str   =   self.get_image_processor()
								__magic_name__		:List[str]   =   self.get_tokenizer()

								__magic_name__		:Union[str, Any]   =   CLIPSegProcessor(tokenizer=__lowerCAmelCase							,       image_processor=__lowerCAmelCase  )

								__magic_name__		:List[str]   =   '''lower newer'''
								__magic_name__		:Any   =   self.prepare_image_inputs()

								__magic_name__		:List[Any]   =   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       A						(    self  ):
								"""simple docstring"""
								__magic_name__		:Dict   =   self.get_image_processor()
								__magic_name__		:Optional[int]   =   self.get_tokenizer()

								__magic_name__		:List[str]   =   CLIPSegProcessor(tokenizer=__lowerCAmelCase							,       image_processor=__lowerCAmelCase  )

								__magic_name__		:List[str]   =   self.prepare_image_inputs()
								__magic_name__		:Dict   =   self.prepare_image_inputs()

								__magic_name__		:List[str]   =   processor(images=__lowerCAmelCase							,       visual_prompt=__lowerCAmelCase  )

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

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







				def       A						(    self  ):
								"""simple docstring"""
								__magic_name__		:List[Any]   =   self.get_image_processor()
								__magic_name__		:Tuple   =   self.get_tokenizer()

								__magic_name__		:Optional[Any]   =   CLIPSegProcessor(tokenizer=__lowerCAmelCase							,       image_processor=__lowerCAmelCase  )

								__magic_name__		:Union[str, Any]   =   [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

								__magic_name__		:List[Any]   =   processor.batch_decode(__lowerCAmelCase  )
								__magic_name__		:Tuple   =   tokenizer.batch_decode(__lowerCAmelCase  )

								self.assertListEqual(__lowerCAmelCase							,       __lowerCAmelCase  )














from pathlib import PurePosixPath
from typing import Optional

import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo

from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url
class     lowerCamelCase_					(   lowerCamelCase			):
				a__       							=	''''''
				a__       							=	'''hf-legacy'''  # "hf://"" is reserved for hffs







				def __init__(    self							,       __lowerCAmelCase = None							,       __lowerCAmelCase = None							,       **__lowerCAmelCase							,       ):
								"""simple docstring"""
								super().__init__(self							,       **__lowerCAmelCase  )
								__magic_name__		:List[Any]   =   repo_info
								__magic_name__		:Dict   =   token
								__magic_name__		:Optional[Any]   =   None







				def       A						(    self  ):
								"""simple docstring"""
								if self.dir_cache is None:
												__magic_name__		:Any   =   {}
												for hf_file in self.repo_info.siblings:
																# TODO(QL): add sizes
																__magic_name__		:Optional[int]   =   {
																    '''name''': hf_file.rfilename,
																    '''size''': None,
																    '''type''': '''file''',
																}
																self.dir_cache.update(
																    {
																        str(__lowerCAmelCase  ): {'''name''': str(__lowerCAmelCase  ), '''size''': None, '''type''': '''directory'''}
																        for d in list(PurePosixPath(hf_file.rfilename  ).parents  )[:-1]
																    }  )







				def       A						(    self							,       __lowerCAmelCase							,       __lowerCAmelCase = "rb"							,       **__lowerCAmelCase							,       ):
								"""simple docstring"""
								if not isinstance(self.repo_info							,       __lowerCAmelCase  ):
												raise NotImplementedError(F'''Open is only implemented for dataset repositories, but got {self.repo_info}'''  )
								__magic_name__		:Union[str, Any]   =   hf_hub_url(self.repo_info.id							,       __lowerCAmelCase							,       revision=self.repo_info.sha  )
								return fsspec.open(
								    __lowerCAmelCase							,       mode=__lowerCAmelCase							,       headers=get_authentication_headers_for_url(__lowerCAmelCase							,       use_auth_token=self.token  )							,       client_kwargs={'''trust_env''': True}							,       ).open()







				def       A						(    self							,       __lowerCAmelCase							,       **__lowerCAmelCase  ):
								"""simple docstring"""
								self._get_dirs()
								__magic_name__		:str   =   self._strip_protocol(__lowerCAmelCase  )
								if path in self.dir_cache:
												return self.dir_cache[path]
								else:
												raise FileNotFoundError(__lowerCAmelCase  )







				def       A						(    self							,       __lowerCAmelCase							,       __lowerCAmelCase=False							,       **__lowerCAmelCase  ):
								"""simple docstring"""
								self._get_dirs()
								__magic_name__		:Union[str, Any]   =   PurePosixPath(path.strip('''/'''  )  )
								__magic_name__		:Dict   =   {}
								for p, f in self.dir_cache.items():
												__magic_name__		:int   =   PurePosixPath(p.strip('''/'''  )  )
												__magic_name__		:Tuple   =   p.parent
												if root == path:
																__magic_name__		:Optional[Any]   =   f
								__magic_name__		:List[Any]   =   list(paths.values()  )
								if detail:
												return out
								else:
												return sorted(f['''name'''] for f in out  )






