


'''simple docstring'''

import importlib
import os

import fsspec
import pytest
from fsspec import register_implementation
from fsspec.registry import _registry as _fsspec_registry

from datasets.filesystems import COMPRESSION_FILESYSTEMS, HfFileSystem, extract_path_from_uri, is_remote_filesystem

from .utils import require_lza, require_zstandard





def __snake_case					(      UpperCAmelCase_						:						int		):
 assert "mock" in _fsspec_registry
 assert "bz2" in _fsspec_registry





def __snake_case					(      ):
 assert "mock" not in _fsspec_registry
 assert "bz2" in _fsspec_registry





def __snake_case					(      ):
 lowerCamelCase_      =  'mock-s3-bucket'
 lowerCamelCase_      =  F'''s3://{mock_bucket}'''
 lowerCamelCase_      =  extract_path_from_uri(__snake_case		)
 assert dataset_path.startswith("s3://"		) is False

 lowerCamelCase_      =  './local/path'
 lowerCamelCase_      =  extract_path_from_uri(__snake_case		)
 assert dataset_path == new_dataset_path





def __snake_case					(      UpperCAmelCase_						:						Union[str, Any]		):
 lowerCamelCase_      =  is_remote_filesystem(__snake_case		)
 assert is_remote is True

 lowerCamelCase_      =  fsspec.filesystem("file"		)

 lowerCamelCase_      =  is_remote_filesystem(__snake_case		)
 assert is_remote is False





@pytest.mark.parametrize("compression_fs_class"					,				__snake_case		)
def __snake_case					(      UpperCAmelCase_						:						Optional[int]					,				UpperCAmelCase_						:						Tuple					,				UpperCAmelCase_						:						Optional[int]					,				UpperCAmelCase_						:						Optional[int]					,				UpperCAmelCase_						:						Dict					,				UpperCAmelCase_						:						Tuple					,				UpperCAmelCase_						:						List[Any]		):
 lowerCamelCase_      =  {'gzip': gz_file, 'xz': xz_file, 'zstd': zstd_file, 'bz2': bza_file, 'lz4': lza_file}
 lowerCamelCase_      =  input_paths[compression_fs_class.protocol]
 if input_path is None:
  lowerCamelCase_      =  F'''for \'{compression_fs_class.protocol}\' compression protocol, '''
  if compression_fs_class.protocol == "lz4":
   reason += require_lza.kwargs["reason"]
  elif compression_fs_class.protocol == "zstd":
   reason += require_zstandard.kwargs["reason"]
  pytest.skip(__snake_case		)
 lowerCamelCase_      =  fsspec.filesystem(compression_fs_class.protocol					,				fo=__snake_case		)
 assert isinstance(__snake_case					,				__snake_case		)
 lowerCamelCase_      =  os.path.basename(__snake_case		)
 lowerCamelCase_      =  expected_filename[: expected_filename.rindex("."		)]
 assert fs.glob("*"		) == [expected_filename]
 with fs.open(__snake_case					,				"r"					,				encoding="utf-8"		) as f, open(__snake_case					,				encoding="utf-8"		) as expected_file:
  assert f.read() == expected_file.read()





@pytest.mark.parametrize("protocol"					,				["zip", "gzip"]		)
def __snake_case					(      UpperCAmelCase_						:						Optional[int]					,				UpperCAmelCase_						:						Optional[int]					,				UpperCAmelCase_						:						Optional[int]		):
 lowerCamelCase_      =  {'zip': zip_jsonl_path, 'gzip': jsonl_gz_path}
 lowerCamelCase_      =  compressed_file_paths[protocol]
 lowerCamelCase_      =  'dataset.jsonl'
 lowerCamelCase_      =  F'''{protocol}://{member_file_path}::{compressed_file_path}'''
 lowerCamelCase_      =  fsspec.get_fs_token_paths(__snake_case		)
 assert fs.isfile(__snake_case		)
 assert not fs.isfile("non_existing_" + member_file_path		)





@pytest.mark.integration
def __snake_case					(      UpperCAmelCase_						:						Tuple					,				UpperCAmelCase_						:						Any					,				UpperCAmelCase_						:						Dict					,				UpperCAmelCase_						:						Tuple		):
 lowerCamelCase_      =  hf_api.dataset_info(__snake_case					,				token=__snake_case		)
 lowerCamelCase_      =  HfFileSystem(repo_info=__snake_case					,				token=__snake_case		)
 assert sorted(hffs.glob("*"		)		) == [".gitattributes", "data"]
 assert hffs.isdir("data"		)
 assert hffs.isfile(".gitattributes"		) and hffs.isfile("data/text_data.txt"		)
 with open(__snake_case		) as f:
  assert hffs.open("data/text_data.txt"					,				"r"		).read() == f.read()







def __snake_case					(      ):
 lowerCamelCase_      =  'bz2'

 # Import module
 import datasets.filesystems

 # Overwrite protocol and reload
 register_implementation(__snake_case					,				__snake_case					,				clobber=__snake_case		)
 with pytest.warns(__snake_case		) as warning_info:
  importlib.reload(datasets.filesystems		)

 assert len(__snake_case		) == 1
 assert (
     str(warning_info[0].message		)
     == F'''A filesystem protocol was already set for {protocol} and will be overwritten.'''
 )










'''simple docstring'''




import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available


if is_vision_available():
  from PIL import Image

  from transformers import AutoProcessor, BertTokenizer, BlipImageProcessor, BlipProcessor, PreTrainedTokenizerFast


@require_vision
class  SCREAMING_SNAKE_CASE    (unittest.TestCase							):


     def 							SCREAMING_SNAKE_CASE  (						self):

          '''simple docstring'''






          __A						: Dict      =       tempfile.mkdtemp()

          __A						: Optional[int]      =       BlipImageProcessor()
          __A						: List[str]      =       BertTokenizer.from_pretrained('hf-internal-testing/tiny-random-BertModel')

          __A						: Any      =       BlipProcessor(_UpperCAmelCase						,	_UpperCAmelCase)

          processor.save_pretrained(self.tmpdirname)


     def 							SCREAMING_SNAKE_CASE  (						self						,	**_UpperCAmelCase):

          '''simple docstring'''






          return AutoProcessor.from_pretrained(self.tmpdirname						,	**_UpperCAmelCase).tokenizer


     def 							SCREAMING_SNAKE_CASE  (						self						,	**_UpperCAmelCase):

          '''simple docstring'''






          return AutoProcessor.from_pretrained(self.tmpdirname						,	**_UpperCAmelCase).image_processor


     def 							SCREAMING_SNAKE_CASE  (						self):

          '''simple docstring'''






          shutil.rmtree(self.tmpdirname)


     def 							SCREAMING_SNAKE_CASE  (						self):

          '''simple docstring'''






          __A						: int      =       [np.random.randint(255						,	size=(3, 30, 400)						,	dtype=np.uinta)]

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

          return image_inputs


     def 							SCREAMING_SNAKE_CASE  (						self):

          '''simple docstring'''






          __A						: int      =       BlipProcessor(tokenizer=self.get_tokenizer()						,	image_processor=self.get_image_processor())
          processor.save_pretrained(self.tmpdirname)

          __A						: int      =       self.get_tokenizer(bos_token='(BOS)'						,	eos_token='(EOS)')
          __A						: List[Any]      =       self.get_image_processor(do_normalize=_UpperCAmelCase						,	padding_value=1.0)

          __A						: Tuple      =       BlipProcessor.from_pretrained(
              self.tmpdirname						,	bos_token='(BOS)'						,	eos_token='(EOS)'						,	do_normalize=_UpperCAmelCase						,	padding_value=1.0)

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

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


     def 							SCREAMING_SNAKE_CASE  (						self):

          '''simple docstring'''






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

          __A						: int      =       BlipProcessor(tokenizer=_UpperCAmelCase						,	image_processor=_UpperCAmelCase)

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

          __A						: str      =       image_processor(_UpperCAmelCase						,	return_tensors='np')
          __A						: str      =       processor(images=_UpperCAmelCase						,	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):

          '''simple docstring'''






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

          __A						: Union[str, Any]      =       BlipProcessor(tokenizer=_UpperCAmelCase						,	image_processor=_UpperCAmelCase)

          __A						: str      =       'lower newer'

          __A						: Dict      =       processor(text=_UpperCAmelCase)

          __A						: Tuple      =       tokenizer(_UpperCAmelCase						,	return_token_type_ids=_UpperCAmelCase)

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


     def 							SCREAMING_SNAKE_CASE  (						self):

          '''simple docstring'''






          __A						: List[Any]      =       self.get_image_processor()
          __A						: Optional[Any]      =       self.get_tokenizer()

          __A						: Optional[Any]      =       BlipProcessor(tokenizer=_UpperCAmelCase						,	image_processor=_UpperCAmelCase)

          __A						: Dict      =       'lower newer'
          __A						: int      =       self.prepare_image_inputs()

          __A						: List[Any]      =       processor(text=_UpperCAmelCase						,	images=_UpperCAmelCase)

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

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


     def 							SCREAMING_SNAKE_CASE  (						self):

          '''simple docstring'''






          __A						: Union[str, Any]      =       self.get_image_processor()
          __A						: Optional[Any]      =       self.get_tokenizer()

          __A						: Union[str, Any]      =       BlipProcessor(tokenizer=_UpperCAmelCase						,	image_processor=_UpperCAmelCase)

          __A						: Tuple      =       [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

          __A						: List[str]      =       processor.batch_decode(_UpperCAmelCase)
          __A						: List[str]      =       tokenizer.batch_decode(_UpperCAmelCase)

          self.assertListEqual(_UpperCAmelCase						,	_UpperCAmelCase)


     def 							SCREAMING_SNAKE_CASE  (						self):

          '''simple docstring'''






          __A						: Any      =       self.get_image_processor()
          __A						: Union[str, Any]      =       self.get_tokenizer()

          __A						: Optional[Any]      =       BlipProcessor(tokenizer=_UpperCAmelCase						,	image_processor=_UpperCAmelCase)

          __A						: str      =       'lower newer'
          __A						: str      =       self.prepare_image_inputs()

          __A						: Optional[int]      =       processor(text=_UpperCAmelCase						,	images=_UpperCAmelCase)

          # For now the processor supports only ['pixel_values', 'input_ids', 'attention_mask']
          self.assertListEqual(list(inputs.keys())						,	['pixel_values', 'input_ids', 'attention_mask'])