

'''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 	_a       (				__lowerCAmelCase		:      List[str]     ):

		"""simple docstring"""

		assert "mock" in _fsspec_registry
		assert "bz2" in _fsspec_registry




def 	_a       (				):

		"""simple docstring"""

		assert "mock" not in _fsspec_registry
		assert "bz2" in _fsspec_registry




def 	_a       (				):

		"""simple docstring"""

		snake_case__						:       Optional[Any]       						=  '''mock-s3-bucket'''
		snake_case__						:       List[Any]       						=  F"""s3://{mock_bucket}"""
		snake_case__						:       List[Any]       						=  extract_path_from_uri(__lowerCAmelCase     )
		assert dataset_path.startswith('''s3://'''     ) is False

		snake_case__						:       Optional[Any]       						=  '''./local/path'''
		snake_case__						:       Tuple       						=  extract_path_from_uri(__lowerCAmelCase     )
		assert dataset_path == new_dataset_path




def 	_a       (				__lowerCAmelCase		:      int     ):

		"""simple docstring"""

		snake_case__						:       Optional[Any]       						=  is_remote_filesystem(__lowerCAmelCase     )
		assert is_remote is True

		snake_case__						:       Dict       						=  fsspec.filesystem('''file'''     )

		snake_case__						:       List[str]       						=  is_remote_filesystem(__lowerCAmelCase     )
		assert is_remote is False




@pytest.mark.parametrize('''compression_fs_class'''   ,							__lowerCAmelCase     )
def 	_a       (				__lowerCAmelCase		:      Optional[int]   ,							__lowerCAmelCase		:      Tuple   ,							__lowerCAmelCase		:      Dict   ,							__lowerCAmelCase		:      Dict   ,							__lowerCAmelCase		:      Union[str, Any]   ,							__lowerCAmelCase		:      Optional[int]   ,							__lowerCAmelCase		:      Tuple     ):

		"""simple docstring"""

		snake_case__						:       List[Any]       						=  {'''gzip''': gz_file, '''xz''': xz_file, '''zstd''': zstd_file, '''bz2''': bza_file, '''lz4''': lza_file}
		snake_case__						:       int       						=  input_paths[compression_fs_class.protocol]
		if input_path is None:
				snake_case__						:       Union[str, Any]       						=  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(__lowerCAmelCase     )
		snake_case__						:       Optional[int]       						=  fsspec.filesystem(compression_fs_class.protocol   ,							fo=__lowerCAmelCase     )
		assert isinstance(__lowerCAmelCase   ,							__lowerCAmelCase     )
		snake_case__						:       Tuple       						=  os.path.basename(__lowerCAmelCase     )
		snake_case__						:       str       						=  expected_filename[: expected_filename.rindex('''.'''     )]
		assert fs.glob('''*'''     ) == [expected_filename]
		with fs.open(__lowerCAmelCase   ,							'''r'''   ,							encoding='''utf-8'''     ) as f, open(__lowerCAmelCase   ,							encoding='''utf-8'''     ) as expected_file:
				assert f.read() == expected_file.read()




@pytest.mark.parametrize('''protocol'''   ,							['''zip''', '''gzip''']     )
def 	_a       (				__lowerCAmelCase		:      Union[str, Any]   ,							__lowerCAmelCase		:      Optional[int]   ,							__lowerCAmelCase		:      int     ):

		"""simple docstring"""

		snake_case__						:       Tuple       						=  {'''zip''': zip_jsonl_path, '''gzip''': jsonl_gz_path}
		snake_case__						:       Any       						=  compressed_file_paths[protocol]
		snake_case__						:       str       						=  '''dataset.jsonl'''
		snake_case__						:       List[str]       						=  F"""{protocol}://{member_file_path}::{compressed_file_path}"""
		snake_case__						,       *snake_case__						:       List[Any]       						=  fsspec.get_fs_token_paths(__lowerCAmelCase     )
		assert fs.isfile(__lowerCAmelCase     )
		assert not fs.isfile('''non_existing_''' + member_file_path     )




@pytest.mark.integration
def 	_a       (				__lowerCAmelCase		:      Dict   ,							__lowerCAmelCase		:      Dict   ,							__lowerCAmelCase		:      int   ,							__lowerCAmelCase		:      Optional[int]     ):

		"""simple docstring"""

		snake_case__						:       Any       						=  hf_api.dataset_info(__lowerCAmelCase   ,							token=__lowerCAmelCase     )
		snake_case__						:       Optional[int]       						=  HfFileSystem(repo_info=__lowerCAmelCase   ,							token=__lowerCAmelCase     )
		assert sorted(hffs.glob('''*'''     )     ) == [".gitattributes", "data"]
		assert hffs.isdir('''data'''     )
		assert hffs.isfile('''.gitattributes'''     ) and hffs.isfile('''data/text_data.txt'''     )
		with open(__lowerCAmelCase     ) as f:
				assert hffs.open('''data/text_data.txt'''   ,							'''r'''     ).read() == f.read()





def 	_a       (				):

		"""simple docstring"""

		snake_case__						:       Optional[Any]       						=  '''bz2'''

		# Import module
		import datasets.filesystems

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

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






'''simple docstring'''


import argparse

from transformers import BigBirdConfig, BigBirdForPreTraining, BigBirdForQuestionAnswering, load_tf_weights_in_big_bird
from transformers.utils import logging


logging.set_verbosity_info()




def 	_a       (				__lowerCAmelCase		:      Union[str, Any]   ,							__lowerCAmelCase		:      Any   ,							__lowerCAmelCase		:      Optional[int]   ,							__lowerCAmelCase		:      List[Any]     ):

		"""simple docstring"""

		snake_case__						:       Any       						=  BigBirdConfig.from_json_file(__lowerCAmelCase     )
		print(F"""Building PyTorch model from configuration: {config}"""     )

		if is_trivia_qa:
				snake_case__						:       str       						=  BigBirdForQuestionAnswering(__lowerCAmelCase     )
		else:
				snake_case__						:       Tuple       						=  BigBirdForPreTraining(__lowerCAmelCase     )

		# Load weights from tf checkpoint
		load_tf_weights_in_big_bird(__lowerCAmelCase   ,							__lowerCAmelCase   ,							is_trivia_qa=__lowerCAmelCase     )

		# Save pytorch-model
		print(F"""Save PyTorch model to {pytorch_dump_path}"""     )
		model.save_pretrained(__lowerCAmelCase     )


if __name__ == "__main__":
					lowerCAmelCase__						:       Union[str, Any]										=						argparse.ArgumentParser()
					# Required parameters
					parser.add_argument(
					    """--tf_checkpoint_path""", default=None, type=str, required=True, help="""Path to the TensorFlow checkpoint path."""
					)
					parser.add_argument(
					    """--big_bird_config_file""",
					    default=None,
					    type=str,
					    required=True,
					    help=(
					        """The config json file corresponding to the pre-trained BERT model. \n"""
					        """This specifies the model architecture."""
					    ),
					)
					parser.add_argument(
					    """--pytorch_dump_path""", default=None, type=str, required=True, help="""Path to the output PyTorch model."""
					)
					parser.add_argument(
					    """--is_trivia_qa""", action="""store_true""", help="""Whether to convert a model with a trivia_qa head."""
					)
					lowerCAmelCase__						:       Optional[int]										=						parser.parse_args()
					convert_tf_checkpoint_to_pytorch(
					    args.tf_checkpoint_path, args.big_bird_config_file, args.pytorch_dump_path, args.is_trivia_qa
					)



