






"""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  __lowerCamelCase					(					lowerCAmelCase__				):
    assert "mock" in _fsspec_registry
    assert "bz2" in _fsspec_registry



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



def  __lowerCamelCase					(					):
    A__							 =       'mock-s3-bucket'
    A__							 =       f'''s3://{mock_bucket}'''
    A__							 =       extract_path_from_uri(lowerCAmelCase__				)
    assert dataset_path.startswith('s3://'				) is False

    A__							 =       './local/path'
    A__							 =       extract_path_from_uri(lowerCAmelCase__				)
    assert dataset_path == new_dataset_path



def  __lowerCamelCase					(					lowerCAmelCase__				):
    A__							 =       is_remote_filesystem(lowerCAmelCase__				)
    assert is_remote is True

    A__							 =       fsspec.filesystem('file'				)

    A__							 =       is_remote_filesystem(lowerCAmelCase__				)
    assert is_remote is False



@pytest.mark.parametrize('compression_fs_class'       ,lowerCAmelCase__				)
def  __lowerCamelCase					(					lowerCAmelCase__       ,lowerCAmelCase__       ,lowerCAmelCase__       ,lowerCAmelCase__       ,lowerCAmelCase__       ,lowerCAmelCase__       ,lowerCAmelCase__				):
    A__							 =       {'gzip': gz_file, 'xz': xz_file, 'zstd': zstd_file, 'bz2': bza_file, 'lz4': lza_file}
    A__							 =       input_paths[compression_fs_class.protocol]
    if input_path is None:
        A__							 =       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__				)
    A__							 =       fsspec.filesystem(compression_fs_class.protocol       ,fo=lowerCAmelCase__				)
    assert isinstance(lowerCAmelCase__       ,lowerCAmelCase__				)
    A__							 =       os.path.basename(lowerCAmelCase__				)
    A__							 =       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  __lowerCamelCase					(					lowerCAmelCase__       ,lowerCAmelCase__       ,lowerCAmelCase__				):
    A__							 =       {'zip': zip_jsonl_path, 'gzip': jsonl_gz_path}
    A__							 =       compressed_file_paths[protocol]
    A__							 =       'dataset.jsonl'
    A__							 =       f'''{protocol}://{member_file_path}::{compressed_file_path}'''
    A__ ,			*A__							 =       fsspec.get_fs_token_paths(lowerCAmelCase__				)
    assert fs.isfile(lowerCAmelCase__				)
    assert not fs.isfile('non_existing_' + member_file_path				)



@pytest.mark.integration
def  __lowerCamelCase					(					lowerCAmelCase__       ,lowerCAmelCase__       ,lowerCAmelCase__       ,lowerCAmelCase__				):
    A__							 =       hf_api.dataset_info(lowerCAmelCase__       ,token=lowerCAmelCase__				)
    A__							 =       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  __lowerCamelCase					(					):
    A__							 =       '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 torch

from transformers import AutoModel





class       snake_case_       (    torch.nn.Module       ):



	"""simple docstring"""

	def __init__(      self  ,					__a="sayef/fsner-bert-base-uncased"						):


					"""simple docstring"""

					super(__a  ,					self						).__init__()

					A__							 =       AutoModel.from_pretrained(__a  ,					return_dict=__a						)
					A__							 =       torch.nn.CosineSimilarity(3  ,					1E-08						)
					A__							 =       torch.nn.Softmax(dim=1						)


	def       _UpperCAmelCase						(      self  ,					**__a						):


					"""simple docstring"""

					return self.bert(**__a						).last_hidden_state


	def       _UpperCAmelCase						(      self  ,					__a						):


					"""simple docstring"""

					return token_embeddings.sum(2  ,					keepdim=__a						)


	def       _UpperCAmelCase						(      self  ,					__a  ,					__a  ,					__a=1						):


					"""simple docstring"""

					return self.softmax(T * self.cos(__a  ,					__a						)						)






	def       _UpperCAmelCase						(      self  ,					__a  ,					__a						):


					"""simple docstring"""

					A__							 =       W_supports['sizes'].tolist()
					A__							 =       W_supports['start_token_id'].item()
					A__							 =       W_supports['end_token_id'].item()

					del W_supports["sizes"]
					del W_supports["start_token_id"]
					del W_supports["end_token_id"]

					A__							 =       self.BERT(**__a						)
					A__							 =       self.BERT(**__a						)

					A__							 =       None
					A__							 =       None

					A__							 =       W_supports['input_ids'] == start_token_id
					A__							 =       W_supports['input_ids'] == end_token_id

					for i, size in enumerate(__a						):
									if i == 0:
													A__							 =       0
									else:
													A__							 =       support_sizes[i - 1]

									A__							 =       S[s : s + size][start_token_masks[s : s + size]]
									A__							 =       S[s : s + size][end_token_masks[s : s + size]]

									A__							 =       torch.matmul(q[i]  ,					s_start.T						).sum(1						).softmax(0						)
									A__							 =       torch.matmul(q[i]  ,					s_end.T						).sum(1						).softmax(0						)

									if p_starts is not None:
													A__							 =       torch.vstack((p_starts, p_start)						)
													A__							 =       torch.vstack((p_ends, p_end)						)
									else:
													A__							 =       p_start
													A__							 =       p_end

					return p_starts, p_ends


