

"""simple docstring"""


import os
from pathlib import Path
from unittest.mock import patch

import pytest
import zstandard as zstd

from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
    OfflineModeIsEnabled,
    cached_path,
    fsspec_get,
    fsspec_head,
    ftp_get,
    ftp_head,
    get_from_cache,
    http_get,
    http_head,
)


a					:str    = "\\n    Text data.\n    Second line of data."

a					:List[Any]    = "file"




@pytest.fixture(scope="""session"""							)
def  _lowercase					(    __lowerCAmelCase							)       ->				Tuple:
      SCREAMING_SNAKE_CASE__   :      Optional[Any]      		=	tmp_path_factory.mktemp("""data"""							) / (FILE_PATH + """.zstd""")
      SCREAMING_SNAKE_CASE__   :      Optional[Any]      		=	bytes(__lowerCAmelCase  ,					"""utf-8"""							)
      with zstd.open(__lowerCAmelCase  ,					"""wb"""							) as f:
            f.write(__lowerCAmelCase							)
      return path




@pytest.fixture
def  _lowercase					(    __lowerCAmelCase							)       ->				int:
      with open(os.path.join(tmpfs.local_root_dir  ,					__lowerCAmelCase							)  ,					"""w"""							) as f:
            f.write(__lowerCAmelCase							)
      return FILE_PATH




@pytest.mark.parametrize("""compression_format"""  ,					["""gzip""", """xz""", """zstd"""]							)
def  _lowercase					(    __lowerCAmelCase  ,					__lowerCAmelCase  ,					__lowerCAmelCase  ,					__lowerCAmelCase  ,					__lowerCAmelCase  ,					__lowerCAmelCase							)       ->				List[str]:
      SCREAMING_SNAKE_CASE__   :      Dict      		=	{"""gzip""": gz_file, """xz""": xz_file, """zstd""": zstd_path}
      SCREAMING_SNAKE_CASE__   :      Dict      		=	input_paths[compression_format]
      SCREAMING_SNAKE_CASE__   :      Dict      		=	tmp_path / """cache"""
      SCREAMING_SNAKE_CASE__   :      Any      		=	DownloadConfig(cache_dir=__lowerCAmelCase  ,					extract_compressed_file=__lowerCAmelCase							)
      SCREAMING_SNAKE_CASE__   :      Union[str, Any]      		=	cached_path(__lowerCAmelCase  ,					download_config=__lowerCAmelCase							)
      with open(__lowerCAmelCase							) as f:
            SCREAMING_SNAKE_CASE__   :      Optional[int]      		=	f.read()
      with open(__lowerCAmelCase							) as f:
            SCREAMING_SNAKE_CASE__   :      Dict      		=	f.read()
      assert extracted_file_content == expected_file_content




@pytest.mark.parametrize("""default_extracted"""  ,					[True, False]							)
@pytest.mark.parametrize("""default_cache_dir"""  ,					[True, False]							)
def  _lowercase					(    __lowerCAmelCase  ,					__lowerCAmelCase  ,					__lowerCAmelCase  ,					__lowerCAmelCase  ,					__lowerCAmelCase							)       ->				Union[str, Any]:
      SCREAMING_SNAKE_CASE__   :      Union[str, Any]      		=	"""custom_cache"""
      SCREAMING_SNAKE_CASE__   :      Dict      		=	"""custom_extracted_dir"""
      SCREAMING_SNAKE_CASE__   :      List[Any]      		=	tmp_path / """custom_extracted_path"""
      if default_extracted:
            SCREAMING_SNAKE_CASE__   :      List[Any]      		=	("""downloads""" if default_cache_dir else custom_cache_dir, """extracted""")
      else:
            monkeypatch.setattr("""datasets.config.EXTRACTED_DATASETS_DIR"""  ,					__lowerCAmelCase							)
            monkeypatch.setattr("""datasets.config.EXTRACTED_DATASETS_PATH"""  ,					str(__lowerCAmelCase							)							)
            SCREAMING_SNAKE_CASE__   :      List[str]      		=	custom_extracted_path.parts[-2:] if default_cache_dir else (custom_cache_dir, custom_extracted_dir)

      SCREAMING_SNAKE_CASE__   :      Optional[int]      		=	xz_file
      SCREAMING_SNAKE_CASE__   :      str      		=	(
          DownloadConfig(extract_compressed_file=__lowerCAmelCase							)
          if default_cache_dir
          else DownloadConfig(cache_dir=tmp_path / custom_cache_dir  ,					extract_compressed_file=__lowerCAmelCase							)
      )
      SCREAMING_SNAKE_CASE__   :      List[str]      		=	cached_path(__lowerCAmelCase  ,					download_config=__lowerCAmelCase							)
      assert Path(__lowerCAmelCase							).parent.parts[-2:] == expected




def  _lowercase					(    __lowerCAmelCase							)       ->				Any:
      # absolute path
      SCREAMING_SNAKE_CASE__   :      Optional[int]      		=	str(Path(__lowerCAmelCase							).resolve()							)
      assert cached_path(__lowerCAmelCase							) == text_file
      # relative path
      SCREAMING_SNAKE_CASE__   :      List[str]      		=	str(Path(__lowerCAmelCase							).resolve().relative_to(Path(os.getcwd()							)							)							)
      assert cached_path(__lowerCAmelCase							) == text_file




def  _lowercase					(    __lowerCAmelCase							)       ->				Union[str, Any]:
      # absolute path
      SCREAMING_SNAKE_CASE__   :      Optional[Any]      		=	str(tmp_path.resolve() / """__missing_file__.txt"""							)
      with pytest.raises(__lowerCAmelCase							):
            cached_path(__lowerCAmelCase							)
      # relative path
      SCREAMING_SNAKE_CASE__   :      Union[str, Any]      		=	"""./__missing_file__.txt"""
      with pytest.raises(__lowerCAmelCase							):
            cached_path(__lowerCAmelCase							)




def  _lowercase					(    __lowerCAmelCase							)       ->				Any:
      SCREAMING_SNAKE_CASE__   :      Union[str, Any]      		=	get_from_cache(F'''tmp://{tmpfs_file}'''							)
      with open(__lowerCAmelCase							) as f:
            SCREAMING_SNAKE_CASE__   :      Optional[int]      		=	f.read()
      assert output_file_content == FILE_CONTENT




@patch("""datasets.config.HF_DATASETS_OFFLINE"""  ,					__lowerCAmelCase							)
def  _lowercase					(    )       ->				List[Any]:
      with pytest.raises(__lowerCAmelCase							):
            cached_path("""https://huggingface.co"""							)




@patch("""datasets.config.HF_DATASETS_OFFLINE"""  ,					__lowerCAmelCase							)
def  _lowercase					(    __lowerCAmelCase							)       ->				Optional[Any]:
      SCREAMING_SNAKE_CASE__   :      List[Any]      		=	tmp_path_factory.mktemp("""data"""							) / """file.html"""
      with pytest.raises(__lowerCAmelCase							):
            http_get("""https://huggingface.co"""  ,					temp_file=__lowerCAmelCase							)
      with pytest.raises(__lowerCAmelCase							):
            http_head("""https://huggingface.co"""							)




@patch("""datasets.config.HF_DATASETS_OFFLINE"""  ,					__lowerCAmelCase							)
def  _lowercase					(    __lowerCAmelCase							)       ->				Optional[int]:
      SCREAMING_SNAKE_CASE__   :      str      		=	tmp_path_factory.mktemp("""data"""							) / """file.html"""
      with pytest.raises(__lowerCAmelCase							):
            ftp_get("""ftp://huggingface.co"""  ,					temp_file=__lowerCAmelCase							)
      with pytest.raises(__lowerCAmelCase							):
            ftp_head("""ftp://huggingface.co"""							)




@patch("""datasets.config.HF_DATASETS_OFFLINE"""  ,					__lowerCAmelCase							)
def  _lowercase					(    __lowerCAmelCase							)       ->				str:
      SCREAMING_SNAKE_CASE__   :      Union[str, Any]      		=	tmp_path_factory.mktemp("""data"""							) / """file.html"""
      with pytest.raises(__lowerCAmelCase							):
            fsspec_get("""s3://huggingface.co"""  ,					temp_file=__lowerCAmelCase							)
      with pytest.raises(__lowerCAmelCase							):
            fsspec_head("""s3://huggingface.co"""							)







"""simple docstring"""


from __future__ import annotations

import unittest

from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow


if is_tf_available():
  import numpy as np
  import tensorflow as tf

  from transformers import TFCamembertModel

@require_tf
@require_sentencepiece
@require_tokenizers
class      __a							(unittest.TestCase):






     '''simple docstring'''

     @slow
     def 					_a			(						self  )  ->      Union[str, Any]:


           """simple docstring"""


           SCREAMING_SNAKE_CASE__   :      Union[str, Any]      		=	TFCamembertModel.from_pretrained("""jplu/tf-camembert-base"""  )

           SCREAMING_SNAKE_CASE__   :      Any      		=	tf.convert_to_tensor(
               [[5, 121, 11, 660, 16, 730, 25_543, 110, 83, 6]]	,    dtype=tf.intaa	,    )  # J'aime le camembert !"

           SCREAMING_SNAKE_CASE__   :      Optional[int]      		=	model(_a  )["""last_hidden_state"""]
           SCREAMING_SNAKE_CASE__   :      List[str]      		=	tf.TensorShape((1, 10, 768)  )
           self.assertEqual(output.shape	,    _a  )
           # compare the actual values for a slice.
           SCREAMING_SNAKE_CASE__   :      Optional[int]      		=	tf.convert_to_tensor(
               [[[-0.0_254, 0.0_235, 0.1_027], [0.0_606, -0.1_811, -0.0_418], [-0.1_561, -0.1_127, 0.2_687]]]	,    dtype=tf.floataa	,    )
           # camembert = torch.hub.load('pytorch/fairseq', 'camembert.v0')
           # camembert.eval()
           # expected_slice = roberta.model.forward(input_ids)[0][:, :3, :3].detach()

           self.assertTrue(np.allclose(output[:, :3, :3].numpy()	,    expected_slice.numpy()	,    atol=1E-4  )  )




