





import json
import os
from pathlib import Path

import pytest

from datasets.download.download_config import DownloadConfig
from datasets.download.download_manager import DownloadManager
from datasets.utils.file_utils import hash_url_to_filename


UpperCAmelCase	:	Optional[int]		     =       """http://www.mocksite.com/file1.txt"""
UpperCAmelCase	:	Optional[int]		     =       """\"text\": [\"foo\", \"foo\"]"""
UpperCAmelCase	:	Optional[int]		     =       """6d8ce9aa78a471c7477201efbeabd3bb01ac2e7d100a6dc024ba1608361f90a8"""







class 				__lowerCAmelCase       :
      _lowercase				:					Dict						=			200
      _lowercase				:					int						=			{"Content-Length": "100"}
      _lowercase				:					int						=			{}







      def    _lowercase  (    self		,      **lowerCAmelCase__							)   ->						Optional[Any]:



        '''simple docstring'''




        return [bytes(_UpperCAmelCase		,      "utf-8"							)]
def      _A       (		*SCREAMING_SNAKE_CASE     :   List[Any]       ,       **SCREAMING_SNAKE_CASE     :   Dict						):





  """simple docstring"""



  return MockResponse()
@pytest.mark.parametrize("urls_type"       ,       [str, list, dict]						)
def      _A       (		SCREAMING_SNAKE_CASE     :   Optional[int]       ,       SCREAMING_SNAKE_CASE     :   int       ,       SCREAMING_SNAKE_CASE     :   List[Any]						):





  """simple docstring"""



  import requests

  monkeypatch.setattr(__UpperCAmelCase       ,       "request"       ,       __UpperCAmelCase						)

  a__	:					int										=URL
  if issubclass(__UpperCAmelCase       ,       __UpperCAmelCase						):
    a__	:					Optional[Any]										=url
  elif issubclass(__UpperCAmelCase       ,       __UpperCAmelCase						):
    a__	:					Union[str, Any]										=[url]
  elif issubclass(__UpperCAmelCase       ,       __UpperCAmelCase						):
    a__	:					Tuple										={'''train''': url}
  a__	:					Any										='''dummy'''
  a__	:					Dict										='''downloads'''
  a__	:					Union[str, Any]										=tmp_path
  a__	:					Optional[int]										=DownloadConfig(
      cache_dir=os.path.join(__UpperCAmelCase       ,       __UpperCAmelCase						)       ,       use_etag=__UpperCAmelCase       ,       )
  a__	:					Tuple										=DownloadManager(dataset_name=__UpperCAmelCase       ,       download_config=__UpperCAmelCase						)
  a__	:					List[str]										=dl_manager.download(__UpperCAmelCase						)
  a__	:					Union[str, Any]										=urls
  for downloaded_paths in [downloaded_paths]:
    if isinstance(__UpperCAmelCase       ,       __UpperCAmelCase						):
      a__	:					Tuple										=[downloaded_paths]
      a__	:					List[Any]										=[urls]
    elif isinstance(__UpperCAmelCase       ,       __UpperCAmelCase						):
      assert "train" in downloaded_paths.keys()
      a__	:					Union[str, Any]										=downloaded_paths.values()
      a__	:					int										=urls.values()
    assert downloaded_paths
    for downloaded_path, input_url in zip(__UpperCAmelCase       ,       __UpperCAmelCase						):
      assert downloaded_path == dl_manager.downloaded_paths[input_url]
      a__	:					Union[str, Any]										=Path(__UpperCAmelCase						)
      a__	:					List[str]										=downloaded_path.parts
      assert parts[-1] == HASH
      assert parts[-2] == cache_subdir
      assert downloaded_path.exists()
      a__	:					Any										=downloaded_path.read_text()
      assert content == CONTENT
      a__	:					List[str]										=downloaded_path.with_suffix(".json"						)
      assert metadata_downloaded_path.exists()
      a__	:					Union[str, Any]										=json.loads(metadata_downloaded_path.read_text()						)
      assert metadata_content == {"url": URL, "etag": None}
@pytest.mark.parametrize("paths_type"       ,       [str, list, dict]						)
def      _A       (		SCREAMING_SNAKE_CASE     :   Any       ,       SCREAMING_SNAKE_CASE     :   Union[str, Any]       ,       SCREAMING_SNAKE_CASE     :   Optional[Any]						):





  """simple docstring"""



  a__	:					Dict										=str(__UpperCAmelCase						)
  if issubclass(__UpperCAmelCase       ,       __UpperCAmelCase						):
    a__	:					List[str]										=filename
  elif issubclass(__UpperCAmelCase       ,       __UpperCAmelCase						):
    a__	:					int										=[filename]
  elif issubclass(__UpperCAmelCase       ,       __UpperCAmelCase						):
    a__	:					Union[str, Any]										={'''train''': filename}
  a__	:					Optional[Any]										='''dummy'''
  a__	:					Tuple										=xz_file.parent
  a__	:					List[str]										='''extracted'''
  a__	:					int										=DownloadConfig(
      cache_dir=__UpperCAmelCase       ,       use_etag=__UpperCAmelCase       ,       )
  a__	:					Optional[int]										=DownloadManager(dataset_name=__UpperCAmelCase       ,       download_config=__UpperCAmelCase						)
  a__	:					List[Any]										=dl_manager.extract(__UpperCAmelCase						)
  a__	:					Any										=paths
  for extracted_paths in [extracted_paths]:
    if isinstance(__UpperCAmelCase       ,       __UpperCAmelCase						):
      a__	:					Tuple										=[extracted_paths]
      a__	:					List[Any]										=[paths]
    elif isinstance(__UpperCAmelCase       ,       __UpperCAmelCase						):
      assert "train" in extracted_paths.keys()
      a__	:					Tuple										=extracted_paths.values()
      a__	:					Union[str, Any]										=paths.values()
    assert extracted_paths
    for extracted_path, input_path in zip(__UpperCAmelCase       ,       __UpperCAmelCase						):
      assert extracted_path == dl_manager.extracted_paths[input_path]
      a__	:					Tuple										=Path(__UpperCAmelCase						)
      a__	:					Union[str, Any]										=extracted_path.parts
      assert parts[-1] == hash_url_to_filename(__UpperCAmelCase       ,       etag=__UpperCAmelCase						)
      assert parts[-2] == extracted_subdir
      assert extracted_path.exists()
      a__	:					List[Any]										=extracted_path.read_text()
      a__	:					List[Any]										=text_file.read_text()
      assert extracted_file_content == expected_file_content
def      _A       (		SCREAMING_SNAKE_CASE     :   Tuple       ,       SCREAMING_SNAKE_CASE     :   str						):





  """simple docstring"""



  assert path.endswith(".jsonl"						)
  for num_items, line in enumerate(__UpperCAmelCase       ,       start=1						):
    a__	:					Any										=json.loads(line.decode("utf-8"						)						)
    assert item.keys() == {"col_1", "col_2", "col_3"}
  assert num_items == 4
@pytest.mark.parametrize("archive_jsonl"       ,       ["tar_jsonl_path", "zip_jsonl_path"]						)
def      _A       (		SCREAMING_SNAKE_CASE     :   Union[str, Any]       ,       SCREAMING_SNAKE_CASE     :   Optional[Any]						):





  """simple docstring"""



  a__	:					Optional[Any]										=request.getfixturevalue(__UpperCAmelCase						)
  a__	:					Union[str, Any]										=DownloadManager()
  for num_jsonl, (path, file) in enumerate(dl_manager.iter_archive(__UpperCAmelCase						)       ,       start=1						):
    _test_jsonl(__UpperCAmelCase       ,       __UpperCAmelCase						)
  assert num_jsonl == 2
@pytest.mark.parametrize("archive_nested_jsonl"       ,       ["tar_nested_jsonl_path", "zip_nested_jsonl_path"]						)
def      _A       (		SCREAMING_SNAKE_CASE     :   Optional[int]       ,       SCREAMING_SNAKE_CASE     :   int						):





  """simple docstring"""



  a__	:					int										=request.getfixturevalue(__UpperCAmelCase						)
  a__	:					Dict										=DownloadManager()
  for num_tar, (path, file) in enumerate(dl_manager.iter_archive(__UpperCAmelCase						)       ,       start=1						):
    for num_jsonl, (subpath, subfile) in enumerate(dl_manager.iter_archive(__UpperCAmelCase						)       ,       start=1						):
      _test_jsonl(__UpperCAmelCase       ,       __UpperCAmelCase						)
  assert num_tar == 1
  assert num_jsonl == 2





def      _A       (		SCREAMING_SNAKE_CASE     :   Any						):





  """simple docstring"""



  a__	:					Optional[int]										=DownloadManager()
  for num_file, file in enumerate(dl_manager.iter_files(__UpperCAmelCase						)       ,       start=1						):
    assert os.path.basename(__UpperCAmelCase						) == ("test.txt" if num_file == 1 else "train.txt")
  assert num_file == 2







"""simple docstring"""






import unittest

import numpy as np

from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow

from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask


if is_flax_available():
       import jax.numpy as jnp

       from transformers.models.roformer.modeling_flax_roformer import (
           FlaxRoFormerForMaskedLM,
           FlaxRoFormerForMultipleChoice,
           FlaxRoFormerForQuestionAnswering,
           FlaxRoFormerForSequenceClassification,
           FlaxRoFormerForTokenClassification,
           FlaxRoFormerModel,
       )


class     UpperCAmelCase						(unittest.TestCase  ):



    """simple docstring"""

    def __init__(   self    ,			_UpperCAmelCase    ,			_UpperCAmelCase=13    ,			_UpperCAmelCase=7    ,			_UpperCAmelCase=True    ,			_UpperCAmelCase=True    ,			_UpperCAmelCase=True    ,			_UpperCAmelCase=True    ,			_UpperCAmelCase=99    ,			_UpperCAmelCase=32    ,			_UpperCAmelCase=5    ,			_UpperCAmelCase=4    ,			_UpperCAmelCase=37    ,			_UpperCAmelCase="gelu"    ,			_UpperCAmelCase=0.1    ,			_UpperCAmelCase=0.1    ,			_UpperCAmelCase=512    ,			_UpperCAmelCase=16    ,			_UpperCAmelCase=2    ,			_UpperCAmelCase=0.02    ,			_UpperCAmelCase=4    ,			):
       lowercase__:   Dict					=      parent
       lowercase__:   List[str]					=      batch_size
       lowercase__:   Optional[Any]					=      seq_length
       lowercase__:   List[Any]					=      is_training
       lowercase__:   int					=      use_attention_mask
       lowercase__:   Tuple					=      use_token_type_ids
       lowercase__:   Union[str, Any]					=      use_labels
       lowercase__:   str					=      vocab_size
       lowercase__:   str					=      hidden_size
       lowercase__:   str					=      num_hidden_layers
       lowercase__:   Optional[int]					=      num_attention_heads
       lowercase__:   List[str]					=      intermediate_size
       lowercase__:   List[str]					=      hidden_act
       lowercase__:   Tuple					=      hidden_dropout_prob
       lowercase__:   int					=      attention_probs_dropout_prob
       lowercase__:   int					=      max_position_embeddings
       lowercase__:   Union[str, Any]					=      type_vocab_size
       lowercase__:   List[Any]					=      type_sequence_label_size
       lowercase__:   Any					=      initializer_range
       lowercase__:   str					=      num_choices






    def _snake_case			(   self							):
       lowercase__:   int					=      ids_tensor([self.batch_size, self.seq_length]    ,			self.vocab_size							)

       lowercase__:   List[Any]					=      None
       if self.use_attention_mask:
          lowercase__:   Tuple					=      random_attention_mask([self.batch_size, self.seq_length]							)

       lowercase__:   List[Any]					=      None
       if self.use_token_type_ids:
          lowercase__:   str					=      ids_tensor([self.batch_size, self.seq_length]    ,			self.type_vocab_size							)

       lowercase__:   Optional[int]					=      RoFormerConfig(
           vocab_size=self.vocab_size    ,			hidden_size=self.hidden_size    ,			num_hidden_layers=self.num_hidden_layers    ,			num_attention_heads=self.num_attention_heads    ,			intermediate_size=self.intermediate_size    ,			hidden_act=self.hidden_act    ,			hidden_dropout_prob=self.hidden_dropout_prob    ,			attention_probs_dropout_prob=self.attention_probs_dropout_prob    ,			max_position_embeddings=self.max_position_embeddings    ,			type_vocab_size=self.type_vocab_size    ,			is_decoder=_UpperCAmelCase    ,			initializer_range=self.initializer_range    ,			)

       return config, input_ids, token_type_ids, attention_mask






    def _snake_case			(   self							):
       lowercase__:   str					=      self.prepare_config_and_inputs()
       lowercase__, lowercase__, lowercase__, lowercase__:   Optional[Any]					=      config_and_inputs
       lowercase__:   Dict					=      {'''input_ids''': input_ids, '''token_type_ids''': token_type_ids, '''attention_mask''': attention_mask}
       return config, inputs_dict



@require_flax
class     UpperCAmelCase						(_UpperCAmelCase    ,unittest.TestCase  ):



    """simple docstring"""

    _UpperCAmelCase	:List[str]						    = True

    _UpperCAmelCase	:Union[str, Any]						    = (
        (
            FlaxRoFormerModel,
            FlaxRoFormerForMaskedLM,
            FlaxRoFormerForSequenceClassification,
            FlaxRoFormerForTokenClassification,
            FlaxRoFormerForMultipleChoice,
            FlaxRoFormerForQuestionAnswering,
        )
        if is_flax_available()
        else ()
    )






    def _snake_case			(   self							):
       lowercase__:   str					=      FlaxRoFormerModelTester(self							)






    @slow
    def _snake_case			(   self							):
       for model_class_name in self.all_model_classes:
          lowercase__:   Dict					=      model_class_name.from_pretrained('''junnyu/roformer_chinese_small'''    ,			from_pt=_UpperCAmelCase							)
          lowercase__:   int					=      model(np.ones((1, 1)							)							)
          self.assertIsNotNone(_UpperCAmelCase							)



@require_flax
class     UpperCAmelCase						(unittest.TestCase  ):



    """simple docstring"""

    @slow
    def _snake_case			(   self							):
       lowercase__:   Any					=      FlaxRoFormerForMaskedLM.from_pretrained('''junnyu/roformer_chinese_base'''							)
       lowercase__:   Optional[int]					=      jnp.array([[0, 1, 2, 3, 4, 5]]							)
       lowercase__:   List[Any]					=      model(_UpperCAmelCase							)[0]

       lowercase__:   str					=      50000

       lowercase__:   Tuple					=      (1, 6, vocab_size)
       self.assertEqual(output.shape    ,			_UpperCAmelCase							)

       lowercase__:   List[Any]					=      jnp.array(
           [[[-0.1_205, -1.0_265, 0.2_922], [-1.5_134, 0.1_974, 0.1_519], [-5.0_135, -3.9_003, -0.8_404]]]							)

       self.assertTrue(jnp.allclose(output[:, :3, :3]    ,			_UpperCAmelCase    ,			atol=1e-4							)							)
