






# Lint as: python3
import os
import re
import urllib.parse
from pathlib import Path
from typing import Callable, List, Optional, Union
from zipfile import ZipFile

from ..utils.file_utils import cached_path, hf_github_url
from ..utils.logging import get_logger
from ..utils.version import Version


__lowerCamelCase	:		List[str]										=   get_logger(__name__)







class  _lowercase   :
      _a							:						str										=							'dummy_data'
      _a							:						Optional[int]										=							'datasets'
      _a							:						Optional[Any]										=							False
      def __init__(     self				,			a				,			a				,			a				,			a = None				,			a = False				,			a = True				,			a = None				,			):
       snake_case__  :    List[Any]							       =0
       snake_case__  :    str							       =dataset_name
       snake_case__  :    int							       =cache_dir
       snake_case__  :    int							       =use_local_dummy_data
       snake_case__  :    int							       =config
       # download_callbacks take a single url as input
       snake_case__  :    List[Callable]							       =download_callbacks or []
       # if False, it doesn't load existing files and it returns the paths of the dummy files relative
       # to the dummy_data zip file root
       snake_case__  :    int							       =load_existing_dummy_data

       # TODO(PVP, QL) might need to make this more general
       snake_case__  :    List[Any]							       =str(a   )
       # to be downloaded
       snake_case__  :    Optional[int]							       =None
       snake_case__  :    Dict							       =None
      @property
      def 						lowercase__					(     self   ):
       if self._dummy_file is None:
        snake_case__  :    Dict							       =self.download_dummy_data()
       return self._dummy_file
      @property
      def 						lowercase__					(     self   ):
       if self.config is not None:
        # structure is dummy / config_name / version_name
        return os.path.join("""dummy"""				,			self.config.name				,			self.version_name   )
       # structure is dummy / version_name
       return os.path.join("""dummy"""				,			self.version_name   )
      @property
      def 						lowercase__					(     self   ):
       return os.path.join(self.dummy_data_folder				,			"""dummy_data.zip"""   )
      def 						lowercase__					(     self   ):
       snake_case__  :    Optional[Any]							       =(
           self.local_path_to_dummy_data if self.use_local_dummy_data is True else self.github_path_to_dummy_data
       )

       snake_case__  :    Union[str, Any]							       =cached_path(
           a				,			cache_dir=self.cache_dir				,			extract_compressed_file=a				,			force_extract=a   )

       return os.path.join(a				,			self.dummy_file_name   )
      @property
      def 						lowercase__					(     self   ):
       return os.path.join(self.datasets_scripts_dir				,			self.dataset_name				,			self.dummy_zip_file   )
      @property
      def 						lowercase__					(     self   ):
       if self._bucket_url is None:
        snake_case__  :    Any							       =hf_github_url(self.dataset_name				,			self.dummy_zip_file.replace(os.sep				,			"""/"""   )   )
       return self._bucket_url
      @property
      def 						lowercase__					(     self   ):
       # return full path if its a dir
       if os.path.isdir(self.dummy_file   ):
        return self.dummy_file
       # else cut off path to file -> example `xsum`.
       return "/".join(self.dummy_file.replace(os.sep				,			"""/"""   ).split("""/"""   )[:-1]   )
      def 						lowercase__					(     self				,			a				,			*a   ):
       if self.load_existing_dummy_data:
        # dummy data is downloaded and tested
        snake_case__  :    int							       =self.dummy_file
       else:
        # dummy data cannot be downloaded and only the path to dummy file is returned
        snake_case__  :    Optional[Any]							       =self.dummy_file_name

       # special case when data_url is a dict
       if isinstance(a				,			a   ):
        return self.create_dummy_data_dict(a				,			a   )
       elif isinstance(a				,			(list, tuple)   ):
        return self.create_dummy_data_list(a				,			a   )
       else:
        return self.create_dummy_data_single(a				,			a   )
      def 						lowercase__					(     self				,			a				,			*a   ):
       return self.download_and_extract(a   )
      def 						lowercase__					(     self				,			a				,			a   ):
       return self.download_and_extract(a   )
      def 						lowercase__					(     self				,			a				,			*a				,			**a   ):
       return path
      def 						lowercase__					(     self   ):
       return {}
      def 						lowercase__					(     self				,			a				,			a   ):
       snake_case__  :    Union[str, Any]							       ={}
       for key, single_urls in data_url.items():
        for download_callback in self.download_callbacks:
         if isinstance(a				,			a   ):
          for single_url in single_urls:
           download_callback(a   )
         else:
          snake_case__  :    List[str]							       =single_urls
          download_callback(a   )
            # we force the name of each key to be the last file / folder name of the url path
            # if the url has arguments, we need to encode them with urllib.parse.quote_plus
        if isinstance(a				,			a   ):
         snake_case__  :    int							       =[os.path.join(a				,			urllib.parse.quote_plus(Path(a   ).name   )   ) for x in single_urls]
        else:
         snake_case__  :    Union[str, Any]							       =single_urls
         snake_case__  :    Optional[int]							       =os.path.join(a				,			urllib.parse.quote_plus(Path(a   ).name   )   )
        snake_case__  :    str							       =value

       # make sure that values are unique
       if all(isinstance(a				,			a   ) for i in dummy_data_dict.values()   ) and len(set(dummy_data_dict.values()   )   ) < len(
           dummy_data_dict.values()   ):
        # append key to value to make its name unique
        snake_case__  :    List[str]							       ={key: value + key for key, value in dummy_data_dict.items()}

       return dummy_data_dict
      def 						lowercase__					(     self				,			a				,			a   ):
       snake_case__  :    Tuple							       =[]
       # trick: if there are many shards named like `data.txt-000001-of-00300`, only use the first one
       snake_case__  :    List[Any]							       =all(bool(re.findall("""[0-9]{3,}-of-[0-9]{3,}"""				,			a   )   ) for url in data_url   )
       snake_case__  :    str							       =all(
           url.startswith("""https://ftp.ncbi.nlm.nih.gov/pubmed/baseline/pubmed"""   ) for url in data_url   )
       if data_url and (is_tf_records or is_pubmed_records):
        snake_case__  :    int							       =[data_url[0]] * len(a   )
       for single_url in data_url:
        for download_callback in self.download_callbacks:
         download_callback(a   )
        # we force the name of each key to be the last file / folder name of the url path
        # if the url has arguments, we need to encode them with urllib.parse.quote_plus
        snake_case__  :    List[Any]							       =os.path.join(a				,			urllib.parse.quote_plus(single_url.split("""/"""   )[-1]   )   )
        dummy_data_list.append(a   )
       return dummy_data_list
      def 						lowercase__					(     self				,			a				,			a   ):
       for download_callback in self.download_callbacks:
        download_callback(a   )
       # we force the name of each key to be the last file / folder name of the url path
       # if the url has arguments, we need to encode them with urllib.parse.quote_plus
       snake_case__  :    str							       =os.path.join(a				,			urllib.parse.quote_plus(data_url.split("""/"""   )[-1]   )   )
       if os.path.exists(a   ) or not self.load_existing_dummy_data:
        return value
       else:
        # Backward compatibility, maybe deprecate at one point.
        # For many datasets with single url calls to dl_manager.download_and_extract,
        # the dummy_data.zip file is actually the zipped downloaded file
        # while now we expected the dummy_data.zip file to be a directory containing
        # the downloaded file.
        return path_to_dummy_data
      def 						lowercase__					(     self   ):
       pass
      def 						lowercase__					(     self   ):
       pass
      def 						lowercase__					(     self				,			a   ):
       def _iter_archive_members(a   ):
        # this preserves the order of the members inside the ZIP archive
        snake_case__  :    int							       =Path(self.dummy_file   ).parent
        snake_case__  :    int							       =path.relative_to(a   )
        with ZipFile(self.local_path_to_dummy_data   ) as zip_file:
         snake_case__  :    List[str]							       =zip_file.namelist()
        for member in members:
         if member.startswith(relative_path.as_posix()   ):
          yield dummy_parent_path.joinpath(a   )

       snake_case__  :    List[Any]							       =Path(a   )
       snake_case__  :    Dict							       =_iter_archive_members(a   ) if self.use_local_dummy_data else path.rglob("""*"""   )
       for file_path in file_paths:
        if file_path.is_file() and not file_path.name.startswith((""".""", """__""")   ):
         yield file_path.relative_to(a   ).as_posix(), file_path.open("""rb"""   )



      def 						lowercase__					(     self				,			a   ):
       if not isinstance(a				,			a   ):
        snake_case__  :    List[Any]							       =[paths]
       for path in paths:
        if os.path.isfile(a   ):
         if os.path.basename(a   ).startswith((""".""", """__""")   ):
          return
         yield path
        else:
         for dirpath, dirnames, filenames in os.walk(a   ):
          if os.path.basename(a   ).startswith((""".""", """__""")   ):
           continue
          dirnames.sort()
          for filename in sorted(a   ):
           if filename.startswith((""".""", """__""")   ):
            continue
           yield os.path.join(a				,			a   )













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  _lowercase   (   unittest.TestCase						):
      def __init__(     self				,			a				,			a=1_3				,			a=7				,			a=True				,			a=True				,			a=True				,			a=True				,			a=9_9				,			a=3_2				,			a=5				,			a=4				,			a=3_7				,			a="gelu"				,			a=0.1				,			a=0.1				,			a=5_1_2				,			a=1_6				,			a=2				,			a=0.02				,			a=4				,			):
       snake_case__  :    Any							       =parent
       snake_case__  :    Dict							       =batch_size
       snake_case__  :    List[Any]							       =seq_length
       snake_case__  :    str							       =is_training
       snake_case__  :    Union[str, Any]							       =use_attention_mask
       snake_case__  :    str							       =use_token_type_ids
       snake_case__  :    int							       =use_labels
       snake_case__  :    Tuple							       =vocab_size
       snake_case__  :    List[str]							       =hidden_size
       snake_case__  :    Dict							       =num_hidden_layers
       snake_case__  :    Optional[Any]							       =num_attention_heads
       snake_case__  :    List[str]							       =intermediate_size
       snake_case__  :    str							       =hidden_act
       snake_case__  :    Union[str, Any]							       =hidden_dropout_prob
       snake_case__  :    Tuple							       =attention_probs_dropout_prob
       snake_case__  :    Tuple							       =max_position_embeddings
       snake_case__  :    str							       =type_vocab_size
       snake_case__  :    Optional[Any]							       =type_sequence_label_size
       snake_case__  :    str							       =initializer_range
       snake_case__  :    List[Any]							       =num_choices
      def 						lowercase__					(     self   ):
       snake_case__  :    Union[str, Any]							       =ids_tensor([self.batch_size, self.seq_length]				,			self.vocab_size   )

       snake_case__  :    Tuple							       =None
       if self.use_attention_mask:
        snake_case__  :    Union[str, Any]							       =random_attention_mask([self.batch_size, self.seq_length]   )

       snake_case__  :    Union[str, Any]							       =None
       if self.use_token_type_ids:
        snake_case__  :    Optional[Any]							       =ids_tensor([self.batch_size, self.seq_length]				,			self.type_vocab_size   )

       snake_case__  :    Tuple							       =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=a				,			initializer_range=self.initializer_range				,			)

       return config, input_ids, token_type_ids, attention_mask



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







@require_flax
class  _lowercase   (   _A						,				unittest.TestCase						):
      _a							:						str										=							True

      _a							:						Optional[Any]										=							(
          (
              FlaxRoFormerModel,
              FlaxRoFormerForMaskedLM,
              FlaxRoFormerForSequenceClassification,
              FlaxRoFormerForTokenClassification,
              FlaxRoFormerForMultipleChoice,
              FlaxRoFormerForQuestionAnswering,
          )
          if is_flax_available()
          else ()
      )
      def 						lowercase__					(     self   ):
       snake_case__  :    Optional[Any]							       =FlaxRoFormerModelTester(self   )



      @slow
      def 						lowercase__					(     self   ):
       for model_class_name in self.all_model_classes:
        snake_case__  :    Tuple							       =model_class_name.from_pretrained("""junnyu/roformer_chinese_small"""				,			from_pt=a   )
        snake_case__  :    List[Any]							       =model(np.ones((1, 1)   )   )
        self.assertIsNotNone(a   )







@require_flax
class  _lowercase   (   unittest.TestCase						):
      @slow
      def 						lowercase__					(     self   ):
       snake_case__  :    Optional[int]							       =FlaxRoFormerForMaskedLM.from_pretrained("""junnyu/roformer_chinese_base"""   )
       snake_case__  :    Tuple							       =jnp.array([[0, 1, 2, 3, 4, 5]]   )
       snake_case__  :    str							       =model(a   )[0]

       snake_case__  :    List[str]							       =5_0_0_0_0

       snake_case__  :    str							       =(1, 6, vocab_size)
       self.assertEqual(output.shape				,			a   )

       snake_case__  :    Optional[int]							       =jnp.array(
           [[[-0.1205, -1.0265, 0.2922], [-1.5134, 0.1974, 0.1519], [-5.0135, -3.9003, -0.8404]]]   )

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





