import pytest

from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader

from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases





def 					lowercase_ (    __snake_case     :							int	,	__snake_case     :							Union[str, Any]      )     -> Tuple:





				'''simple docstring'''


				assert isinstance(_lowerCAmelCase	,	_lowerCAmelCase      )
				assert dataset.num_rows == 4
				assert dataset.num_columns == 1
				assert dataset.column_names == ["text"]
				for feature, expected_dtype in expected_features.items():
								assert dataset.features[feature].dtype == expected_dtype





@pytest.mark.parametrize("keep_in_memory"	,	[False, True]      )
def 					lowercase_ (    __snake_case     :							Optional[int]	,	__snake_case     :							int	,	__snake_case     :							Optional[int]      )     -> Any:





				'''simple docstring'''


				snake_case__      :Dict         =   tmp_path / "cache"
				snake_case__      :List[str]         =   {"text": "string"}
				with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
								snake_case__      :str         =   TextDatasetReader(_lowerCAmelCase	,	cache_dir=_lowerCAmelCase	,	keep_in_memory=_lowerCAmelCase      ).read()
				_check_text_dataset(_lowerCAmelCase	,	_lowerCAmelCase      )





@pytest.mark.parametrize(
    "features"	,	[
        None,
        {"text": "string"},
        {"text": "int32"},
        {"text": "float32"},
    ]	,	)
def 					lowercase_ (    __snake_case     :							int	,	__snake_case     :							Dict	,	__snake_case     :							Optional[Any]      )     -> str:





				'''simple docstring'''


				snake_case__      :int         =   tmp_path / "cache"
				snake_case__      :Tuple         =   {"text": "string"}
				snake_case__      :Optional[Any]         =   features.copy() if features else default_expected_features
				snake_case__      :List[Any]         =   (
				    Features({feature: Value(_lowerCAmelCase      ) for feature, dtype in features.items()}      ) if features is not None else None
				)
				snake_case__      :Any         =   TextDatasetReader(_lowerCAmelCase	,	features=_lowerCAmelCase	,	cache_dir=_lowerCAmelCase      ).read()
				_check_text_dataset(_lowerCAmelCase	,	_lowerCAmelCase      )





@pytest.mark.parametrize("split"	,	[None, NamedSplit("train"      ), "train", "test"]      )
def 					lowercase_ (    __snake_case     :							Dict	,	__snake_case     :							str	,	__snake_case     :							int      )     -> Tuple:





				'''simple docstring'''


				snake_case__      :Union[str, Any]         =   tmp_path / "cache"
				snake_case__      :List[Any]         =   {"text": "string"}
				snake_case__      :Dict         =   TextDatasetReader(_lowerCAmelCase	,	cache_dir=_lowerCAmelCase	,	split=_lowerCAmelCase      ).read()
				_check_text_dataset(_lowerCAmelCase	,	_lowerCAmelCase      )
				assert dataset.split == split if split else "train"





@pytest.mark.parametrize("path_type"	,	[str, list]      )
def 					lowercase_ (    __snake_case     :							Dict	,	__snake_case     :							Union[str, Any]	,	__snake_case     :							List[Any]      )     -> Optional[int]:





				'''simple docstring'''


				if issubclass(_lowerCAmelCase	,	_lowerCAmelCase      ):
								snake_case__      :Dict         =   text_path
				elif issubclass(_lowerCAmelCase	,	_lowerCAmelCase      ):
								snake_case__      :int         =   [text_path]
				snake_case__      :List[Any]         =   tmp_path / "cache"
				snake_case__      :Optional[int]         =   {"text": "string"}
				snake_case__      :Union[str, Any]         =   TextDatasetReader(_lowerCAmelCase	,	cache_dir=_lowerCAmelCase      ).read()
				_check_text_dataset(_lowerCAmelCase	,	_lowerCAmelCase      )





def 					lowercase_ (    __snake_case     :							Dict	,	__snake_case     :							int	,	__snake_case     :							List[Any]=("train",)      )     -> Tuple:





				'''simple docstring'''


				assert isinstance(_lowerCAmelCase	,	_lowerCAmelCase      )
				for split in splits:
								snake_case__      :Dict         =   dataset_dict[split]
								assert dataset.num_rows == 4
								assert dataset.num_columns == 1
								assert dataset.column_names == ["text"]
								for feature, expected_dtype in expected_features.items():
												assert dataset.features[feature].dtype == expected_dtype





@pytest.mark.parametrize("keep_in_memory"	,	[False, True]      )
def 					lowercase_ (    __snake_case     :							Tuple	,	__snake_case     :							Optional[Any]	,	__snake_case     :							Any      )     -> Union[str, Any]:





				'''simple docstring'''


				snake_case__      :Optional[int]         =   tmp_path / "cache"
				snake_case__      :Dict         =   {"text": "string"}
				with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
								snake_case__      :Dict         =   TextDatasetReader({"train": text_path}	,	cache_dir=_lowerCAmelCase	,	keep_in_memory=_lowerCAmelCase      ).read()
				_check_text_datasetdict(_lowerCAmelCase	,	_lowerCAmelCase      )





@pytest.mark.parametrize(
    "features"	,	[
        None,
        {"text": "string"},
        {"text": "int32"},
        {"text": "float32"},
    ]	,	)
def 					lowercase_ (    __snake_case     :							List[Any]	,	__snake_case     :							List[Any]	,	__snake_case     :							int      )     -> Union[str, Any]:





				'''simple docstring'''


				snake_case__      :List[Any]         =   tmp_path / "cache"
				# CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
				snake_case__      :Optional[int]         =   {"text": "string"}
				snake_case__      :Optional[int]         =   features.copy() if features else default_expected_features
				snake_case__      :str         =   (
				    Features({feature: Value(_lowerCAmelCase      ) for feature, dtype in features.items()}      ) if features is not None else None
				)
				snake_case__      :Tuple         =   TextDatasetReader({"train": text_path}	,	features=_lowerCAmelCase	,	cache_dir=_lowerCAmelCase      ).read()
				_check_text_datasetdict(_lowerCAmelCase	,	_lowerCAmelCase      )





@pytest.mark.parametrize("split"	,	[None, NamedSplit("train"      ), "train", "test"]      )
def 					lowercase_ (    __snake_case     :							List[Any]	,	__snake_case     :							Any	,	__snake_case     :							Union[str, Any]      )     -> Dict:





				'''simple docstring'''


				if split:
								snake_case__      :Tuple         =   {split: text_path}
				else:
								snake_case__      :List[str]         =   "train"
								snake_case__      :List[str]         =   {"train": text_path, "test": text_path}
				snake_case__      :str         =   tmp_path / "cache"
				snake_case__      :int         =   {"text": "string"}
				snake_case__      :str         =   TextDatasetReader(_lowerCAmelCase	,	cache_dir=_lowerCAmelCase      ).read()
				_check_text_datasetdict(_lowerCAmelCase	,	_lowerCAmelCase	,	splits=list(path.keys()      )      )
				assert all(dataset[split].split == split for split in path.keys()      )







import os
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path

from huggingface_hub import HfFolder, delete_repo
from huggingface_hub.file_download import http_get
from requests.exceptions import HTTPError

from transformers import (
    AlbertTokenizer,
    AutoTokenizer,
    BertTokenizer,
    BertTokenizerFast,
    GPTaTokenizerFast,
    is_tokenizers_available,
)
from transformers.testing_utils import TOKEN, USER, is_staging_test, require_tokenizers
from transformers.tokenization_utils import Trie


sys.path.append(str(Path(__file__).parent.parent / "utils"))

from test_module.custom_tokenization import CustomTokenizer  # noqa E402


if is_tokenizers_available():
	from test_module.custom_tokenization_fast import CustomTokenizerFast


class 					_snake_case						(			unittest.TestCase ):






	def    lowerCAmelCase_							(		self       )						->    List[Any]:
					# A mock response for an HTTP head request to emulate server down
					snake_case__      :Tuple         =   mock.Mock()
					snake_case__      :List[str]         =   500
					snake_case__      :Any         =   {}
					snake_case__      :Union[str, Any]         =   HTTPError
					snake_case__      :Tuple         =   {}

					# Download this model to make sure it's in the cache.
					snake_case__      :Any         =   BertTokenizer.from_pretrained("hf-internal-testing/tiny-random-bert"       )

					# Under the mock environment we get a 500 error when trying to reach the tokenizer.
					with mock.patch("requests.Session.request"					,return_value=UpperCamelCase       ) as mock_head:
									snake_case__      :Dict         =   BertTokenizer.from_pretrained("hf-internal-testing/tiny-random-bert"       )
									# This check we did call the fake head request
									mock_head.assert_called()






	@require_tokenizers
	def    lowerCAmelCase_							(		self       )						->    Dict:
					# A mock response for an HTTP head request to emulate server down
					snake_case__      :Union[str, Any]         =   mock.Mock()
					snake_case__      :int         =   500
					snake_case__      :Any         =   {}
					snake_case__      :Dict         =   HTTPError
					snake_case__      :List[Any]         =   {}

					# Download this model to make sure it's in the cache.
					snake_case__      :Optional[int]         =   GPTaTokenizerFast.from_pretrained("gpt2"       )

					# Under the mock environment we get a 500 error when trying to reach the tokenizer.
					with mock.patch("requests.Session.request"					,return_value=UpperCamelCase       ) as mock_head:
									snake_case__      :Any         =   GPTaTokenizerFast.from_pretrained("gpt2"       )
									# This check we did call the fake head request
									mock_head.assert_called()






	def    lowerCAmelCase_							(		self       )						->    int:
					# This test is for deprecated behavior and can be removed in v5
					try:
									snake_case__      :Union[str, Any]         =   tempfile.mktemp()
									with open(UpperCamelCase					,"wb"       ) as f:
													http_get("https://huggingface.co/albert-base-v1/resolve/main/spiece.model"					,UpperCamelCase       )

									snake_case__      :Tuple         =   AlbertTokenizer.from_pretrained(UpperCamelCase       )
					finally:
									os.remove(UpperCamelCase       )

					# Supporting this legacy load introduced a weird bug where the tokenizer would load local files if they are in
					# the current folder and have the right name.
					if os.path.isfile("tokenizer.json"       ):
									# We skip the test if the user has a `tokenizer.json` in this folder to avoid deleting it.
									return
					try:
									with open("tokenizer.json"					,"wb"       ) as f:
													http_get("https://huggingface.co/hf-internal-testing/tiny-random-bert/blob/main/tokenizer.json"					,UpperCamelCase       )
									snake_case__      :Dict         =   AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-gpt2"       )
									# The tiny random BERT has a vocab size of 1024, tiny gpt2 as a vocab size of 1000
									self.assertEqual(tokenizer.vocab_size					,1_000       )
									# Tokenizer should depend on the remote checkpoint, not the local tokenizer.json file.

					finally:
									os.remove("tokenizer.json"       )






	def    lowerCAmelCase_							(		self       )						->    Union[str, Any]:
					# This test is for deprecated behavior and can be removed in v5
					snake_case__      :Union[str, Any]         =   AlbertTokenizer.from_pretrained("https://huggingface.co/albert-base-v1/resolve/main/spiece.model"       )




@is_staging_test
class 					_snake_case						(			unittest.TestCase ):
	_A          =   ['[UNK]', '[CLS]', '[SEP]', '[PAD]', '[MASK]', 'bla', 'blou']






	@classmethod
	def    lowerCAmelCase_							(		cls       )						->    Optional[int]:
					snake_case__      :List[str]         =   TOKEN
					HfFolder.save_token(UpperCamelCase       )






	@classmethod
	def    lowerCAmelCase_							(		cls       )						->    Union[str, Any]:
					try:
									delete_repo(token=cls._token					,repo_id="test-tokenizer"       )
					except HTTPError:
									pass

					try:
									delete_repo(token=cls._token					,repo_id="valid_org/test-tokenizer-org"       )
					except HTTPError:
									pass

					try:
									delete_repo(token=cls._token					,repo_id="test-dynamic-tokenizer"       )
					except HTTPError:
									pass






	def    lowerCAmelCase_							(		self       )						->    Optional[Any]:
					with tempfile.TemporaryDirectory() as tmp_dir:
									snake_case__      :List[str]         =   os.path.join(UpperCamelCase					,"vocab.txt"       )
									with open(UpperCamelCase					,"w"					,encoding="utf-8"       ) as vocab_writer:
													vocab_writer.write("".join([x + "\n" for x in self.vocab_tokens]       )       )
									snake_case__      :str         =   BertTokenizer(UpperCamelCase       )

					tokenizer.push_to_hub("test-tokenizer"					,use_auth_token=self._token       )
					snake_case__      :Dict         =   BertTokenizer.from_pretrained(f'{USER}/test-tokenizer'       )
					self.assertDictEqual(new_tokenizer.vocab					,tokenizer.vocab       )

					# Reset repo
					delete_repo(token=self._token					,repo_id="test-tokenizer"       )

					# Push to hub via save_pretrained
					with tempfile.TemporaryDirectory() as tmp_dir:
									tokenizer.save_pretrained(UpperCamelCase					,repo_id="test-tokenizer"					,push_to_hub=UpperCamelCase					,use_auth_token=self._token       )

					snake_case__      :List[str]         =   BertTokenizer.from_pretrained(f'{USER}/test-tokenizer'       )
					self.assertDictEqual(new_tokenizer.vocab					,tokenizer.vocab       )






	def    lowerCAmelCase_							(		self       )						->    Optional[int]:
					with tempfile.TemporaryDirectory() as tmp_dir:
									snake_case__      :List[Any]         =   os.path.join(UpperCamelCase					,"vocab.txt"       )
									with open(UpperCamelCase					,"w"					,encoding="utf-8"       ) as vocab_writer:
													vocab_writer.write("".join([x + "\n" for x in self.vocab_tokens]       )       )
									snake_case__      :Any         =   BertTokenizer(UpperCamelCase       )

					tokenizer.push_to_hub("valid_org/test-tokenizer-org"					,use_auth_token=self._token       )
					snake_case__      :Any         =   BertTokenizer.from_pretrained("valid_org/test-tokenizer-org"       )
					self.assertDictEqual(new_tokenizer.vocab					,tokenizer.vocab       )

					# Reset repo
					delete_repo(token=self._token					,repo_id="valid_org/test-tokenizer-org"       )

					# Push to hub via save_pretrained
					with tempfile.TemporaryDirectory() as tmp_dir:
									tokenizer.save_pretrained(
									    UpperCamelCase					,repo_id="valid_org/test-tokenizer-org"					,push_to_hub=UpperCamelCase					,use_auth_token=self._token       )

					snake_case__      :Union[str, Any]         =   BertTokenizer.from_pretrained("valid_org/test-tokenizer-org"       )
					self.assertDictEqual(new_tokenizer.vocab					,tokenizer.vocab       )






	@require_tokenizers
	def    lowerCAmelCase_							(		self       )						->    Any:
					CustomTokenizer.register_for_auto_class()
					with tempfile.TemporaryDirectory() as tmp_dir:
									snake_case__      :str         =   os.path.join(UpperCamelCase					,"vocab.txt"       )
									with open(UpperCamelCase					,"w"					,encoding="utf-8"       ) as vocab_writer:
													vocab_writer.write("".join([x + "\n" for x in self.vocab_tokens]       )       )
									snake_case__      :Optional[int]         =   CustomTokenizer(UpperCamelCase       )

					# No fast custom tokenizer
					tokenizer.push_to_hub("test-dynamic-tokenizer"					,use_auth_token=self._token       )

					snake_case__      :Union[str, Any]         =   AutoTokenizer.from_pretrained(f'{USER}/test-dynamic-tokenizer'					,trust_remote_code=UpperCamelCase       )
					# Can't make an isinstance check because the new_model.config is from the CustomTokenizer class of a dynamic module
					self.assertEqual(tokenizer.__class__.__name__					,"CustomTokenizer"       )

					# Fast and slow custom tokenizer
					CustomTokenizerFast.register_for_auto_class()
					with tempfile.TemporaryDirectory() as tmp_dir:
									snake_case__      :int         =   os.path.join(UpperCamelCase					,"vocab.txt"       )
									with open(UpperCamelCase					,"w"					,encoding="utf-8"       ) as vocab_writer:
													vocab_writer.write("".join([x + "\n" for x in self.vocab_tokens]       )       )

									snake_case__      :Tuple         =   BertTokenizerFast.from_pretrained(UpperCamelCase       )
									bert_tokenizer.save_pretrained(UpperCamelCase       )
									snake_case__      :List[Any]         =   CustomTokenizerFast.from_pretrained(UpperCamelCase       )

					tokenizer.push_to_hub("test-dynamic-tokenizer"					,use_auth_token=self._token       )

					snake_case__      :List[Any]         =   AutoTokenizer.from_pretrained(f'{USER}/test-dynamic-tokenizer'					,trust_remote_code=UpperCamelCase       )
					# Can't make an isinstance check because the new_model.config is from the FakeConfig class of a dynamic module
					self.assertEqual(tokenizer.__class__.__name__					,"CustomTokenizerFast"       )
					snake_case__      :List[str]         =   AutoTokenizer.from_pretrained(
					    f'{USER}/test-dynamic-tokenizer'					,use_fast=UpperCamelCase					,trust_remote_code=UpperCamelCase       )
					# Can't make an isinstance check because the new_model.config is from the FakeConfig class of a dynamic module
					self.assertEqual(tokenizer.__class__.__name__					,"CustomTokenizer"       )




class 					_snake_case						(			unittest.TestCase ):






	def    lowerCAmelCase_							(		self       )						->    List[Any]:
					snake_case__      :int         =   Trie()
					trie.add("Hello 友達"       )
					self.assertEqual(trie.data					,{"H": {"e": {"l": {"l": {"o": {" ": {"友": {"達": {"": 1}}}}}}}}}       )
					trie.add("Hello"       )
					trie.data
					self.assertEqual(trie.data					,{"H": {"e": {"l": {"l": {"o": {"": 1, " ": {"友": {"達": {"": 1}}}}}}}}}       )






	def    lowerCAmelCase_							(		self       )						->    int:
					snake_case__      :List[str]         =   Trie()
					self.assertEqual(trie.split("[CLS] This is a extra_id_100"       )					,["[CLS] This is a extra_id_100"]       )
					trie.add("[CLS]"       )
					trie.add("extra_id_1"       )
					trie.add("extra_id_100"       )
					self.assertEqual(trie.split("[CLS] This is a extra_id_100"       )					,["[CLS]", " This is a ", "extra_id_100"]       )






	def    lowerCAmelCase_							(		self       )						->    str:
					snake_case__      :Optional[Any]         =   Trie()
					trie.add("A"       )
					self.assertEqual(trie.split("ABC"       )					,["A", "BC"]       )
					self.assertEqual(trie.split("BCA"       )					,["BC", "A"]       )






	def    lowerCAmelCase_							(		self       )						->    Dict:
					snake_case__      :Any         =   Trie()
					trie.add("TOKEN]"       )
					trie.add("[SPECIAL_TOKEN]"       )
					self.assertEqual(trie.split("This is something [SPECIAL_TOKEN]"       )					,["This is something ", "[SPECIAL_TOKEN]"]       )






	def    lowerCAmelCase_							(		self       )						->    Tuple:
					snake_case__      :List[Any]         =   Trie()
					trie.add("A"       )
					trie.add("P"       )
					trie.add("[SPECIAL_TOKEN]"       )
					self.assertEqual(trie.split("This is something [SPECIAL_TOKEN]"       )					,["This is something ", "[SPECIAL_TOKEN]"]       )






	def    lowerCAmelCase_							(		self       )						->    Tuple:
					snake_case__      :str         =   Trie()
					trie.add("AB"       )
					trie.add("B"       )
					trie.add("C"       )
					self.assertEqual(trie.split("ABC"       )					,["AB", "C"]       )






	def    lowerCAmelCase_							(		self       )						->    Union[str, Any]:
					snake_case__      :Dict         =   Trie()
					trie.add("ABC"       )
					trie.add("B"       )
					trie.add("CD"       )
					self.assertEqual(trie.split("ABCD"       )					,["ABC", "D"]       )






	def    lowerCAmelCase_							(		self       )						->    int:
					# Even if the offsets are wrong, we necessarily output correct string
					# parts.
					snake_case__      :Optional[int]         =   Trie()
					snake_case__      :Union[str, Any]         =   trie.cut_text("ABC"					,[0, 0, 2, 1, 2, 3]       )
					self.assertEqual(UpperCamelCase					,["AB", "C"]       )