
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils_fast import AddedToken, PreTrainedTokenizerFast
from ...utils import logging


__SCREAMING_SNAKE_CASE				:							int		       =		logging.get_logger(__name__)

__SCREAMING_SNAKE_CASE				:							List[Any]		       =		{"vocab_file": "spiece.model", "tokenizer_file": "tokenizer.json"}

__SCREAMING_SNAKE_CASE				:							List[str]		       =		{
    "vocab_file": {
        "TsinghuaAI/CPM-Generate": "https://huggingface.co/TsinghuaAI/CPM-Generate/resolve/main/spiece.model",
    },
    "tokenizer_file": {
        "TsinghuaAI/CPM-Generate": "https://huggingface.co/TsinghuaAI/CPM-Generate/resolve/main/tokenizer.json",
    },
}






class 				__lowerCAmelCase      (      UpperCamelCase_	):

						"""simple docstring"""






						def __init__(     self       :			int   ,     lowerCAmelCase       :			int=None   ,     lowerCAmelCase       :			Optional[int]=None   ,     lowerCAmelCase       :			Tuple=False   ,     lowerCAmelCase       :			Dict=True   ,     lowerCAmelCase       :			Optional[int]=False   ,     lowerCAmelCase       :			Optional[int]="<s>"   ,     lowerCAmelCase       :			int="</s>"   ,     lowerCAmelCase       :			Optional[int]="<unk>"   ,     lowerCAmelCase       :			Any="<sep>"   ,     lowerCAmelCase       :			int="<pad>"   ,     lowerCAmelCase       :			Optional[int]="<cls>"   ,     lowerCAmelCase       :			Any="<mask>"   ,     lowerCAmelCase       :			Optional[int]=["<eop>", "<eod>"]   ,     **lowerCAmelCase       :			Any   ,     ):
													A_ 						=		AddedToken(__UpperCamelCase   ,     lstrip=__UpperCamelCase   ,     rstrip=__UpperCamelCase  ) if isinstance(__UpperCamelCase   ,     __UpperCamelCase  ) else mask_token

													super().__init__(
													    vocab_file=__UpperCamelCase   ,     tokenizer_file=__UpperCamelCase   ,     do_lower_case=__UpperCamelCase   ,     remove_space=__UpperCamelCase   ,     keep_accents=__UpperCamelCase   ,     bos_token=__UpperCamelCase   ,     eos_token=__UpperCamelCase   ,     unk_token=__UpperCamelCase   ,     sep_token=__UpperCamelCase   ,     pad_token=__UpperCamelCase   ,     cls_token=__UpperCamelCase   ,     mask_token=__UpperCamelCase   ,     additional_special_tokens=__UpperCamelCase   ,     **__UpperCamelCase   ,     )

													A_ 						=		3
													A_ 						=		do_lower_case
													A_ 						=		remove_space
													A_ 						=		keep_accents
													A_ 						=		vocab_file
													A_ 						=		False if not self.vocab_file else True

													try:
																				import jieba
													except ModuleNotFoundError as error:
																				raise error.__class__(
																				    "You need to install jieba to use CpmTokenizer or CpmTokenizerFast. "
																				    "See https://pypi.org/project/jieba/ for installation."  )
													A_ 						=		jieba
													A_ 						=		str.maketrans(" \n"   ,     "\u2582\u2583"  )






						def 							_UpperCAmelCase					(     self       :			str   ,     lowerCAmelCase       :			int   ,     lowerCAmelCase       :			List[str] = None  ):
													A_ 						=		[self.sep_token_id]
													A_ 						=		[self.cls_token_id]
													if token_ids_a is None:
																				return token_ids_a + sep + cls
													return token_ids_a + sep + token_ids_a + sep + cls






						def 							_UpperCAmelCase					(     self       :			Tuple   ,     lowerCAmelCase       :			int   ,     lowerCAmelCase       :			int = None  ):
													A_ 						=		[self.sep_token_id]
													A_ 						=		[2]

													if token_ids_a is None:
																				return len(token_ids_a + sep  ) * [0] + cls_segment_id
													return len(token_ids_a + sep  ) * [0] + len(token_ids_a + sep  ) * [1] + cls_segment_id






						def 							_UpperCAmelCase					(     self       :			str   ,     lowerCAmelCase       :			Any   ,     lowerCAmelCase       :			Any = None  ):


													if not self.can_save_slow_tokenizer:
																				raise ValueError(
																				    "Your fast tokenizer does not have the necessary information to save the vocabulary for a slow "
																				    "tokenizer."  )

													if not os.path.isdir(__UpperCamelCase  ):
																				logger.error(F"Vocabulary path ({save_directory}) should be a directory"  )
																				return
													A_ 						=		os.path.join(
													    __UpperCamelCase   ,     (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]  )

													if os.path.abspath(self.vocab_file  ) != os.path.abspath(__UpperCamelCase  ):
																				copyfile(self.vocab_file   ,     __UpperCamelCase  )

													return (out_vocab_file,)






						def 							_UpperCAmelCase					(     self       :			int   ,     lowerCAmelCase       :			Union[str, Any]   ,     *lowerCAmelCase       :			Optional[Any]   ,     **lowerCAmelCase       :			Dict  ):
													A_ 						=		[
													    ''' '''.join([x.translate(self.translator  ) for x in self.jieba.cut(__UpperCamelCase   ,     cut_all=__UpperCamelCase  )]  )
													    for text in batch_text_or_text_pairs
													]
													return super()._batch_encode_plus(__UpperCamelCase   ,     *__UpperCamelCase   ,     **__UpperCamelCase  )






						def 							_UpperCAmelCase					(     self       :			List[Any]   ,     *lowerCAmelCase       :			Any   ,     **lowerCAmelCase       :			str  ):
													A_ 						=		super()._decode(*__UpperCamelCase   ,     **__UpperCamelCase  )
													A_ 						=		text.replace(" "   ,     ""  ).replace("\u2582"   ,     " "  ).replace("\u2583"   ,     "\n"  )
													return text









'''simple docstring'''
import unittest

import numpy as np

from transformers import is_tf_available
from transformers.testing_utils import require_tf


if is_tf_available():
							import tensorflow as tf

							from transformers.activations_tf import get_tf_activation






@require_tf
class 				__lowerCAmelCase      (      unittest.TestCase	):

						"""simple docstring"""






						def 							_UpperCAmelCase					(     self       :			List[Any]  ):
													A_ 						=		tf.constant([-1_00, -1.0, -0.1, 0, 0.1, 1.0, 1_0_0.0]  )
													A_ 						=		get_tf_activation("gelu"  )
													A_ 						=		get_tf_activation("gelu_10"  )

													A_ 						=		gelu(lowerCAmelCase  )
													A_ 						=		geluaa(lowerCAmelCase  )

													A_ 						=		tf.where(y_gelu_aa < 1_0.0   ,     1.0   ,     0.0  )

													self.assertEqual(tf.math.reduce_max(lowerCAmelCase  ).numpy().item()   ,     1_0.0  )
													self.assertTrue(np.allclose(y_gelu * clipped_mask   ,     y_gelu_aa * clipped_mask  )  )






						def 							_UpperCAmelCase					(     self       :			Union[str, Any]  ):
													get_tf_activation("gelu"  )
													get_tf_activation("gelu_10"  )
													get_tf_activation("gelu_fast"  )
													get_tf_activation("gelu_new"  )
													get_tf_activation("glu"  )
													get_tf_activation("mish"  )
													get_tf_activation("quick_gelu"  )
													get_tf_activation("relu"  )
													get_tf_activation("sigmoid"  )
													get_tf_activation("silu"  )
													get_tf_activation("swish"  )
													get_tf_activation("tanh"  )
													with self.assertRaises(lowerCAmelCase  ):
																				get_tf_activation("bogus"  )
													with self.assertRaises(lowerCAmelCase  ):
																				get_tf_activation(lowerCAmelCase  )





