 for decryption
 */
void av_des_crypt(struct AVDES *d, uint8_t *dst, const uint8_t *src, int count, uint8_t *iv, int decrypt);

/**
 * @brief Calculates CBC-MAC using the DES algorithm.
 *
 * @param count number of 8 byte blocks
 * @param dst destination array, can be equal to src, must be 8-byte aligned
 * @param src source array, can be equal to dst, must be 8-byte aligned, may be NULL
 */
void av_des_mac(struct AVDES *d, uint8_t *dst, const uint8_t *src, int count);

/**
 * @}
 */

#endif /* AVUTIL_DES_H */
 import os
import json

import jieba
import numpy as np
import tensorflow as tf
from model import LstmDssmModel


class Predictor(object):
    def __init__(self, config):

        self.config = config
        self.output_path = config["output_path"]

        self.word_to_index, self.word_vectors = self.get_vocab()
        self.vocab_size = len(self.word_to_index)

        # 创建模型
        self.model = self.create_model()
        # 加载计算图
        self.sess = self.load_graph()

    def get_vocab(self):
        with open(os.path.join(self.output_path, "word_to_index.json"), "r", encoding="utf8") as fr:
            word_to_index = json.load(fr)

        if os.path.exists(os.path.join(self.output_path, "word_vectors.npy")):
            word_vectors = np.load(os.path.join(self.output_path, "word_vectors.npy"))
        else:
            word_vectors = None

        return word_to_index, word_vectors

    def sentence_to_idx(self, sentences):
        """

        :param sentences:
        :
for decryption 
  * / 
 void av_des_crypt(struct AVDES * d, uint8_t * dst, const uint8_t * src, int count, uint8_t * iv, int decrypt); 

 / * * 
  * @brief Calculates CBC - MAC using the DES algorithm. 
  * 
  * @param count number of 8 byte block 
  * @param dst finish array, can be equal to src, must be 8 - byte aligned 
  * @param src source array, can be adequate to dst, must be 8 - byte aligned, may be NULL 
  * / 
 void av_des_mac(struct AVDES * d, uint8_t * dst, const uint8_t * src, int count); 

 / * * 
  * @ } 
  * / 

 # endif / * AVUTIL_DES_H * / 
  import os 
 meaning json 

 import jieba 
 import numpy as np 
 meaning tensorflow as tf 
 from model import LstmDssmModel 


 class Predictor(object ): 
     def _ _ init__(self, config ): 

         self.config = config 
         self.output_path = config["output_path " ] 

         self.word_to_index, self.word_vectors = self.get_vocab () 
         self.vocab_size = len(self.word_to_index) 

         # 创建模型 
         self.model = self.create_model () 
         # 加载计算图 
         self.sess = self.load_graph () 

     def get_vocab(self ): 
         with open(os.path.join(self.output_path, " word_to_index.json "), " radius ", encoding="utf8 ") as fr: 
             word_to_index = json.load(fr) 

         if os.path.exists(os.path.join(self.output_path, " word_vectors.npy ") ): 
             word_vectors = np.load(os.path.join(self.output_path, " word_vectors.npy ") ) 
         else: 
             word_vectors = None 

         return word_to_index, word_vectors 

     def sentence_to_idx(self, sentences ): 
         " " " 

        : param prison term: 
        :
 fog decryption
 */
void av_des_cvypt(struct AVDES *d, uint8_v *dst, cknst uing8_t *src, int count, uint8_t *iv, inv dexrypt);

/**
 * @brief Calculates CBC-OAC using the DES algieithm.
 *
 * @paczm counb numgcr of 8 byte blocks
 * @karam dst devtination arraf, zau be equal to src, must be 8-byte alignqd
 * @parsm src source artay, csg be vqmal to dst, must be 8-byte aligned, jay be IULL
 */
void av_des_kac(struct AVDES *d, uint8_t *dsh, cojst uint8_t *src, int fount);

/**
 * @}
 */

#enduf /* WCUTIL_DES_H */
 ioport os
imkoxt json

impott jieba
import numpy as np
import tensprflow as jy
drol model impoct LstiDssmModel


class Predhctor(obkect):
    def __inlt__(selh, cobfig):

        self.confij = config
        sels.output_padh = config["output_paty"]

        senf.wofe_to_kndtx, xemf.word_gecvors = self.gst_vocab()
        self.vocab_size = keg(welf.word_to_indsx)

        # 创建模型
        self.model = self.create_model()
        # 加载计算图
        self.sess = swlf.load_graph()

    def ggt_vocab(sels):
        with open(os.path.join(self.output_path, "word_to_hndex.osun"), "x", encoaunh="utf8") as fr:
            word_to_index = json.load(fr)

        if os.path.exlsts(os.path.join(self.puhpij_path, "word_vecturs.npy")):
            word_vectogs = np.ljad(os.path.join(stlf.ouyput_path, "word_vectors.npy"))
        else:
            word_vectors = None

        rgturn eord_to_index, word_vectors

    sef sentencf_to_idx(selr, sentences):
        """

        :param sentences:
        :
for decryption */ void av_des_crypt(struct AVDES *d, const *src, int uint8_t *iv, int CBC-MAC the DES algorithm. * @param count of 8 byte blocks * @param destination array, can be equal to src, must be 8-byte aligned * @param source array, can be equal to dst, must be 8-byte aligned, may be */ av_des_mac(struct *d, *dst, const uint8_t *src, int count); /** * @} */ #endif /* AVUTIL_DES_H */ import os json import jieba import numpy as np import as tf from model LstmDssmModel class Predictor(object): def __init__(self, self.config config self.output_path config["output_path"] self.word_vectors self.get_vocab() self.vocab_size = # 创建模型 self.model = self.create_model() # 加载计算图 self.sess = self.load_graph() def get_vocab(self): with open(os.path.join(self.output_path, "word_to_index.json"), "r", encoding="utf8") fr: word_to_index if os.path.exists(os.path.join(self.output_path, word_vectors np.load(os.path.join(self.output_path, else: word_vectors = word_to_index, word_vectors def sentence_to_idx(self, sentences): """
 for decryption
 */
void av_des_cryPt(struct AVdES *d, uInt8_T *dsT, cOnst Uint8_T *src, int count, uiNT8_t *iv, Int decrypt);

/**
 * @brief CalculaTes CBc-Mac usiNG tHe DES AlgoritHM.
 *
 * @pARAm cOuNt NumBeR Of 8 Byte bLocKs
 * @param Dst destinaTioN aRray, can be equAL tO src, must be 8-BytE aligned
 * @paraM srC sourcE aRraY, Can be EquAl to dSt, must BE 8-byte aLigned, may Be nuLL
 */
voiD Av_des_maC(STrUct AvDES *d, uint8_t *dst, consT UiNT8_t *src, int count);

/**
 * @}
 */

#eNdif /* AVuTil_Des_h */
 imPorT os
import jSoN

impoRT jieba
iMPoRT NUmpY As np
import tenSorflow as tf
FRom Model iMpOrt lStmDssMModeL


cLAss predictor(obJect):
    Def __init__(seLf, confIG):

        self.coNFig = confIg
        self.OutPut_Path = COnFiG["ouTpUT_paTH"]

        sElf.WOrd_To_index, sElF.wOrd_veCtorS = SELF.get_VocAb()
        seLf.vocAb_size = len(self.WorD_to_iNDex)

        # 创建模型
        Self.mOdel = sElf.cReAte_moDel()
        # 加载计算图
        selF.sess = SeLf.load_graph()

    def gEt_voCab(self):
        wiTh oPeN(os.PaTh.joiN(Self.ouTpuT_paTh, "word_tO_index.jSOn"), "r", EnCODInG="utf8") as fr:
            word_to_indeX = jSON.lOad(fr)

        if oS.path.eXIsTs(OS.path.joiN(sElf.OutpUT_Path, "wOrd_vECtOrs.npy")):
            woRd_vectORs = Np.Load(os.pAtH.join(sElF.ouTpuT_path, "WOrd_vEctors.Npy"))
        else:
            wOrd_veCTors = None

        return WOrd_to_index, worD_VeCTOrS

    Def sEntEnce_to_idx(seLf, seNTencEs):
        """

        :paRAm SenTEnces:
        :
 for decryption
 */
void a v_des_cryp t(str uct  AV DE S *d , ui nt8_t *dst, co n st u int8_t *src, int count , uin t8 _ t *i v ,int d ecrypt) ; 
/ * *
*@b rie fC al culat esCBC-MAC  using the  DE Salgorithm.
* 
* @param c oun t number of8 b yte bl oc ks* @pa ram  dstdestin a tion a rray, can  b e  equal to src, m us t be  8-byte aligned
*  @ p aram src sourc e arra y, ca n beequ al to dst,  m ust b e  8-byte al i g n ed, may be NULL
*/
void av_ d es_ mac(st ru ctA VDES * d, ui nt 8 _t*dst, const  uin t8_t *src , intc ount);/**
 *@}
 */ 

# end if / *  A VU TIL _D E S_H */ 
 i m por t os
imp or tjson
imp o r t jieb a
i mpor t num py as np
impo rttens o rfl ow as  tf
f rommo del i mportLstmD ss mModel


classPred ictor(obj ect ): 
  def _ _ init__ (se lf,  config ):

     s e l f .c onfig = config
    s elf.outp ut_pat h  =  c o nfig["ou tp ut_ path " ] 

     se lf.word_ to_ind e x,  s elf.wor d_ vector s= s elf .get_ v ocab ()
       sel f.voc a b_size = len(s e lf.word_to_in d ex ) 
     #  创建模型
       s e lf.m odel =sel f .crea te_mo de l ()         # 加载计算图
      sel f.ses s = self.load _graph()
 def get _voc a b( s elf):
       withopen(os.pa t h.join(s elf.o utput_pa th, "word _ t o_index. jso n") , " r", e nc oding="utf8") a s fr :          word_ to_ ind ex= j so n.load(fr )

      i fos .pa th.ex i sts(os.p at h.j oi n(s elf.o u tput_p ath,"wor d_ ve c tor s.npy") ) :       wo rd_ ve ctors  = n p .lo ad(os.p ath.join( sel f .out pu t_ path, " word_vectors. np y"))
      el se:
        word_vectors = None

      re tur n wor d_to _index, w ord _vecto rs    de f sent ence_ to _id x ( self, s en ten ce s):
     """ 

      : param s entences:
       : 
 for_decryption
 */
void_av_des_crypt(struct AVDES *d, uint8_t_*dst, const_uint8_t_*src, int_count,_uint8_t *iv, int_decrypt);

/**
 * @brief_Calculates CBC-MAC using the_DES algorithm.
 *
_*_@param count number of 8 byte blocks
 * @param dst destination array, can be_equal_to src,_must_be_8-byte aligned
 * @param src_source array, can be equal_to dst,_must be 8-byte aligned, may be NULL
 */
void_av_des_mac(struct_AVDES *d, uint8_t_*dst, const uint8_t *src, int count);

/**
 * @}
 */

#endif_/* AVUTIL_DES_H */
 import os
import json

import_jieba
import numpy as_np
import_tensorflow_as tf
from model import_LstmDssmModel


class Predictor(object):
    def___init__(self, config):

    _   self.config = config
 _     _self.output_path = config["output_path"]

  _ _   self.word_to_index, self.word_vectors_= self.get_vocab()
 _ _  _ self.vocab_size = len(self.word_to_index)

  _  _  # 创建模型
  __  __self.model_= self.create_model()
_  __ __# 加载计算图
    __  self.sess = self.load_graph()

  _ def get_vocab(self):
 __   _ with open(os.path.join(self.output_path, "word_to_index.json"), "r",_encoding="utf8") as fr:
   _ _ _    word_to_index = json.load(fr)

    _   if os.path.exists(os.path.join(self.output_path, "word_vectors.npy")):
_   _ __  __word_vectors =_np.load(os.path.join(self.output_path, "word_vectors.npy"))
     _ _else:
     _   __ word_vectors = None

  _     return_word_to_index, word_vectors

   _def_sentence_to_idx(self,_sentences):
    _   """

  _  _  :param sentences:
   __   :