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Re-initialisation is not supported.gensim.models.word2vec_corpusfilecompiletime version %s of module '%.100s' does not match runtime version %sShared Cython type %.200s is not a type objectShared Cython type %.200s has the wrong size, try recompiling__pyx_t_6gensim_6models_19word2vec_corpusfile_REAL_t (__pyx_t_6gensim_6models_19word2vec_corpusfile_REAL_t, __pyx_t_6gensim_6models_19word2vec_corpusfile_REAL_t, int, int)__pyx_t_6gensim_6models_19word2vec_corpusfile_REAL_t (__pyx_t_6gensim_6models_19word2vec_corpusfile_REAL_t, __pyx_t_6gensim_6models_19word2vec_corpusfile_REAL_t, PY_LONG_LONG, PY_LONG_LONG, PY_LONG_LONG, PY_LONG_LONG, int, int)Unable to initialize pickling for %s__pyx_t_6gensim_6models_14word2vec_inner_scopy_ptr__pyx_t_6gensim_6models_14word2vec_inner_saxpy_ptr__pyx_t_6gensim_6models_14word2vec_inner_sdot_ptr__pyx_t_6gensim_6models_14word2vec_inner_dsdot_ptr__pyx_t_6gensim_6models_14word2vec_inner_snrm2_ptr__pyx_t_6gensim_6models_14word2vec_inner_sscal_ptr__pyx_t_6gensim_6models_14word2vec_inner_REAL_t [0x3E8]__pyx_t_6gensim_6models_14word2vec_inner_our_dot_ptr__pyx_t_6gensim_6models_14word2vec_inner_our_saxpy_ptrunsigned PY_LONG_LONG (unsigned PY_LONG_LONG *)void (__pyx_t_5numpy_uint32_t const *, __pyx_t_5numpy_uint8_t const *, int const , __pyx_t_6gensim_6models_14word2vec_inner_REAL_t *, __pyx_t_6gensim_6models_14word2vec_inner_REAL_t *, int const , __pyx_t_5numpy_uint32_t const , __pyx_t_6gensim_6models_14word2vec_inner_REAL_t const , __pyx_t_6gensim_6models_14word2vec_inner_REAL_t *, __pyx_t_6gensim_6models_14word2vec_inner_REAL_t *, __pyx_t_5numpy_uint32_t const , int const , __pyx_t_6gensim_6models_14word2vec_inner_REAL_t *)unsigned PY_LONG_LONG (int const , __pyx_t_5numpy_uint32_t *, unsigned PY_LONG_LONG, __pyx_t_6gensim_6models_14word2vec_inner_REAL_t *, __pyx_t_6gensim_6models_14word2vec_inner_REAL_t *, int const , __pyx_t_5numpy_uint32_t const , __pyx_t_5numpy_uint32_t const , __pyx_t_6gensim_6models_14word2vec_inner_REAL_t const , __pyx_t_6gensim_6models_14word2vec_inner_REAL_t *, unsigned PY_LONG_LONG, __pyx_t_6gensim_6models_14word2vec_inner_REAL_t *, __pyx_t_5numpy_uint32_t const , int const , __pyx_t_6gensim_6models_14word2vec_inner_REAL_t *)void (__pyx_t_5numpy_uint32_t const *, __pyx_t_5numpy_uint8_t const *, int *, __pyx_t_6gensim_6models_14word2vec_inner_REAL_t *, __pyx_t_6gensim_6models_14word2vec_inner_REAL_t *, __pyx_t_6gensim_6models_14word2vec_inner_REAL_t *, int const , __pyx_t_5numpy_uint32_t const *, __pyx_t_6gensim_6models_14word2vec_inner_REAL_t const , __pyx_t_6gensim_6models_14word2vec_inner_REAL_t *, int, int, int, int, __pyx_t_6gensim_6models_14word2vec_inner_REAL_t *, __pyx_t_5numpy_uint32_t const , int const , __pyx_t_6gensim_6models_14word2vec_inner_REAL_t *)unsigned PY_LONG_LONG (int const , __pyx_t_5numpy_uint32_t *, unsigned PY_LONG_LONG, int *, __pyx_t_6gensim_6models_14word2vec_inner_REAL_t *, __pyx_t_6gensim_6models_14word2vec_inner_REAL_t *, __pyx_t_6gensim_6models_14word2vec_inner_REAL_t *, int const , __pyx_t_5numpy_uint32_t const *, __pyx_t_6gensim_6models_14word2vec_inner_REAL_t const , __pyx_t_6gensim_6models_14word2vec_inner_REAL_t *, int, int, int, int, unsigned PY_LONG_LONG, __pyx_t_6gensim_6models_14word2vec_inner_REAL_t *, __pyx_t_5numpy_uint32_t const , int const , __pyx_t_6gensim_6models_14word2vec_inner_REAL_t *)PyObject *(struct __pyx_t_6gensim_6models_14word2vec_inner_Word2VecConfig *, PyObject *, PyObject *, PyObject *, PyObject *, struct __pyx_opt_args_6gensim_6models_14word2vec_inner_init_w2v_config *__pyx_optional_args)Cython module failed to register with collections.abc modulegensim/models/word2vec_corpusfile.pyxinit 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±PèøWP3¨$	þÿÿo€2ÿÿÿoðÿÿo¢0ùÿÿo@
(L6pFpVpfpvp†p–p¦p¶pÆpÖpæpöpqq&q6qFqVqfqvq†q–q¦q¶qÆqÖqæqöqrr&r6rFrVrfrvr†r–r¦r¶rÆrÖrærörss&s6sFsVsfsvs†s–s¦s¶sÆsÖsæsöstt&t6tFtVtftvt†t–t¦t¶tÆtÖtætötuu&u6uFuVufuvu†u–u¦u¶uÆuÖuæuöuvv&v6vFvVvfvvv†v–v¦v¶vÆvÖvævövww&w6wFwVwfwvw†w–w¦w¶wÆwÖwæwöwxx&x6xFxVxfxvx†x–x¦x¶xÆxÖxæxöxyy&y6yFyVyfyvy†y–y¦y¶yÆyÖyæyöyzzÿÿÿÿÿÿÿÿtrain_epoch_cbow(model, corpus_file, offset, _cython_vocab, _cur_epoch, _expected_examples, _expected_words, _work, _neu1, compute_loss)
Train CBOW model for one epoch by training on an input stream. This function is used only in multistream mode.

    Called internally from :meth:`~gensim.models.word2vec.Word2Vec.train`.

    Parameters
    ----------
    model : :class:`~gensim.models.word2vec.Word2Vec`
        The Word2Vec model instance to train.
    corpus_file : str
        Path to corpus file.
    _cur_epoch : int
        Current epoch number. Used for calculating and decaying learning rate.
    _work : np.ndarray
        Private working memory for each worker.
    _neu1 : np.ndarray
        Private working memory for each worker.
    compute_loss : bool
        Whether or not the training loss should be computed in this batch.

    Returns
    -------
    int
        Number of words in the vocabulary actually used for training (They already existed in the vocabulary
        and were not discarded by negative sampling).
    train_epoch_sg(model, corpus_file, offset, _cython_vocab, _cur_epoch, _expected_examples, _expected_words, _work, _neu1, compute_loss)
Train Skipgram model for one epoch by training on an input stream. This function is used only in multistream mode.

    Called internally from :meth:`~gensim.models.word2vec.Word2Vec.train`.

    Parameters
    ----------
    model : :class:`~gensim.models.word2vec.Word2Vec`
        The Word2Vec model instance to train.
    corpus_file : str
        Path to corpus file.
    _cur_epoch : int
        Current epoch number. Used for calculating and decaying learning rate.
    _work : np.ndarray
        Private working memory for each worker.
    _neu1 : np.ndarray
        Private working memory for each worker.
    compute_loss : bool
        Whether or not the training loss should be computed in this batch.

    Returns
    -------
    int
        Number of words in the vocabulary actually used for training (They already existed in the vocabulary
        and were not discarded by negative sampling).
    CythonLineSentence.next_batch(self) -> vector[vector[string]]CythonLineSentence.__reduce__(self)CythonLineSentence.reset(self) -> voidCythonLineSentence._chunk_sentence(self, vector[string] sent) -> vector[vector[string]]CythonLineSentence._read_chunked_sentence(self) -> vector[vector[string]]CythonLineSentence.read_sentence(self) -> vector[string]CythonLineSentence.is_eof(self) -> boolrebuild_cython_line_sentence(source, max_sentence_length)CythonVocab.__setstate_cython__(self, __pyx_state)CythonVocab.__reduce_cython__(self)
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