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ÿÿD	ÿÿFÿÿkÿÿÿÿµÿÿÚÿÿÿÿÿ$ÿÿIÿÿqÿÿ™ÿÿÑCÿÿ_Cÿÿ=>ÿÿ4>ÿÿ+>ÿÿ">ÿÿÄCÿÿ[Cÿÿ€Cÿÿ¥CÿÿDÿÿunable to allocate shape and strides.numpy.core.umath failed to importno default __reduce__ due to non-trivial __cinit__got differing extents in dimension %d (got %d and %d)Unable to convert item to objectOut of bounds on buffer access (axis %d)Invalid mode, expected 'c' or 'fortran', got %sIndirect dimensions not supportedIncompatible checksums (%s vs 0xcc6d452 = (_multitasks, _rehearsal_model, cfg, model, moves, name, scorer, vocab))Incompatible checksums (%s vs 0xb068931 = (name))Empty shape tuple for cython.arrayDependencyParser.add_multitask_objectiveDependencyParser.__setstate_cython__DependencyParser.__reduce_cython__Cannot create writable memory view from read-only memoryviewCannot assign to read-only memoryviewCan only create a buffer that is contiguous in memory.Buffer view does not expose strides_parser_internals.transition_systemnumpy.core.multiarray failed to import
[model]
@architectures = "spacy.TransitionBasedParser.v2"
state_type = "parser"
extra_state_tokens = false
hidden_width = 64
maxout_pieces = 2
use_upper = true

[model.tok2vec]
@architectures = "spacy.HashEmbedCNN.v2"
pretrained_vectors = null
width = 96
depth = 4
embed_size = 2000
window_size = 1
maxout_pieces = 3
subword_features = true
DependencyParser.init_multitask_objectivesDependencyParser._ensure_labels_are_added<strided and direct or indirect>parser_score.<locals>.dep_getterDependencyParser.scored_parsesunable to allocate array data.spacy/pipeline/dep_parser.pyx__pyx_unpickle_DependencyParserparser_score.<locals>.has_sentsupdate_with_oracle_cut_sizeitemsize <= 0 for cython.arrayspacy.pipeline.dep_parserinit_multitask_objectivesInvalid shape in axis %d: %d._parser_internals.nonprojCannot index with type '%s'_ensure_labels_are_added<contiguous and indirect>add_multitask_objective<MemoryView of %r at 0x%x>spacy.parser_scorer.v1<MemoryView of %r object>default_score_weights<contiguous and direct><strided and indirect>default_model_configDEFAULT_PARSER_MODELtoken.is_sent_startincorrect_spans_key<strided and direct>make_parser_scorercline_in_traceback__pyx_unpickle_Enumscore_label_dict_parser_internalsmake_beam_parserdep_las_per_typebeam_update_probTransitionSystemDependencyParser__setstate_cython__score_head_dict__pyx_PickleErrormin_action_freqmerge_subtokensget_beam_parsesdtype_is_objectallocate_bufferView.MemoryViewsents_per_typehas_annotationdeprojectivizedefault_configscored_parses__reduce_cython____pyx_getbufferignore_labelsuse_setstatestringsource__pyx_checksumparser_scoreoutput_layermt_componentlearn_tokenslabel_scoresget_examplesbeam_densityscore_spansmake_parserhead_scoresdefaultdictcollectionsbeam_parserPickleErrorMemoryErrorImportErrortoken.headsetdefaultscore_deps__pyx_vtable____pyx_resultmultitasksmove_namesinitializedep_getterbeam_widthValueErrorSENT_STARTIndexErrortoken.depthinc.apiscorers__reduce_ex____pyx_statehas_sentsfunctionsenumeratedoc.sentsas_stringTypeErrorDELIMITER__setstate__registry__pyx_typelanguagelabelleritemsize__getstate__from_strexamplesOptionalLanguageIterableEllipsisCallablestringsset_dimsents_rsents_psents_f@scorersresultsnonprojmemviewhas_refget_reffortranfactorydep_uasdep_lasassignsupdateunpacktypingstructscorer__reduce__pickleparsesparser__name__labelskwargs__import__getterformatencode_dictappendScorerConfigvocabtokensuperstatestartsplitshapesentsscorerangepunctmovesmodellowerlabelitemsfloatflagserror__class__beamsModelASCIIutil__test__stopstepsizeselfpackndimnamemode__main____init__headdocs__dict__beambaseattrobjnlp__new__intgetdocdepcfg-nOidpicO%s() got multiple values for keyword argument '%U'%.200s() keywords must be strings%s() got an unexpected keyword argument '%U'%.200s() takes no arguments (%zd given)%.200s() takes exactly one argument (%zd given)Bad call flags in __Pyx_CyFunction_Call. METH_OLDARGS is no longer supported!%.200s() takes no keyword arguments while calling a Python objectNULL result without error in PyObject_Call%.200s.%.200s is not a type object%.200s.%.200s size changed, may indicate binary incompatibility. Expected %zd from C header, got %zd from PyObject%s.%s size changed, may indicate binary incompatibility. Expected %zd from C header, got %zd from PyObjectinvalid vtable found for imported type%.200s does not export expected C variable %.200sC variable %.200s.%.200s has wrong signature (expected %.500s, got %.500s)Interpreter change detected - this module can only be loaded into one interpreter per process.Acquisition count is %d (line %d)__annotations__ must be set to a dict object__defaults__ must be set to a tuple object__kwdefaults__ must be set to a dict object__qualname__ must be set to a string object__name__ must be set to a string objectfunction's dictionary may not be deletedsetting function's dictionary to a non-dict__int__ returned non-int (type %.200s).  The ability to return an instance of a strict subclass of int is deprecated, and may be removed in a future version of Python.__%.4s__ returned non-%.4s (type %.200s)vector::_M_range_check: __n (which is %zu) >= this->size() (which is %zu)View.MemoryView.refcount_objects_in_sliceView.MemoryView.refcount_objects_in_slice_with_gilView.MemoryView.array.__dealloc__View.MemoryView.memoryview.__dealloc__value too large to convert to intraise: exception class must be a subclass of BaseExceptioncalling %R should have returned an instance of BaseException, not %R'%.200s' object is not subscriptablecannot fit '%.200s' into an index-sized integerView.MemoryView._memoryviewslice.__dealloc__View.MemoryView._memoryviewslice.base.__get__View.MemoryView.memoryview.size.__get__View.MemoryView.memoryview.nbytes.__get__View.MemoryView.memoryview.itemsize.__get__View.MemoryView.memoryview.ndim.__get__View.MemoryView.memoryview.suboffsets.__get__View.MemoryView.memoryview.shape.__get__View.MemoryView.memoryview.base.__get__Cannot convert %.200s to %.200sView.MemoryView.get_slice_from_memviewView.MemoryView.memoryview.is_f_contigView.MemoryView.memoryview.is_c_contigView.MemoryView.memoryview.__str__View.MemoryView.memoryview.__len__View.MemoryView.memoryview.setitem_indexedView.MemoryView.array.memview.__get__View.MemoryView.array.__getattr__View.MemoryView.array.__setitem__Subscript deletion not supported by %.200sView.MemoryView.array.get_memviewView.MemoryView.array.__getitem__View.MemoryView._memoryviewslice.__setstate_cython__View.MemoryView._memoryviewslice.__reduce_cython__View.MemoryView.memoryview.__setstate_cython__View.MemoryView.memoryview.__reduce_cython__View.MemoryView.array.__setstate_cython__View.MemoryView.array.__reduce_cython__spacy.pipeline.dep_parser.DependencyParser._ensure_labels_are_addedspacy.pipeline.dep_parser.make_parser_scorer'%.50s' object has no attribute '%U'View.MemoryView.memoryview_fromsliceView.MemoryView.memoryview_copy_from_sliceView.MemoryView.assert_direct_dimensionsView.MemoryView.memoryview.setitem_slice_assign_scalar%.200s() takes %.8s %zd positional argument%.1s (%zd given)View.MemoryView.memoryview.strides.__get__View.MemoryView.memoryview.__repr__spacy.pipeline.dep_parser.DependencyParser.postprocesses.__get__spacy.pipeline.dep_parser.parser_score.has_sentsPyObject_GetBuffer: view==NULL argument is obsoleteView.MemoryView.memoryview.__getbuffer__View.MemoryView.array.__getbuffer__spacy.pipeline.dep_parser.DependencyParser.add_multitask_objective'NoneType' object is not subscriptablehasattr(): attribute name must be stringView.MemoryView.__pyx_unpickle_Enum__set_stateView.MemoryView.Enum.__setstate_cython__Cannot transpose memoryview with indirect dimensionsView.MemoryView.transpose_memsliceView.MemoryView.memoryview_copyView.MemoryView.memoryview.T.__get__View.MemoryView.copy_data_to_tempView.MemoryView.memoryview_copy_contentsCannot copy memoryview slice with indirect dimensions (axis %d)View.MemoryView.array_cwrapperView.MemoryView.memoryview_cwrappermemviewslice is already initialized!View.MemoryView.memoryview.copy_fortranView.MemoryView.memoryview.copyView.MemoryView.memoryview.setitem_slice_assignmentView.MemoryView.memoryview.assign_item_from_objectView.MemoryView._memoryviewslice.assign_item_from_objectView.MemoryView.memoryview.is_sliceView.MemoryView.Enum.__reduce_cython__spacy.pipeline.dep_parser.DependencyParser.__reduce_cython__spacy.pipeline.dep_parser.parser_score.dep_getter__pyx_unpickle_DependencyParser__set_statespacy.pipeline.dep_parser.__pyx_unpickle_DependencyParser__set_statespacy.pipeline.dep_parser.DependencyParser.__setstate_cython__View.MemoryView.memoryview.__cinit____pyx_unpickle_DependencyParserspacy.pipeline.dep_parser.__pyx_unpickle_DependencyParserView.MemoryView.__pyx_unpickle_Enumdictionary changed size during iterationtoo many values to unpack (expected %zd)need more than %zd value%.1s to unpack'NoneType' object is not iterablespacy.pipeline.dep_parser.parser_scorespacy.pipeline.dep_parser.DependencyParser.__init__Unable to initialize pickling for %sModule 'dep_parser' has already been imported. Re-initialisation is not supported.compiletime 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 recompilingspacy.pipeline.transition_parserspacy.pipeline._parser_internals.stateclassspacy.pipeline._parser_internals.transition_systemspacy.pipeline._parser_internals.arc_eagerstruct __pyx_t_5spacy_7structs_LexemeC__pyx_t_5spacy_8typedefs_attr_t%.200s does not export expected C function %.200suint64_t (void *, int, uint64_t)C function %.200s.%.200s has wrong signature (expected %.500s, got %.500s)__Pyx_PyMODINIT_FUNC PyInit_dep_parser(void)init spacy.pipeline.dep_parserspacy.pipeline.dep_parser.DependencyParser.init_multitask_objectivesView.MemoryView.memoryview.convert_item_to_objectView.MemoryView._memoryviewslice.convert_item_to_objectinteger division or modulo by zerovalue too large to perform divisionView.MemoryView.pybuffer_indexView.MemoryView.memoryview.get_item_pointerspacy.pipeline.dep_parser.make_parserspacy.pipeline.dep_parser.make_beam_parserspacy.pipeline.dep_parser.DependencyParser.scored_parsesView.MemoryView.array.__cinit__Argument '%.200s' has incorrect type (expected %.200s, got %.200s)Argument '%.200s' must not be Noneobject of type 'NoneType' has no len()expected bytes, NoneType foundView.MemoryView.memoryview.__setitem__spacy.pipeline.dep_parser.DependencyParser.labels.__get__All dimensions preceding dimension %d must be indexed and not slicedView.MemoryView.slice_memviewsliceStep may not be zero (axis %d)local variable '%s' referenced before assignmentView.MemoryView.memoryview.__getitem__spacy/pipeline/_parser_internals/_state.pxdspacy.pipeline.dep_parser._memoryviewsliceInternal class for passing memoryview slices to Pythonspacy.pipeline.dep_parser.memoryviewspacy.pipeline.dep_parser.Enumspacy.pipeline.dep_parser.arrayspacy.pipeline.dep_parser.DependencyParserDependencyParser(vocab, model, name='parser', moves=None, update_with_oracle_cut_size=100, *, min_action_freq=30, learn_tokens=False, beam_width=1, beam_density=0.0, beam_update_prob=0.0, multitasks=tuple(), incorrect_spans_key=None, scorer=parser_score)
Pipeline component for dependency parsing.

    DOCS: https://spacy.io/api/dependencyparser
    vector::_M_realloc_insert59__pyx_t_5spacy_8pipeline_17_parser_internals_6_state_StateCà?{®Gáz„?ð?0123456789not enough space for format expansion (Please submit full bug report at https://gcc.gnu.org/bugsbasic_string::_S_construct null not validbasic_string::_M_construct null not validbasic_string::_M_create%s: __pos (which is %zu) > this->size() (which is %zu)basic_string::at: __n (which is %zu) >= this->size() (which is %zu)basic_string::erasebasic_string::_M_replace_auxbasic_string::insertbasic_string::replacebasic_string::_M_replacebasic_string::assignbasic_string::appendbasic_string::copybasic_string::comparebasic_string::basic_stringstring::stringbasic_string::substrÿÿÿÿÿÿÿÿ
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ÿÿÿÿÿÿÿÿ__pyx_unpickle_DependencyParser(__pyx_type, long __pyx_checksum, __pyx_state)DependencyParser.__setstate_cython__(self, __pyx_state)DependencyParser.__reduce_cython__(self)DependencyParser._ensure_labels_are_added(self, docs)DependencyParser.scored_parses(self, beams)
Return two dictionaries with scores for each beam/doc that was processed:
        one containing (i, head) keys, and another containing (i, label) keys.
        DependencyParser.init_multitask_objectives(self, get_examples, nlp=None, **cfg)DependencyParser.add_multitask_objective(self, mt_component)Create a DependencyParser.
        make_parser_scorer()parser_score(examples, **kwargs)
Score a batch of examples.

    examples (Iterable[Example]): The examples to score.
    RETURNS (Dict[str, Any]): The scores, produced by Scorer.score_spans
        and Scorer.score_deps.

    DOCS: https://spacy.io/api/dependencyparser#score
    make_beam_parser(nlp: Language, name: str, model: Model, moves: Optional[TransitionSystem], update_with_oracle_cut_size: int, learn_tokens: bool, min_action_freq: int, beam_width: int, beam_density: float, beam_update_prob: float, scorer: Optional[Callable])
Create a transition-based DependencyParser component that uses beam-search.
    The dependency parser jointly learns sentence segmentation and labelled
    dependency parsing, and can optionally learn to merge tokens that had been
    over-segmented by the tokenizer.

    The parser uses a variant of the non-monotonic arc-eager transition-system
    described by Honnibal and Johnson (2014), with the addition of a "break"
    transition to perform the sentence segmentation. Nivre's pseudo-projective
    dependency transformation is used to allow the parser to predict
    non-projective parses.

    The parser is trained using a global objective. That is, it learns to assign
    probabilities to whole parses.

    model (Model): The model for the transition-based parser. The model needs
        to have a specific substructure of named components --- see the
        spacy.ml.tb_framework.TransitionModel for details.
    moves (Optional[TransitionSystem]): This defines how the parse-state is created,
        updated and evaluated. If 'moves' is None, a new instance is
        created with `self.TransitionSystem()`. Defaults to `None`.
    update_with_oracle_cut_size (int): During training, cut long sequences into
        shorter segments by creating intermediate states based on the gold-standard
        history. The model is not very sensitive to this parameter, so you usually
        won't need to change it. 100 is a good default.
    beam_width (int): The number of candidate analyses to maintain.
    beam_density (float): The minimum ratio between the scores of the first and
        last candidates in the beam. This allows the parser to avoid exploring
        candidates that are too far behind. This is mostly intended to improve
        efficiency, but it can also improve accuracy as deeper search is not
        always better.
    beam_update_prob (float): The chance of making a beam update, instead of a
        greedy update. Greedy updates are an approximation for the beam updates,
        and are faster to compute.
    learn_tokens (bool): Whether to learn to merge subtokens that are split
        relative to the gold standard. Experimental.
    min_action_freq (int): The minimum frequency of labelled actions to retain.
        Rarer labelled actions have their label backed-off to "dep". While this
        primarily affects the label accuracy, it can also affect the attachment
        structure, as the labels are used to represent the pseudo-projectivity
        transformation.
    make_parser(nlp: Language, name: str, model: Model, moves: Optional[TransitionSystem], update_with_oracle_cut_size: int, learn_tokens: bool, min_action_freq: int, scorer: Optional[Callable])
Create a transition-based DependencyParser component. The dependency parser
    jointly learns sentence segmentation and labelled dependency parsing, and can
    optionally learn to merge tokens that had been over-segmented by the tokenizer.

    The parser uses a variant of the non-monotonic arc-eager transition-system
    described by Honnibal and Johnson (2014), with the addition of a "break"
    transition to perform the sentence segmentation. Nivre's pseudo-projective
    dependency transformation is used to allow the parser to predict
    non-projective parses.

    The parser is trained using an imitation learning objective. The parser follows
    the actions predicted by the current weights, and at each state, determines
    which actions are compatible with the optimal parse that could be reached
    from the current state. The weights such that the scores assigned to the
    set of optimal actions is increased, while scores assigned to other
    actions are decreased. Note that more than one action may be optimal for
    a given state.

    model (Model): The model for the transition-based parser. The model needs
        to have a specific substructure of named components --- see the
        spacy.ml.tb_framework.TransitionModel for details.
    moves (Optional[TransitionSystem]): This defines how the parse-state is created,
        updated and evaluated. If 'moves' is None, a new instance is
        created with `self.TransitionSystem()`. Defaults to `None`.
    update_with_oracle_cut_size (int): During training, cut long sequences into
        shorter segments by creating intermediate states based on the gold-standard
        history. The model is not very sensitive to this parameter, so you usually
        won't need to change it. 100 is a good default.
    learn_tokens (bool): Whether to learn to merge subtokens that are split
        relative to the gold standard. Experimental.
    min_action_freq (int): The minimum frequency of labelled actions to retain.
        Rarer labelled actions have their label backed-off to "dep". While this
        primarily affects the label accuracy, it can also affect the attachment
        structure, as the labels are used to represent the pseudo-projectivity
        transformation.
    scorer (Optional[Callable]): The scoring method.
    
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