# coding: utf8 from __future__ import unicode_literals import bz2 import ujson import re import numpy from libc.string cimport memset, memcpy from libc.stdint cimport int32_t from libc.math cimport sqrt from cymem.cymem cimport Address from collections import OrderedDict from .lexeme cimport EMPTY_LEXEME from .lexeme cimport Lexeme from .strings cimport hash_string from .typedefs cimport attr_t from .cfile cimport CFile from .tokens.token cimport Token from .attrs cimport PROB, LANG from .structs cimport SerializedLexemeC from .compat import copy_reg, pickle, basestring_ from .lemmatizer import Lemmatizer from .attrs import intify_attrs from .vectors import Vectors from . import util from . import attrs from . import symbols from ._ml import link_vectors_to_models cdef class Vocab: """A look-up table that allows you to access `Lexeme` objects. The `Vocab` instance also provides access to the `StringStore`, and owns underlying C-data that is shared between `Doc` objects. """ def __init__(self, lex_attr_getters=None, tag_map=None, lemmatizer=None, strings=tuple(), **deprecated_kwargs): """Create the vocabulary. lex_attr_getters (dict): A dictionary mapping attribute IDs to functions to compute them. Defaults to `None`. tag_map (dict): A dictionary mapping fine-grained tags to coarse-grained parts-of-speech, and optionally morphological attributes. lemmatizer (object): A lemmatizer. Defaults to `None`. strings (StringStore): StringStore that maps strings to integers, and vice versa. RETURNS (Vocab): The newly constructed vocab object. """ lex_attr_getters = lex_attr_getters if lex_attr_getters is not None else {} tag_map = tag_map if tag_map is not None else {} if lemmatizer in (None, True, False): lemmatizer = Lemmatizer({}, {}, {}) self.mem = Pool() self._by_hash = PreshMap() self._by_orth = PreshMap() self.strings = StringStore() self.length = 0 if strings: for string in strings: _ = self[string] for name in tag_map.keys(): if name: self.strings.add(name) self.lex_attr_getters = lex_attr_getters self.morphology = Morphology(self.strings, tag_map, lemmatizer) self.vectors = Vectors(self.strings) property lang: def __get__(self): langfunc = None if self.lex_attr_getters: langfunc = self.lex_attr_getters.get(LANG, None) return langfunc('_') if langfunc else '' def __len__(self): """The current number of lexemes stored. RETURNS (int): The current number of lexemes stored. """ return self.length def add_flag(self, flag_getter, int flag_id=-1): """Set a new boolean flag to words in the vocabulary. The flag_getter function will be called over the words currently in the vocab, and then applied to new words as they occur. You'll then be able to access the flag value on each token, using token.check_flag(flag_id). See also: `Lexeme.set_flag`, `Lexeme.check_flag`, `Token.set_flag`, `Token.check_flag`. flag_getter (callable): A function `f(unicode) -> bool`, to get the flag value. flag_id (int): An integer between 1 and 63 (inclusive), specifying the bit at which the flag will be stored. If -1, the lowest available bit will be chosen. RETURNS (int): The integer ID by which the flag value can be checked. EXAMPLE: >>> MY_PRODUCT = nlp.vocab.add_flag(lambda text: text in ['spaCy', 'dislaCy']) >>> doc = nlp(u'I like spaCy') >>> assert doc[2].check_flag(MY_PRODUCT) == True """ if flag_id == -1: for bit in range(1, 64): if bit not in self.lex_attr_getters: flag_id = bit break else: raise ValueError( "Cannot find empty bit for new lexical flag. All bits between " "0 and 63 are occupied. You can replace one by specifying the " "flag_id explicitly, e.g. nlp.vocab.add_flag(your_func, flag_id=IS_ALPHA") elif flag_id >= 64 or flag_id < 1: raise ValueError( "Invalid value for flag_id: %d. Flag IDs must be between " "1 and 63 (inclusive)" % flag_id) for lex in self: lex.set_flag(flag_id, flag_getter(lex.orth_)) self.lex_attr_getters[flag_id] = flag_getter return flag_id cdef const LexemeC* get(self, Pool mem, unicode string) except NULL: """Get a pointer to a `LexemeC` from the lexicon, creating a new `Lexeme` if necessary, using memory acquired from the given pool. If the pool is the lexicon's own memory, the lexeme is saved in the lexicon. """ if string == u'': return &EMPTY_LEXEME cdef LexemeC* lex cdef hash_t key = hash_string(string) lex = self._by_hash.get(key) cdef size_t addr if lex != NULL: if lex.orth != self.strings[string]: raise LookupError.mismatched_strings( lex.orth, self.strings[string], string) return lex else: return self._new_lexeme(mem, string) cdef const LexemeC* get_by_orth(self, Pool mem, attr_t orth) except NULL: """Get a pointer to a `LexemeC` from the lexicon, creating a new `Lexeme` if necessary, using memory acquired from the given pool. If the pool is the lexicon's own memory, the lexeme is saved in the lexicon. """ if orth == 0: return &EMPTY_LEXEME cdef LexemeC* lex lex = self._by_orth.get(orth) if lex != NULL: return lex else: return self._new_lexeme(mem, self.strings[orth]) cdef const LexemeC* _new_lexeme(self, Pool mem, unicode string) except NULL: cdef hash_t key if len(string) < 3 or self.length < 10000: mem = self.mem cdef bint is_oov = mem is not self.mem lex = mem.alloc(sizeof(LexemeC), 1) lex.orth = self.strings.add(string) lex.length = len(string) lex.id = self.length if self.lex_attr_getters is not None: for attr, func in self.lex_attr_getters.items(): value = func(string) if isinstance(value, unicode): value = self.strings.add(value) if attr == PROB: lex.prob = value elif value is not None: Lexeme.set_struct_attr(lex, attr, value) if is_oov: lex.id = 0 else: key = hash_string(string) self._add_lex_to_vocab(key, lex) assert lex != NULL, string return lex cdef int _add_lex_to_vocab(self, hash_t key, const LexemeC* lex) except -1: self._by_hash.set(key, lex) self._by_orth.set(lex.orth, lex) self.length += 1 def __contains__(self, unicode string): """Check whether the string has an entry in the vocabulary. string (unicode): The ID string. RETURNS (bool) Whether the string has an entry in the vocabulary. """ key = hash_string(string) lex = self._by_hash.get(key) return lex is not NULL def __iter__(self): """Iterate over the lexemes in the vocabulary. YIELDS (Lexeme): An entry in the vocabulary. """ cdef attr_t orth cdef size_t addr for orth, addr in self._by_orth.items(): yield Lexeme(self, orth) def __getitem__(self, id_or_string): """Retrieve a lexeme, given an int ID or a unicode string. If a previously unseen unicode string is given, a new lexeme is created and stored. id_or_string (int or unicode): The integer ID of a word, or its unicode string. If `int >= Lexicon.size`, `IndexError` is raised. If `id_or_string` is neither an int nor a unicode string, `ValueError` is raised. RETURNS (Lexeme): The lexeme indicated by the given ID. EXAMPLE: >>> apple = nlp.vocab.strings['apple'] >>> assert nlp.vocab[apple] == nlp.vocab[u'apple'] """ cdef attr_t orth if type(id_or_string) == unicode: orth = self.strings.add(id_or_string) else: orth = id_or_string return Lexeme(self, orth) cdef const TokenC* make_fused_token(self, substrings) except NULL: cdef int i tokens = self.mem.alloc(len(substrings) + 1, sizeof(TokenC)) for i, props in enumerate(substrings): props = intify_attrs(props, strings_map=self.strings, _do_deprecated=True) token = &tokens[i] # Set the special tokens up to have arbitrary attributes lex = self.get_by_orth(self.mem, props[attrs.ORTH]) token.lex = lex if attrs.TAG in props: self.morphology.assign_tag(token, props[attrs.TAG]) for attr_id, value in props.items(): Token.set_struct_attr(token, attr_id, value) Lexeme.set_struct_attr(lex, attr_id, value) return tokens @property def vectors_length(self): return self.vectors.data.shape[1] def clear_vectors(self, new_dim=None): """Drop the current vector table. Because all vectors must be the same width, you have to call this to change the size of the vectors. """ if new_dim is None: new_dim = self.vectors.data.shape[1] self.vectors = Vectors(self.strings, new_dim) def get_vector(self, orth): """Retrieve a vector for a word in the vocabulary. Words can be looked up by string or int ID. RETURNS: A word vector. Size and shape determed by the vocab.vectors instance. Usually, a numpy ndarray of shape (300,) and dtype float32. RAISES: If no vectors data is loaded, ValueError is raised. """ if isinstance(orth, basestring_): orth = self.strings.add(orth) if orth in self.vectors.key2row: return self.vectors[orth] else: return numpy.zeros((self.vectors_length,), dtype='f') def set_vector(self, orth, vector): """Set a vector for a word in the vocabulary. Words can be referenced by string or int ID. RETURNS: None """ if not isinstance(orth, basestring_): orth = self.strings[orth] self.vectors.add(orth, vector=vector) def has_vector(self, orth): """Check whether a word has a vector. Returns False if no vectors have been loaded. Words can be looked up by string or int ID.""" if isinstance(orth, basestring_): orth = self.strings.add(orth) return orth in self.vectors def to_disk(self, path, **exclude): """Save the current state to a directory. path (unicode or Path): A path to a directory, which will be created if it doesn't exist. Paths may be either strings or `Path`-like objects. """ path = util.ensure_path(path) if not path.exists(): path.mkdir() self.strings.to_disk(path / 'strings.json') with (path / 'lexemes.bin').open('wb') as file_: file_.write(self.lexemes_to_bytes()) if self.vectors is not None: self.vectors.to_disk(path) def from_disk(self, path, **exclude): """Loads state from a directory. Modifies the object in place and returns it. path (unicode or Path): A path to a directory. Paths may be either strings or `Path`-like objects. RETURNS (Vocab): The modified `Vocab` object. """ path = util.ensure_path(path) self.strings.from_disk(path / 'strings.json') with (path / 'lexemes.bin').open('rb') as file_: self.lexemes_from_bytes(file_.read()) if self.vectors is not None: self.vectors.from_disk(path, exclude='strings.json') link_vectors_to_models(self) return self def to_bytes(self, **exclude): """Serialize the current state to a binary string. **exclude: Named attributes to prevent from being serialized. RETURNS (bytes): The serialized form of the `Vocab` object. """ def deserialize_vectors(): if self.vectors is None: return None else: return self.vectors.to_bytes(exclude='strings.json') getters = OrderedDict(( ('strings', lambda: self.strings.to_bytes()), ('lexemes', lambda: self.lexemes_to_bytes()), ('vectors', deserialize_vectors) )) return util.to_bytes(getters, exclude) def from_bytes(self, bytes_data, **exclude): """Load state from a binary string. bytes_data (bytes): The data to load from. **exclude: Named attributes to prevent from being loaded. RETURNS (Vocab): The `Vocab` object. """ def serialize_vectors(b): if self.vectors is None: return None else: return self.vectors.from_bytes(b, exclude='strings') setters = OrderedDict(( ('strings', lambda b: self.strings.from_bytes(b)), ('lexemes', lambda b: self.lexemes_from_bytes(b)), ('vectors', lambda b: serialize_vectors(b)) )) util.from_bytes(bytes_data, setters, exclude) return self def lexemes_to_bytes(self): cdef hash_t key cdef size_t addr cdef LexemeC* lexeme = NULL cdef SerializedLexemeC lex_data cdef int size = 0 for key, addr in self._by_hash.items(): if addr == 0: continue size += sizeof(lex_data.data) byte_string = b'\0' * size byte_ptr = byte_string cdef int j cdef int i = 0 for key, addr in self._by_hash.items(): if addr == 0: continue lexeme = addr lex_data = Lexeme.c_to_bytes(lexeme) for j in range(sizeof(lex_data.data)): byte_ptr[i] = lex_data.data[j] i += 1 return byte_string def lexemes_from_bytes(self, bytes bytes_data): """Load the binary vocabulary data from the given string.""" cdef LexemeC* lexeme cdef hash_t key cdef unicode py_str cdef int i = 0 cdef int j = 0 cdef SerializedLexemeC lex_data chunk_size = sizeof(lex_data.data) cdef unsigned char* bytes_ptr = bytes_data for i in range(0, len(bytes_data), chunk_size): lexeme = self.mem.alloc(1, sizeof(LexemeC)) for j in range(sizeof(lex_data.data)): lex_data.data[j] = bytes_ptr[i+j] Lexeme.c_from_bytes(lexeme, lex_data) py_str = self.strings[lexeme.orth] assert self.strings[py_str] == lexeme.orth, (py_str, lexeme.orth) key = hash_string(py_str) self._by_hash.set(key, lexeme) self._by_orth.set(lexeme.orth, lexeme) self.length += 1 def pickle_vocab(vocab): sstore = vocab.strings morph = vocab.morphology length = vocab.length data_dir = vocab.data_dir lex_attr_getters = vocab.lex_attr_getters lexemes_data = vocab.lexemes_to_bytes() return (unpickle_vocab, (sstore, morph, data_dir, lex_attr_getters, lexemes_data, length)) def unpickle_vocab(sstore, morphology, data_dir, lex_attr_getters, bytes lexemes_data, int length): cdef Vocab vocab = Vocab() vocab.length = length vocab.strings = sstore vocab.morphology = morphology vocab.data_dir = data_dir vocab.lex_attr_getters = lex_attr_getters vocab.lexemes_from_bytes(lexemes_data) vocab.length = length link_vectors_to_models(vocab) return vocab copy_reg.pickle(Vocab, pickle_vocab, unpickle_vocab) class LookupError(Exception): @classmethod def mismatched_strings(cls, id_, id_string, original_string): return cls( "Error fetching a Lexeme from the Vocab. When looking up a string, " "the lexeme returned had an orth ID that did not match the query string. " "This means that the cached lexeme structs are mismatched to the " "string encoding table. The mismatched:\n" "Query string: {query}\n" "Orth cached: {orth_str}\n" "ID of orth: {orth_id}".format( query=repr(original_string), orth_str=repr(id_string), orth_id=id_) )