from __future__ import unicode_literals from libc.stdio cimport fopen, fclose, fread, fwrite, FILE from libc.string cimport memset from libc.stdint cimport int32_t from libc.stdint cimport uint64_t import bz2 from os import path import io import math import json import tempfile from .lexeme cimport EMPTY_LEXEME from .lexeme cimport Lexeme from .strings cimport hash_string from .orth cimport word_shape from .typedefs cimport attr_t from .cfile cimport CFile from .lemmatizer import Lemmatizer from . import attrs from . import symbols from cymem.cymem cimport Address from . import util from .serialize.packer cimport Packer from .attrs cimport PROB try: import copy_reg except ImportError: import copyreg as copy_reg DEF MAX_VEC_SIZE = 100000 cdef float[MAX_VEC_SIZE] EMPTY_VEC memset(EMPTY_VEC, 0, sizeof(EMPTY_VEC)) memset(&EMPTY_LEXEME, 0, sizeof(LexemeC)) EMPTY_LEXEME.vector = EMPTY_VEC cdef class Vocab: '''A map container for a language's LexemeC structs. ''' @classmethod def from_dir(cls, data_dir, get_lex_attr=None): if not path.exists(data_dir): raise IOError("Directory %s not found -- cannot load Vocab." % data_dir) if not path.isdir(data_dir): raise IOError("Path %s is a file, not a dir -- cannot load Vocab." % data_dir) tag_map = json.load(open(path.join(data_dir, 'tag_map.json'))) lemmatizer = Lemmatizer.from_dir(path.join(data_dir, '..')) if path.exists(path.join(data_dir, 'serializer.json')): serializer_freqs = json.load(open(path.join(data_dir, 'serializer.json'))) else: serializer_freqs = None cdef Vocab self = cls(get_lex_attr=get_lex_attr, tag_map=tag_map, lemmatizer=lemmatizer, serializer_freqs=serializer_freqs) if path.exists(path.join(data_dir, 'strings.json')): with io.open(path.join(data_dir, 'strings.json'), 'r', encoding='utf8') as file_: self.strings.load(file_) self.load_lexemes(path.join(data_dir, 'lexemes.bin')) if path.exists(path.join(data_dir, 'vec.bin')): self.vectors_length = self.load_vectors_from_bin_loc(path.join(data_dir, 'vec.bin')) return self def __init__(self, get_lex_attr=None, tag_map=None, lemmatizer=None, serializer_freqs=None): if tag_map is None: tag_map = {} if lemmatizer is None: lemmatizer = Lemmatizer({}, {}, {}) self.mem = Pool() self._by_hash = PreshMap() self._by_orth = PreshMap() self.strings = StringStore() # Load strings in a special order, so that we have an onset number for # the vocabulary. This way, when words are added in order, the orth ID # is the frequency rank of the word, plus a certain offset. The structural # strings are loaded first, because the vocab is open-class, and these # symbols are closed class. for name in symbols.NAMES + list(sorted(tag_map.keys())): if name: _ = self.strings[name] self.get_lex_attr = get_lex_attr self.morphology = Morphology(self.strings, tag_map, lemmatizer) self.serializer_freqs = serializer_freqs self.length = 1 self._serializer = None property serializer: def __get__(self): if self._serializer is None: freqs = [] self._serializer = Packer(self, self.serializer_freqs) return self._serializer def __len__(self): """The current number of lexemes stored.""" return self.length def __reduce__(self): tmp_dir = tempfile.mkdtemp() lex_loc = path.join(tmp_dir, 'lexemes.bin') str_loc = path.join(tmp_dir, 'strings.json') vec_loc = path.join(tmp_dir, 'vec.bin') self.dump(lex_loc) with io.open(str_loc, 'w', encoding='utf8') as file_: self.strings.dump(file_) self.dump_vectors(vec_loc) state = (str_loc, lex_loc, vec_loc, self.morphology, self.get_lex_attr, self.serializer_freqs, self.data_dir) return (unpickle_vocab, state, None, None) 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[lex.orth], 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 cdef bint is_oov = mem is not self.mem if len(string) < 3: mem = self.mem lex = mem.alloc(sizeof(LexemeC), 1) lex.orth = self.strings[string] lex.length = len(string) lex.id = self.length lex.vector = mem.alloc(self.vectors_length, sizeof(float)) if self.get_lex_attr is not None: for attr, func in self.get_lex_attr.items(): value = func(string) if isinstance(value, unicode): value = self.strings[value] if attr == PROB: lex.prob = value else: 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 __iter__(self): 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. Args: id_or_string (int or unicode): The integer ID of a word, or its unicode string. If an int >= Lexicon.size, IndexError is raised. If id_or_string is neither an int nor a unicode string, ValueError is raised. Returns: lexeme (Lexeme): An instance of the Lexeme Python class, with data copied on instantiation. ''' cdef attr_t orth if type(id_or_string) == unicode: orth = self.strings[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): token = &tokens[i] # Set the special tokens up to have morphology and lemmas if # specified, otherwise use the part-of-speech tag (if specified) token.lex = self.get(self.mem, props['F']) if 'pos' in props: self.morphology.assign_tag(token, props['pos']) if 'L' in props: tokens[i].lemma = self.strings[props['L']] for feature, value in props.get('morph', {}).items(): self.morphology.assign_feature(&token.morph, feature, value) return tokens def dump(self, loc): if path.exists(loc): assert not path.isdir(loc) cdef bytes bytes_loc = loc.encode('utf8') if type(loc) == unicode else loc cdef CFile fp = CFile(bytes_loc, 'wb') cdef size_t st cdef size_t addr cdef hash_t key for key, addr in self._by_hash.items(): lexeme = addr fp.write_from(&lexeme.orth, sizeof(lexeme.orth), 1) fp.write_from(&lexeme.flags, sizeof(lexeme.flags), 1) fp.write_from(&lexeme.id, sizeof(lexeme.id), 1) fp.write_from(&lexeme.length, sizeof(lexeme.length), 1) fp.write_from(&lexeme.orth, sizeof(lexeme.orth), 1) fp.write_from(&lexeme.lower, sizeof(lexeme.lower), 1) fp.write_from(&lexeme.norm, sizeof(lexeme.norm), 1) fp.write_from(&lexeme.shape, sizeof(lexeme.shape), 1) fp.write_from(&lexeme.prefix, sizeof(lexeme.prefix), 1) fp.write_from(&lexeme.suffix, sizeof(lexeme.suffix), 1) fp.write_from(&lexeme.cluster, sizeof(lexeme.cluster), 1) fp.write_from(&lexeme.prob, sizeof(lexeme.prob), 1) fp.write_from(&lexeme.sentiment, sizeof(lexeme.sentiment), 1) fp.write_from(&lexeme.l2_norm, sizeof(lexeme.l2_norm), 1) fp.close() def load_lexemes(self, loc): if not path.exists(loc): raise IOError('LexemeCs file not found at %s' % loc) fp = CFile(loc, 'rb') cdef LexemeC* lexeme cdef hash_t key cdef unicode py_str cdef attr_t orth assert sizeof(orth) == sizeof(lexeme.orth) i = 0 while True: try: fp.read_into(&orth, 1, sizeof(orth)) except IOError: break lexeme = self.mem.alloc(sizeof(LexemeC), 1) # Copy data from the file into the lexeme fp.read_into(&lexeme.flags, 1, sizeof(lexeme.flags)) fp.read_into(&lexeme.id, 1, sizeof(lexeme.id)) fp.read_into(&lexeme.length, 1, sizeof(lexeme.length)) fp.read_into(&lexeme.orth, 1, sizeof(lexeme.orth)) fp.read_into(&lexeme.lower, 1, sizeof(lexeme.lower)) fp.read_into(&lexeme.norm, 1, sizeof(lexeme.norm)) fp.read_into(&lexeme.shape, 1, sizeof(lexeme.shape)) fp.read_into(&lexeme.prefix, 1, sizeof(lexeme.prefix)) fp.read_into(&lexeme.suffix, 1, sizeof(lexeme.suffix)) fp.read_into(&lexeme.cluster, 1, sizeof(lexeme.cluster)) fp.read_into(&lexeme.prob, 1, sizeof(lexeme.prob)) fp.read_into(&lexeme.sentiment, 1, sizeof(lexeme.sentiment)) fp.read_into(&lexeme.l2_norm, 1, sizeof(lexeme.l2_norm)) lexeme.vector = EMPTY_VEC py_str = self.strings[lexeme.orth] key = hash_string(py_str) self._by_hash.set(key, lexeme) self._by_orth.set(lexeme.orth, lexeme) self.length += 1 i += 1 fp.close() def dump_vectors(self, out_loc): cdef int32_t vec_len = self.vectors_length cdef int32_t word_len cdef bytes word_str cdef char* chars cdef Lexeme lexeme cdef CFile out_file = CFile(out_loc, 'wb') for lexeme in self: word_str = lexeme.orth_.encode('utf8') vec = lexeme.c.vector word_len = len(word_str) out_file.write_from(&word_len, 1, sizeof(word_len)) out_file.write_from(&vec_len, 1, sizeof(vec_len)) chars = word_str out_file.write_from(chars, word_len, sizeof(char)) out_file.write_from(vec, vec_len, sizeof(float)) out_file.close() def load_vectors(self, file_): cdef LexemeC* lexeme cdef attr_t orth cdef int32_t vec_len = -1 for line_num, line in enumerate(file_): pieces = line.split() word_str = pieces.pop(0) if vec_len == -1: vec_len = len(pieces) elif vec_len != len(pieces): raise VectorReadError.mismatched_sizes(file_, line_num, vec_len, len(pieces)) orth = self.strings[word_str] lexeme = self.get_by_orth(self.mem, orth) lexeme.vector = self.mem.alloc(self.vectors_length, sizeof(float)) for i, val_str in enumerate(pieces): lexeme.vector[i] = float(val_str) return vec_len def load_vectors_from_bin_loc(self, loc): cdef CFile file_ = CFile(loc, b'rb') cdef int32_t word_len cdef int32_t vec_len = 0 cdef int32_t prev_vec_len = 0 cdef float* vec cdef Address mem cdef attr_t string_id cdef bytes py_word cdef vector[float*] vectors cdef int line_num = 0 cdef Pool tmp_mem = Pool() while True: try: file_.read_into(&word_len, sizeof(word_len), 1) except IOError: break file_.read_into(&vec_len, sizeof(vec_len), 1) if prev_vec_len != 0 and vec_len != prev_vec_len: raise VectorReadError.mismatched_sizes(loc, line_num, vec_len, prev_vec_len) if 0 >= vec_len >= MAX_VEC_SIZE: raise VectorReadError.bad_size(loc, vec_len) chars = file_.alloc_read(tmp_mem, word_len, sizeof(char)) vec = file_.alloc_read(self.mem, vec_len, sizeof(float)) string_id = self.strings[chars[:word_len]] while string_id >= vectors.size(): vectors.push_back(EMPTY_VEC) assert vec != NULL vectors[string_id] = vec line_num += 1 cdef LexemeC* lex cdef size_t lex_addr cdef int i for orth, lex_addr in self._by_orth.items(): lex = lex_addr if lex.lower < vectors.size(): lex.vector = vectors[lex.lower] for i in range(vec_len): lex.l2_norm += (lex.vector[i] * lex.vector[i]) lex.l2_norm = math.sqrt(lex.l2_norm) else: lex.vector = EMPTY_VEC return vec_len def unpickle_vocab(strings_loc, lex_loc, vec_loc, morphology, get_lex_attr, serializer_freqs, data_dir): cdef Vocab vocab = Vocab() vocab.get_lex_attr = get_lex_attr vocab.morphology = morphology vocab.strings = morphology.strings vocab.data_dir = data_dir vocab.serializer_freqs = serializer_freqs with io.open(strings_loc, 'r', encoding='utf8') as file_: vocab.strings.load(file_) vocab.load_lexemes(lex_loc) if vec_loc is not None: vocab.vectors_length = vocab.load_vectors_from_bin_loc(vec_loc) return vocab copy_reg.constructor(unpickle_vocab) def write_binary_vectors(in_loc, out_loc): cdef CFile out_file = CFile(out_loc, 'wb') cdef Address mem cdef int32_t word_len cdef int32_t vec_len cdef char* chars with bz2.BZ2File(in_loc, 'r') as file_: for line in file_: pieces = line.split() word = pieces.pop(0) mem = Address(len(pieces), sizeof(float)) vec = mem.ptr for i, val_str in enumerate(pieces): vec[i] = float(val_str) word_len = len(word) vec_len = len(pieces) out_file.write_from(&word_len, 1, sizeof(word_len)) out_file.write_from(&vec_len, 1, sizeof(vec_len)) chars = word out_file.write_from(chars, len(word), sizeof(char)) out_file.write_from(vec, vec_len, sizeof(float)) 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=original_string, orth_str=id_string, orth_id=id_) ) class VectorReadError(Exception): @classmethod def mismatched_sizes(cls, loc, line_num, prev_size, curr_size): return cls( "Error reading word vectors from %s on line %d.\n" "All vectors must be the same size.\n" "Prev size: %d\n" "Curr size: %d" % (loc, line_num, prev_size, curr_size)) @classmethod def bad_size(cls, loc, size): return cls( "Error reading word vectors from %s.\n" "Vector size: %d\n" "Max size: %d\n" "Min size: 1\n" % (loc, size, MAX_VEC_SIZE))