mirror of https://github.com/explosion/spaCy.git
287 lines
9.5 KiB
Cython
287 lines
9.5 KiB
Cython
# cython: infer_types=True
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# cython: profile=True
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# coding: utf8
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from collections import OrderedDict
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from cpython.exc cimport PyErr_CheckSignals
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from spacy import util
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from spacy.errors import Errors, Warnings, user_warning
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from cymem.cymem cimport Pool
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from preshed.maps cimport PreshMap
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from cpython.mem cimport PyMem_Malloc
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from cpython.exc cimport PyErr_SetFromErrno
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from libc.stdio cimport FILE, fopen, fclose, fread, fwrite, feof, fseek
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from libc.stdint cimport int32_t, int64_t
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from libc.stdlib cimport qsort
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from .typedefs cimport hash_t
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from os import path
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from libcpp.vector cimport vector
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cdef class Candidate:
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def __init__(self, KnowledgeBase kb, entity_hash, alias_hash, prior_prob):
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self.kb = kb
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self.entity_hash = entity_hash
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self.alias_hash = alias_hash
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self.prior_prob = prior_prob
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@property
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def entity(self):
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"""RETURNS (uint64): hash of the entity's KB ID/name"""
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return self.entity_hash
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@property
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def entity_(self):
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"""RETURNS (unicode): ID/name of this entity in the KB"""
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return self.kb.vocab.strings[self.entity_hash]
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@property
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def alias(self):
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"""RETURNS (uint64): hash of the alias"""
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return self.alias_hash
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@property
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def alias_(self):
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"""RETURNS (unicode): ID of the original alias"""
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return self.kb.vocab.strings[self.alias_hash]
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@property
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def prior_prob(self):
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return self.prior_prob
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cdef class KnowledgeBase:
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def __init__(self, Vocab vocab):
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self.vocab = vocab
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self.mem = Pool()
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self._entry_index = PreshMap()
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self._alias_index = PreshMap()
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self.vocab.strings.add("")
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self._create_empty_vectors(dummy_hash=self.vocab.strings[""])
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def __len__(self):
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return self.get_size_entities()
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def get_size_entities(self):
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return len(self._entry_index)
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def get_entity_strings(self):
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return [self.vocab.strings[x] for x in self._entry_index][1:] # removing the dummy element on index 0
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def get_size_aliases(self):
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return len(self._alias_index)
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def get_alias_strings(self):
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return [self.vocab.strings[x] for x in self._alias_index][1:] # removing the dummy element on index 0
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def add_entity(self, unicode entity, float prob=0.5, vectors=None, features=None):
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"""
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Add an entity to the KB, optionally specifying its log probability based on corpus frequency
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Return the hash of the entity ID/name at the end
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"""
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cdef hash_t entity_hash = self.vocab.strings.add(entity)
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# Return if this entity was added before
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if entity_hash in self._entry_index:
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user_warning(Warnings.W018.format(entity=entity))
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return
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cdef int32_t dummy_value = 342
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new_index = self.c_add_entity(entity_hash=entity_hash, prob=prob,
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vector_rows=&dummy_value, feats_row=dummy_value)
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self._entry_index[entity_hash] = new_index
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# TODO self._vectors_table.get_pointer(vectors),
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# self._features_table.get(features))
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return entity_hash
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def add_alias(self, unicode alias, entities, probabilities):
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"""
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For a given alias, add its potential entities and prior probabilies to the KB.
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Return the alias_hash at the end
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"""
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# Throw an error if the length of entities and probabilities are not the same
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if not len(entities) == len(probabilities):
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raise ValueError(Errors.E132.format(alias=alias,
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entities_length=len(entities),
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probabilities_length=len(probabilities)))
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# Throw an error if the probabilities sum up to more than 1
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prob_sum = sum(probabilities)
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if prob_sum > 1:
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raise ValueError(Errors.E133.format(alias=alias, sum=prob_sum))
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cdef hash_t alias_hash = self.vocab.strings.add(alias)
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# Return if this alias was added before
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if alias_hash in self._alias_index:
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user_warning(Warnings.W017.format(alias=alias))
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return
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cdef vector[int64_t] entry_indices
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cdef vector[float] probs
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for entity, prob in zip(entities, probabilities):
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entity_hash = self.vocab.strings[entity]
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if not entity_hash in self._entry_index:
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raise ValueError(Errors.E134.format(alias=alias, entity=entity))
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entry_index = <int64_t>self._entry_index.get(entity_hash)
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entry_indices.push_back(int(entry_index))
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probs.push_back(float(prob))
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new_index = self.c_add_aliases(alias_hash=alias_hash, entry_indices=entry_indices, probs=probs)
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self._alias_index[alias_hash] = new_index
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return alias_hash
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def get_candidates(self, unicode alias):
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""" TODO: where to put this functionality ?"""
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cdef hash_t alias_hash = self.vocab.strings[alias]
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alias_index = <int64_t>self._alias_index.get(alias_hash)
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alias_entry = self._aliases_table[alias_index]
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return [Candidate(kb=self,
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entity_hash=self._entries[entry_index].entity_hash,
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alias_hash=alias_hash,
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prior_prob=prob)
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for (entry_index, prob) in zip(alias_entry.entry_indices, alias_entry.probs)
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if entry_index != 0]
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def dump(self, loc):
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cdef Writer writer = Writer(loc)
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# dumping the entry records in the order in which they are in the _entries vector.
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# index 0 is a dummy object not stored in the _entry_index and can be ignored.
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i = 1
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for entry_hash, entry_index in sorted(self._entry_index.items(), key=lambda x: x[1]):
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entry = self._entries[entry_index]
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print("dumping")
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print("index", entry_index)
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print("hash", entry.entity_hash)
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assert entry.entity_hash == entry_hash
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assert entry_index == i
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print("prob", entry.prob)
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print("")
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writer.write(entry_index, entry.entity_hash, entry.prob)
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i = i+1
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writer.close()
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cpdef load_bulk(self, int nr_entities, loc):
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# TODO: nr_entities from header in file (Reader constructor)
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cdef int64_t entry_id
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cdef hash_t entity_hash
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cdef float prob
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cdef EntryC entry
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cdef int32_t dummy_value = 342
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cdef Reader reader = Reader(loc)
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to_read = self.get_size_entities()
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self._entry_index = PreshMap(nr_entities+1)
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self._entries = entry_vec(nr_entities+1)
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# we assume the data was written in sequence
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# index 0 is a dummy object not stored in the _entry_index and can be ignored.
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# TODO: should we initialize the dummy objects ?
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cdef int i = 1
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while reader.read(self.mem, &entry_id, &entity_hash, &prob) and i <= nr_entities:
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assert i == entry_id
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entry.entity_hash = entity_hash
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entry.prob = prob
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# TODO features and vectors
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entry.vector_rows = &dummy_value
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entry.feats_row = dummy_value
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print("bulk loading")
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print("i", i)
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print("entryID", entry_id)
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print("hash", entry.entity_hash)
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print("prob", entry.prob)
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print("")
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self._entries[i] = entry
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self._entry_index[entity_hash] = i
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i += 1
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cdef class Writer:
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def __init__(self, object loc):
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if path.exists(loc):
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assert not path.isdir(loc), "%s is directory." % loc
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cdef bytes bytes_loc = loc.encode('utf8') if type(loc) == unicode else loc
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self._fp = fopen(<char*>bytes_loc, 'wb')
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assert self._fp != NULL
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fseek(self._fp, 0, 0)
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def close(self):
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cdef size_t status = fclose(self._fp)
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assert status == 0
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cdef int write(self, int64_t entry_id, hash_t entry_hash, float entry_prob) except -1:
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# TODO: feats_rows and vector rows
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_write(&entry_id, sizeof(entry_id), self._fp)
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_write(&entry_hash, sizeof(entry_hash), self._fp)
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_write(&entry_prob, sizeof(entry_prob), self._fp)
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cdef int _write(void* value, size_t size, FILE* fp) except -1:
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status = fwrite(value, size, 1, fp)
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assert status == 1, status
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cdef class Reader:
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def __init__(self, object loc):
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assert path.exists(loc)
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assert not path.isdir(loc)
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cdef bytes bytes_loc = loc.encode('utf8') if type(loc) == unicode else loc
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self._fp = fopen(<char*>bytes_loc, 'rb')
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if not self._fp:
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PyErr_SetFromErrno(IOError)
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status = fseek(self._fp, 0, 0) # this can be 0 if there is no header
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def __dealloc__(self):
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fclose(self._fp)
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cdef int read(self, Pool mem, int64_t* entry_id, hash_t* entity_hash, float* prob) except -1:
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status = fread(entry_id, sizeof(int64_t), 1, self._fp)
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if status < 1:
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if feof(self._fp):
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return 0 # end of file
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raise IOError("error reading entry ID from input file")
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status = fread(entity_hash, sizeof(hash_t), 1, self._fp)
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if status < 1:
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if feof(self._fp):
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return 0 # end of file
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raise IOError("error reading entity hash from input file")
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status = fread(prob, sizeof(float), 1, self._fp)
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if status < 1:
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if feof(self._fp):
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return 0 # end of file
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raise IOError("error reading entity prob from input file")
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if feof(self._fp):
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return 0
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else:
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return 1
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