“我正在尝试使用spacy训练ner模型。它在CPU上正常工作。但是，当我尝试使用GPU执行该模型时，出现以下错误。Spacy版本2.1.4，CUDA版本10.1”
“我尝试重新安装Thinc，但仍然出现错误”
from __future__ import unicode_literals, print_function
import plac
import random
from pathlib import Path
import spacy
from spacy.util import minibatch, compounding
import json
spacy.require_gpu()
nlp = spacy.blank("en")
ner = nlp.create_pipe("ner")
ner = nlp.create_pipe("ner")
for _, annotations in TRAIN_DATA:
for ent in annotations.get("entities"):
ner.add_label(ent[2])
optimizer = nlp.begin_training()
“我遇到以下错误”
“ CUDARuntimeError
追溯（最近一次通话）
在
----> 1 optimizer = nlp.begin_training()
begin_training(self, get_gold_tuples, sgd, component_cfg, **cfg)中的G：\ Anaconda3 \ lib \ site-packages \ spacy \ language.py
547 if self.vocab.vectors.data.shape[1] >= 1:
548 self.vocab.vectors.data = Model.ops.asarray(self.vocab.vectors.data)
--> 549 link_vectors_to_models(self.vocab)
550 if self.vocab.vectors.data.shape[1]:
551 cfg["pretrained_vectors"] = self.vocab.vectors.name
link_vectors_to_models(vocab)中的G：\ Anaconda3 \ lib \ site-packages \ spacy_ml.py
297 else:
298 word.rank = 0
--> 299 data = ops.asarray(vectors.data)
300 # Set an entry here, so that vectors are accessed by StaticVectors
301 # (unideal, I know)
ops.pyx in thinc.neural.ops.CupyOps.asarray()
array(obj, dtype, copy, order, subok, ndmin)中的G：\ Anaconda3 \ lib \ site-packages \ cupy \ creation \ from_data.py
39
40 """
---> 41 return core.array(obj, dtype, copy, order, subok, ndmin)
42
43
cupy.core.core.array()中的cupy \ core \ core.pyx
cupy.core.core.array()中的cupy \ core \ core.pyx
cupy.core.core.ndarray.__init__()中的cupy \ core \ core.pyx
cupy.cuda.memory.alloc()中的cupy \ cuda \ memory.pyx
cupy.cuda.memory.MemoryPool.malloc()中的cupy \ cuda \ memory.pyx
cupy.cuda.memory.MemoryPool.malloc()中的cupy \ cuda \ memory.pyx
cupy.cuda.device.get_device_id()中的cupy \ cuda \ device.pyx
cupy.cuda.runtime.getDevice()中的cupy \ cuda \ runtime.pyx
cupy.cuda.runtime.check_status()中的cupy \ cuda \ runtime.pyx
CUDARuntimeError：cudaErrorUnknown：未知错误”