我正在尝试在Sagemaker实例的MXNet上制作转移学习方法。培训和服务从本地开始，没有任何问题，我正在使用该python代码进行预测：
def predict_mx(net, fname):
with open(fname, 'rb') as f:
img = image.imdecode(f.read())
plt.imshow(img.asnumpy())
plt.show()
data = transform(img, -1, test_augs)
plt.imshow(data.transpose((1,2,0)).asnumpy()/255)
plt.show()
data = data.expand_dims(axis=0)
return net.predict(data.asnumpy().tolist())
我检查
data.asnumpy().tolist()没问题，然后pyplot绘制图像（firts是原始图像，第二个是调整大小的图像）。但是net.predict会引发错误：---------------------------------------------------------------------------
JSONDecodeError Traceback (most recent call last)
<ipython-input-171-ea0f1f5bdc72> in <module>()
----> 1 predict_mx(predictor.predict, './data2/burgers-imgnet/00103785.jpg')
<ipython-input-170-150a72b14997> in predict_mx(net, fname)
30 plt.show()
31 data = data.expand_dims(axis=0)
---> 32 return net(data.asnumpy().tolist())
33
~/Projects/Lab/ML/AWS/v/lib64/python3.6/site-packages/sagemaker/predictor.py in predict(self, data)
89 if self.deserializer is not None:
90 # It's the deserializer's responsibility to close the stream
---> 91 return self.deserializer(response_body, response['ContentType'])
92 data = response_body.read()
93 response_body.close()
~/Projects/Lab/ML/AWS/v/lib64/python3.6/site-packages/sagemaker/predictor.py in __call__(self, stream, content_type)
290 """
291 try:
--> 292 return json.load(codecs.getreader('utf-8')(stream))
293 finally:
294 stream.close()
/usr/lib64/python3.6/json/__init__.py in load(fp, cls, object_hook, parse_float, parse_int, parse_constant, object_pairs_hook, **kw)
297 cls=cls, object_hook=object_hook,
298 parse_float=parse_float, parse_int=parse_int,
--> 299 parse_constant=parse_constant, object_pairs_hook=object_pairs_hook, **kw)
300
301
/usr/lib64/python3.6/json/__init__.py in loads(s, encoding, cls, object_hook, parse_float, parse_int, parse_constant, object_pairs_hook, **kw)
352 parse_int is None and parse_float is None and
353 parse_constant is None and object_pairs_hook is None and not kw):
--> 354 return _default_decoder.decode(s)
355 if cls is None:
356 cls = JSONDecoder
/usr/lib64/python3.6/json/decoder.py in decode(self, s, _w)
337
338 """
--> 339 obj, end = self.raw_decode(s, idx=_w(s, 0).end())
340 end = _w(s, end).end()
341 if end != len(s):
/usr/lib64/python3.6/json/decoder.py in raw_decode(self, s, idx)
355 obj, end = self.scan_once(s, idx)
356 except StopIteration as err:
--> 357 raise JSONDecodeError("Expecting value", s, err.value) from None
358 return obj, end
JSONDecodeError: Expecting value: line 1 column 1 (char 0)
我试图json.dumps我的数据，并且没有问题。
请注意，我尚未在AWS上部署该服务，我希望能够在本地进行模型和预测的测试，然后进行更大的训练并在以后提供服务。
谢谢你的帮助
最佳答案
对net.predict的调用工作正常。
似乎您使用的是SageMaker Python SDK的predict_fn进行托管。调用predict_fn后，MXNet容器将尝试将您的预测序列化为JSON，然后再将其发送回客户端。您可以在此处查看执行此操作的代码：https://github.com/aws/sagemaker-mxnet-container/blob/master/src/mxnet_container/serve/transformer.py#L132
容器无法序列化，因为net.predict不返回可序列化的对象。您可以通过返回列表来解决此问题：
return net.predict(data.asnumpy().tolist()).asnumpy().tolist()
另一种选择是使用transform_fn而不是prediction_fn，以便您可以自行处理输出序列化。您可以在此处https://github.com/aws/sagemaker-python-sdk/blob/e93eff66626c0ab1f292048451c4c3ac7c39a121/examples/cli/host/script.py#L41看到transform_fn的示例
关于python - Sagemaker预测本地实例，JSON错误，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/50675708/