Question

在使用trust-constr方法使用scipy.optimize.minimize时，我得到了以下UserWarning：

Caused by: com.fasterxml.jackson.databind.exc.MismatchedInputException: Cannot construct instance of `com.gxxx.mxxx.common.dto.UserDetailsDto` (although at least one Creator exists): no String-argument constructor/factory method to deserialize from String value ('{"field1":20000,"field2":20000,"type":""}')

at org.apache.kafka.clients.consumer.KafkaConsumer.pollForFetches(KafkaConsumer.java:1230)
at org.apache.kafka.clients.consumer.KafkaConsumer.poll(KafkaConsumer.java:1187)
at org.apache.kafka.clients.consumer.KafkaConsumer.poll(KafkaConsumer.java:1154)
at org.springframework.kafka.listener.KafkaMessageListenerContainer$ListenerConsumer.pollAndInvoke(KafkaMessageListenerContainer.java:741)
at org.springframework.kafka.listener.KafkaMessageListenerContainer$ListenerConsumer.run(KafkaMessageListenerContainer.java:698)
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.lang.Thread.run(Thread.java:748)
org.apache.kafka.common.errors.SerializationException: Error deserializing key/value for partition kafakaqueue.identify-1 at offset 326355379. If needed, please seek past the record to continue consumption.

我有一个线性函数，因此我想尝试将hessian设置为零。但这如何工作？我尝试了以“ hess = None”作为参数的最简单方法。好的，尝试不好。

这是调用求解器的行：

 scipy\optimize\_hessian_update_strategy.py:187: UserWarning: delta_grad == 0.0. Check if the approximated function is linear. If the function is linear better results can be obtained by defining the Hessian as zero instead of using quasi-Newton approximations. 'approximations.', UserWarning)

Answer 1

定义约束时，您要设置

    hess = lambda x, v: numpy.zeros((n, n))

n是数组的维数。请注意，您也可以使用LinearConstraint object

将Hessian定义为零

1 个答案: