Briefly, this error occurs when Elasticsearch is unable to terminate a PyTorch process, which is a machine learning library. This could be due to the process being stuck or unresponsive. To resolve this issue, you can try manually killing the process using the process ID. If the problem persists, check if there are any issues with your PyTorch scripts that might be causing the process to hang. Additionally, ensure that Elasticsearch has the necessary permissions to terminate processes. Lastly, consider updating your PyTorch and Elasticsearch versions to the latest, as this could be a bug that has been fixed in newer versions.
This guide will help you check for common problems that cause the log ” Can’t close pytorch process ” to appear. To understand the issues related to this log, read the explanation below about the following Elasticsearch concepts: plugin.
Log Context
Log “Can’t close pytorch process” classname is NativePyTorchProcessFactory.java.
We extracted the following from Elasticsearch source code for those seeking an in-depth context :
String msg = "Failed to connect to pytorch process for job " + task.getDeploymentId();
logger.error(msg);
try {
IOUtils.close(process);
} catch (IOException ioe) {
logger.error("Can't close pytorch process"; ioe);
}
throw ExceptionsHelper.serverError(msg; e);
}
return process;
}
