stateful

Why is using jhipster oauth2 stateful, and how to implement it?

由 最后都变了- 提交于 2019-12-11 17:59:08
问题 Using Jhipster (monolith, oauth2, with registry) forces our users to log-in every once in a while. After searching a bit, we assume that it's because we have multiple instances of our monolith and sometimes the users get routed to different instances. So I have 2 questions: Why does Jhipster implement oauth2 in a stateful way? How should we handle this, assuming we're staying with the current configuration? 来源： https://stackoverflow.com/questions/54169816/why-is-using-jhipster-oauth2-stateful

Stateful LSTM in Keras: reset with fit, evaluate, and predict?

由 蓝咒 提交于 2019-12-11 10:19:23
问题 I'd like to expand on this question of when to reset states. Stateful LSTM: When to reset states? Suppose I train a stateful model as such: for i in range(epochs): model.fit(X_train, y_train, epochs=1, batch_size=1, shuffle=False) model.reset_states() My training and test sets are from one time-series data set, with the test set following immediately after the training set. Next, I want to evaluate the test set and get an array of the predictions. score = model.evaluate(X_test, y_test, batch

ERROR Error cleaning broadcast Exception [duplicate]

由 痞子三分冷 提交于 2019-12-11 07:36:10
问题 This question already has answers here : What are possible reasons for receiving TimeoutException: Futures timed out after [n seconds] when working with Spark [duplicate] (4 answers) Closed 2 years ago . I get the following error while running my spark streaming application, we have a large application running multiple stateful (with mapWithState) and stateless operations. It's getting difficult to isolate the error since spark itself hangs and the only error we see is in the spark log and

Implement Cache in Azure Service Fabric

由 与世无争的帅哥 提交于 2019-12-07 18:41:15
问题 I am working on a project in which I need a set of data frequently and currently for getting that data I have to make call to 3rd party Service which is taking lot of time.So what I want is to maintain a local cache .The Data is modified very infrequently or is almost constant .What is the best way of implementing this in Azure Service Fabric.I am currently thinking of making the Microservice stateful . Is is the best way to do this?When node goes down it should copy its local cache to other

Keras Stateful LSTM fit_generator how to use batch_size > 1

由 霸气de小男生 提交于 2019-12-07 12:42:07
问题 I want to train an stateful LSTM network using the functional API in Keras. The fit method is fit_generator . I am able to train it, using: batch_size = 1 My Input layer is: Input(shape=(n_history, n_cols),batch_shape=(batch_size, n_history, n_cols), dtype='float32', name='daily_input') The generator is as follows: def training_data(): while 1: for i in range(0,pdf_daily_data.shape[0]-n_history,1): x = f(i)() # f(i) shape is (1, n_history, n_cols) y = y(i) yield (x,y) And then the fit is:

JAX-WS: stateful WS fails in a standalone process

由 ☆樱花仙子☆ 提交于 2019-12-07 05:46:27
问题 I have a stateful web service deployed onto Tomcat. It consists of factory service and main API service, and works just fine. Factory service returns a W3CEndpointReference to main API instance, and client uses the session. Now, I'm trying to run the very same service as a standalone application. In this case, the W3CEndpointReference returned by the factory suddenly starts to point to factory URI, not to main service one. When references from runs against Tomcat and standalone are compared,

Issue with stateful EJB - keeps one session for all users

由 末鹿安然 提交于 2019-12-06 13:30:48
问题 I am quite new to EJB. I need stateful bean in my EAR application. I have created simple stateful session bean in an ejb module: @Stateful public class Test { public Test() { } private int i; @PostConstruct public void initialize() { i = 0; } public int getI() { return i++; } } And I call it from servlet in a war module: public class TestServlet extends HttpServlet { @EJB Test test; protected void processRequest(HttpServletRequest request, HttpServletResponse response) throws ServletException

Implement Cache in Azure Service Fabric

由 核能气质少年 提交于 2019-12-06 12:43:47
I am working on a project in which I need a set of data frequently and currently for getting that data I have to make call to 3rd party Service which is taking lot of time.So what I want is to maintain a local cache .The Data is modified very infrequently or is almost constant .What is the best way of implementing this in Azure Service Fabric.I am currently thinking of making the Microservice stateful . Is is the best way to do this?When node goes down it should copy its local cache to other node.If making it stateful is good than How should i go on implementing this? Renan Fagundes Well, you

Keras Stateful LSTM fit_generator how to use batch_size > 1

由 你。 提交于 2019-12-05 18:24:23
I want to train an stateful LSTM network using the functional API in Keras. The fit method is fit_generator . I am able to train it, using: batch_size = 1 My Input layer is: Input(shape=(n_history, n_cols),batch_shape=(batch_size, n_history, n_cols), dtype='float32', name='daily_input') The generator is as follows: def training_data(): while 1: for i in range(0,pdf_daily_data.shape[0]-n_history,1): x = f(i)() # f(i) shape is (1, n_history, n_cols) y = y(i) yield (x,y) And then the fit is: model.fit_generator(training_data(), steps_per_epoch=pdf_daily_data.shape[0]//batch_size,... This works

Is RenderStrategy.ONE_PASS_RENDER a reasonable way to get rid of page version parameters like ?1 in a Wicket application?

由 我的梦境 提交于 2019-12-05 01:18:35
问题 We've been using Wicket 1.3.7 for a few years now and are currently in the process of upgrading our project to wicket 6.x I did a lot of research regarding to the page version parameters (e.g. ?1 ) being append to every URL, and how to get rid of them. (Could not find detailed information on this in the official documentation, unfortunately.) While doing so I read a lot of statements (from Wicket developers and users like It is needed to keep track of the page version, otherwise it would not
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