prun | Distributed cron and job scheduler | Cron Utils library
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kandi X-RAY | prun Summary
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QUESTION
I was prunning a model and came across a library TensorFlow model optimization so initially, we have
I trained this model on a default dataset and it gave me an accuracy of 96 percent which is good. then I saved the model in a JSON file and saved its weight in h5 file now I loaded this model into another script to prune it after applying prunning and compiling the model I got this model summary
although the model is prunned well and there is a significant amount of reduction in parameters but the problem here is why parameters increased after applying the prunning and also even after rmoving non-trainable parameters still the prunned and simple model has same number of parameters can anyone explain me if this is normal or i am doing something wrong. Also please explain why this is happening. Thank you in advance to all of you :)
...ANSWER
Answered 2021-Feb-08 at 13:17It is normal. Pruning doesn't change the original model's structure. So it is not meant to reduce the number of parameters.
Pruning is a model optimization technique that eliminates not commonly used(by other words you can say unnecessary) values in the weights.
2nd model summary shows the parameters added for pruning. They are the non-trainable parameters. Non-trainable parameters stand for masking. In a nutshell, tensorflow adds non-trainable masks to each of the weights in the network to specify which of the weights should be pruned. The masks consist of 0s and 1s.
QUESTION
We have a SpringBoot application and are using Jersey to audit incoming HTTP requests.
We implemented a Jersey ContainerRequestFilter to retrieve the incoming HttpServletRequest and use the HttpServletRequest's getParameterMap() method to extract both query and form data and place it in our audit.
This aligns with the javadoc for the getParameterMap():
"Request parameters are extra information sent with the request. For HTTP servlets, parameters are contained in the query string or posted form data."
And here is the documentation pertaining to the filter:
Upon updating SpringBoot, we found that the getParameterMap() no longer returned form data, but still returned query data.
We found that SpringBoot 2.1 is the last version to support our code. In SpringBoot 2.2 the version of Jersey was updated 2.29, but upon reviewing the release notes we don't see anything related to this.
What changed? What would we need to change to support SpringBoot 2.2 / Jersey 2.29?
Here is a simplified version of our code:
JerseyRequestFilter - our filter
...ANSWER
Answered 2020-Dec-16 at 10:06Alright, after a ton of debugging code and digging through github repos I found the following:
There is a filter, that reads the body inputstream of the request if it is a POST request
, making it unusable for further usage. This is the HiddenHttpMethodFilter
. This filter, however, puts the content of the body, if it is application/x-www-form-urlencoded
into the requests parameterMap
.
See this github issue: https://github.com/spring-projects/spring-framework/issues/21439
This filter was active by default in spring-boot 2.1.X.
Since this behavior is unwanted in most cases, a property was created to enable/disable it and with spring-boot 2.2.X it was deactivated by default.
Since your code relies on this filter, you can enable it via the following property:
QUESTION
I was wondering if there was a way to pass arguments the a class extending the Service class from the Javafx concurrent package. I would like ProteinariumThread to take in a String argument like ClusterID seen below:
...ANSWER
Answered 2020-Jun-08 at 18:18You just need to give your service class a constructor and/or method which accepts the necessary argument. As services are meant to be reusable, it'd probably be best to allow configuration throughout the service's lifetime by exposing a property:
QUESTION
The other day, I wrote a console game of Tic-Tac-Toe in c++ for my son. He wanted me to add a computer, and I ended us using the minimax algorithm for the first time. I did some quick testing, but really just gave my laptop to my son as soon as it was printing stuff, who played with it for a couple minuets. I looked over his sholder once or twice, and noticed that it wasn't playing optimally, iv'e been trying to debug it, but I can't see where it goes wrong. I tried getting rid of alpha beta prunning, but that did not change anything.
For context, on the board the computer is -1, blank is 0, and the player is 1.
Here is the minimax function:
...ANSWER
Answered 2020-Jun-02 at 22:28It looks like you only call minimax with a depth of three, so the algorithm will only look up to three moves ahead, if you want optimal play you need to set the depth to > 9, so that the agent is always looking ahead to the end of the game.
QUESTION
I'm getting this error in a google colab notebook. Do I need to install something or it's just not possible to use pypy inside colab? I've tried this simple script:
...ANSWER
Answered 2020-Apr-14 at 03:30You can use pypy in Colab once you install it on the Colab VM:
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