I have some confusion with steps_per_epoch. Any clarification is appreciated.
I read that steps_per_epoch is normally set to number of samples/batch size. However, I am following this tutorial https://medium.com/the-owl/k-fold-cross-validation-in-keras-3ec4a3a00538
that uses train_data_generator=idg.flow_from_dataframe().
Am I correct in setting steps_per_epoch to be len(train_data_generator)/32 instead of len(training_data)/32.
Thank you in advance!
Related
How can I specify in the construction of the HistFactory the signal and background to be 2-dimensional distributions?
I have understood than in RooStats you need to change the TH1 to a TH2.
At the moment to write my model in the json file can I use a ndarray to do something similar?.
Which is the correct way to do this?
I hope someone can help me and thank you in advance.
Currently the best way is to unroll the distributions e.g.
{'data': 2darray.ravel().tolist()}
Since mathematically it doesn't make any difference.
If you want to convert from XML+ROOT this is not yet supported (but could be). If so, please open an issue on GitHub.
Thanks for using pyhf!
Has anyone found an Input Mask library that works with Vuetify using a directive? I have tried Cleave.js, vue-mask, imask, and a few other and they all seem to fall short or are buggy. Any suggestions would be appreciated.
is there a specific thing that you are trying to achieve, the mask that they have by default you can use to mask text fields already they have some pre-made and you can customize to your needs. I'm just curious as what you are trying to achieve.
Thanks for your response. I have looked at the provided masks but they dont work for my needs. For instance, I want to have an input field that only accepts numbers but isnt limited to the amount of numbers. If I put mask="####" as the attribute it will only allow numbers but only 4 digits. If I want to allow unlimited numbers how would I accomplish that? Thanks for your help
If anyone know where can see different values (settings) of a parameter? For example, if we need to change a default value, which other options do we have to set.
Thanks
The default settings are located in the according .ned file of your module. If you have a setup for your simulation you're usually changing your parameters in the omnetpp.ini file.
The TicToc tutorial gives you all information according to this, especially TicToc 7 might be useful for you.
I am using tutorial from here.
I use mask_rcnn_inception_v2 detection model with my own dataset. I want to add PNG mask, i use some applications to do it. but I wonder how i put this data to be used in detection. I see the mention anywhere.
How to implement the PNG mask in object detection ? (where i put it, how to use it)
Do you know how to launch the evaluation and training in same time on tensorboard i see it is possible.
generally where i can ask all Tensorflow general question as configuration file explanations
On Github Tensorflow it is specified we have to ask question here because not a Tensorflow issue and great community here with some great guys!
thanks to guy on github he points a missing configuration in pipeline.config
number_of_stages: 3
and it changes all the result i can see the mask now. youpi !
For any further information, there's a good explanation here:
https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/instance_segmentation.md
It explains how to prepare you masks and what to modify.
On Veins applications (veins/src/modules/application/app_name.(cc, h), how to get values like
*.car[*].appl.numVehicles from theini file?
I can get values like sim-time-limit (see below) and anothers createad by me one, by I can't acess values on *.car[*].* or *.rsu[*].* from ini file.
stringTmp = ev.getConfig()->getConfigValue("sim-time-limit");
I'd appreciate any help
I got the "numVehicles" parameter from the .ini file using the following codification:
long numV = Veins::TraCIScenarioManagerLaunchdAccess().get()->par("numVehicles").longValue();
I hope this can help you.
Douglas
Reading parameter values of a module can be done via a call to this module's par(...) method.
I would highly recommend doing the TicToc tutorial, where this is demonstrated succinctly