I'm trying to train my model with new intent and entities but I see an error called "string indices must be integers" as you can see:
Please help with a quick fix. Thanks
what you need to do is this.
you need to disable the gazette in the pipeline.
Go to settings up! in NLU pipeline, remove name: rasa_addons.nlu.components.gazette.Gazette
Thanks
Related
I have trained Kaldi models (tri1b ... tri3b) and I am get WERs. I have also successfully installed sclite as well inside kalde/tools
I have read through the few pages of sclite documentations available. the only useful information I have been able to gather is that I need a ref.txt and hyp.txt.
can anyone please guide me step by step how to run the sclite too?
I am new to ML and W&B, and I am trying to use W&B to do a hyperparameter sweep. I created a few sweeps and when I run them I get a bunch of new runs in my project (as I would expect):
Image: New runs being created
However, all of the new runs say "no metrics logged yet" (Image) and are instead all of their metrics are going into one run (the one with the green dot in the photo above). This makes it not useable, of course, since all the metrics and images and graph data for many different runs are all being crammed into one run.
Is there anyone that has some experience in W&B? I feel like this is an issue that should be relatively straightforward to solve - like something in the W&B config that I need to change.
Any help would be appreciated. I didn't give too many details because I am hoping this is relatively straightforward, but if there are any specific questions I'd be happy to provide more info. The basics:
Using Google Colab for training
Project is a PyTorch-YOLOv3 object detection model that is based on this: https://github.com/ultralytics/yolov3
Thanks! 😊
Update: I think I figured it out.
I was using the train.py code from the repository I linked in the question, and part of that code specifies the id of the run (used for resuming).
I removed the part where it specifies the ID, and it is now working :)
Old code:
wandb_run = wandb.init(config=opt, resume="allow",
project='YOLOv3' if opt.project == 'runs/train' else Path(opt.project).stem,
name=save_dir.stem,
id=ckpt.get('wandb_id') if 'ckpt' in locals() else None)
New code:
wandb_run = wandb.init(config=opt, resume="allow",
project='YOLOv3' if opt.project == 'runs/train' else Path(opt.project).stem,
name=save_dir.stem)
So I'm learning a little bit about Taurus and was trying to apply some pass fail criteria to my .jmx script. When I try to evaluate a specific sampler, it seems to not run the pass fail criteria at all, but if I were to do a simple avg-rt > 10s, continue as failed , this works, but the issue is I want to evaluate each sampler specifically.
Here is a screenshot of my .yml file
I was using this link as reference to follow but I can't seem to get it to work with my script.
https://dzone.com/articles/running-your-load-tests-with-pass-fail-criteria-a
Any help and advice would be appreciated :)
Thank you!
For me it seems to run pass/fail criteria
As you like screenshots here is the screenshot of Taurus YAML file:
And here is the screenshot of "test.jmx" which basically uses simple single Dummy Sampler:
Just in case here is the link to the official documentation of the subsystem: Pass/Fail Criteria
So the issue was that spaces matter lol.
rewriting it as avg-rt of first_navigate>1s, continue as failed does the trick :)
I download and run the file from the link below
https://github.com/keunwoochoi/keras_callbacks_example
But the it has the error "Sequential has no attribute "validation_data"". Can anyone explain for me?
Try using self.model.predict(self.validation_data[0]). That is what worked for me.
You can always check what is in the object with dir().
I had the same problem using self.model.validation_data. Checking with dir(self.model) showed me that there was indeed no attribute validation_data for my particular problem. But then checking dir(self) I could find it.
i had the same issue.
here is the solution:
use self.validation_data in your custom callback class
provide validation_data = (x,y) in your fit method.
if point 2 is not done, self.validation_data will be empty.
hope this helps
This would work on the object of type keras.engine.training.Model.
Try self.model.validation_data
Try self.validation_data instead of self.model.validation_data for Keras 2.0 and after.
You'll also have to define validation_data within fit(). Using train_test_split, validation_data=(X_test, y_test).
Example: https://www.kaggle.com/yassinealouini/f2-score-per-epoch-in-keras
I am trying to use the Sphinx4 library for speech recognition, but I cannot seem to figure out the correct combination of acoustic model-dictionary-language model. I have tried out various combinations and I get a different error every time.
I am trying to follow the tutorial on http://cmusphinx.sourceforge.net/wiki/tutorialsphinx4. I do not have a config.xml as I would if I was using ConfigurationManager instead of Configuration, because there is no perceivable way of passing the location of the config file to the Configuration itself (ConfigMgr takes it as an argument to the constructor); and that might be my problem right there. I just do not know how to point to one, and since the tutorial says "It is possible to configure low-level components of the application through XML file although you should do that ONLY IF you understand what is going on.", I assume having a config.xml file is not compulsory.
Combining the latest dictionary (7b - obtained from Sourceforge) with the latest acoustic model (cmusphinx-en-us-5.2.tar.gz - from SF again) and the language model (cmusphinx-5.0-en-us.lm.gz - from SF again) results in NullPointerException in startRecognition. The issue is similar to the problem here: sphinx-4 NullPointerException at startRecognition, but the link given in the answer no longer works. I obtained 0.7a from SF (since that is the dict the link seems to point at), but I am getting even earlier in the execution Error loading word: ;;; when I use that one. I tried downloading latest models and dict from the Github repo, that results in java.lang.IndexOutOfBoundsException: Index: 16128, Size: 16128.
Any help is much appreciated!
You need to use latest code from github
http://github.com/cmusphinx/sphinx4
as described by tutorial
http://cmusphinx.sourceforge.net/wiki/tutorialsphinx4
Correct models (en-us) are already included, you should not replace anything. You should not configure any XML files, use samples as provided in the sources.