ProjectBabble
torchinfo
| ProjectBabble | torchinfo | |
|---|---|---|
| 1 | 3 | |
| 183 | 2,307 | |
| 12.6% | - | |
| 8.5 | 6.9 | |
| 3 months ago | 3 days ago | |
| Python | Python | |
| Apache License 2.0 | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
ProjectBabble
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Vive focus 3 facial tracker with index
hm, maybe you could get the camera itself to work on PC but i don't think youd be able to switch on the LED's. If you somehow get it working, you can use it with project babble
torchinfo
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[D] PyTorch and Tensorflow Performance Different on the same model, dataset and hyperparameters
It may be a good idea to compare the implementation of the models using Keras's Model.summary and PyTorch's torchinfo.
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after adding a nn.Dropout() layer, the number of parameters won't change?
No they wont change. If you are interested in viewing parameters check out Torchinfo https://github.com/TylerYep/torchinfo
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zero_grad() is supposed to be invoked every time one data point passed? How does a scalar.backward() from a loss function affect another model parameters?
You can use torchinfo, it has a # params column and it's a nice way to log and debug a NN architecture to make sure all the layers you expect are connected.
What are some alternatives?
merged_depth - Monocular Depth Estimation - Weighted-average prediction from multiple pre-trained depth estimation models
QualityScaler - QualityScaler - image/video deeplearning upscaling for any GPU
torchgeo - TorchGeo: datasets, samplers, transforms, and pre-trained models for geospatial data
MMdnn - MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.
TorchGA - Train PyTorch Models using the Genetic Algorithm with PyGAD
deepo - Setup and customize deep learning environment in seconds.
torchSR - Super Resolution datasets and models in Pytorch
d2l-en - Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
install_torch - This script can be used to automatically install torch and CUDA.