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Based on our record, Extism should be more popular than TensorFlow. It has been mentiond 19 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
I started using WebAssembly in earnest a few months ago to make a backend auth library that works in several different languages[0]. It's built on Extism[1], which abstracts away some of the interfacing complexity. It's been an awesome experience. Frequently feels like magic. WASM is in an interesting place. The value has clearly been proved with a pretty minimal core spec. Now there's a big push to implement a... - Source: Hacker News / about 1 month ago
Application plugins could also be wasm. That lets plugin authors write in any language they want and have their plugin work. That's the idea behind the Extism framework: https://extism.org/. - Source: Hacker News / 3 months ago
The WebAssembly component model is aimed at having composable components that can call each other. The components can be written in any language, compiled to WebAssembly, and interoperate: https://github.com/WebAssembly/component-model/ https://github.com/extism/extism A project to bring WebAssembly plugins to Godot: https://github.com/ashtonmeuser/godot-wasm Wasmer can be embedded in applications:... - Source: Hacker News / 4 months ago
This is exactly what we created Extism[0] and XTP[1] for! [0]: https://extism.org. - Source: Hacker News / 7 months ago
This is an exciting option as it provides a sandboxed environment to run code. One caveat is that you need an environment with Javascript bindings. However, an interesting project called Extism facilitates that. You might want to follow their tutorial. - Source: dev.to / 10 months ago
Converting the images to a tensor: Deep learning models work with tensors, so the images should be converted to tensors. This can be done using the to_tensor function from the PyTorch library or convert_to_tensor from the Tensorflow library. - Source: dev.to / about 2 years ago
So I went to tensorflow.org to find some function that can generate a CSR representation of a matrix, and I found this function https://www.tensorflow.org/api_docs/python/tf/raw_ops/DenseToCSRSparseMatrix. Source: almost 3 years ago
Can anyone offer up an explanation for why there is a performance difference, and if possible, what could be done to fix it. I'm using the installation guidelines found on tensorflow.org and installing tf2.7 through pip using an anaconda3 env. Source: almost 3 years ago
I don't have much experience with TensorFlow, but I'd recommend starting with TensorFlow.org. Source: about 3 years ago
I have looked at this TensorFlow website and TensorFlow.org and some of the examples are written by others, and it seems that I am stuck in RNNs. What is the best way to install TensorFlow, to follow the documentation and learn the methods in RNNs in Python? Is there a good tutorial/resource? Source: about 3 years ago
OpenCL - Application and Data, Languages & Frameworks, and Language Extensions
PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...
Wasmer - The Universal WebAssembly Runtime
Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.
Docker Compose - Define and run multi-container applications with Docker
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.