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Found 4 papers, 1 papers with code
Torch.fx: Practical Program Capture and Transformation for Deep Learning in Python
Modern deep learning frameworks provide imperative, eager execution programming interfaces embedded in Python to provide a productive development experience.
CompilerGym: Robust, Performant Compiler Optimization Environments for AI Research
What is needed is an easy, reusable experimental infrastructure for real world compiler optimization tasks that can serve as a common benchmark for comparing techniques, and as a platform to accelerate progress in the field.
Using Python for Model Inference in Deep Learning
We evaluate our design on a suite of popular PyTorch models on Github, showing how they can be packaged in our inference format, and comparing their performance to TorchScript.
Tight Prediction Intervals Using Expanded Interval Minimization
Many prior techniques for generating prediction intervals make assumptions on the distribution of error, which causes them to work poorly for problems with asymmetric distributions.
