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The relevant metric is the literature - adoption is driven by new models, and most new models in academia are being implemented in PyTorch or JAX. (In particula
by adw 4y ago
The relevant metric is the literature - adoption is driven by new models, and most new models in academia are being implemented in PyTorch or JAX. (In particular, TensorFlow 2 is nowhere to be seen.) The new grads joining the workforce are going to continue to use the tools they are comfortable with and new projects are built around new models.
- grepLeigh 4y agoIf you're familiar with the plumbing/porcelain API paradigm, JAX depends on TensorFlow plumbing (XLA) with a more ergonomic porcelain API. You might not see TensorFlow's plumbing much anymore if you're a new grad running experiments in a notebook, but the "porcelain API" is just the tip of the ice berg of modern machine learning. If you do any work on the JAX framework, you're frequently working with both the JAX and TensorFlow code repositories: https://github.com/google/jax/blob/main/WORKSPACE#L17 https://github.com/google/jax/blob/main/WORKSPACE#L17
- zone411 4y agoYes, I have been reading a lot of papers in the last couple of years and the corresponding code, if available, is using PyTorch much more often than TensorFlow.