
DOCS . JAX . DEV {
}
Title:
The Autodiff Cookbook β JAX documentation
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4 years and 8 months (reg. 2020-11-01).
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Keywords {π}
function, def, return, jax, jacobian, grad, functions, reversemode, matrix, vector, jvp, products, product, key, autodiff, check, point, type, vjps, complex, inputs, jacfwd, jacrev, tangent, python, write, efficient, forwardmode, vjp, import, evaluating, jvps, randomsplitkey, subkey, hessianvector, hessian, back, differentiation, vmap, linear, loss, wgrad, matrices, loop, matrixjacobian, works, forward, full, result, map,
Topics {βοΈ}
aka multi-process/multi-host jax equivalently jacobian-transpose-vector products gauss-newton vector products cauchy-riemann equations ensure vmapped matrix-jacobian products vmapped jacobian-matrix products vmapped matrix-jacobian product' vmapped jacobian-matrix product' '\nvmapped matrix-jacobian product' '\nvmapped jacobian-matrix product' complex-valued operations internally aka reverse-mode autodiff aka forward-mode autodiff hessian-vector product function random hessian-vector products evaluating vector-jacobian products evaluating jacobian-vector products vjps hessian-vector products taking vector-valued gradients distributed data loading write fast matrix-jacobian jvp-transformed function executes reverse-mode automatic differentiation differentiating scalar-valued functions forward-mode automatic differentiation multi-controller jax vector-jacobian products jacobian-vector product host offloading introduction pull-back single vectors neat autodiff ideas custom data types matrix-jacobian products jacobian-matrix products real-valued loss functions fast jacobian-matrix matrix-jacobian product vector-valued gradients reverse-mode composing vjps fixed-points estimating hot tangent vector vector-matrix multiplies training neural networks vector-valued arguments jacobian pre-accumulation functional differential geometry reverse-mode autodiff nested lists/dicts/tuples full jacobian matrix forward-mode autodiff
Questions {β}
- What about VJPs?
- What about convenience wrappers like grad, jacfwd, and jacrev?
- Whatβs with the negatives?
External Links {π}(20)
- Income figures for https://github.com/jax-ml/jax
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- Revenue of https://en.wikipedia.org/wiki/Holomorphic_function
- Learn how profitable https://en.wikipedia.org/wiki/Cauchy%E2%80%93Riemann_equations is on a monthly basis
Libraries {π}
- Bootstrap
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