CustomVjp ========= Define custom Vision-Jacobian Product (backward pass) for valid differentiation. **Abstract Signature:** ``CustomVjp(fun: Callable, nondiff_argnums: tuple = ())`` .. raw:: html

PyTorch

API: torch.autograd.function.Function
Strategy: Direct Mapping

JAX (Core)

API: jax.custom_vjp
Strategy: Direct Mapping

TensorFlow

API: tf.custom_gradient
Strategy: Direct Mapping

Flax NNX

API: flax.nnx.custom_vjp
Strategy: Direct Mapping

PaxML / Praxis

API: jax.custom_vjp
Strategy: Direct Mapping