Dear Forum, I am trying to add ODE into machine learning pipeline and calculate the gradient of an ode layer that takes the RHS as an argument. We tried to feed the RHS, in terms of inputFunction(t), into ODE (i.e. fiip function). In fiip, inputFunction(t) is extracted from p, which is fed in funct…

Failure to calculate the gradient of ODE with the RHS as an argument: "LoadError: TypeError: in TrackedReal, in V, expected V<:Real, got Type{Any}"

ChrisRackauckas June 15, 2020, 11:30pm 2

Are you using Julia v1.4?

Topic		Replies	Views
Getting gradients for DiffEq with single derivative Optimization (Mathematical)	3	835	June 17, 2020
Taking gradients when propagating through an ODE solver Machine Learning question	6	650	June 3, 2020
Flux.gradient throws MethodError even though loss is evaluated just fine New to Julia question , diffeq	3	580	April 16, 2022
Using Flux: gradient on DifferentialEquations: solve results in an error New to Julia question , diffeq , differentiation	11	1050	May 8, 2023
The tracked parameters are not updated during Flux.training General Usage diffeq , flux	2	805	July 6, 2020