AMEVA-Forge Documentation

Release 2.0.0 Initializing WebGPU... [ Live WebGPU Studio ] [ GitHub Repository ]

5. Autograd GradCheck (Analytical vs Finite Difference)

Mathematically verifies WebGPU automatic differentiation by comparing analytical backward gradients with finite-difference numerical approximations.

Device Target: WebGPU
Max Grad Error (|Δ|): --
GradCheck Status: Ready
Latency: 0.0 ms

Select Target Differentiable Function

WebGPU Gradient Verification Results

Click Execute to run automatic differentiation.
Param / Index Analytical Grad Finite Diff (ε=1e-4) Error (|Δ|) Verdict
Waiting for execution...

Dynamic Backward DAG Nodes

Technical & Mathematical Deep-Dive