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This library provides ordinary differential equation (ODE) solvers implemented in PyTorch. Backpropagation through ODE solutions is supported using the adjoint method for constant memory cost. For usage of ODE solvers in deep learning applications. As the solvers are implemented in PyTorch, algorithms in this repository are fully supported to run on the GPU.
| Package | Summary | Distribution | Download |
| python3-torchdiffeq-0.2.5-3.fc42.noarch.html | Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation | Fedora Rawhide for x86_64 | python3-torchdiffeq-0.2.5-3.fc42.noarch.rpm |
| python3-torchdiffeq-0.2.5-3.fc42.noarch.html | Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation | Fedora Rawhide for aarch64 | python3-torchdiffeq-0.2.5-3.fc42.noarch.rpm |
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