Add --solver argparse option to example scripts#229
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Explicitly opt out of sparse tensor invariant checks when converting scipy CSR matrices to torch CSR tensors. The input from scipy already guarantees sorted, deduplicated indices, so the checks are unnecessary. This silences the PyTorch UserWarning about implicit invariant check state.
Remove old jax_example.py and tutorial.ipynb, replace with 5 self-contained examples matching the PyTorch set: - hello_world: differentiate through least-squares, compare with jnp.linalg.lstsq - batching: batched least-squares in one call - lqr: learn LQR value function via trajectory rollouts (BPTT) - optimal_transport: sensitivity analysis of entropy-regularized OT - signal_denoising: learn TV denoising params with optax Adam Add run_example.sh with ./run_example.sh all support. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Remove hardcoded solver and device-specific code from examples. Solver is now configurable via --solver flag (DIFFCP, MOREAU, CUCLARABEL, MPAX). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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Summary
solver=cp.CUCLARABELand GPU/device-specific code fromtorch_example.pyandjax_example.py--solverargparse flag so users can choose any supported solver (DIFFCP, MOREAU, CUCLARABEL, MPAX)--solveris not specifiedTest plan
python examples/torch/torch_example.py(default solver)python examples/torch/torch_example.py --solver MOREAUpython examples/jax/jax_example.py(default solver)python examples/jax/jax_example.py --solver MOREAU🤖 Generated with Claude Code