Installation

Setup Access

Moreau is distributed via Gemfury and requires an access token.

1. Request access to get your token

2. Add to ~/.pip/pip.conf:

   [global]
   index-url = https://<your-token>:@pypi.fury.io/optimalintellect/
   extra-index-url = https://pypi.org/simple/
   

---

Quick Install

CPU Only

pip install moreau

Pure Python interface with Rust-based CPU solver.

GPU Support

pip install moreau[cuda]

CUDA 12 by default, or moreau[cuda13] for CUDA 13. Requires Python 3.12+.

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Choose Your Framework

PyTorch

pip install moreau[torch]

Requirements: PyTorch >= 2.0

Provides moreau.torch.Solver for neural network integration with autograd support.

JAX

pip install jax

Requirements: JAX >= 0.4.0

Provides moreau.jax.Solver compatible with jax.grad, jax.vmap, and jax.jit.

All

pip install moreau[all]

Install CPU + CUDA + PyTorch. Install JAX separately.

---

Verify Installation

Basic

import moreau
import numpy as np
from scipy import sparse

# Simple QP
P = sparse.diags([1.0, 1.0], format='csr')
q = np.array([1.0, 1.0])
A = sparse.csr_matrix([[1.0, 0.0], [0.0, 1.0]])
b = np.array([0.5, 0.5])

cones = moreau.Cones(num_nonneg_cones=2)
solver = moreau.Solver(P, q, A, b, cones=cones)
solution = solver.solve()

print(f"Solution: {solution.x}")
print(f"Status: {solver.info.status}")
print("Installation successful!")

PyTorch

import torch
from moreau.torch import Solver
import moreau

cones = moreau.Cones(num_nonneg_cones=2)
solver = Solver(
    n=2, m=2,
    P_row_offsets=torch.tensor([0, 1, 2]),
    P_col_indices=torch.tensor([0, 1]),
    A_row_offsets=torch.tensor([0, 1, 2]),
    A_col_indices=torch.tensor([0, 1]),
    cones=cones,
)

P_values = torch.tensor([1.0, 1.0], dtype=torch.float64)
A_values = torch.tensor([1.0, 1.0], dtype=torch.float64)
solver.setup(P_values, A_values)

q = torch.tensor([1.0, 1.0], dtype=torch.float64, requires_grad=True)
b = torch.tensor([0.5, 0.5], dtype=torch.float64)
solution = solver.solve(q, b)

print(f"Solution: {solution.x}")
print(f"Device: {solver.device}")
print("PyTorch installation successful!")

JAX

import jax.numpy as jnp
from moreau.jax import Solver
import moreau

cones = moreau.Cones(num_nonneg_cones=2)
solver = Solver(
    n=2, m=2,
    P_row_offsets=jnp.array([0, 1, 2]),
    P_col_indices=jnp.array([0, 1]),
    A_row_offsets=jnp.array([0, 1, 2]),
    A_col_indices=jnp.array([0, 1]),
    cones=cones,
)

P_data = jnp.array([1.0, 1.0])
A_data = jnp.array([1.0, 1.0])
q = jnp.array([1.0, 1.0])
b = jnp.array([0.5, 0.5])

solution = solver.solve(P_data, A_data, q, b)

print(f"Solution: {solution.x}")
print(f"Device: {solver.device}")
print("JAX installation successful!")

---

GPU Acceleration

CUDA Support

For NVIDIA GPUs, the CUDA backend provides significant speedups, especially for batched problems.

Check GPU availability:

import moreau

print(f"Available devices: {moreau.available_devices()}")
print(f"Default device: {moreau.default_device()}")
print(f"CUDA available: {moreau.device_available('cuda')}")

Force GPU usage:

settings = moreau.Settings(device='cuda')
solver = moreau.Solver(P, q, A, b, cones=cones, settings=settings)

---

Dependencies

Core Dependencies

Package	Version	Purpose
Python	>= 3.9	Runtime
NumPy	>= 1.19.0	Array operations
SciPy	>= 1.6.0	Sparse matrices
Pydantic	>= 2.0.0	Data validation
moreau-cpu	>= 0.1.0	CPU solver backend

Optional Dependencies

Package	Version	Purpose
moreau-cuda12	>= 0.1.0 (Python >= 3.12)	GPU solver backend
moreau-cuda13	>= 0.1.0 (Python >= 3.12)	GPU solver backend
PyTorch	>= 2.0	PyTorch integration
JAX	>= 0.4.0	JAX integration

---

Troubleshooting

ImportError: moreau-cpu not found

The core CPU backend is required. Install it with:

pip install moreau-cpu

Or reinstall moreau:

pip install --force-reinstall moreau

CUDA not detected

Ensure you have:

1. An NVIDIA GPU with CUDA support

2. CUDA drivers installed

3. The CUDA backend: pip install moreau[cuda]

Check CUDA availability:

import moreau
print(moreau.device_available('cuda'))

PyTorch/JAX import errors

Install the framework-specific extras:

pip install moreau[torch]  # For PyTorch
pip install jax            # For JAX