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https://github.com/L-yang-yang/cugenopt.git
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54 lines
1.3 KiB
Python
54 lines
1.3 KiB
Python
"""
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cuGenOpt — GPU-accelerated general-purpose metaheuristic solver
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All problems (built-in and custom) use the same JIT compilation pipeline.
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First call to each problem type takes ~8s to compile; subsequent calls are cached.
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Usage:
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import numpy as np
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import cugenopt
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dist = np.random.rand(20, 20).astype(np.float32)
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dist = (dist + dist.T) / 2
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np.fill_diagonal(dist, 0)
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result = cugenopt.solve_tsp(dist, time_limit=5.0, seed=42)
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print(f"Best distance: {result['objective']:.2f}")
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print(f"Route: {result['solution'][0]}")
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"""
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from cugenopt.builtins import (
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solve_tsp,
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solve_knapsack,
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solve_qap,
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solve_assignment,
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solve_vrp,
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solve_vrptw,
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solve_graph_color,
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solve_bin_packing,
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solve_load_balance,
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gpu_info,
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)
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from cugenopt.jit import compile_and_solve as solve_custom, clear_cache
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from cugenopt.validation import CuGenOptValidationError, CuGenOptCompileError
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from cugenopt.operators import CustomOperator
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__version__ = "0.2.0"
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__all__ = [
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"solve_tsp",
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"solve_knapsack",
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"solve_qap",
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"solve_assignment",
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"solve_vrp",
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"solve_vrptw",
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"solve_graph_color",
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"solve_bin_packing",
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"solve_load_balance",
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"gpu_info",
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"solve_custom",
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"clear_cache",
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"CuGenOptValidationError",
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"CuGenOptCompileError",
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"CustomOperator",
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]
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