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"Eigenvalues did not converge" error uncovered by Coverage-guided Fuzzing #101
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Most minimal code to reproduce is here: import numpy as np
from cmaes import CMA
def main():
mean = np.array([1.34078079e+138, 1.34078079e+138, 1.34078079e+138], dtype=float)
optimizer = CMA(mean=mean, sigma=1e-16)
while True:
solutions = []
for _ in range(optimizer.population_size):
x = np.zeros(3)
solutions.append((x, 0.0))
optimizer.tell(solutions)
if __name__ == "__main__":
main()
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Fixed the previous error at 3c1dd0d, then found new errors:
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Bug reports
To uncover bugs, I use hypothesis for coverage-guided fuzzing.
Expected Behavior
Does not raise exception.
Context
Please provide any relevant information about your setup. This is important in case the issue is not reproducible except for under certain conditions.
hypothesis
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