50 lines
1.3 KiB
Nix
50 lines
1.3 KiB
Nix
{ lib
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, fetchFromGitHub
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, buildPythonPackage
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, numpy
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, scipy
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, torch
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, autograd
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, nose2
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, matplotlib
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, tensorflow
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}:
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buildPythonPackage rec {
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pname = "pymanopt";
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version = "2.0.0";
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src = fetchFromGitHub {
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owner = pname;
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repo = pname;
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rev = "refs/tags/${version}";
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sha256 = "sha256-dqyduExNgXIbEFlgkckaPfhLFSVLqPgwAOyBUdowwiQ=";
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};
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propagatedBuildInputs = [ numpy scipy torch ];
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checkInputs = [ nose2 autograd matplotlib tensorflow ];
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checkPhase = ''
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runHook preCheck
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# FIXME: Some numpy regression?
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# Traceback (most recent call last):
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# File "/build/source/tests/manifolds/test_hyperbolic.py", line 270, in test_second_order_function_approximation
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# self.run_hessian_approximation_test()
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# File "/build/source/tests/manifolds/_manifold_tests.py", line 29, in run_hessian_approximation_test
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# assert np.allclose(np.linalg.norm(error), 0) or (2.95 <= slope <= 3.05)
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# AssertionError
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rm tests/manifolds/test_hyperbolic.py
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nose2 tests -v
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runHook postCheck
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'';
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pythonImportsCheck = [ "pymanopt" ];
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meta = {
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description = "Python toolbox for optimization on Riemannian manifolds with support for automatic differentiation";
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homepage = "https://www.pymanopt.org/";
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license = lib.licenses.bsd3;
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maintainers = with lib.maintainers; [ yl3dy ];
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};
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}
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