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numpy: revert change to use bitwise xor instead of logical_xor
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numpy/ufuncs.py

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Original file line numberDiff line numberDiff line change
@@ -128,7 +128,7 @@ def load(self, tensor, suiteSparse):
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# Run benchmarks against the FROSTT collection.
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FROSTTTensors = TensorCollectionFROSTT()
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@pytest.mark.parametrize("tensor", FROSTTTensors.getTensors())
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@pytest.mark.parametrize("ufunc", [numpy.bitwise_xor, numpy.ldexp, numpy.right_shift])
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@pytest.mark.parametrize("ufunc", [numpy.logical_xor, numpy.ldexp, numpy.right_shift])
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def bench_pydata_frostt_ufunc_sparse(tacoBench, tensor, ufunc):
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frTensor, other = inputCache.load(tensor, False)
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def bench():
@@ -145,7 +145,7 @@ def bench():
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else:
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tacoBench(bench, extra_info)
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fusedFuncs = [lambda a, b, c: numpy.bitwise_and(numpy.bitwise_xor(a, b), c)]
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fusedFuncs = [lambda a, b, c: numpy.logical_and(numpy.logical_xor(a, b), c)]
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fusedFuncNames = ["xorAndFused"]
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fusedFuncs = zip(fusedFuncs, fusedFuncNames)
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@pytest.mark.parametrize("tensor", FROSTTTensors.getTensors())
@@ -162,7 +162,7 @@ def bench():
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tacoBench(bench, extra_info)
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# Run benchmarks against the SuiteSparse collection.
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@pytest.mark.parametrize("ufunc", [numpy.bitwise_xor, numpy.ldexp, numpy.right_shift])
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@pytest.mark.parametrize("ufunc", [numpy.logical_xor, numpy.ldexp, numpy.right_shift])
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def bench_pydata_suitesparse_ufunc_sparse(tacoBench, ufunc):
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tensor = SuiteSparseTensor(os.getenv('SUITESPARSE_TENSOR_PATH'))
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ssTensor, other = inputCache.load(tensor, True)

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