57 lines
1.4 KiB
Python
57 lines
1.4 KiB
Python
'''
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Test parallel-vectorize with numpy.fromfunc.
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Uses the work load from test_parallel_vectorize.
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'''
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from test_parallel_vectorize import *
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import numpy as np
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def main():
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module = Module.new(__name__)
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spufdef = SpecializedParallelUFunc(ParallelUFuncPosix(num_thread=2),
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UFuncCore_D_D(),
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Work_D_D())
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sppufunc = spufdef(module)
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module.verify()
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mpm = PassManager.new()
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pmbuilder = PassManagerBuilder.new()
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pmbuilder.opt_level = 3
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pmbuilder.populate(mpm)
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mpm.run(module)
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# print module
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# run
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exe = CExecutor(module)
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funcptr = exe.engine.get_pointer_to_function(sppufunc)
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print("Function pointer: %x" % funcptr)
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ptr_t = long # py2 only
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# Becareful that fromfunc does not provide full error checking yet.
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# If typenum is out-of-bound, we have nasty memory corruptions.
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# For instance, -1 for typenum will cause segfault.
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# If elements of type-list (2nd arg) is tuple instead,
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# there will also memory corruption. (Seems like code rewrite.)
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typenum = np.dtype(np.double).num
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ufunc = np.fromfunc([ptr_t(funcptr)], [[typenum, typenum]], 1, 1, [None])
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x = np.linspace(0., 10., 1000)
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x.dtype=np.double
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# print x
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ans = ufunc(x)
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# print ans
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if not ( ans == x/2.345 ).all():
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raise ValueError('Computation failed')
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else:
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print('Good')
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if __name__ == '__main__':
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main()
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