def test_float(self):
v1 = [
0, 1.0497366, 0.8494359, 0.66231006, 0.66231006, 0.8494359,
0, 0.66231006, 0.33652836, 0, 0, 0.5359344,
0.8494359, 0.66231006, 1.0497366, 0.33652836, 0.66231006, 0.8494359,
0.6800841, 0.33652836]
gen = libMHCUDA.minhash_cuda_init(len(v1), 128, devices=1, seed=7, verbosity=2)
vars = libMHCUDA.minhash_cuda_retrieve_vars(gen)
bgen = WeightedMinHashGenerator.__new__(WeightedMinHashGenerator)
bgen.dim = len(v1)
bgen.rs, bgen.ln_cs, bgen.betas = vars
bgen.sample_size = 128
bgen.seed = None
m = csr_matrix(numpy.array(v1, dtype=numpy.float32))
hashes = libMHCUDA.minhash_cuda_calc(gen, m).astype(numpy.int32)
libMHCUDA.minhash_cuda_fini(gen)
self.assertEqual(hashes.shape, (1, 128, 2))
true_hashes = numpy.array([bgen.minhash(v1).hashvalues], dtype=numpy.int32)
self.assertEqual(true_hashes.shape, (1, 128, 2))
try:
self.assertTrue((hashes == true_hashes).all())
except AssertionError as e:
print("---- TRUE ----")
print(true_hashes)
print("---- FALSE ----")
print(hashes)
raise e from None
def test_deferred(self):
v1 = [1, 0, 0, 0, 3, 4, 5, 0, 0, 0, 0, 6, 7, 8, 0, 0, 0, 0, 0, 0, 9, 10, 4]
v2 = [2, 0, 0, 0, 4, 3, 8, 0, 0, 0, 0, 4, 7, 10, 0, 0, 0, 0, 0, 0, 9, 0, 0]
gen = libMHCUDA.minhash_cuda_init(len(v1), 128, devices=1, verbosity=2)
vars = libMHCUDA.minhash_cuda_retrieve_vars(gen)
libMHCUDA.minhash_cuda_fini(gen)
gen = libMHCUDA.minhash_cuda_init(
len(v1), 128, devices=1, deferred=True, verbosity=2)
libMHCUDA.minhash_cuda_assign_vars(gen, *vars)
bgen = WeightedMinHashGenerator.__new__(WeightedMinHashGenerator)
bgen.dim = len(v1)
bgen.rs, bgen.ln_cs, bgen.betas = vars
bgen.sample_size = 128
bgen.seed = None
m = csr_matrix(numpy.array([v1, v2], dtype=numpy.float32))
hashes = libMHCUDA.minhash_cuda_calc(gen, m)
libMHCUDA.minhash_cuda_fini(gen)
self.assertEqual(hashes.shape, (2, 128, 2))
true_hashes = numpy.array([bgen.minhash(v1).hashvalues,
bgen.minhash(v2).hashvalues], dtype=numpy.uint32)
self.assertEqual(true_hashes.shape, (2, 128, 2))
try:
self.assertTrue((hashes == true_hashes).all())
except AssertionError as e:
print("---- TRUE ----")
print(true_hashes)
print("---- FALSE ----")
print(hashes)
raise e from None