def testSameDim(self):
A = CuMatrix()
B = CuMatrix()
self.assertTrue(same_dim_cu_matrix(A, B))
A = CuMatrix.new_from_size(10, 10)
B = CuMatrix.new_from_size(10, 9)
self.assertFalse(same_dim_cu_matrix(A, B))
def testApproxEqual(self):
A = CuMatrix()
B = CuMatrix()
self.assertTrue(approx_equal_cu_matrix(A, B))
A.SetZero()
B.SetZero()
self.assertTrue(approx_equal_cu_matrix(A, B))
B.set_randn()
B.Scale(10.0)
self.assertFalse(approx_equal_cu_matrix(A, B))
def testNew(self):
A = CuMatrix()
self.assertIsNotNone(A)
self.assertEqual(0, A.num_rows())
self.assertEqual(0, A.num_cols())
dim = A.dim()
self.assertEqual(0, dim.rows)
self.assertEqual(0, dim.cols)
A = CuMatrix.new_from_size(10, 10)
self.assertIsNotNone(A)
self.assertEqual(10, A.num_rows())
self.assertEqual(10, A.num_cols())
dim = A.dim()
self.assertEqual(10, dim.rows)
self.assertEqual(10, dim.cols)
A = CuMatrix.new_from_matrix(Matrix([[2, 3], [5, 7]]))
self.assertIsNotNone(A)
self.assertEqual(2, A.num_rows())
self.assertEqual(2, A.num_cols())
B = CuMatrix.new_from_other(A)
self.assertIsNotNone(B)
self.assertEqual(2, B.num_rows())
self.assertEqual(2, B.num_cols())
def testResize(self):
A = CuMatrix()
A.resize(10, 10)
self.assertEqual(10, A.num_rows())
self.assertEqual(10, A.num_cols())
# A.resize(-1, -1) #This hard-crashes
A.resize(0, 0)
def aux(size_multiple):
num_matrices = 256
time_in_secs = 0.2
sizes = []
for i in range(num_matrices):
num_rows = kaldi_math.rand_int(1, 10)
num_rows *= num_rows
num_rows *= size_multiple
num_cols = kaldi_math.rand_int(1, 10)
num_cols *= num_cols
num_cols *= size_multiple
# There is a typo in kaldi
sizes.append((num_rows, num_rows))
matrices = [CuMatrix() for _ in range(num_matrices)]
tim = Timer()
num_floats_processed = 0
while tim.elapsed() < time_in_secs:
matrix = kaldi_math.rand_int(0, num_matrices - 1)
if matrices[matrix].num_rows() == 0:
num_rows, num_cols = sizes[matrix]
matrices[matrix].resize(num_rows, num_cols,
MatrixResizeType.UNDEFINED)
num_floats_processed += num_rows * num_cols
else:
matrices[matrix].resize(0, 0)
gflops = num_floats_processed / (tim.elapsed() * 1.0e9)
print(
"For CuMatrix::Reize float, for size multiple {}, speed was {} gigaflops"
.format(size_multiple, gflops))