def testMultipleOutputExecute(self):
data = np.random.random((5, 9))
# test multiple outputs
arr1 = mt.tensor(data.copy(), chunk_size=3)
result = mt.modf(arr1).execute()
expected = np.modf(data)
np.testing.assert_array_equal(result[0], expected[0])
np.testing.assert_array_equal(result[1], expected[1])
# test 1 output
arr2 = mt.tensor(data.copy(), chunk_size=3)
result = ((arr2 + 1) * 2).execute()
expected = (data + 1) * 2
np.testing.assert_array_equal(result, expected)
# test multiple outputs, but only execute 1
arr3 = mt.tensor(data.copy(), chunk_size=3)
arrs = mt.split(arr3, 3, axis=1)
result = arrs[0].execute()
expected = np.split(data, 3, axis=1)[0]
np.testing.assert_array_equal(result, expected)
# test multiple outputs, but only execute 1
data = np.random.randint(0, 10, (5, 5))
arr3 = mt.tensor(data)
arrs = mt.linalg.qr(arr3)
result = arrs[0].execute()
expected = np.linalg.qr(data)[0]
np.testing.assert_array_almost_equal(result, expected)
def testSessionExecute(self):
a = mt.random.rand(10, 20)
res = a.sum().execute()
self.assertTrue(np.isscalar(res))
self.assertLess(res, 200)
data = np.random.random((5, 9))
# test multiple outputs
arr1 = mt.tensor(data.copy(), chunks=3)
result = mt.modf(arr1).execute()
expected = np.modf(data)
np.testing.assert_array_equal(result[0], expected[0])
np.testing.assert_array_equal(result[1], expected[1])
# test 1 output
arr2 = mt.tensor(data.copy(), chunks=3)
result = ((arr2 + 1) * 2).execute()
expected = (data + 1) * 2
np.testing.assert_array_equal(result, expected)
# test multiple outputs, but only execute 1
arr3 = mt.tensor(data.copy(), chunks=3)
arrs = mt.split(arr3, 3, axis=1)
result = arrs[0].execute()
expected = np.split(data, 3, axis=1)[0]
np.testing.assert_array_equal(result, expected)
def test_multiple_output_execute(setup):
data = np.random.random((5, 9))
# test multiple outputs
arr1 = mt.tensor(data.copy(), chunk_size=3)
result = mt.modf(arr1).execute().fetch()
expected = np.modf(data)
np.testing.assert_array_equal(result[0], expected[0])
np.testing.assert_array_equal(result[1], expected[1])
# test 1 output
arr2 = mt.tensor(data.copy(), chunk_size=3)
result = ((arr2 + 1) * 2).to_numpy()
expected = (data + 1) * 2
np.testing.assert_array_equal(result, expected)
# test multiple outputs, but only execute 1
arr3 = mt.tensor(data.copy(), chunk_size=3)
arrs = mt.split(arr3, 3, axis=1)
result = arrs[0].to_numpy()
expected = np.split(data, 3, axis=1)[0]
np.testing.assert_array_equal(result, expected)
# test multiple outputs, but only execute 1
data = np.random.randint(0, 10, (5, 5))
arr3 = (mt.tensor(data) + 1) * 2
arrs = mt.linalg.qr(arr3)
result = (arrs[0] + 1).to_numpy()
expected = np.linalg.qr((data + 1) * 2)[0] + 1
np.testing.assert_array_almost_equal(result, expected)
result = (arrs[0] + 2).to_numpy()
expected = np.linalg.qr((data + 1) * 2)[0] + 2
np.testing.assert_array_almost_equal(result, expected)
s = mt.shape(0)
result = s.execute().fetch()
expected = np.shape(0)
assert result == expected
def testMultipleOutputExecute(self):
with option_context({'eager_mode': True}):
data = np.random.random((5, 9))
arr1 = mt.tensor(data.copy(), chunk_size=3)
result = mt.modf(arr1)
expected = np.modf(data)
np.testing.assert_array_equal(result[0].fetch(), expected[0])
np.testing.assert_array_equal(result[1].fetch(), expected[1])
arr3 = mt.tensor(data.copy(), chunk_size=3)
result1, result2, result3 = mt.split(arr3, 3, axis=1)
expected = np.split(data, 3, axis=1)
np.testing.assert_array_equal(result1.fetch(), expected[0])
np.testing.assert_array_equal(result2.fetch(), expected[1])
np.testing.assert_array_equal(result3.fetch(), expected[2])
def testSessionExecute(self):
a = mt.random.rand(10, 20)
res = a.sum().execute()
self.assertTrue(np.isscalar(res))
self.assertLess(res, 200)
data = np.random.random((5, 9))
# test multiple outputs
arr1 = mt.tensor(data.copy(), chunk_size=3)
result = mt.modf(arr1).execute()
expected = np.modf(data)
np.testing.assert_array_equal(result[0], expected[0])
np.testing.assert_array_equal(result[1], expected[1])
# test 1 output
arr2 = mt.tensor(data.copy(), chunk_size=3)
result = ((arr2 + 1) * 2).execute()
expected = (data + 1) * 2
np.testing.assert_array_equal(result, expected)
# test multiple outputs, but only execute 1
arr3 = mt.tensor(data.copy(), chunk_size=3)
arrs = mt.split(arr3, 3, axis=1)
result = arrs[0].execute()
expected = np.split(data, 3, axis=1)[0]
np.testing.assert_array_equal(result, expected)
# test run the same tensor
arr4 = mt.tensor(data.copy(), chunk_size=3) + 1
result1 = arr4.execute()
expected = data + 1
np.testing.assert_array_equal(result1, expected)
result2 = arr4.execute()
np.testing.assert_array_equal(result1, result2)
# test run the same tensor with single chunk
arr4 = mt.tensor(data.copy())
result1 = arr4.execute()
expected = data
np.testing.assert_array_equal(result1, expected)
result2 = arr4.execute()
np.testing.assert_array_equal(result1, result2)
# test run same key tensor
arr5 = mt.ones((10, 10), chunk_size=3)
result1 = arr5.execute()
del arr5
arr6 = mt.ones((10, 10), chunk_size=3)
result2 = arr6.execute()
np.testing.assert_array_equal(result1, result2)
