def test_matrix_vector(self):
xy_lt = core.LabeledTensor(tf.reshape(tf.range(6), (2, 3)), ['x', 'y'])
y_lt = core.LabeledTensor(tf.range(3), ['y'])
matmul_lt = ops.matmul(xy_lt, y_lt)
golden_lt = core.LabeledTensor(
tf.matmul(xy_lt.tensor, tf.reshape(y_lt.tensor, (-1, 1)))[:, 0], ['x'])
self.assertLabeledTensorsEqual(matmul_lt, golden_lt)
matmul_lt = ops.matmul(y_lt, xy_lt)
self.assertLabeledTensorsEqual(matmul_lt, golden_lt)
def test_matrix_matrix_axis_order(self):
xy_lt = core.LabeledTensor(tf.reshape(tf.range(6), (2, 3)), ['x', 'y'])
yz_lt = core.LabeledTensor(tf.reshape(tf.range(12), (3, 4)), ['y', 'z'])
golden_lt = core.LabeledTensor(
tf.matmul(xy_lt.tensor, yz_lt.tensor), ['x', 'z'])
with core.axis_order_scope(['x', 'y', 'z']):
matmul_lt = ops.matmul(xy_lt, yz_lt)
self.assertLabeledTensorsEqual(matmul_lt, golden_lt)
matmul_lt = ops.matmul(yz_lt, xy_lt)
self.assertLabeledTensorsEqual(matmul_lt, golden_lt)
def test_invalid(self):
scalar_lt = core.LabeledTensor(array_ops.ones(()), [])
x_lt = core.LabeledTensor(array_ops.ones((2, )), ['x'])
x2_lt = core.LabeledTensor(array_ops.ones((3, )), ['x'])
y_lt = core.LabeledTensor(array_ops.ones((3, )), ['y'])
xy_lt = core.LabeledTensor(array_ops.ones((2, 3)), ['x', 'y'])
xyz_lt = core.LabeledTensor(array_ops.ones((2, 3, 1)), ['x', 'y', 'z'])
with self.assertRaisesRegexp(ValueError, 'inputs with at least rank'):
ops.matmul(x_lt, scalar_lt)
with self.assertRaises(NotImplementedError):
ops.matmul(x_lt, xyz_lt)
with self.assertRaisesRegexp(ValueError, 'exactly one axis in common'):
ops.matmul(x_lt, y_lt)
with self.assertRaises(NotImplementedError):
ops.matmul(xy_lt, xy_lt)
with self.assertRaisesRegexp(ValueError, 'does not match'):
ops.matmul(x_lt, x2_lt)
def test_invalid(self):
scalar_lt = core.LabeledTensor(array_ops.ones(()), [])
x_lt = core.LabeledTensor(array_ops.ones((2,)), ['x'])
x2_lt = core.LabeledTensor(array_ops.ones((3,)), ['x'])
y_lt = core.LabeledTensor(array_ops.ones((3,)), ['y'])
xy_lt = core.LabeledTensor(array_ops.ones((2, 3)), ['x', 'y'])
xyz_lt = core.LabeledTensor(array_ops.ones((2, 3, 1)), ['x', 'y', 'z'])
with self.assertRaisesRegexp(ValueError, 'inputs with at least rank'):
ops.matmul(x_lt, scalar_lt)
with self.assertRaises(NotImplementedError):
ops.matmul(x_lt, xyz_lt)
with self.assertRaisesRegexp(ValueError, 'exactly one axis in common'):
ops.matmul(x_lt, y_lt)
with self.assertRaises(NotImplementedError):
ops.matmul(xy_lt, xy_lt)
with self.assertRaisesRegexp(ValueError, 'does not match'):
ops.matmul(x_lt, x2_lt)
def test_matrix_matrix(self):
xy_lt = core.LabeledTensor(tf.reshape(tf.range(6), (2, 3)), ['x', 'y'])
yz_lt = core.LabeledTensor(tf.reshape(tf.range(12), (3, 4)), ['y', 'z'])
matmul_lt = ops.matmul(xy_lt, yz_lt)
golden_lt = core.LabeledTensor(
tf.matmul(xy_lt.tensor, yz_lt.tensor), ['x', 'z'])
self.assertLabeledTensorsEqual(matmul_lt, golden_lt)
transpose = lambda x: core.transpose(x, list(x.axes.keys())[::-1])
matmul_lt = ops.matmul(xy_lt, transpose(yz_lt))
self.assertLabeledTensorsEqual(matmul_lt, golden_lt)
matmul_lt = ops.matmul(transpose(xy_lt), yz_lt)
self.assertLabeledTensorsEqual(matmul_lt, golden_lt)
matmul_lt = ops.matmul(transpose(xy_lt), transpose(yz_lt))
self.assertLabeledTensorsEqual(matmul_lt, golden_lt)
matmul_lt = ops.matmul(yz_lt, xy_lt)
self.assertLabeledTensorsEqual(matmul_lt, transpose(golden_lt))
def test_vector_vector(self):
x_lt = core.LabeledTensor(math_ops.range(3), ['x'])
matmul_lt = ops.matmul(x_lt, x_lt)
golden_lt = core.convert_to_labeled_tensor(5)
self.assertLabeledTensorsEqual(matmul_lt, golden_lt)
def test_name(self):
x_lt = core.LabeledTensor(array_ops.ones((3, )), ['x'])
matmul_lt = ops.matmul(x_lt, x_lt)
self.assertIn('lt_matmul', matmul_lt.name)
def test_vector_vector(self): x_lt = core.LabeledTensor(math_ops.range(3), ['x']) matmul_lt = ops.matmul(x_lt, x_lt) golden_lt = core.convert_to_labeled_tensor(5) self.assertLabeledTensorsEqual(matmul_lt, golden_lt)
def test_name(self):
x_lt = core.LabeledTensor(array_ops.ones((3,)), ['x'])
matmul_lt = ops.matmul(x_lt, x_lt)
self.assertIn('lt_matmul', matmul_lt.name)
