def test_name(self):
align_lt_0, align_lt_1, _ = core.align(self.original_lt,
self.original_lt)
self.assertIn('lt_align', align_lt_0.name)
self.assertIn('/0', align_lt_0.name)
self.assertIn('lt_align', align_lt_1.name)
self.assertIn('/1', align_lt_1.name)
def test_identical_shaped_inputs(self):
offset_tensor = self.original_lt.tensor + 1
offset_lt = core.LabeledTensor(offset_tensor, self.original_lt.axes)
align_lt, align_offset_lt, broadcast_axes = core.align(
self.original_lt, offset_lt)
self.assertLabeledTensorsEqual(align_lt, self.original_lt)
self.assertLabeledTensorsEqual(align_offset_lt, offset_lt)
self.assertEqual(broadcast_axes, self.original_lt.axes)
def test_identical_shaped_inputs(self):
offset_tensor = self.original_lt.tensor + 1
offset_lt = core.LabeledTensor(offset_tensor, self.original_lt.axes)
align_lt, align_offset_lt, broadcast_axes = core.align(self.original_lt,
offset_lt)
self.assertLabeledTensorsEqual(align_lt, self.original_lt)
self.assertLabeledTensorsEqual(align_offset_lt, offset_lt)
self.assertEqual(broadcast_axes, self.original_lt.axes)
def test_different_inputs(self):
# The correct axis ordering is ['x', 'channel', 'probs'].
align_x_probs_lt, align_channel_probs_lt, broadcast_axes = core.align(
self.x_probs_lt, self.channel_probs_lt)
x_probs_golden_lt = core.LabeledTensor(
tf.reshape(self.x_probs_lt.tensor, [self.x_size, 1, self.probs_size]),
[self.a0, 'channel', self.a3])
self.assertLabeledTensorsEqual(align_x_probs_lt, x_probs_golden_lt)
channel_probs_golden_lt = core.LabeledTensor(
tf.reshape(self.channel_probs_lt.tensor,
[1, self.channel_size, self.probs_size]),
['x', self.a1, self.a3])
self.assertLabeledTensorsEqual(align_channel_probs_lt,
channel_probs_golden_lt)
self.assertEqual(broadcast_axes, core.Axes([self.a0, self.a1, self.a3]))
def test_axis_order_scope(self):
xz_lt = core.LabeledTensor(array_ops.ones((2, 3)), ['x', 'z'])
yz_lt = core.LabeledTensor(array_ops.ones((4, 3)), ['y', 'z'])
_, _, broadcast_axes = core.align(xz_lt, yz_lt)
self.assertEqual(list(broadcast_axes.keys()), ['x', 'y', 'z'])
_, _, broadcast_axes = core.align(yz_lt, xz_lt)
self.assertEqual(list(broadcast_axes.keys()), ['y', 'x', 'z'])
with core.axis_order_scope(['x', 'y', 'z']):
_, _, broadcast_axes = core.align(yz_lt, xz_lt)
self.assertEqual(list(broadcast_axes.keys()), ['x', 'y', 'z'])
with core.axis_order_scope(['x', 'y']):
with self.assertRaises(core.AxisOrderError):
core.align(xz_lt, yz_lt)
with self.assertRaises(core.AxisOrderError):
core.align(yz_lt, xz_lt)
def test_different_inputs(self):
# The correct axis ordering is ['x', 'channel', 'probs'].
align_x_probs_lt, align_channel_probs_lt, broadcast_axes = core.align(
self.x_probs_lt, self.channel_probs_lt)
x_probs_golden_lt = core.LabeledTensor(
array_ops.reshape(self.x_probs_lt.tensor,
[self.x_size, 1, self.probs_size]),
[self.a0, 'channel', self.a3])
self.assertLabeledTensorsEqual(align_x_probs_lt, x_probs_golden_lt)
channel_probs_golden_lt = core.LabeledTensor(
array_ops.reshape(self.channel_probs_lt.tensor,
[1, self.channel_size, self.probs_size]),
['x', self.a1, self.a3])
self.assertLabeledTensorsEqual(align_channel_probs_lt,
channel_probs_golden_lt)
self.assertEqual(broadcast_axes, core.Axes([self.a0, self.a1, self.a3]))
def test_axis_order_scope(self):
xz_lt = core.LabeledTensor(tf.ones((2, 3)), ['x', 'z'])
yz_lt = core.LabeledTensor(tf.ones((4, 3)), ['y', 'z'])
_, _, broadcast_axes = core.align(xz_lt, yz_lt)
self.assertEqual(list(broadcast_axes.keys()), ['x', 'y', 'z'])
_, _, broadcast_axes = core.align(yz_lt, xz_lt)
self.assertEqual(list(broadcast_axes.keys()), ['y', 'x', 'z'])
with core.axis_order_scope(['x', 'y', 'z']):
_, _, broadcast_axes = core.align(yz_lt, xz_lt)
self.assertEqual(list(broadcast_axes.keys()), ['x', 'y', 'z'])
with core.axis_order_scope(['x', 'y']):
with self.assertRaises(core.AxisOrderError):
core.align(xz_lt, yz_lt)
with self.assertRaises(core.AxisOrderError):
core.align(yz_lt, xz_lt)
def test_invalid_input(self):
lt_0 = core.LabeledTensor(array_ops.zeros([5]), [('a', range(5))])
lt_1 = core.LabeledTensor(array_ops.zeros([5]), [('a', range(1, 6))])
with self.assertRaises(ValueError):
core.align(lt_0, lt_1)
def test_invalid_input(self):
lt_0 = core.LabeledTensor(tf.zeros([5]), [('a', range(5))])
lt_1 = core.LabeledTensor(tf.zeros([5]), [('a', range(1, 6))])
with self.assertRaises(ValueError):
core.align(lt_0, lt_1)
def test_name(self):
align_lt_0, align_lt_1, _ = core.align(self.original_lt, self.original_lt)
self.assertIn('lt_align', align_lt_0.name)
self.assertIn('/0', align_lt_0.name)
self.assertIn('lt_align', align_lt_1.name)
self.assertIn('/1', align_lt_1.name)
