def test_single_param_multi_ellipsis(self):
with self.assertRaisesRegexp(ValueError, 'Found multiple `...`'):
slicing._slice_single_param(array_ops.zeros([7, 6, 5, 4, 3]),
param_ndims_to_matrix_ndims=2,
slices=make_slices[:, ..., 2, ...],
batch_shape=constant_op.constant(
[7, 6, 5]))
def test_single_param_too_many_slices(self):
with self.assertRaises(
(IndexError, ValueError, errors.InvalidArgumentError)):
slicing._slice_single_param(array_ops.zeros([7, 6, 5, 4, 3]),
param_ndims_to_matrix_ndims=2,
slices=make_slices[:, :3, ..., -2:, :],
batch_shape=constant_op.constant(
[7, 6, 5]))
def test_single_param_slice_start_broadcastdim(self):
sliced = slicing._slice_single_param(array_ops.zeros([7, 1, 5, 4, 3]),
param_ndims_to_matrix_ndims=2,
slices=make_slices[:, 2:],
batch_shape=constant_op.constant(
[7, 6, 5]))
self.assertAllEqual((7, 1, 5, 4, 3), self.evaluate(sliced).shape)
def test_single_param_slice_newaxis_trailing(self):
sliced = slicing._slice_single_param(
array_ops.zeros([7, 6, 5, 4, 3]),
param_ndims_to_matrix_ndims=2,
slices=make_slices[..., array_ops.newaxis, :],
batch_shape=constant_op.constant([7, 6, 5]))
self.assertAllEqual((7, 6, 1, 5, 4, 3), self.evaluate(sliced).shape)
def test_single_param_slice_stop_leadingdim(self):
sliced = slicing._slice_single_param(
array_ops.zeros([7, 6, 5, 4, 3]),
param_ndims_to_matrix_ndims=2,
slices=make_slices[:2],
batch_shape=constant_op.constant([7, 6, 5], dtype=dtypes.int32))
self.assertAllEqual((2, 6, 5, 4, 3), self.evaluate(sliced).shape)
def test_single_param_slice_withstep_broadcastdim(self):
event_dim = 3
sliced = slicing._slice_single_param(
array_ops.zeros([1, 1, event_dim]),
param_ndims_to_matrix_ndims=1,
slices=make_slices[44:-52:-3, -94::],
batch_shape=constant_op.constant([2, 7], dtype=dtypes.int32))
self.assertAllEqual((1, 1, event_dim), self.evaluate(sliced).shape)
def test_single_param_slice_broadcast_batch_leading_newaxis(self):
sliced = slicing._slice_single_param(
array_ops.zeros([4, 3, 1]), # batch = [4, 3], event = [1]
param_ndims_to_matrix_ndims=1,
slices=make_slices[array_ops.newaxis, ..., array_ops.newaxis, 2:,
array_ops.newaxis],
batch_shape=constant_op.constant([7, 4, 3]))
expected = array_ops.zeros(
[1, 4, 3])[array_ops.newaxis, ..., array_ops.newaxis, 2:,
array_ops.newaxis].shape + [1]
self.assertAllEqual(expected, self.evaluate(sliced).shape)
def test_single_param_slice_tensor_broadcastdim(self):
param = array_ops.placeholder_with_default(array_ops.zeros(
[7, 1, 5, 4, 3]),
shape=None)
idx = array_ops.placeholder_with_default(constant_op.constant(
2, dtype=dtypes.int32),
shape=[])
sliced = slicing._slice_single_param(param,
param_ndims_to_matrix_ndims=2,
slices=make_slices[:, idx],
batch_shape=constant_op.constant(
[7, 6, 5]))
self.assertAllEqual((7, 5, 4, 3), self.evaluate(sliced).shape)