def test2DRaggedTensorWithOneRaggedDimension(self): values = ['a', 'b', 'c', 'd', 'e', 'f', 'g'] rt1 = ragged.from_row_splits(values, [0, 2, 5, 6, 6, 7]) rt2 = ragged.from_row_splits(values, [0, 7]) rt3 = ragged.from_row_splits(values, [0, 0, 7, 7]) self.assertEqual(self.evaluate(ragged.bounding_shape(rt1)).tolist(), [5, 3]) self.assertEqual(self.evaluate(ragged.bounding_shape(rt2)).tolist(), [1, 7]) self.assertEqual(self.evaluate(ragged.bounding_shape(rt3)).tolist(), [3, 7])
def test3DRaggedTensorWithOneRaggedDimension(self):
values = [[0, 1], [2, 3], [4, 5], [6, 7], [8, 9], [10, 11], [12, 13]]
rt1 = ragged.from_row_splits(values, [0, 2, 5, 6, 6, 7])
rt2 = ragged.from_row_splits(values, [0, 7])
rt3 = ragged.from_row_splits(values, [0, 0, 7, 7])
with self.test_session():
self.assertEqual(ragged.bounding_shape(rt1).eval().tolist(), [5, 3, 2])
self.assertEqual(ragged.bounding_shape(rt2).eval().tolist(), [1, 7, 2])
self.assertEqual(ragged.bounding_shape(rt3).eval().tolist(), [3, 7, 2])
def test3DRaggedTensorWithOneRaggedDimension(self):
values = [[0, 1], [2, 3], [4, 5], [6, 7], [8, 9], [10, 11], [12, 13]]
rt1 = ragged.from_row_splits(values, [0, 2, 5, 6, 6, 7])
rt2 = ragged.from_row_splits(values, [0, 7])
rt3 = ragged.from_row_splits(values, [0, 0, 7, 7])
self.assertEqual(
self.evaluate(ragged.bounding_shape(rt1)).tolist(), [5, 3, 2])
self.assertEqual(
self.evaluate(ragged.bounding_shape(rt2)).tolist(), [1, 7, 2])
self.assertEqual(
self.evaluate(ragged.bounding_shape(rt3)).tolist(), [3, 7, 2])
def testRaggedTensorSplitsMismatchErrorAtRuntime(self):
splits1 = array_ops.placeholder_with_default(
constant_op.constant([0, 3, 3, 5], dtypes.int64), None)
splits2 = array_ops.placeholder_with_default(
constant_op.constant([0, 1, 3, 5], dtypes.int64), None)
x = ragged.from_row_splits([3, 1, 4, 1, 5], splits1)
y = ragged.from_row_splits([1, 2, 3, 4, 5], splits2)
result = ragged.map_inner_values(math_ops.add, x, y)
with self.test_session():
self.assertRaisesRegexp(
errors.InvalidArgumentError,
r'\[Inputs must have identical ragged splits\] '
r'\[Condition x == y did not hold element-wise:\].*', result.eval)
def testRaggedTensorSplitsMismatchErrorAtRuntime(self):
splits1 = array_ops.placeholder_with_default(
constant_op.constant([0, 3, 3, 5], dtypes.int64), None)
splits2 = array_ops.placeholder_with_default(
constant_op.constant([0, 1, 3, 5], dtypes.int64), None)
x = ragged.from_row_splits([3, 1, 4, 1, 5], splits1)
y = ragged.from_row_splits([1, 2, 3, 4, 5], splits2)
result = ragged.map_inner_values(math_ops.add, x, y)
with self.test_session():
self.assertRaisesRegexp(
errors.InvalidArgumentError,
r'\[Inputs must have identical ragged splits\] '
r'\[Condition x == y did not hold element-wise:\].*',
result.eval)
def testShapeMismatchError2(self):
rt = ragged.constant([
[[111, 112, 113, 114], [121]], # row 0
[], # row 1
[[], [321, 322], [331]], # row 2
[[411, 412]] # row 3
]) # pyformat: disable
segment_ids = ragged.constant([[1, 2], [1], [1, 1, 2], [2]])
# Error is raised at graph-building time if we can detect it then.
self.assertRaisesRegexp(
errors.InvalidArgumentError,
'segment_ids.shape must be a prefix of data.shape.*',
ragged.segment_sum, rt, segment_ids, 3)
# Otherwise, error is raised when we run the graph.
segment_ids2 = ragged.from_row_splits(
array_ops.placeholder_with_default(segment_ids.values, None),
array_ops.placeholder_with_default(segment_ids.row_splits, None))
segmented2 = ragged.segment_sum(rt, segment_ids2, 3)
with self.test_session():
self.assertRaisesRegexp(
errors.InvalidArgumentError,
'segment_ids.shape must be a prefix of data.shape.*',
segmented2.eval)
def testUnknownRankError(self):
x = ragged.constant([[1, 2], [3]])
y = ragged.from_row_splits(
array_ops.placeholder_with_default([1, 2, 3], shape=None), x.row_splits)
with self.assertRaisesRegexp(
ValueError, r'Unable to broadcast: unknown rank'):
ragged.add(x, y)
def testUnknownRankError(self):
x = ragged.constant([[1, 2], [3]])
y = ragged.from_row_splits(
array_ops.placeholder_with_default([1, 2, 3], shape=None), x.row_splits)
with self.assertRaisesRegexp(
ValueError, r'Unable to broadcast: unknown rank'):
ragged.add(x, y)
def testExplicitAxisOptimizations(self):
rt = ragged.from_row_splits(b'a b c d e f g'.split(), [0, 2, 5, 6, 6, 7])
with self.test_session():
self.assertEqual(ragged.bounding_shape(rt, 0).eval().tolist(), 5)
self.assertEqual(ragged.bounding_shape(rt, 1).eval().tolist(), 3)
self.assertEqual(
ragged.bounding_shape(rt, [1, 0]).eval().tolist(), [3, 5])
def testUnknownRankError(self):
x = ragged.constant([[1, 2], [3]])
y = ragged.from_row_splits(
array_ops.placeholder_with_default([1, 2, 3], shape=None), x.row_splits)
with self.assertRaisesRegexp(
ValueError, r'Ragged elementwise ops require that rank \(number '
r'of dimensions\) be statically known.'):
ragged.add(x, y)
def testExplicitAxisOptimizations(self):
rt = ragged.from_row_splits(b'a b c d e f g'.split(),
[0, 2, 5, 6, 6, 7])
with self.test_session():
self.assertEqual(ragged.bounding_shape(rt, 0).eval().tolist(), 5)
self.assertEqual(ragged.bounding_shape(rt, 1).eval().tolist(), 3)
self.assertEqual(
ragged.bounding_shape(rt, [1, 0]).eval().tolist(), [3, 5])
def testRaggedBatchGatherUnknownRankError(self):
params = [['a', 'b'], ['c', 'd']]
indices = array_ops.placeholder(dtypes.int32, shape=None)
ragged_indices = ragged.from_row_splits(indices, [0, 2, 4])
with self.assertRaisesRegexp(
ValueError, 'batch_gather does not allow indices with unknown shape.'):
ragged.batch_gather(params, indices)
with self.assertRaisesRegexp(
ValueError, 'batch_gather does not allow indices with unknown shape.'):
ragged.batch_gather(params, ragged_indices)
def testRaggedBatchGatherUnknownRankError(self):
params = [['a', 'b'], ['c', 'd']]
indices = array_ops.placeholder(dtypes.int32, shape=None)
ragged_indices = ragged.from_row_splits(indices, [0, 2, 4])
with self.assertRaisesRegexp(
ValueError, 'batch_gather does not allow indices with unknown shape.'):
ragged.batch_gather(params, indices)
with self.assertRaisesRegexp(
ValueError, 'batch_gather does not allow indices with unknown shape.'):
ragged.batch_gather(params, ragged_indices)
def testKernelErrors(self):
# An empty vector, defined using a placeholder to ensure that we can't
# determine that it's invalid at graph-construction time.
empty_vector = array_ops.placeholder_with_default(array_ops.zeros(
[0], dtypes.int64),
shape=None)
bad_rt1 = ragged.from_row_splits(row_splits=[2, 3], values=[1, 2, 3])
with self.test_session():
bad_split0_error = r'First value of ragged splits must be 0.*'
self.assertRaisesRegexp(errors.InvalidArgumentError,
bad_split0_error,
ragged.to_sparse(bad_rt1).eval)
bad_rt2 = ragged.from_row_splits(row_splits=[0, 5],
values=empty_vector)
bad_rt3 = ragged.from_row_splits(row_splits=[0, 1],
values=ragged.from_row_splits(
row_splits=[0, 5],
values=empty_vector))
with self.test_session():
split_mismatch1_error = r'Final value of ragged splits must match.*'
for rt in [bad_rt2, bad_rt3]:
self.assertRaisesRegexp(errors.InvalidArgumentError,
split_mismatch1_error,
ragged.to_sparse(rt).eval)
bad_rt4 = ragged.from_row_splits(row_splits=[0, 5],
values=ragged.from_row_splits(
row_splits=[0],
values=empty_vector))
with self.test_session():
split_mismatch2_error = r'Final value of ragged splits must match.*'
self.assertRaisesRegexp(errors.InvalidArgumentError,
split_mismatch2_error,
ragged.to_sparse(bad_rt4).eval)
bad_rt5 = ragged.from_row_splits(row_splits=empty_vector, values=[])
with self.test_session():
empty_splits_error = (r'ragged splits may not be empty.*')
self.assertRaisesRegexp(errors.InvalidArgumentError,
empty_splits_error,
ragged.to_sparse(bad_rt5).eval)
def testShapeMismatchError2(self):
rt = ragged.constant([
[[111, 112, 113, 114], [121]], # row 0
[], # row 1
[[], [321, 322], [331]], # row 2
[[411, 412]] # row 3
]) # pyformat: disable
segment_ids = ragged.constant([[1, 2], [1], [1, 1, 2], [2]])
# Error is raised at graph-building time if we can detect it then.
self.assertRaisesRegexp(
errors.InvalidArgumentError,
'segment_ids.shape must be a prefix of data.shape.*',
ragged.segment_sum, rt, segment_ids, 3)
# Otherwise, error is raised when we run the graph.
segment_ids2 = ragged.from_row_splits(
array_ops.placeholder_with_default(segment_ids.values, None),
array_ops.placeholder_with_default(segment_ids.row_splits, None))
segmented2 = ragged.segment_sum(rt, segment_ids2, 3)
with self.test_session():
self.assertRaisesRegexp(
errors.InvalidArgumentError,
'segment_ids.shape must be a prefix of data.shape.*', segmented2.eval)
def testKernelErrors(self):
# An empty vector, defined using a placeholder to ensure that we can't
# determine that it's invalid at graph-construction time.
empty_vector = array_ops.placeholder_with_default(
array_ops.zeros([0], dtypes.int64), shape=None)
bad_rt1 = ragged.from_row_splits(row_splits=[2, 3], values=[1, 2, 3])
with self.test_session():
bad_split0_error = r'First value of ragged splits must be 0.*'
self.assertRaisesRegexp(errors.InvalidArgumentError, bad_split0_error,
ragged.to_sparse(bad_rt1).eval)
bad_rt2 = ragged.from_row_splits(row_splits=[0, 5], values=empty_vector)
bad_rt3 = ragged.from_row_splits(
row_splits=[0, 1],
values=ragged.from_row_splits(row_splits=[0, 5], values=empty_vector))
with self.test_session():
split_mismatch1_error = r'Final value of ragged splits must match.*'
for rt in [bad_rt2, bad_rt3]:
self.assertRaisesRegexp(errors.InvalidArgumentError,
split_mismatch1_error,
ragged.to_sparse(rt).eval)
bad_rt4 = ragged.from_row_splits(
row_splits=[0, 5],
values=ragged.from_row_splits(row_splits=[0], values=empty_vector))
with self.test_session():
split_mismatch2_error = r'Final value of ragged splits must match.*'
self.assertRaisesRegexp(errors.InvalidArgumentError,
split_mismatch2_error,
ragged.to_sparse(bad_rt4).eval)
bad_rt5 = ragged.from_row_splits(row_splits=empty_vector, values=[])
with self.test_session():
empty_splits_error = (r'ragged splits may not be empty.*')
self.assertRaisesRegexp(errors.InvalidArgumentError, empty_splits_error,
ragged.to_sparse(bad_rt5).eval)
def testExplicitAxisOptimizations(self):
rt = ragged.from_row_splits(b'a b c d e f g'.split(), [0, 2, 5, 6, 6, 7])
self.assertEqual(self.evaluate(ragged.bounding_shape(rt, 0)).tolist(), 5)
self.assertEqual(self.evaluate(ragged.bounding_shape(rt, 1)).tolist(), 3)
self.assertEqual(
self.evaluate(ragged.bounding_shape(rt, [1, 0])).tolist(), [3, 5])