def testNonRaggedSparseTensor(self):
# "index_suffix" means the value of the innermost dimension of the index
# (i.e., indices[i][-1]).
# See comments in _assert_sparse_indices_are_ragged_right() for more
# details/background.
# index_suffix of first index is not zero.
st1 = sparse_tensor.SparseTensor(indices=[[0, 1], [0, 2], [2, 0]],
values=[1, 2, 3],
dense_shape=[3, 3])
with self.assertRaisesRegexp(errors.InvalidArgumentError,
r'.*SparseTensor is not right-ragged'):
self.evaluate(RaggedTensor.from_sparse(st1))
# index_suffix of an index that starts a new row is not zero.
st2 = sparse_tensor.SparseTensor(indices=[[0, 0], [0, 1], [2, 1]],
values=[1, 2, 3],
dense_shape=[3, 3])
with self.assertRaisesRegexp(errors.InvalidArgumentError,
r'.*SparseTensor is not right-ragged'):
self.evaluate(RaggedTensor.from_sparse(st2))
# index_suffix of an index that continues a row skips a cell.
st3 = sparse_tensor.SparseTensor(indices=[[0, 1], [0, 1], [0, 3]],
values=[1, 2, 3],
dense_shape=[3, 3])
with self.assertRaisesRegexp(errors.InvalidArgumentError,
r'.*SparseTensor is not right-ragged'):
self.evaluate(RaggedTensor.from_sparse(st3))
def testGoodPartialSparseTensorRank(self):
if not context.executing_eagerly():
st1 = sparse_tensor.SparseTensor(
indices=[[0, 0]],
values=[0],
dense_shape=array_ops.placeholder(dtypes.int64))
st2 = sparse_tensor.SparseTensor(
indices=array_ops.placeholder(dtypes.int64),
values=[0],
dense_shape=[4, 3])
# Shouldn't throw ValueError
RaggedTensor.from_sparse(st1)
RaggedTensor.from_sparse(st2)
def testGoodPartialSparseTensorRank(self):
if not context.executing_eagerly():
st1 = sparse_tensor.SparseTensor(indices=[[0, 0]],
values=[0],
dense_shape=array_ops.placeholder(
dtypes.int64))
st2 = sparse_tensor.SparseTensor(indices=array_ops.placeholder(
dtypes.int64),
values=[0],
dense_shape=[4, 3])
# Shouldn't throw ValueError
RaggedTensor.from_sparse(st1)
RaggedTensor.from_sparse(st2)
def testEmpty(self):
st = sparse_tensor.SparseTensor(
indices=array_ops.zeros([0, 2], dtype=dtypes.int64),
values=[],
dense_shape=[4, 3])
rt = RaggedTensor.from_sparse(st)
self.assertRaggedEqual(rt, [[], [], [], []])
def testDocStringExample(self):
st = sparse_tensor.SparseTensor(
indices=[[0, 0], [0, 1], [0, 2], [1, 0], [3, 0]],
values=[1, 2, 3, 4, 5],
dense_shape=[4, 3])
rt = RaggedTensor.from_sparse(st)
self.assertRaggedEqual(rt, [[1, 2, 3], [4], [], [5]])
def testEmpty(self):
st = sparse_tensor.SparseTensor(indices=array_ops.zeros(
[0, 2], dtype=dtypes.int64),
values=[],
dense_shape=[4, 3])
rt = RaggedTensor.from_sparse(st)
self.assertRaggedEqual(rt, [[], [], [], []])
def testDocStringExample(self):
st = sparse_tensor.SparseTensor(indices=[[0, 0], [0, 1], [0, 2],
[1, 0], [3, 0]],
values=[1, 2, 3, 4, 5],
dense_shape=[4, 3])
rt = RaggedTensor.from_sparse(st)
self.assertRaggedEqual(rt, [[1, 2, 3], [4], [], [5]])
def testNonRaggedSparseTensor(self):
# "index_suffix" means the value of the innermost dimension of the index
# (i.e., indices[i][-1]).
# See comments in _assert_sparse_indices_are_ragged_right() for more
# details/background.
# index_suffix of first index is not zero.
st1 = sparse_tensor.SparseTensor(
indices=[[0, 1], [0, 2], [2, 0]], values=[1, 2, 3], dense_shape=[3, 3])
with self.assertRaisesRegexp(errors.InvalidArgumentError,
r'.*SparseTensor is not right-ragged'):
self.evaluate(RaggedTensor.from_sparse(st1))
# index_suffix of an index that starts a new row is not zero.
st2 = sparse_tensor.SparseTensor(
indices=[[0, 0], [0, 1], [2, 1]], values=[1, 2, 3], dense_shape=[3, 3])
with self.assertRaisesRegexp(errors.InvalidArgumentError,
r'.*SparseTensor is not right-ragged'):
self.evaluate(RaggedTensor.from_sparse(st2))
# index_suffix of an index that continues a row skips a cell.
st3 = sparse_tensor.SparseTensor(
indices=[[0, 1], [0, 1], [0, 3]], values=[1, 2, 3], dense_shape=[3, 3])
with self.assertRaisesRegexp(errors.InvalidArgumentError,
r'.*SparseTensor is not right-ragged'):
self.evaluate(RaggedTensor.from_sparse(st3))