def testSparseFillEmptyRowsGrad(self):
reverse_index_map = [2, 1]
grad_values = [0, 1, 2, 3]
d_values, d_default_value = self.evaluate(
gen_sparse_ops.SparseFillEmptyRowsGrad(
reverse_index_map=reverse_index_map, grad_values=grad_values))
self.assertAllEqual([2, 1], d_values)
self.assertEqual(3, d_default_value)
def testSparseFillEmptyRowsGradMatrix(self):
reverse_index_map = [0, 1]
grad_values = [[0, 1], [2, 3]]
# Note: Eager mode and graph mode throw different errors here. Graph mode
# will fail with a ValueError from the shape checking logic, while Eager
# will fail with an InvalidArgumentError from the kernel itself.
if context.executing_eagerly():
with self.assertRaisesRegex(errors.InvalidArgumentError,
r'grad_values must be a vector'):
self.evaluate(
gen_sparse_ops.SparseFillEmptyRowsGrad(
reverse_index_map=reverse_index_map, grad_values=grad_values))
else:
with self.assertRaisesRegex(ValueError,
r'Shape must be rank 1 but is rank 2'):
self.evaluate(
gen_sparse_ops.SparseFillEmptyRowsGrad(
reverse_index_map=reverse_index_map, grad_values=grad_values))
def testSparseFillEmptyRowsGradLargeIndexMapValue(self):
reverse_index_map = [2, 10]
grad_values = [0, 1, 2, 3]
with self.assertRaisesRegex(
errors.InvalidArgumentError,
r'Elements in reverse index must be in \[0, 4\)'):
self.evaluate(
gen_sparse_ops.SparseFillEmptyRowsGrad(
reverse_index_map=reverse_index_map, grad_values=grad_values))
