def check_backward(self, x_data, y_grad):
slices = []
for i, s in enumerate(self.slices):
if isinstance(s, numpy.ndarray):
s = chainer.cuda.cupy.array(s)
if isinstance(s, list):
s = chainer.cuda.cupy.array(s, dtype=numpy.int32)
slices.append(s)
slices = tuple(slices)
gradient_check.check_backward(
functions.GetItem(slices), (x_data,), y_grad, dtype='d')
def check_backward(self, x_data, y_grad):
gradient_check.check_backward(functions.GetItem(self.slices),
(x_data, ), y_grad)