def __init__(self):
super(BatchToSpaceNet, self).__init__()
block_size = 2
crops = [[0, 0], [0, 0]]
self.batch_to_space = P.BatchToSpace(block_size, crops)
'block': P.DiagPart(),
'desc_inputs': [[4, 4]],
'desc_bprop': [[4]],
}),
('SpaceToBatch_1', {
'block': P.SpaceToBatch(2, [[0, 0], [0, 0]]),
'desc_inputs': [[1, 3, 2, 2]],
'desc_bprop': [[4, 3, 1, 1]],
}),
('SpaceToBatch_2', {
'block': P.SpaceToBatch(2, [[1, 1], [0, 4]]),
'desc_inputs': [[1, 3, 2, 2]],
'desc_bprop': [[4, 3, 2, 4]],
}),
('BatchToSpace_1', {
'block': P.BatchToSpace(2, [[0, 0], [0, 0]]),
'desc_inputs': [[4, 3, 1, 1]],
'desc_bprop': [[1, 3, 2, 2]],
}),
('BatchToSpace_2', {
'block': P.BatchToSpace(2, [[0, 0], [0, 1]]),
'desc_inputs': [[4, 3, 1, 1]],
'desc_bprop': [[1, 3, 2, 1]],
}),
]
test_case_other_ops = [
('ScalarLog', {
'block': F.scalar_log,
'desc_const': [0.0],
'desc_inputs': [],
def __init__(self, block_shape, crops):
super(BatchToSpace, self).__init__()
self.batch_to_space = P.BatchToSpace(block_shape, crops)
self.bs = block_shape
self.cr = crops