'desc_inputs': [[1, 3, 4, 4]],
'desc_bprop': [[1, 3, 4, 4]]}),
('ReLUV2', {
'block': P.ReLUV2(),
'desc_inputs': [[1, 3, 4, 4]],
'desc_bprop': [[1, 3, 4, 4], [1, 3, 4, 4]]}),
('ReLUGrad', {
'block': G.ReluGrad(),
'desc_inputs': [[1, 3, 4, 4], [1, 3, 4, 4]],
'skip': ['backward']}),
('Elu', {
'block': P.Elu(),
'desc_inputs': [[2, 3, 4]],
'desc_bprop': [[2, 3, 4]]}),
('EluGrad', {
'block': G.EluGrad(),
'desc_inputs': [[2, 3, 4], [2, 3, 4]],
'desc_bprop': [[2, 3, 4]],
'skip': ['backward']}),
('Sigmoid', {
'block': P.Sigmoid(),
'desc_inputs': [[1, 3, 4, 4]],
'desc_bprop': [[1, 3, 4, 4]]}),
('MaxPool', {
'block': P.MaxPool(ksize=(2, 2), strides=(2, 2), padding="VALID"),
'desc_inputs': [[100, 3, 28, 28]],
'desc_bprop': [[100, 3, 14, 14]]}),
('MaxPoolGrad', {
'block': G.MaxPoolGrad(ksize=(2, 2), strides=(2, 2), padding="VALID"),
'desc_inputs': [[3, 4, 6, 6], [3, 4, 3, 3], [3, 4, 3, 3]],
'desc_bprop': [[3, 4, 6, 6]],
def __init__(self):
super(NetEluGrad, self).__init__()
self.eluGrad = G.EluGrad()