'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()