def get_primitives(cls, **primitive_kwargs) -> [CNNPrimitive]: act = dict(act_fun='relu', order='act_w_bn') df = dict(act_inplace=False, bn_affine=True, use_bn=True) return [ CNNPrimitive(cls=SepConvLayer, kwargs=dict(k_size=3, dilation=1, **act, **df), stacked=2), CNNPrimitive(cls=SepConvLayer, kwargs=dict(k_size=5, dilation=1, **act, **df), stacked=2), CNNPrimitive(cls=SepConvLayer, kwargs=dict(k_size=3, dilation=2, **act, **df)), CNNPrimitive(cls=SepConvLayer, kwargs=dict(k_size=5, dilation=2, **act, **df)), CNNPrimitive(PoolingLayer, kwargs=dict(k_size=3, pool_type='max', act_fun=None, order='w_bn', **df)), CNNPrimitive(PoolingLayer, kwargs=dict(k_size=3, pool_type='avg', act_fun=None, order='w_bn', **df)), StrideChoiceCNNPrimitive([ CNNPrimitive(cls=SkipLayer, kwargs=dict()), CNNPrimitive(cls=FactorizedReductionLayer, kwargs=dict(**act, **df)) ]), CNNPrimitive(cls=ZeroLayer, kwargs=dict()), ]
def get_primitives(cls, **primitive_kwargs) -> [CNNPrimitive]: act = dict(act_fun='relu', order='act_w_bn', act_inplace=False, bn_affine=False, use_bn=True) return [ CNNPrimitive(cls=ZeroLayer, kwargs=dict()), StrideChoiceCNNPrimitive([ CNNPrimitive(cls=LinearTransformerLayer, kwargs=dict()), CNNPrimitive(cls=FactorizedReductionLayer, kwargs=dict(**act)) ]), CNNPrimitive(cls=ConvLayer, kwargs=dict(k_size=1, dilation=1, **act)), CNNPrimitive(cls=ConvLayer, kwargs=dict(k_size=3, dilation=1, **act)), CNNPrimitive(PoolingConvLayer, kwargs=dict(k_size=3, pool_type='avg', act_fun=None, order='w', bn_affine=False, use_bn=False, bias=False)), ]
def get_primitives(cls, **primitive_kwargs) -> [CNNPrimitive]: act = dict(act_fun='relu', order='act_w_bn') df = dict(act_inplace=False, bn_affine=True, use_bn=True) dfnb = df.copy() dfnb['use_bn'] = False return [ CNNPrimitive(cls=SepConvLayer, kwargs=dict(k_size=3, dilation=1, **act, **df), stacked=2), CNNPrimitive(cls=SepConvLayer, kwargs=dict(k_size=5, dilation=1, **act, **df), stacked=2), CNNPrimitive(cls=SepConvLayer, kwargs=dict(k_size=3, dilation=2, **act, **df)), CNNPrimitive(cls=SepConvLayer, kwargs=dict(k_size=5, dilation=2, **act, **df)), DifferentConfigPrimitive( CNNPrimitive(PoolingLayer, kwargs=dict(k_size=3, pool_type='max', act_fun=None, order='w_bn', **df)), CNNPrimitive(PoolingLayer, kwargs=dict(k_size=3, pool_type='max', act_fun=None, order='w', **dfnb))), DifferentConfigPrimitive( CNNPrimitive(PoolingLayer, kwargs=dict(k_size=3, pool_type='avg', act_fun=None, order='w_bn', **df)), CNNPrimitive(PoolingLayer, kwargs=dict(k_size=3, pool_type='avg', act_fun=None, order='w', **dfnb))), StrideChoiceCNNPrimitive([ CNNPrimitive(cls=LinearTransformerLayer, kwargs=dict()), CNNPrimitive(cls=FactorizedReductionLayer, kwargs=dict(**act, **df)) ]), ]