def __init__(self, block, num_classes=100): super(ResNetModelParallel, self).__init__() self.relu = P.ReLU().shard(((1, dev_num, 1, 1),)) self.maxpool = MaxPool2d(kernel_size=3, stride=2, pad_mode="same") self.layer1 = MakeLayer0( block, in_channels=64, out_channels=256, stride=1) self.pool = M.ReduceMean(keep_dims=True).shard(strategy_no_weight) self.fc = fc_with_initialize(64 * block.expansion, num_classes) self.flatten = Flatten()
def __init__(self, block, num_classes=100): super(ResNet, self).__init__() self.conv1 = conv7x7(3, 64, stride=2) self.bn1 = bn_with_initialize(64) self.relu = P.ReLU().set_strategy(strategy_no_weight) self.maxpool = MaxPool2d(kernel_size=3, stride=2, pad_mode="same") self.layer1 = MakeLayer0(block, in_channels=64, out_channels=256, stride=1) self.pool = M.ReduceMean( keep_dims=True).set_strategy(strategy_no_weight) self.fc = fc_with_initialize(64 * block.expansion, num_classes) self.flatten = Flatten()