Created by: henrystrident

When I create a model with a .pdparams file , an error occures like this: RuntimeError: Parameter not found, Can't not find [ features.conv0.weight ] in stat_dictuse_structured_name is set to [True]. And my code:

import paddle.fluid as fluid
import paddle.fluid.dygraph.nn as nn


def make_layers(cfg, batch_norm=False):
    layers = []
    in_channels = 3
    for i in range(len(cfg)):
        v = cfg[i]
        if v == 'M':
            layers.append(('pool'+str(i), nn.Pool2D(pool_stride=2, pool_size=2, pool_type='max')))
        else:
            if batch_norm:
                conv_2D = nn.Conv2D(num_channels=in_channels,
                                    num_filters=v,
                                    filter_size=3,
                                    padding=1)
                layers.extend([('conv'+str(i), conv_2D), nn.BatchNorm(num_channels=v, act='relu')])
            else:
                conv_2D = nn.Conv2D(num_channels=in_channels,
                                    num_filters=v,
                                    filter_size=3,
                                    padding=1,
                                    act='relu')
                layers.append(('conv'+str(i), conv_2D))
            in_channels = v
    return fluid.dygraph.Sequential(*layers)


class VGG(fluid.dygraph.Layer):
    def __init__(self, features):
        super(VGG, self).__init__()
        self.features = features
        self.reg_layer = fluid.dygraph.Sequential(('reg_layer_conv1', nn.Conv2D(num_channels=512,
                                                                                num_filters=256,
                                                                                filter_size=3,
                                                                                padding=1,
                                                                                act='relu')),
                                                  ('reg_layer_conv2', nn.Conv2D(num_channels=256,
                                                                                num_filters=128,
                                                                                filter_size=3,
                                                                                padding=1,
                                                                                act='relu')),
                                                  ('reg_layer_conv3', nn.Conv2D(num_channels=128,
                                                                                num_filters=1,
                                                                                filter_size=1)))

    def forward(self, x):
        x = self.features(x)
        x = fluid.layers.resize_bilinear(x, out_shape=[64, 64])
        x = self.reg_layer(x)
        return fluid.layers.abs(x)


def vgg():
    return VGG(make_layers(cfg['E']))


cfg = {
    'E': [64, 64, 'M', 128, 128, 'M', 256, 256, 256, 256, 'M', 512, 512, 512, 512, 'M', 512, 512, 512, 512]
}

if __name__ == '__main__':
    with fluid.dygraph.guard():
        save_model = vgg()
        save_parameters = save_model.state_dict()
        fluid.save_dygraph(save_parameters, './test_params')
        load_model = vgg()
        load_model.set_dict('./test_params')