def load_weights(self, pretrained_path):

        model = CRNN10(self.class_num, self.pool_type, self.pool_size, self.interp_ratio)
        checkpoint = torch.load(pretrained_path, map_location=lambda storage, loc: storage)
        model.load_state_dict(checkpoint['model_state_dict'])

        self.conv_block1 = model.conv_block1
        self.conv_block2 = model.conv_block2
        self.conv_block3 = model.conv_block3
        self.conv_block4 = model.conv_block4

        init_gru(self.gru)
        init_layer(self.event_fc)
        init_layer(self.azimuth_fc)
        init_layer(self.elevation_fc)
Example #2
0
    def __init__(self,
                 class_num,
                 pool_type='avg',
                 pool_size=(2, 2),
                 pretrained_path=None):

        super().__init__(class_num,
                         pool_type,
                         pool_size,
                         pretrained_path=pretrained_path)

        if pretrained_path:
            self.load_weights(pretrained_path)

        self.gru = nn.GRU(input_size=512,
                          hidden_size=256,
                          num_layers=1,
                          batch_first=True,
                          bidirectional=True)

        init_gru(self.gru)
        init_layer(self.event_fc)
        init_layer(self.azimuth_fc)
        init_layer(self.elevation_fc)
Example #3
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    def init_weights(self):

        init_gru(self.gru)
        init_layer(self.event_fc)
        init_layer(self.azimuth_fc)
        init_layer(self.elevation_fc)
Example #4
0
    def init_weights(self):

        init_gru(self.gru_1)
        init_gru(self.gru_2)
        init_layer(self.event_fc)