Changed yolo model's size to fit on hardware

hpvm/test/epoch_dnn/torch_dnn/yolo/model.py

@@ -61,11 +61,11 @@ class TinyYoloV2(lnn.module.Darknet):
                 ('8_max',           nn.MaxPool2d(2, 2)),
                 ('9_convbatch',     lnn.layer.Conv2dBatchReLU(128, 256, 3, 1, 1, momentum=momentum)),
                 ('10_max',          nn.MaxPool2d(2, 2)),
-                ('11_convbatch',    lnn.layer.Conv2dBatchReLU(256, 512, 3, 1, 1, momentum=momentum)),
+                ('11_convbatch',    lnn.layer.Conv2dBatchReLU(256, 384, 3, 1, 1, momentum=momentum)),
                 ('12_max',          lnn.layer.PaddedMaxPool2d(2, 1, (0, 1, 0, 1))),
-                ('13_convbatch',    lnn.layer.Conv2dBatchReLU(512, 1024, 3, 1, 1, momentum=momentum)),
-                ('14_convbatch',    lnn.layer.Conv2dBatchReLU(1024, 1024, 3, 1, 1, momentum=momentum)),
-                ('15_conv',         nn.Conv2d(1024, len(self.anchors)*(5+self.num_classes), 1, 1, 0)),
+                ('13_convbatch',    lnn.layer.Conv2dBatchReLU(384, 384, 3, 1, 1, momentum=momentum)),
+                ('14_convbatch',    lnn.layer.Conv2dBatchReLU(384, 384, 3, 1, 1, momentum=momentum)),
+                ('15_conv',         nn.Conv2d(384, len(self.anchors)*(5+self.num_classes), 1, 1, 0)),
             ])
         )
         # fmt: on