if layer.nweights == 0:
return None
- if (layer.n * layer.c * layer.size * layer.size) != layer.nweights:
+ if (layer.n * layer.c // layer.groups * layer.size * layer.size) != layer.nweights:
raise RuntimeError("layer weights size not matching with n c h w")
params = {}
- shape = (layer.n, layer.c, layer.size, layer.size)
+ shape = (layer.n, layer.c // layer.groups, layer.size, layer.size)
weights = self._read_memory_buffer(shape, layer.weights)
biases = self._read_memory_buffer((layer.n, ), layer.biases)
verify_darknet_frontend(net)
LIB.free_network(net)
+def test_forward_resnext50():
+ '''test resnet50 model'''
+ model_name = 'resnext50'
+ cfg_name = model_name + '.cfg'
+ weights_name = model_name + '.weights'
+ cfg_url = 'https://github.com/pjreddie/darknet/blob/master/cfg/' + cfg_name + '?raw=true'
+ weights_url = 'http://pjreddie.com/media/files/' + weights_name + '?raw=true'
+ net = _load_net(cfg_url, cfg_name, weights_url, weights_name)
+ verify_darknet_frontend(net)
+ LIB.free_network(net)
+
+
def test_forward_yolov2():
'''test yolov2 model'''
model_name = 'yolov2'
if __name__ == '__main__':
test_forward_resnet50()
+ test_forward_resnext50()
test_forward_alexnet()
test_forward_extraction()
test_forward_yolov2()