def build_net(graph: nx.DiGraph):
try:
if not hasattr(os.environ, 'GLOG_minloglevel'):
os.environ['GLOG_minloglevel'] = '2'
import caffe
log.info('Partial inference via the framework is available')
except ImportError:
log.warning(
'pyCaffe is not available. Partial inference via the framework is not '
+ 'possible')
return
try:
net = caffe.Net(graph.proto_path, graph.caffemodel_path, caffe.TEST)
except Exception as err:
raise Error(
'Error happened while constructing caffe.Net in the Caffe fallback function: {}. '
+ refer_to_faq_msg(12), str(err)) from err
inputs_node_name = find_inputs(graph)
reshape_flag = False
for i in inputs_node_name:
new_input_shape = graph.node[i]['shape'].astype(int)
top_node = get_node_top(graph, i)
caffe_shape = list(net.blobs[top_node].shape)
if not np.all(caffe_shape == new_input_shape):
net.blobs[top_node].reshape(*[int(x) for x in new_input_shape])
reshape_flag = True
if reshape_flag:
net.reshape()
try:
net.forward()
except KeyError as err:
log.error('Error happened in Caffe net.forward: {}.'.format(str(err)))
log.error(
'It may point to the known bug in pycaffe when top and name of the layer do not match.'
)
log.error('Please make sure that the latest pycaffe is used.')
raise Error(
'Cannot infer shapes due to exception in Caffe: {}. ' +
refer_to_faq_msg(13), str(err)) from err
except Exception as err:
raise Error(
'Cannot infer shapes in Caffe net.forward due to exception: {}.' +
refer_to_faq_msg(13), str(err)) from err
graph.__setattr__('caffe_net', net)
