def test_caffe_same_name_layer(self):
proto = caffe_pb2.NetParameter()
text_format.Merge(proto_str_multi_input + proto_same_name_layers, proto)
graph = Graph()
caffe_pb_to_nx(graph, proto, None)
# 6 nodes because: 2 inputs + 2 convolutions + 2 identity nodes used as fake outputs
np.testing.assert_equal(len(graph.nodes()), 6)
def test_caffe_pb_to_nx_one_input(self):
proto = caffe_pb2.NetParameter()
text_format.Merge(proto_str_one_input, proto)
input_shapes = caffe_pb_to_nx(Graph(), proto, None)
expected_input_shapes = {'Input0': np.array([1, 3, 224, 224])}
for i in expected_input_shapes:
np.testing.assert_array_equal(input_shapes[i],
expected_input_shapes[i])
def test_caffe_pb_to_multi_input(self):
proto = caffe_pb2.NetParameter()
text_format.Merge(proto_str_multi_input + layer_proto_str, proto)
input_shapes = caffe_pb_to_nx(Graph(), proto, None)
expected_input_shapes = {
'data': np.array([1, 3, 224, 224]),
'data1': np.array([1, 3])
}
for i in expected_input_shapes:
np.testing.assert_array_equal(input_shapes[i], expected_input_shapes[i])
def test_caffe_pb_to_nx_old_styled_multi_input(self):
proto = caffe_pb2.NetParameter()
text_format.Merge(proto_str_old_styled_multi_input + layer_proto_str,
proto)
self.assertRaises(Error, caffe_pb_to_nx, Graph(), proto, None)
