def _rename_versioned_blob_in_proto(
proto: caffe2_pb2.NetDef,
old_name: str,
new_name: str,
version: int,
ssa: List[Tuple[List[Tuple[str, int]], List[Tuple[str, int]]]],
start_versions: Dict[str, int],
end_versions: Dict[str, int],
):
""" In given proto, rename all blobs with matched version """
# Operater list
for op, i_th_ssa in zip(proto.op, ssa):
versioned_inputs, versioned_outputs = i_th_ssa
for i in range(len(op.input)):
if versioned_inputs[i] == (old_name, version):
op.input[i] = new_name
for i in range(len(op.output)):
if versioned_outputs[i] == (old_name, version):
op.output[i] = new_name
# external_input
if start_versions.get(old_name, 0) == version:
for i in range(len(proto.external_input)):
if proto.external_input[i] == old_name:
proto.external_input[i] = new_name
# external_output
if end_versions.get(old_name, 0) == version:
for i in range(len(proto.external_output)):
if proto.external_output[i] == old_name:
proto.external_output[i] = new_name
def fakeFp16FuseOps(net : NetDef) -> NetDef:
net_str = net.SerializeToString()
out_str = C.fakeFp16FuseOps(net_str)
out_net = NetDef()
out_net.ParseFromString(out_str)
return out_net
#! /usr/bin/env python # -*- coding: utf-8 -*- from caffe2.python import workspace, model_helper from caffe2.proto.caffe2_pb2 import NetDef import numpy as np exec_data = "./squeezenet/exec_net.pb" predict_data = "./squeezenet/predict_net.pb" init_net = NetDef() init_net.ParseFromString(open(exec_data).read()) predict_net = NetDef() predict_net.ParseFromString(open(predict_data).read()) # print(predict_net) predict_net.name = "myfirstnet" init_net.name = "mynet" workspace.CreateNet(init_net) workspace.CreateNet(predict_net) workspace.RunNet(predict_net.name)