diff --git a/python/tools/converter.py b/python/tools/converter.py
index 55b89d0149eb601ca363b9488ab45f3e6af703b1..09b64dd75cb0a6738c3a7233f2ce891cadf1f620 100644
--- a/python/tools/converter.py
+++ b/python/tools/converter.py
@@ -20,29 +20,45 @@ def main(unused_args):
     print("Input graph file '" + FLAGS.model_file + "' does not exist!")
     return -1
 
-  model_checksum = file_checksum(FLAGS.input)
+  model_checksum = file_checksum(FLAGS.model_file)
   if FLAGS.model_checksum != "" and FLAGS.model_checksum != model_checksum:
     print("Model checksum mismatch: %s != %s" % (model_checksum, FLAGS.model_checksum))
     return -1
 
-  if FLAGS.runtime == 'dsp':
-    from lib.python.tools import tf_dsp_converter_lib
-    output_graph_def = tf_dsp_converter_lib.convert_to_mace_pb(
-      FLAGS.model_file, FLAGS.input_node, FLAGS.output_node, FLAGS.dsp_mode)
-  else:
+  if FLAGS.platform == 'caffe':
+    if not os.path.isfile(FLAGS.weight_file):
+      print("Input weight file '" + FLAGS.weight_file + "' does not exist!")
+      return -1
+
+    weight_checksum = file_checksum(FLAGS.weight_file)
+    if FLAGS.weight_checksum != "" and FLAGS.weight_checksum != weight_checksum:
+      print("Weight checksum mismatch: %s != %s" % (weight_checksum, FLAGS.weight_checksum))
+      return -1
+
+    if FLAGS.runtime == 'dsp':
+      print("DSP not support caffe model yet.")
+      return -1
+
     input_shape = []
     if FLAGS.input_shape != "":
       input_shape.extend([int(x) for x in FLAGS.input_shape.split(',')])
-    if FLAGS.platform == 'tensorflow':
+    from lib.python.tools import caffe_converter_lib
+    output_graph_def = caffe_converter_lib.convert_to_mace_pb(
+      FLAGS.model_file, FLAGS.weight_file, FLAGS.input_node, input_shape, FLAGS.output_node,
+      FLAGS.data_type, FLAGS.runtime, FLAGS.winograd)
+  elif FLAGS.platform == 'tensorflow':
+    if FLAGS.runtime == 'dsp':
+      from lib.python.tools import tf_dsp_converter_lib
+      output_graph_def = tf_dsp_converter_lib.convert_to_mace_pb(
+        FLAGS.model_file, FLAGS.input_node, FLAGS.output_node, FLAGS.dsp_mode)
+    else:
+      input_shape = []
+      if FLAGS.input_shape != "":
+        input_shape.extend([int(x) for x in FLAGS.input_shape.split(',')])
       from lib.python.tools import tf_converter_lib
       output_graph_def = tf_converter_lib.convert_to_mace_pb(
         FLAGS.model_file, FLAGS.input_node, input_shape, FLAGS.output_node,
         FLAGS.data_type, FLAGS.runtime, FLAGS.winograd)
-    elif FLAGS.platform == 'caffe':
-      from lib.python.tools import caffe_converter_lib
-      output_graph_def = caffe_converter_lib.convert_to_mace_pb(
-        FLAGS.model_file, FLAGS.weight_file, FLAGS.input_node, input_shape, FLAGS.output_node,
-        FLAGS.data_type, FLAGS.runtime, FLAGS.winograd)
 
   if FLAGS.output_type == 'source':
     source_converter_lib.convert_to_source(output_graph_def, model_checksum, FLAGS.template, FLAGS.obfuscate,
@@ -82,6 +98,11 @@ def parse_args():
     type=str,
     default="",
     help="Model file sha256 checksum")
+  parser.add_argument(
+    "--weight_checksum",
+    type=str,
+    default="",
+    help="Weight file sha256 checksum")
   parser.add_argument(
     "--output",
     type=str,