Remove unused code.

python/tools/converter.py

@@ -8,19 +8,22 @@ from lib.python.tools import source_converter_lib
 
 FLAGS = None
 
-def md5(fname):
-  hash_md5 = hashlib.md5()
+def file_checksum(fname):
+  hash_func = hashlib.sha256()
   with open(fname, "rb") as f:
     for chunk in iter(lambda: f.read(4096), b""):
-      hash_md5.update(chunk)
-  return hash_md5.hexdigest()
+      hash_func.update(chunk)
+  return hash_func.hexdigest()
 
 def main(unused_args):
   if not os.path.isfile(FLAGS.model_file):
     print("Input graph file '" + FLAGS.model_file + "' does not exist!")
     return -1
 
-  mode_pb_checksum = md5(FLAGS.model_file)
+  model_checksum = file_checksum(FLAGS.input)
+  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
@@ -42,7 +45,7 @@ def main(unused_args):
         FLAGS.data_type, FLAGS.runtime, FLAGS.winograd)
 
   if FLAGS.output_type == 'source':
-    source_converter_lib.convert_to_source(output_graph_def, mode_pb_checksum, FLAGS.template, FLAGS.obfuscate,
+    source_converter_lib.convert_to_source(output_graph_def, model_checksum, FLAGS.template, FLAGS.obfuscate,
       FLAGS.model_tag, FLAGS.output, FLAGS.runtime, FLAGS.embed_model_data)
   else:
     with open(FLAGS.output, "wb") as f:
@@ -74,6 +77,11 @@ def parse_args():
     type=str,
     default="",
     help="Caffe data file to load.")
+  parser.add_argument(
+    "--model_checksum",
+    type=str,
+    default="",
+    help="Model file sha256 checksum")
   parser.add_argument(
     "--output",
     type=str,

python/tools/tf_converter.py

-import argparse
-import sys
-import hashlib
-import tensorflow as tf
-from tensorflow import gfile
-from lib.proto import mace_pb2
-from lib.python.tools import tf_converter_lib
-from lib.python.tools import tf_dsp_converter_lib
-from lib.python.tools import source_converter_lib
-
-# ./bazel-bin/mace/python/tools/tf_converter --input quantized_test.pb --output quantized_test_dsp.pb --runtime dsp --input_dim input_node,1,28,28,3
-
-FLAGS = None
-
-def file_checksum(fname):
-  hash_func = hashlib.sha256()
-  with open(fname, "rb") as f:
-    for chunk in iter(lambda: f.read(4096), b""):
-      hash_func.update(chunk)
-  return hash_func.hexdigest()
-
-def main(unused_args):
-  if not gfile.Exists(FLAGS.input):
-    print("Input graph file '" + FLAGS.input + "' does not exist!")
-    return -1
-
-  model_checksum = file_checksum(FLAGS.input)
-  if FLAGS.model_checksum != "" and FLAGS.model_checksum != model_checksum:
-    print("Model checksum mismatch: %s != %s" % (model_checksum, FLAGS.model_checksum))
-    return -1
-
-  input_graph_def = tf.GraphDef()
-  with gfile.Open(FLAGS.input, "rb") as f:
-    data = f.read()
-    input_graph_def.ParseFromString(data)
-
-  if FLAGS.runtime == 'dsp':
-    output_graph_def = tf_dsp_converter_lib.convert_to_mace_pb(
-      input_graph_def, 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(',')])
-    output_graph_def = tf_converter_lib.convert_to_mace_pb(
-      input_graph_def, 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,
-      FLAGS.model_tag, FLAGS.output, FLAGS.runtime, FLAGS.embed_model_data)
-  else:
-    with gfile.GFile(FLAGS.output, "wb") as f:
-      f.write(output_graph_def.SerializeToString())
-    with gfile.GFile(FLAGS.output + '_txt', "wb") as f:
-      # output_graph_def.ClearField('tensors')
-      f.write(str(output_graph_def))
-  print("Model conversion is completed.")
-
-def str2bool(v):
-  if v.lower() in ('yes', 'true', 't', 'y', '1'):
-    return True
-  elif v.lower() in ('no', 'false', 'f', 'n', '0'):
-    return False
-  else:
-    raise argparse.ArgumentTypeError('Boolean value expected.')
-
-def parse_args():
-  """Parses command line arguments."""
-  parser = argparse.ArgumentParser()
-  parser.register("type", "bool", lambda v: v.lower() == "true")
-  parser.add_argument(
-    "--input",
-    type=str,
-    default="",
-    help="TensorFlow \'GraphDef\' file to load.")
-  parser.add_argument(
-    "--model_checksum",
-    type=str,
-    default="",
-    help="Model file sha256 checksum")
-  parser.add_argument(
-    "--output",
-    type=str,
-    default="",
-    help="File to save the output graph to.")
-  parser.add_argument(
-    "--runtime",
-    type=str,
-    default="cpu",
-    help="Runtime: cpu/gpu/dsp")
-  parser.add_argument(
-    "--input_node",
-    type=str,
-    default="input_node",
-    help="e.g., input_node")
-  parser.add_argument(
-    "--output_node",
-    type=str,
-    default="softmax",
-    help="e.g., softmax")
-  parser.add_argument(
-    "--data_type",
-    type=str,
-    default='DT_FLOAT',
-    help="e.g., DT_HALF/DT_FLOAT")
-  parser.add_argument(
-    "--output_type",
-    type=str,
-    default="pb",
-    help="output type: source/pb")
-  parser.add_argument(
-    "--template",
-    type=str,
-    default="",
-    help="template path")
-  parser.add_argument(
-    "--obfuscate",
-    type=str2bool,
-    nargs='?',
-    const=False,
-    default=False,
-    help="obfuscate model names")
-  parser.add_argument(
-    "--model_tag",
-    type=str,
-    default="",
-    help="model tag for generated function and namespace")
-  parser.add_argument(
-    "--winograd",
-    type=str2bool,
-    nargs='?',
-    const=False,
-    default=False,
-    help="open winograd convolution or not")
-  parser.add_argument(
-    "--dsp_mode",
-    type=int,
-    default=0,
-    help="dsp run mode, defalut=0")
-  parser.add_argument(
-    "--input_shape",
-    type=str,
-    default="",
-    help="input shape.")
-  parser.add_argument(
-    "--embed_model_data",
-    type=str2bool,
-    default=True,
-    help="input shape.")
-  return parser.parse_known_args()
-
-
-if __name__ == '__main__':
-  FLAGS, unparsed = parse_args()
-  main(unused_args=[sys.argv[0]] + unparsed)