mirror of
https://github.com/opencv/opencv.git
synced 2024-12-13 16:09:23 +08:00
63 lines
2.3 KiB
Python
63 lines
2.3 KiB
Python
|
# This file is part of OpenCV project.
|
||
|
|
# It is subject to the license terms in the LICENSE file found in the top-level directory
|
||
|
|
# of this distribution and at http://opencv.org/license.html.
|
||
|
|
#
|
||
|
|
# Copyright (C) 2017, Intel Corporation, all rights reserved.
|
||
|
|
# Third party copyrights are property of their respective owners.
|
||
|
|
import tensorflow as tf
|
||
|
|
import struct
|
||
|
|
import argparse
|
||
|
|
import numpy as np
|
||
|
|
|
||
|
|
parser = argparse.ArgumentParser(description='Convert weights of a frozen TensorFlow graph to fp16.')
|
||
|
|
parser.add_argument('--input', required=True, help='Path to frozen graph.')
|
||
|
|
parser.add_argument('--output', required=True, help='Path to output graph.')
|
||
|
|
parser.add_argument('--ops', default=['Conv2D', 'MatMul'], nargs='+',
|
||
|
|
help='List of ops which weights are converted.')
|
||
|
|
args = parser.parse_args()
|
||
|
|
|
||
|
|
DT_FLOAT = 1
|
||
|
|
DT_HALF = 19
|
||
|
|
|
||
|
|
# For the frozen graphs, an every node that uses weights connected to Const nodes
|
||
|
|
# through an Identity node. Usually they're called in the same way with '/read' suffix.
|
||
|
|
# We'll replace all of them to Cast nodes.
|
||
|
|
|
||
|
|
# Load the model
|
||
|
|
with tf.gfile.FastGFile(args.input) as f:
|
||
|
|
graph_def = tf.GraphDef()
|
||
|
|
graph_def.ParseFromString(f.read())
|
||
|
|
|
||
|
|
# Set of all inputs from desired nodes.
|
||
|
|
inputs = []
|
||
|
|
for node in graph_def.node:
|
||
|
|
if node.op in args.ops:
|
||
|
|
inputs += node.input
|
||
|
|
|
||
|
|
weightsNodes = []
|
||
|
|
for node in graph_def.node:
|
||
|
|
# From the whole inputs we need to keep only an Identity nodes.
|
||
|
|
if node.name in inputs and node.op == 'Identity' and node.attr['T'].type == DT_FLOAT:
|
||
|
|
weightsNodes.append(node.input[0])
|
||
|
|
|
||
|
|
# Replace Identity to Cast.
|
||
|
|
node.op = 'Cast'
|
||
|
|
node.attr['DstT'].type = DT_FLOAT
|
||
|
|
node.attr['SrcT'].type = DT_HALF
|
||
|
|
del node.attr['T']
|
||
|
|
del node.attr['_class']
|
||
|
|
|
||
|
|
# Convert weights to halfs.
|
||
|
|
for node in graph_def.node:
|
||
|
|
if node.name in weightsNodes:
|
||
|
|
node.attr['dtype'].type = DT_HALF
|
||
|
|
node.attr['value'].tensor.dtype = DT_HALF
|
||
|
|
|
||
|
|
floats = node.attr['value'].tensor.tensor_content
|
||
|
|
|
||
|
|
floats = struct.unpack('f' * (len(floats) / 4), floats)
|
||
|
|
halfs = np.array(floats).astype(np.float16).view(np.uint16)
|
||
|
|
node.attr['value'].tensor.tensor_content = struct.pack('H' * len(halfs), *halfs)
|
||
|
|
|
||
|
|
tf.train.write_graph(graph_def, "", args.output, as_text=False)
|