Question

我使用GPU重新训练TensorFlow Inception-v3模型文件'retrained_graph.pb'。

我将'retrained_graph.pb'文件转移到没有GPU的AWS EC2 t2.micro服务器（ubuntu 16.04.2）。

当我在我的EC2服务器上尝试下面的推理脚本'label_image.py'时，

import tensorflow as tf
import sys
from tensorflow.python.platform import gfile


# change this as you see fit
image_path = sys.argv[1]

# Read in the image_data
image_data = tf.gfile.FastGFile(image_path, 'rb').read()

# Loads label file, strips off carriage return
label_lines = [line.rstrip() for line
                   in tf.gfile.GFile('/home/ubuntu/tf_files/retrained_labels.txt')]

# Unpersists graph from file

with tf.gfile.FastGFile('./retrained_graph.pb', 'rb') as f:
    graph_def = tf.GraphDef()
    graph_def.ParseFromString(f.read())
    _ = tf.import_graph_def(graph_def, name='')
with tf.Session() as sess:
    # Feed the image_data as input to the graph and get first prediction
    softmax_tensor = sess.graph.get_tensor_by_name('final_result:0')

    predictions = sess.run(softmax_tensor, \
             {'DecodeJpeg/contents:0': image_data})

    # Sort to show labels of first prediction in order of confidence
    top_k = predictions[0].argsort()[-len(predictions[0]):][::-1]

    for node_id in top_k:
        human_string = label_lines[node_id]
        score = predictions[0][node_id]
        print('%s::%.5f::' % (human_string, score))

它不适用于此错误

Traceback (most recent call last):
  File "label_image.py", line 20, in <module>
    graph_def.ParseFromString(f.read())
google.protobuf.message.DecodeError: Error parsing message

但对另一个受过非gpu支持培训的模型的推断在同一个脚本'label_image.py'上运行良好

如何在非GPU环境下运行此推理脚本？

GPU训练的.pb模型不适用于仅CPU的机器

0 个答案: