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[英]Tensorflow : What is the relationship between .ckpt file and .ckpt.meta and .ckpt.index , and .pb file
[英]Conversion of .pb file to .ckpt (tensorflow)
我设法使用此脚本将预训练的 .ckpt 模型转换为 .pb(protobuf)格式:
import os
import tensorflow as tf
# Get the current directory
dir_path = os.path.dirname(os.path.realpath(__file__))
print "Current directory : ", dir_path
save_dir = dir_path + '/Protobufs'
graph = tf.get_default_graph()
# Create a session for running Ops on the Graph.
sess = tf.Session()
print("Restoring the model to the default graph ...")
saver = tf.train.import_meta_graph(dir_path + '/model.ckpt.meta')
saver.restore(sess,tf.train.latest_checkpoint(dir_path))
print("Restoring Done .. ")
print "Saving the model to Protobuf format: ", save_dir
#Save the model to protobuf (pb and pbtxt) file.
tf.train.write_graph(sess.graph_def, save_dir, "Binary_Protobuf.pb", False)
tf.train.write_graph(sess.graph_def, save_dir, "Text_Protobuf.pbtxt", True)
print("Saving Done .. ")
现在,我想要的是 Vice-verca 程序。 如何加载 protobuf 文件并将其转换为 .ckpt(检查点)格式?
我正在尝试使用以下脚本来做到这一点,但它总是失败:
import tensorflow as tf
import argparse
# Pass the filename as an argument
parser = argparse.ArgumentParser()
parser.add_argument("--frozen_model_filename", default="/path-to-pb-file/Binary_Protobuf.pb", type=str, help="Pb model file to import")
args = parser.parse_args()
# We load the protobuf file from the disk and parse it to retrieve the
# unserialized graph_def
with tf.gfile.GFile(args.frozen_model_filename, "rb") as f:
graph_def = tf.GraphDef()
graph_def.ParseFromString(f.read())
#saver=tf.train.Saver()
with tf.Graph().as_default() as graph:
tf.import_graph_def(
graph_def,
input_map=None,
return_elements=None,
name="prefix",
op_dict=None,
producer_op_list=None
)
sess = tf.Session(graph=graph)
saver=tf.train.Saver()
save_path = saver.save(sess, "path-to-ckpt/model.ckpt")
print("Model saved to chkp format")
我相信拥有这些转换脚本会非常有帮助。
PS:权重已经嵌入到 .pb 文件中。
谢谢。
似乎您只在两个文件中获得了图形定义,而不是冻结模型。
# This two lines only save the graph as proto file; it doesn't save the variables and their values.
tf.train.write_graph(sess.graph_def, save_dir, "Binary_Protobuf.pb", False)
tf.train.write_graph(sess.graph_def, save_dir, "Text_Protobuf.pbtxt", True)
使用freeze_graph 文件获得冻结图
如果您在 pb 文件中加载模型,是否可以将其重新训练为预训练模型。 我使用“tf.global_variables()”来获取可以训练的变量,但是当我加载 pb 模型时没有任何变量返回。
tf.global_variables()
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