本文介绍了Tensorflow中的C ++等价于python:tf.Graph.get_tensor_by_name()?的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!
问题描述
Tensorflow中python的tf.Graph.get_tensor_by_name(name)相当于C ++吗?谢谢!
What is the C++ equivalent of python: tf.Graph.get_tensor_by_name(name) in Tensorflow? Thanks!
这是我要运行的代码,但输出为空的
:
Here is the code I am trying to run, but I get an empty output
:
Status status = NewSession(SessionOptions(), &session); // create new session
ReadBinaryProto(tensorflow::Env::Default(), model, &graph_def); // read Graph
session->Create(graph_def); // add Graph to Tensorflow session
std::vector<tensorflow::Tensor> output; // create Tensor to store output
std::vector<string> vNames; // vector of names for required graph nodes
vNames.push_back("some_name"); // I checked names and they are presented in loaded Graph
session->Run({}, vNames, {}, &output); // ??? As a result I have empty output
推荐答案
有一种方法直接从graph_def获取神经节点。
,如果您只想要节点的形状类型: some_name:
there is a way to get neural node from graph_def directly.if u only want the shape\type of node: "some_name":
void readPB(GraphDef & graph_def)
{
int i;
for (i = 0; i < graph_def.node_size(); i++)
{
if (graph_def.node(i).name() == "inputx")
{
graph_def.node(i).PrintDebugString();
}
}
}
结果:
name: "inputx"
op: "Placeholder"
attr {
key: "dtype"
value {
type: DT_FLOAT
}
}
attr {
key: "shape"
value {
shape {
dim {
size: -1
}
dim {
size: 5120
}
}
}
}
尝试节点的成员函数并获取信息。
try member functins of the node and get the informations.
这篇关于Tensorflow中的C ++等价于python:tf.Graph.get_tensor_by_name()?的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持!