CODEWITHSUNDEEP
tensorflow
peastman
peastman

Reputation: 1279

Error loading TensorFlow graph with C API

I'm trying to use the TensorFlow C API to load and execute a graph. It keeps failing and I can't figure out why.

I first use this Python script to create a very simple graph and save it to a file.

import tensorflow as tf
graph = tf.Graph()
with graph.as_default():
    input = tf.placeholder(tf.float32, [10, 3], name='input')
    output = tf.reduce_sum(input**2, name='output')
tf.train.write_graph(graph, '.', 'test.pbtxt')

Then I use this C++ code to load it in.

#include <fstream>
#include <iostream>
#include <string>
#include <c_api.h>

using namespace std;

int main() {
    ifstream graphFile("test.pbtxt");
    string graphText((istreambuf_iterator<char>(graphFile)), istreambuf_iterator<char>());
    TF_Buffer* buffer = TF_NewBufferFromString(graphText.c_str(), graphText.size());
    TF_Graph* graph = TF_NewGraph();
    TF_ImportGraphDefOptions* importOptions = TF_NewImportGraphDefOptions();
    TF_Status* status = TF_NewStatus();
    TF_GraphImportGraphDef(graph, buffer, importOptions, status);
    cout<<TF_GetCode(status)<<endl;
    return 0;
}

The status code it prints is 3, or TF_INVALID_ARGUMENT. Which argument is invalid and why? I verified the file contents are loaded correctly into graphText, and all the other arguments are trivial.

Upvotes: 1

Views: 798

Answers (1)

Mario Garc&#237;a
Mario Garc&#237;a

Reputation: 71

First of all, I think you should write the Graph with as_graph_def(), in your case:

with open('test.pb', 'wb') as f:
    f.write(graph.as_graph_def().SerializeToString())

Apart from it, I recommend you not to use the C API directly as it is error prone with memory leaks. Instead I have tried your code using cppflow, a C++ wrapper, and it works like a charm. I have used the following code:

# Load model    
Model model("../test.pb");

# Declare tensors by name
auto input = new Tensor(model, "input");
auto output  = new Tensor(model, "output");

# Feed data
std::vector<float> data(30, 1);
input->set_data(data);

# Run and show
model.run(input, output);
std::cout << output->get_data<float>()[0] << std::endl;

Upvotes: 1

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