Added comments, scripts and updated example to show how to pass config options to TF.

Author: AfaqSabirIBEX

examples/load_model/create_config_options.py

@@ -0,0 +1,15 @@
+import tensorflow as tf
+
+def create_serialized_options(fraction, growth):
+    gpu_options = tf.GPUOptions(per_process_gpu_memory_fraction=fraction, allow_growth=growth)
+    config = tf.ConfigProto(gpu_options=gpu_options)
+    serialized = config.SerializeToString()
+    return list(map(hex, serialized))
+
+if __name__ == "__main__":
+    print("Create serialized options which allow TF to use a certain percentage of GPU memory and allow TF to expand this memory if required.")
+    for i in range(1, 10):
+        memory_fraction_to_use = 0.1
+        enable_memory_growth = True
+        print("GPU memory to be used: ", i * 10.0, "%")
+        print(create_serialized_options(memory_fraction_to_use, enable_memory_growth))

examples/load_model/main.cpp

@@ -9,6 +9,13 @@
 #include <iomanip>
 
 int main() {
+    // Load model with a path to the .pb file. 
+    // An optional std::vector<uint8_t> parameter can be used to supply Tensorflow with
+    // session options. The vector must represent a serialized ConfigProto which can be 
+    // generated manually in python. See create_config_options.py.
+    // Example:
+    // const std::vector<uint8_t> ModelConfigOptions = { 0x32, 0xb, 0x9, 0x9a, 0x99, 0x99, 0x99, 0x99, 0x99, 0xb9, 0x3f, 0x20, 0x1 };
+    // Model model("../model.pb", ModelConfigOptions);
     Model model("../model.pb");
     model.init();
 

include/Model.h

@@ -19,6 +19,7 @@ class Tensor;
 
 class Model {
 public:
+    // Pass a path to the model file and optional Tensorflow config options. See examples/load_model/main.cpp.
     explicit Model(const std::string& model_filename, const std::vector<uint8_t>& config_options = {});
 
     // Rule of five, moving is easy as the pointers can be copied, copying not as i have no idea how to copy