How about gpu configuration

[GallonDeng]

nice work! I am wondering whether the model will use all available gpus and all memory by default. If it does, how to set it? thanks

[serizba]

Well, it is not easy to set the configuration using the C API. As far as I known the only way to set the options is something like this:

First, in Python you create a configproto and serialize its content:

import tensorflow as tf  
myoptions = tf.GPUOptions(allow_growth=True,visible_device_list='2')
config = tf.ConfigProto(gpu_options=myoptions)

serialized = config.SerializeToString()
print(list(map(hex, serialized)))

The code above prints something like (0x01, 0x02, 0x03...). After that you can write the printed hex string in your C++ code, (in Model.cpp, in the constructor):

// Create the session.
// Model.cpp#L15
TF_SessionOptions* sess_opts = TF_NewSessionOptions();

uint8_t config[5] ={0x01, 0x02, 0x03, 0x04, 0x05};  // <- New line
TF_SetConfig(session_opts,(void*)config,7,status); // <- New line

// Model.cpp#L17
this->session = TF_NewSession(this->graph, sess_opts, this->status);

Now the model will run with your configuration. Hope it works!

[barisdemiray]

I'd say it's seamless to this project, we'd just need to pick a TensorFlow built with GPU support and set CUDA_VISIBLE_DEVICES environment variable. Even though there probably must be a programmatic way of doing this too.

[GallonDeng]

yes, just set CUDA_VISIBLE_DEVICES environment variable in the shell or system. It will work. Thanks