Memory error

[TatyanaGreenkina]

Hi! I was working with relational-gcn with my dataset (X.shape = [17069, 300], num relations = 11) and I got some problems with GPU's memmory. I have two GeForce GTX 1080 Ti

InternalError: 2 root error(s) found.
  (0) Internal: Dst tensor is not initialized.
	 [[{{node _arg_input_11_0_6}}]]
	 [[loss_2/add/_147]]
  (1) Internal: Dst tensor is not initialized.
	 [[{{node _arg_input_11_0_6}}]]
0 successful operations.
0 derived errors ignored.

Stats:
Limit:                 10977044071
InUse:                  8214125056
MaxInUse:               8214411008
NumAllocs:                     130
MaxAllocSize:           1220657664

The code for setup GPUs usage

gpus = tf.config.experimental.list_physical_devices('GPU')
    if gpus:
        try:
            # Restrict TensorFlow to only use the fourth GPU
            tf.config.experimental.set_visible_devices(gpus[0], 'GPU')
            tf.config.experimental.per_process_gpu_memory_fraction=0.4

            # Currently, memory growth needs to be the same across GPUs
            for gpu in gpus:
                tf.config.experimental.set_memory_growth(gpu, True)
            logical_gpus = tf.config.experimental.list_logical_devices('GPU')
            print(len(gpus), "Physical GPUs,", len(logical_gpus), "Logical GPUs")
        except RuntimeError as e:
            # Memory growth must be set before GPUs have been initialized
            print(e)

Is it possible to vary the amount of memory when training the model?

Please, let me know if I'm doing something wrong