tensorflow.python.framework.errors_impl.ResourceExhaustedError

[AastaLLL]

Hi,

To deploy a model, you will also need some memory for input/output/intermediate tensor.
As a result, the real required memory is much more than the model itself.

Would you mind to check the memory status with tegrastats and share with us?

$ sudo tegrastats

Please also try the configure shared below to see if helps.

- TFv1.15

Resource Exhausted Error

Hi, Could you try to set some limitation on the TensorFlow memory usage to see if helps first? 1. Limit the maximal memory available for TensorFlow gpu_options = tf.GPUOptions(per_process_gpu_memory_fraction=0.6) sess = tf.Session(config=tf.ConfigProto(gpu_options=gpu_options)) 2. Allow gradually memory allocation config = tf.ConfigProto() config.gpu_options.allow_growth=True sess = tf.Session(config=config) Thanks.

- TFv2.x

Jetson Nano running out of memory: ResourceExhaustedError: OOM when allocating tensor with shape[3,3,512,1024

Hi, For TensorFlow v2.x, please try the following: device = tf.config.list_physical_devices('GPU') tf.config.experimental.set_memory_growth(device[0], True) tf.config.experimental.set_virtual_device_configuration(device[0], [tf.config.experimental.VirtualDeviceConfiguration(memory_limit=1024)]) Thanks.

Thanks.