Tensorflow is not running on GPU

Autonomous Machines Jetson & Embedded Systems Jetson Nano
1

Hi, i’m trying to run TF 2.4.1 as a python3.8 module on Jetson Nano. I’ve build a python module on x86_64 machine using qemu-user-static emulation. But as long as i see, it gives me no logging device placement:
I did:

import tensorflow as tf
print("Num GPUs Available: ", len(tf.config.list_physical_devices(‘GPU’)))
Num GPUs Available: 1

tf.debugging.set_log_device_placement(True)
a = tf.constant([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]])
b = tf.constant([[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]])
c = tf.matmul(a, b)

print(c)
Tensor(“MatMul_5:0”, shape=(2, 2), dtype=float32)

So, as you can see no such messages i can see:

Executing op _EagerConst in device /job:localhost/replica:0/task:0/device:GPU:0
Executing op _EagerConst in device /job:localhost/replica:0/task:0/device:GPU:0
Executing op MatMul in device /job:localhost/replica:0/task:0/device:GPU:0
tf.Tensor(
[[22. 28.]
[49. 64.]], shape=(2, 2), dtype=float32)

3

Hi,

Do you want to enable the log for device placement?
If yes, would you mind checking the below document to enable it?

Thanks.

4

Hi, thanks for the help! I tried to, but it looks like something i still miss:

root@jetson-nano:/fr# python3
Python 3.8.0 (default, Dec 9 2021, 17:53:27)
[GCC 8.4.0] on linux
Type “help”, “copyright”, “credits” or “license” for more information.
import tensorflow as tf
2022-04-13 11:48:56.873596: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.10.2
2022-04-13 11:49:01.917924: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.10.2

tf.debugging.set_log_device_placement(
… enabled
… )
Traceback (most recent call last):
File “”, line 2, in
NameError: name ‘enabled’ is not defined

5

This one works well

tf.debugging.set_log_device_placement(
enabled=True
)

6

Good to know this.
Do you get the device placement log after applying the API?

Thanks.

8

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