Jetson nano tensorflow 2.4.0

i have installed jetpack v 4.5.1
and i installed tensorflow from https://developer.download.nvidia.com/compute/redist/jp/v45/tensorflow/tensorflow-2.4.0+nv21.4-cp36-cp36m-linux_aarch64.whl
with all needed dependencies
i just tried a small test:

import numpy as np
import tensorflow as tf

D = tf.convert_to_tensor(np.array([[1., 2., 3.], [-3., -7., -1.], [0., 5., -2.]]))
print(tf.linalg.det(D))
...
and this stops with 
tensorflow/core/kernels/linalg/determinant_op_gpu.cu.cc:136] Non-OK-status: GpuLaunchKernel( DeterminantFromPivotedLUKernel<Scalar, false>, config.block_count, config.thread_per_block, 0, device.stream(), config.virtual_thread_count, n, lu_factor.data(), pivots, nullptr, output.data()) status: Internal: too many resources requested for launch

i tried several things, for days now, and always the same error: GpuLaunchKernel  status: Internal: too many resources requested for launch

is there a workaround or a other tensorflow version

Hi,

This is a known issue and we are still checking this.

Is TensorFlow 1…15.x acceptable for you?
If yes, please give it a try.

Thanks.

hi,
thanks for the quick response
i’ll give tf1 a try, but i have to reprogram all my codes and models
so is there a plan when this issue with tf2 will be fixed, or when a working release of tf2 is released

thanks

Hi,

We can reproduce this issue in our environment.
And it’s checking the details with our internal team.

Will share more information with you later.
Thanks.