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IteratorGetNext: unsupported op: No registered 'IteratorGetNext' OpKernel for XLA_GPU_JIT

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When I try to run the code I get an error:

#Related info to xs:
names = [name for name in os.listdir(cdir + xname) if name.endswith('.png')]
xs = [np.array(Image.open(cdir + sat + name).convert('RGB'),dtype="float32") for name in names]
xs = [x/255.0 for x in xs]
xs = np.asarray(xs)

with tf.device("/device:XLA_GPU:0"):
history = model.fit(xs,
ys,
validation_split = 0.1,
epochs=EPOCHS,
batch_size = BATCH_SIZE,
)

OS Platform and Distribution (e.g., Linux Ubuntu 16.04):

Distributor ID: Ubuntu
Description: Ubuntu 18.04.5 LTS
Release: 18.04
Codename: bionic

TensorFlow installed from (source or binary):
binary
pip3.6 install tensorflow==2.1.0 tensorflow-gpu==2.1.0
pip3.7 install tensorflow==2.1.0 tensorflow-gpu==2.1.0

TensorFlow version (use command below):
2.1.0

Python version:
import platform
import sys
print(platform.python_version()) #jupyter notebook
print(sys.version)
print(sys.version_info)
3.6.9
3.6.9 (default, Jul 17 2020, 12:50:27)
[GCC 8.4.0]
sys.version_info(major=3, minor=6, micro=9, releaselevel='final', serial=0)

CUDA/cuDNN version:
nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2019 NVIDIA Corporation
Built on Sun_Jul_28_19:07:16_PDT_2019
Cuda compilation tools, release 10.1, V10.1.243

GPU model and memory:
nvidia-smi
Wed Sep 30 13:07:10 2020
+
+
| NVIDIA-SMI 455.23.05 Driver Version: 455.23.05 CUDA Version: 11.1 |
|
+
+
+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 GeForce 920M On | 00000000:03:00.0 N/A | N/A |
| N/A 43C P8 N/A / N/A | 118MiB / 2004MiB | N/A Default |
| | | N/A |
+
+
+
+

+
+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| No running processes found |
+
+

After following all steps from here - https://www.tensorflow.org/install/gpu and installing all these GPU doesn't work

# Add NVIDIA package repositories
wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-repo-ubuntu1804_10.1.243-1_amd64.deb
sudo apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/7fa2af80.pub
sudo dpkg -i cuda-repo-ubuntu1804_10.1.243-1_amd64.deb
sudo apt-get update
wget http://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/nvidia-machine-learning-repo-ubuntu1804_1.0.0-1_amd64.deb
with machine learning course
sudo apt install ./nvidia-machine-learning-repo-ubuntu1804_1.0.0-1_amd64.deb
sudo apt-get update
# Install NVIDIA driver
sudo apt-get install --no-install-recommends nvidia-driver-450
# Reboot. Check that GPUs are visible using the command: nvidia-smi
# Install development and runtime libraries (~4GB)
sudo apt-get install --no-install-recommends \
cuda-10-1 \
libcudnn7=7.6.5.32-1+cuda10.1 \
libcudnn7-dev=7.6.5.32-1+cuda10.1
# Install TensorRT. Requires that libcudnn7 is installed above.
sudo apt-get install -y --no-install-recommends libnvinfer6=6.0.1-1+cuda10.1 \
libnvinfer-dev=6.0.1-1+cuda10.1 \
libnvinfer-plugin6=6.0.1-1+cuda10.1
asked Sep 30, 2020 in Other/Legacy by tobimarsh43 New to the Community (0 points)

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