Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Not able to run my retinanet on gpu #1596

Open
KAKAROT12419 opened this issue Jan 19, 2024 · 0 comments
Open

Not able to run my retinanet on gpu #1596

KAKAROT12419 opened this issue Jan 19, 2024 · 0 comments

Comments

@KAKAROT12419
Copy link

KAKAROT12419 commented Jan 19, 2024

I have tensorflow=2.30, cuda toolkit=10.2, and cudNN=7.6.5 everything is correct at the time of initialization and checking the libraries are fine, but it is not taking GPU instead of compiling on CPU. I will give you detailed commands. Please Please Help..

CUDA_VISIBLE_DEVICES=5 /home/akashnegi/retina/retinanet/keras-retinanet-main/keras_retinanet/bin/train.py --gpu 5 csv /home/akashnegi/retina/retinanet/Retinanet-Tutorial/xray/annotation/train_label.csv /home/akashnegi/retina/retinanet/Retinanet-Tutorial/xray/class/class.csv
2024-01-19 06:14:53.761719: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcudart.so.10.1
Using TensorFlow backend.
2024-01-19 06:14:54.676816: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcuda.so.1
2024-01-19 06:14:54.744977: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1716] Found device 0 with properties:
pciBusID: 0000:0b:00.0 name: Tesla V100-SXM2-32GB computeCapability: 7.0
coreClock: 1.53GHz coreCount: 80 deviceMemorySize: 31.75GiB deviceMemoryBandwidth: 836.37GiB/s
2024-01-19 06:14:54.745026: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcudart.so.10.1
2024-01-19 06:14:54.746702: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcublas.so.10
2024-01-19 06:14:54.748573: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcufft.so.10
2024-01-19 06:14:54.748863: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcurand.so.10
2024-01-19 06:14:54.750684: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcusolver.so.10
2024-01-19 06:14:54.751682: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcusparse.so.10
2024-01-19 06:14:54.755340: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcudnn.so.7
2024-01-19 06:14:54.757429: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1858] Adding visible gpu devices: 0
Creating model, this may take a second...
2024-01-19 06:14:55.277390: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN)to use the following CPU instructions in performance-critical operations: AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2024-01-19 06:14:55.287450: I tensorflow/core/platform/profile_utils/cpu_utils.cc:104] CPU Frequency: 2194975000 Hz
2024-01-19 06:14:55.290323: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x55e9a303f910 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2024-01-19 06:14:55.290382: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version
2024-01-19 06:14:55.291734: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1257] Device interconnect StreamExecutor with strength 1 edge matrix:
2024-01-19 06:14:55.291749: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1263]
Model: "retinanet"

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

1 participant