Hi,
Currently, I am trying out a project from https://github.com/MaybeShewill-CV/attentive-gan-derainnet and unable to run the given test code due to not being able to detect GPU. Full error shown below.
VGG16 Network init complete
WARNING:tensorflow:From /home/oliver/Downloads/attentive-gan-derainnet-master/attentive_gan_model/derain_drop_net.py:84: The name tf.variable_scope is deprecated. Please use tf.compat.v1.variable_scope instead.
WARNING:tensorflow:From /home/oliver/Downloads/attentive-gan-derainnet-master/attentive_gan_model/cnn_basenet.py:71: The name tf.get_variable is deprecated. Please use tf.compat.v1.get_variable instead.
WARNING:tensorflow:From /home/oliver/Downloads/attentive-gan-derainnet-master/attentive_gan_model/cnn_basenet.py:402: conv2d_transpose (from tensorflow.python.layers.convolutional) is deprecated and will be removed in a future version.
Instructions for updating:
Use tf.keras.layers.Conv2DTranspose instead.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow_core/python/layers/convolutional.py:1279: Layer.apply (from tensorflow.python.keras.engine.base_layer) is deprecated and will be removed in a future version.
Instructions for updating:
Please use layer.__call__ method instead.
WARNING:tensorflow:From /home/oliver/Downloads/attentive-gan-derainnet-master/attentive_gan_model/cnn_basenet.py:167: The name tf.nn.avg_pool is deprecated. Please use tf.nn.avg_pool2d instead.
WARNING:tensorflow:From tools/test_model.py:87: The name tf.ConfigProto is deprecated. Please use tf.compat.v1.ConfigProto instead.
WARNING:tensorflow:From tools/test_model.py:92: The name tf.Session is deprecated. Please use tf.compat.v1.Session instead.
2019-12-20 17:53:17.246953: W tensorflow/core/platform/profile_utils/cpu_utils.cc:98] Failed to find bogomips in /proc/cpuinfo; cannot determine CPU frequency
2019-12-20 17:53:17.247993: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x1d0b5bf0 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2019-12-20 17:53:17.248072: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version
2019-12-20 17:53:17.256615: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1
2019-12-20 17:53:17.364778: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:950] ARM64 does not support NUMA - returning NUMA node zero
2019-12-20 17:53:17.365080: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x1d3f7b90 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices:
2019-12-20 17:53:17.365128: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA Tegra X2, Compute Capability 6.2
2019-12-20 17:53:17.365675: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:950] ARM64 does not support NUMA - returning NUMA node zero
2019-12-20 17:53:17.365788: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 0 with properties:
name: NVIDIA Tegra X2 major: 6 minor: 2 memoryClockRate(GHz): 1.02
pciBusID: 0000:00:00.0
2019-12-20 17:53:17.365984: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.0
2019-12-20 17:53:17.397423: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10.0
2019-12-20 17:53:17.426466: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10.0
2019-12-20 17:53:17.465343: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10.0
2019-12-20 17:53:17.507393: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10.0
2019-12-20 17:53:17.532817: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10.0
2019-12-20 17:53:17.612222: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2019-12-20 17:53:17.612716: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:950] ARM64 does not support NUMA - returning NUMA node zero
2019-12-20 17:53:17.613058: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:950] ARM64 does not support NUMA - returning NUMA node zero
2019-12-20 17:53:17.613143: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1746] Adding visible gpu devices: 0
2019-12-20 17:53:17.613381: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.0
2019-12-20 17:53:20.302402: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1159] Device interconnect StreamExecutor with strength 1 edge matrix:
2019-12-20 17:53:20.302484: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1165] 0
2019-12-20 17:53:20.302535: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1178] 0: N
2019-12-20 17:53:20.303093: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:950] ARM64 does not support NUMA - returning NUMA node zero
2019-12-20 17:53:20.303514: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:950] ARM64 does not support NUMA - returning NUMA node zero
2019-12-20 17:53:20.303735: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1304] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 6281 MB memory) -> physical GPU (device: 0, name: NVIDIA Tegra X2, pci bus id: 0000:00:00.0, compute capability: 6.2)
I have installed tensorflow-gpu library and using a cuda 10-0.
After running the test code, my proccessing speed will be very slow and i was unable to achieve my results even though no error message was shown.
Please help ! thanks in advance