Hi everyone,
I developed a custom object detection with TensorFlow 1.14 using ssd_mobilenet_v2. I want to deploy the model on the Nano that has Tensorflow 1.13 for nano installed. The graph is not compatible and it fails to do a prediction. So I installed TensorFlow 1.14 on the nano but now, I am getting the following error:
2019-07-29 09:49:47.926014: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:973] ARM64 does not support NUMA - returning NUMA node zero
2019-07-29 09:49:47.926093: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1746] Adding visible gpu devices: 0
2019-07-29 09:49:47.926205: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.0
2019-07-29 09:49:47.927832: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1159] Device interconnect StreamExecutor with strength 1 edge matrix:
2019-07-29 09:49:47.927966: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1165] 0
2019-07-29 09:49:47.927992: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1178] 0: N
2019-07-29 09:49:47.928260: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:973] ARM64 does not support NUMA - returning NUMA node zero
2019-07-29 09:49:47.928519: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:973] ARM64 does not support NUMA - returning NUMA node zero
2019-07-29 09:49:47.928660: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1304] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 1761 MB memory) -> physical GPU (device: 0, name: NVIDIA Tegra X1, pci bus id: 0000:00:00.0, compute capability: 5.3)
2019-07-29 09:59:14.916523: F tensorflow/stream_executor/cuda/cuda_driver.cc:175] Check failed: err == cudaSuccess || err == cudaErrorInvalidValue Unexpected CUDA error: unknown error
Now I am thinking of converting the graph using tensorRT but it’s only compatible with Tensorflow 1.12
Any idea to solve this?