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  1. Number of training examples = 34799
  2. Number of testing examples = 12630
  3. Image data shape = (32, 32)
  4. Number of classes = 43
  5. Training Set: 34799 samples
  6. Validation Set: 4410 samples
  7. Test Set: 12630 samples
  8. I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcublas.8.0.dylib locally
  9. I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcudnn.5.dylib locally
  10. I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcufft.8.0.dylib locally
  11. I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcuda.1.dylib locally
  12. I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcurand.8.0.dylib locally
  13. W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.
  14. W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.
  15. W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
  16. W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.
  17. W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations.
  18. I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:874] OS X does not support NUMA - returning NUMA node zero
  19. I tensorflow/core/common_runtime/gpu/gpu_device.cc:885] Found device 0 with properties:
  20. name: GeForce GT 750M
  21. major: 3 minor: 0 memoryClockRate (GHz) 0.9255
  22. pciBusID 0000:01:00.0
  23. Total memory: 2.00GiB
  24. Free memory: 1.62GiB
  25. I tensorflow/core/common_runtime/gpu/gpu_device.cc:906] DMA: 0
  26. I tensorflow/core/common_runtime/gpu/gpu_device.cc:916] 0: Y
  27. I tensorflow/core/common_runtime/gpu/gpu_device.cc:975] Creating TensorFlow device (/gpu:0) -> (device: 0, name: GeForce GT 750M, pci bus id: 0000:01:00.0)
  28. Training...
  29.  
  30. E tensorflow/stream_executor/cuda/cuda_dnn.cc:397] could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR
  31. E tensorflow/stream_executor/cuda/cuda_dnn.cc:364] could not destroy cudnn handle: CUDNN_STATUS_BAD_PARAM
  32. F tensorflow/core/kernels/conv_ops.cc:605] Check failed: stream->parent()->GetConvolveAlgorithms(&algorithms)
  33. Abort trap: 6
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