python中tensorflow_python – 如何解释TensorFlow输出?

python3 tensorflow_test.py > out

第一部分stream_executor看起来像它的加载依赖项。

I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcublas.so locally

I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcudnn.so locally

I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcufft.so locally

I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcuda.so.1 locally

I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcurand.so locally

什么是NUMA节点?

I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:900] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero

我认为这是当它找到可用的GPU

I tensorflow/core/common_runtime/gpu/gpu_init.cc:102] Found device 0 with properties:

name: Tesla K40c

major: 3 minor: 5 memoryClockRate (GHz) 0.745

pciBusID 0000:01:00.0

Total memory: 11.25GiB

Free memory: 11.15GiB

一些gpu初始化?什么是DMA?

I tensorflow/core/common_runtime/gpu/gpu_init.cc:126] DMA: 0

I tensorflow/core/common_runtime/gpu/gpu_init.cc:136] 0: Y

I tensorflow/core/common_runtime/gpu/gpu_device.cc:755] Creating TensorFlow device (/gpu:0) -> (device: 0, name: Tesla K40c, pci bus id: 0000:01:00.0)

为什么会出错E?

E tensorflow/stream_executor/cuda/cuda_driver.cc:932] failed to allocate 11.15G (11976531968 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY

I tensorflow/core/common_runtime/gpu/pool_allocator.cc:244] PoolAllocator: After 3160 get requests, put_count=2958 evicted_count=1000 eviction_rate=0.338066 and unsatisfied allocation rate=0.412025

I tensorflow/core/common_runtime/gpu/pool_allocator.cc:256] Raising pool_size_limit_ from 100 to 110

I tensorflow/core/common_runtime/gpu/pool_allocator.cc:244] PoolAllocator: After 1743 get requests, put_count=1970 evicted_count=1000 eviction_rate=0.507614 and unsatisfied allocation rate=0.456684

I tensorflow/core/common_runtime/gpu/pool_allocator.cc:256] Raising pool_size_limit_ from 256 to 281

I tensorflow/core/common_runtime/gpu/pool_allocator.cc:244] PoolAllocator: After 1986 get requests, put_count=2519 evicted_count=1000 eviction_rate=0.396983 and unsatisfied allocation rate=0.264854

I tensorflow/core/common_runtime/gpu/pool_allocator.cc:256] Raising pool_size_limit_ from 655 to 720

I tensorflow/core/common_runtime/gpu/pool_allocator.cc:244] PoolAllocator: After 28728 get requests, put_count=28680 evicted_count=1000 eviction_rate=0.0348675 and unsatisfied allocation rate=0.0418407

I tensorflow/core/common_runtime/gpu/pool_allocator.cc:256] Raising pool_size_limit_ from 1694 to 1863

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