python - 设置 Anaconda 环境的良好做法是什么？Linux中的环境变量

Question

最近，我经常使用 Tensorflow 和 Anaconda 环境。我发现为每个项目创建一个新的 python 环境是一种很好的做法，可以避免在库版本和依赖满足方面造成污染和泄漏。我在 Linux 中忽略了使用环境变量的这种做法，我相信我目前的问题与弄乱其中一些有关。

我的问题是：在 python 包和环境变量方面创建一个完全隔离的编码环境，这样同一个变量，比如 LD_LIBRARY_PATH，将包含与当前项目相关的路径，有什么好的做法？

我目前的谜团是：

Anaconda：我有 2 个 Anaconda 环境，比如 env_a 和 env_b，其中tensorflow-gpu安装了相同的软件包。当我tf.test.is_gpu_available()在env_a上执行时，它会通过我在下面带来的一系列信息按摩来识别我的 GPU。在env_b上 ，在加载动态库的一系列失败后，它无法识别 gpu。我也把警告/信息按摩带到了下面。

环境路径：/.bashrc我在文件 中添加了 LD_LIBRARY_PATH 的路径。所以每次我启动一个终端时，它都会加载它们。

我提到 LD_LIBRARY_PATH 的原因是，当env_b无法识别 gpu 时，它会出现在警告消息中。显然 LD_LIBRARY_PATH 与 env_a 配合得很好，而与 env_b 配合得不好。

env_b 的失败按摩

2019-09-29 16:35:29.702531: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 3600000000 Hz
2019-09-29 16:35:29.703074: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x557bcdfb6460 executing computations on platform Host. Devices:
2019-09-29 16:35:29.703089: I tensorflow/compiler/xla/service/service.cc:175]   StreamExecutor device (0): <undefined>, <undefined>
2019-09-29 16:35:29.703835: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcuda.so.1
2019-09-29 16:35:29.725176: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1005] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-09-29 16:35:29.725495: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1640] Found device 0 with properties: 
name: GeForce GTX 1070 Ti major: 6 minor: 1 memoryClockRate(GHz): 1.683
pciBusID: 0000:01:00.0
2019-09-29 16:35:29.725567: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Could not dlopen library 'libcudart.so.10.0'; dlerror: libcudart.so.10.0: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: :/home/asheryartsev/UnrealEngine-4.18/Engine/Binaries:/home/asheryartsev/UnrealEngine-4.18/Engine/Binaries
2019-09-29 16:35:29.725613: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Could not dlopen library 'libcublas.so.10.0'; dlerror: libcublas.so.10.0: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: :/home/asheryartsev/UnrealEngine-4.18/Engine/Binaries:/home/asheryartsev/UnrealEngine-4.18/Engine/Binaries
2019-09-29 16:35:29.725657: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Could not dlopen library 'libcufft.so.10.0'; dlerror: libcufft.so.10.0: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: :/home/asheryartsev/UnrealEngine-4.18/Engine/Binaries:/home/asheryartsev/UnrealEngine-4.18/Engine/Binaries
2019-09-29 16:35:29.725700: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Could not dlopen library 'libcurand.so.10.0'; dlerror: libcurand.so.10.0: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: :/home/asheryartsev/UnrealEngine-4.18/Engine/Binaries:/home/asheryartsev/UnrealEngine-4.18/Engine/Binaries
2019-09-29 16:35:29.725742: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Could not dlopen library 'libcusolver.so.10.0'; dlerror: libcusolver.so.10.0: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: :/home/asheryartsev/UnrealEngine-4.18/Engine/Binaries:/home/asheryartsev/UnrealEngine-4.18/Engine/Binaries
2019-09-29 16:35:29.725785: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Could not dlopen library 'libcusparse.so.10.0'; dlerror: libcusparse.so.10.0: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: :/home/asheryartsev/UnrealEngine-4.18/Engine/Binaries:/home/asheryartsev/UnrealEngine-4.18/Engine/Binaries
2019-09-29 16:35:29.725825: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Could not dlopen library 'libcudnn.so.7'; dlerror: libcudnn.so.7: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: :/home/asheryartsev/UnrealEngine-4.18/Engine/Binaries:/home/asheryartsev/UnrealEngine-4.18/Engine/Binaries
2019-09-29 16:35:29.725833: W tensorflow/core/common_runtime/gpu/gpu_device.cc:1663] Cannot dlopen some GPU libraries. Skipping registering GPU devices...
2019-09-29 16:35:29.788211: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1181] Device interconnect StreamExecutor with strength 1 edge matrix:
2019-09-29 16:35:29.788236: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1187]      0 
2019-09-29 16:35:29.788241: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1200] 0:   N 
2019-09-29 16:35:29.789433: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1005] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-09-29 16:35:29.789753: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x557bcfea7e30 executing computations on platform CUDA. Devices:
2019-09-29 16:35:29.789765: I tensorflow/compiler/xla/service/service.cc:175]   StreamExecutor device (0): GeForce GTX 1070 Ti, Compute Capability 6.1
False

env_a 的成功按摩

2019-09-30 11:13:32.469410: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX AVX2 FMA
2019-09-30 11:13:32.498599: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 3600000000 Hz
2019-09-30 11:13:32.499157: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x55a5de3541f0 executing computations on platform Host. Devices:
2019-09-30 11:13:32.499185: I tensorflow/compiler/xla/service/service.cc:175]   StreamExecutor device (0): <undefined>, <undefined>
2019-09-30 11:13:32.500030: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcuda.so.1
2019-09-30 11:13:32.502295: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1005] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-09-30 11:13:32.502622: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1640] Found device 0 with properties: 
name: GeForce GTX 1070 Ti major: 6 minor: 1 memoryClockRate(GHz): 1.683
pciBusID: 0000:01:00.0
2019-09-30 11:13:32.502735: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcudart.so.10.1
2019-09-30 11:13:32.503876: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcublas.so.10
2019-09-30 11:13:32.505077: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcufft.so.10
2019-09-30 11:13:32.505250: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcurand.so.10
2019-09-30 11:13:32.506538: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcusolver.so.10
2019-09-30 11:13:32.507201: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcusparse.so.10
2019-09-30 11:13:32.509645: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcudnn.so.7
2019-09-30 11:13:32.509724: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1005] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-09-30 11:13:32.510038: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1005] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-09-30 11:13:32.510289: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1763] Adding visible gpu devices: 0
2019-09-30 11:13:32.510314: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcudart.so.10.1
2019-09-30 11:13:32.567936: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1181] Device interconnect StreamExecutor with strength 1 edge matrix:
2019-09-30 11:13:32.567961: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1187]      0 
2019-09-30 11:13:32.567966: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1200] 0:   N 
2019-09-30 11:13:32.568099: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1005] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-09-30 11:13:32.568419: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1005] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-09-30 11:13:32.568706: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1005] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-09-30 11:13:32.568978: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1326] Created TensorFlow device (/device:GPU:0 with 6822 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1070 Ti, pci bus id: 0000:01:00.0, compute capability: 6.1)
2019-09-30 11:13:32.570348: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x55a5e1a6e070 executing computations on platform CUDA. Devices:
2019-09-30 11:13:32.570365: I tensorflow/compiler/xla/service/service.cc:175]   StreamExecutor device (0): GeForce GTX 1070 Ti, Compute Capability 6.1
True

标签： pythontensorflowanacondaenvironment-variables