Я тренировал своих моделей, когда мне казалось, что они бегут очень медленно. После некоторого покопания я заметил, что устройство GPU 0 имеет тип xla_cpu и не проходит через мой графический процессор. Устройство xla_gpu указано в списке, но при принудительном использовании tensforflow оно просто вылетает, говоря, что не может найти ptaxs.
Для получения информации о среде, пожалуйста, прокрутите блок ошибки.
Это Cra sh отчет при использовании строки кода:
whith tf.device('/device:XLA_GPU:0'): model.fit(dataSetGenerator, epochs=1, steps_per_epoch=self.steps_per_epoch)
Я получаю следующую ошибку
2020-05-25 15:11:23.103677: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce GTX 1050 Ti computeCapability: 6.1
coreClock: 1.62GHz coreCount: 6 deviceMemorySize: 4.00GiB deviceMemoryBandwidth: 104.43GiB/s
2020-05-25 15:11:23.104045: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2020-05-25 15:11:23.104234: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_10.dll
2020-05-25 15:11:23.104414: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cufft64_10.dll
2020-05-25 15:11:23.104597: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library curand64_10.dll
2020-05-25 15:11:23.104761: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusolver64_10.dll
2020-05-25 15:11:23.104977: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusparse64_10.dll
2020-05-25 15:11:23.105248: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll
2020-05-25 15:11:23.105810: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0
2020-05-25 15:11:23.106793: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce GTX 1050 Ti computeCapability: 6.1
coreClock: 1.62GHz coreCount: 6 deviceMemorySize: 4.00GiB deviceMemoryBandwidth: 104.43GiB/s
2020-05-25 15:11:23.107632: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2020-05-25 15:11:23.107840: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_10.dll
2020-05-25 15:11:23.107957: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cufft64_10.dll
2020-05-25 15:11:23.108142: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library curand64_10.dll
2020-05-25 15:11:23.108257: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusolver64_10.dll
2020-05-25 15:11:23.108371: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusparse64_10.dll
2020-05-25 15:11:23.108487: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll
2020-05-25 15:11:23.108877: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0
2020-05-25 15:11:23.109054: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix:
2020-05-25 15:11:23.109592: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0
2020-05-25 15:11:23.109666: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N
2020-05-25 15:11:23.109998: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 2990 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1050 Ti, pci bus id: 0000:01:00.0, compute capability: 6.1)
2020-05-25 15:12:20.827825: W tensorflow/compiler/jit/xla_device.cc:398] XLA_GPU and XLA_CPU devices are deprecated and will be removed in subsequent releases. Instead, use either @tf.function(experimental_compile=True) for must-compile semantics, or run with TF_XLA_FLAGS=--tf_xla_auto_jit=2 for auto-clustering best-effort compilation.
2020-05-25 15:12:24.752427: W tensorflow/compiler/xla/service/gpu/nvptx_compiler.cc:70] Can't find ptxas binary in ${CUDA_DIR}/bin. Will back to the GPU driver for PTX -> sass compilation. This is OK so long as you don't see a warning below about an out-of-date driver version. Custom ptxas location can be specified using $PATH.
2020-05-25 15:12:24.752721: W tensorflow/compiler/xla/service/gpu/nvptx_compiler.cc:71] Searched for CUDA in the following directories:
2020-05-25 15:12:24.752826: W tensorflow/compiler/xla/service/gpu/nvptx_compiler.cc:74] ./cuda_sdk_lib
2020-05-25 15:12:24.752907: W tensorflow/compiler/xla/service/gpu/nvptx_compiler.cc:74] C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v10.1
2020-05-25 15:12:24.753020: W tensorflow/compiler/xla/service/gpu/nvptx_compiler.cc:74] .
2020-05-25 15:12:24.753091: W tensorflow/compiler/xla/service/gpu/nvptx_compiler.cc:76] You can choose the search directory by setting xla_gpu_cuda_data_dir in HloModule's DebugOptions. For most apps, setting the environment variable XLA_FLAGS=--xla_gpu_cuda_data_dir=/path/to/cuda will work.
2020-05-25 15:12:24.753332: W tensorflow/compiler/xla/service/gpu/nvptx_compiler.cc:197] Couldn't read CUDA driver version.
2020-05-25 15:12:24.753533: I tensorflow/compiler/jit/xla_compilation_cache.cc:241] Compiled cluster using XLA! This line is logged at most once for the lifetime of the process.
2020-05-25 15:12:24.785710: W tensorflow/compiler/xla/service/gpu/nvptx_compiler.cc:70] Can't find ptxas binary in ${CUDA_DIR}/bin. Will back to the GPU driver for PTX -> sass compilation. This is OK so long as you don't see a warning below about an out-of-date driver version. Custom ptxas location can be specified using $PATH.
2020-05-25 15:12:24.786148: W tensorflow/compiler/xla/service/gpu/nvptx_compiler.cc:71] Searched for CUDA in the following directories:
2020-05-25 15:12:24.786295: W tensorflow/compiler/xla/service/gpu/nvptx_compiler.cc:74] ./cuda_sdk_lib
2020-05-25 15:12:24.786424: W tensorflow/compiler/xla/service/gpu/nvptx_compiler.cc:74] C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v10.1
2020-05-25 15:12:24.786541: W tensorflow/compiler/xla/service/gpu/nvptx_compiler.cc:74] .
2020-05-25 15:12:24.786617: W tensorflow/compiler/xla/service/gpu/nvptx_compiler.cc:76] You can choose the search directory by setting xla_gpu_cuda_data_dir in HloModule's DebugOptions. For most apps, setting the environment variable XLA_FLAGS=--xla_gpu_cuda_data_dir=/path/to/cuda will work.
Traceback (most recent call last):
File "D:/PiChess/Core/Main.py", line 68, in <module>
ForEx10d5w5m.TrainActiveModels()
File "D:\PiChess\Core\DatasetTemplates\ForEx_10d_5w_5m.py", line 705, in TrainActiveModels
with tf.device('/device:XLA_GPU:0'): model.fit(dataSetGenerator, epochs=1, steps_per_epoch=self.steps_per_epoch)
File "D:\PiChess\Core\venv\lib\site-packages\tensorflow\python\keras\engine\training.py", line 66, in _method_wrapper
return method(self, *args, **kwargs)
File "D:\PiChess\Core\venv\lib\site-packages\tensorflow\python\keras\engine\training.py", line 848, in fit
tmp_logs = train_function(iterator)
File "D:\PiChess\Core\venv\lib\site-packages\tensorflow\python\eager\def_function.py", line 580, in __call__
result = self._call(*args, **kwds)
File "D:\PiChess\Core\venv\lib\site-packages\tensorflow\python\eager\def_function.py", line 644, in _call
return self._stateless_fn(*args, **kwds)
File "D:\PiChess\Core\venv\lib\site-packages\tensorflow\python\eager\function.py", line 2420, in __call__
return graph_function._filtered_call(args, kwargs) # pylint: disable=protected-access
File "D:\PiChess\Core\venv\lib\site-packages\tensorflow\python\eager\function.py", line 1665, in _filtered_call
self.captured_inputs)
File "D:\PiChess\Core\venv\lib\site-packages\tensorflow\python\eager\function.py", line 1746, in _call_flat
ctx, args, cancellation_manager=cancellation_manager))
File "D:\PiChess\Core\venv\lib\site-packages\tensorflow\python\eager\function.py", line 598, in call
ctx=ctx)
File "D:\PiChess\Core\venv\lib\site-packages\tensorflow\python\eager\execute.py", line 60, in quick_execute
inputs, attrs, num_outputs)
tensorflow.python.framework.errors_impl.InvalidArgumentError: Function invoked by the following node is not compilable: {{node __inference_train_function_1659}} = __inference_train_function_1659[_XlaMustCompile=true, config_proto="\n\007\n\003CPU\020\001\n\007\n\003GPU\020\0012\005*\0010J\0008\001", executor_type=""](dummy_input, dummy_input, dummy_input, dummy_input, dummy_input, dummy_input, dummy_input, dummy_input, dummy_input, dummy_input, dummy_input, dummy_input, dummy_input, dummy_input, dummy_input, dummy_input, dummy_input, dummy_input, dummy_input, dummy_input, dummy_input, dummy_input, dummy_input, dummy_input, dummy_input, dummy_input, dummy_input, dummy_input, dummy_input, dummy_input).
Uncompilable nodes:
IteratorGetNext: unsupported op: No registered 'IteratorGetNext' OpKernel for XLA_GPU_JIT devices compatible with node {{node IteratorGetNext}}
Stacktrace:
Node: __inference_train_function_1659, function:
Node: IteratorGetNext, function: __inference_train_function_1659
[Op:__inference_train_function_1659]
О CUDA
PS C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\bin> nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2019 NVIDIA Corporation
Built on Fri_Feb__8_19:08:26_Pacific_Standard_Time_2019
Cuda compilation tools, release 10.1, V10.1.105
Для cudnn у меня есть следующая информация
PS C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\bin> type "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\include\cudnn.h" | findstr "CUDNN_MAJOR CUDNN_MINOR CUDNN_PATCHLEVEL"
#define CUDNN_MAJOR 7
#define CUDNN_MINOR 6
#define CUDNN_PATCHLEVEL 5
#define CUDNN_VERSION (CUDNN_MAJOR * 1000 + CUDNN_MINOR * 100 + CUDNN_PATCHLEVEL)
Я использовал следующий python скрипт, чтобы получить, надеюсь, более полезную информацию, чтобы помочь отладить это.
import tensorflow as tf
from tensorflow.python.client import device_lib
print(device_lib.list_local_devices())
# sess = tf.Session(config=tf.ConfigProto(log_device_placement=True))
print(tf.__version__)
#os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
print(tf.test.is_gpu_available())
print(tf.test.is_gpu_available(
cuda_only=False,
min_cuda_compute_capability=None
))
print(tf.test.is_gpu_available(
cuda_only=True,
min_cuda_compute_capability=None
))
print(tf.test.is_built_with_cuda())
import sys
print(sys.version)
import ctypes
print(ctypes.WinDLL('cudnn64_7.dll'))
print("Num GPUs Available: ", len(tf.config.experimental.list_physical_devices('GPU')))
Это дало мне следующий результат.
D:\PiChess\Core\venv\Scripts\python.exe D:/PiChess/Core/test2.py
2020-05-25 15:09:57.190323: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2020-05-25 15:09:59.098417: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2
2020-05-25 15:09:59.106107: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x256e9b45470 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2020-05-25 15:09:59.106369: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version
2020-05-25 15:09:59.107813: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library nvcuda.dll
2020-05-25 15:09:59.332317: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce GTX 1050 Ti computeCapability: 6.1
coreClock: 1.62GHz coreCount: 6 deviceMemorySize: 4.00GiB deviceMemoryBandwidth: 104.43GiB/s
2020-05-25 15:09:59.332965: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2020-05-25 15:09:59.336063: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_10.dll
2020-05-25 15:09:59.340072: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cufft64_10.dll
2020-05-25 15:09:59.340908: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library curand64_10.dll
2020-05-25 15:09:59.343596: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusolver64_10.dll
2020-05-25 15:09:59.345793: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusparse64_10.dll
2020-05-25 15:09:59.351064: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll
2020-05-25 15:09:59.351981: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0
2020-05-25 15:09:59.937899: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix:
2020-05-25 15:09:59.938075: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0
2020-05-25 15:09:59.938167: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N
2020-05-25 15:09:59.938673: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/device:GPU:0 with 2990 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1050 Ti, pci bus id: 0000:01:00.0, compute capability: 6.1)
2020-05-25 15:09:59.941582: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x2568c2c4ab0 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices:
2020-05-25 15:09:59.941737: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): GeForce GTX 1050 Ti, Compute Capability 6.1
WARNING:tensorflow:From D:/PiChess/Core/test2.py:11: is_gpu_available (from tensorflow.python.framework.test_util) is deprecated and will be removed in a future version.
Instructions for updating:
Use `tf.config.list_physical_devices('GPU')` instead.
2020-05-25 15:09:59.943635: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce GTX 1050 Ti computeCapability: 6.1
coreClock: 1.62GHz coreCount: 6 deviceMemorySize: 4.00GiB deviceMemoryBandwidth: 104.43GiB/s
2020-05-25 15:09:59.943963: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2020-05-25 15:09:59.944147: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_10.dll
2020-05-25 15:09:59.944321: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cufft64_10.dll
2020-05-25 15:09:59.944476: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library curand64_10.dll
2020-05-25 15:09:59.944615: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusolver64_10.dll
2020-05-25 15:09:59.944739: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusparse64_10.dll
2020-05-25 15:09:59.944877: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll
2020-05-25 15:09:59.945388: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0
2020-05-25 15:09:59.945684: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix:
2020-05-25 15:09:59.945803: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0
2020-05-25 15:09:59.945877: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N
2020-05-25 15:09:59.946315: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/device:GPU:0 with 2990 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1050 Ti, pci bus id: 0000:01:00.0, compute capability: 6.1)
2020-05-25 15:09:59.947867: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce GTX 1050 Ti computeCapability: 6.1
coreClock: 1.62GHz coreCount: 6 deviceMemorySize: 4.00GiB deviceMemoryBandwidth: 104.43GiB/s
2020-05-25 15:09:59.948101: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2020-05-25 15:09:59.948249: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_10.dll
2020-05-25 15:09:59.948364: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cufft64_10.dll
2020-05-25 15:09:59.948479: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library curand64_10.dll
2020-05-25 15:09:59.948596: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusolver64_10.dll
2020-05-25 15:09:59.948734: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusparse64_10.dll
2020-05-25 15:09:59.948863: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll
2020-05-25 15:09:59.949266: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0
2020-05-25 15:09:59.949555: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix:
2020-05-25 15:09:59.949672: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0
2020-05-25 15:09:59.949742: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N
2020-05-25 15:09:59.950111: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/device:GPU:0 with 2990 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1050 Ti, pci bus id: 0000:01:00.0, compute capability: 6.1)
2020-05-25 15:09:59.951438: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce GTX 1050 Ti computeCapability: 6.1
coreClock: 1.62GHz coreCount: 6 deviceMemorySize: 4.00GiB deviceMemoryBandwidth: 104.43GiB/s
2020-05-25 15:09:59.951764: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2020-05-25 15:09:59.951930: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_10.dll
2020-05-25 15:09:59.952125: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cufft64_10.dll
2020-05-25 15:09:59.952412: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library curand64_10.dll
2020-05-25 15:09:59.952587: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusolver64_10.dll
2020-05-25 15:09:59.952763: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusparse64_10.dll
2020-05-25 15:09:59.952939: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll
2020-05-25 15:09:59.953318: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0
2020-05-25 15:09:59.953440: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix:
2020-05-25 15:09:59.953558: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0
2020-05-25 15:09:59.953632: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N
2020-05-25 15:09:59.953935: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/device:GPU:0 with 2990 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1050 Ti, pci bus id: 0000:01:00.0, compute capability: 6.1)
2020-05-25 15:09:59.955052: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce GTX 1050 Ti computeCapability: 6.1
coreClock: 1.62GHz coreCount: 6 deviceMemorySize: 4.00GiB deviceMemoryBandwidth: 104.43GiB/s
2020-05-25 15:09:59.955586: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
[name: "/device:CPU:0"
device_type: "CPU"
memory_limit: 268435456
locality {
}
incarnation: 3593757145487346910
, name: "/device:XLA_CPU:0"
device_type: "XLA_CPU"
memory_limit: 17179869184
locality {
}
incarnation: 15151200481806228159
physical_device_desc: "device: XLA_CPU device"
, name: "/device:GPU:0"
device_type: "GPU"
memory_limit: 3136264601
locality {
bus_id: 1
links {
}
}
incarnation: 17283739609840781326
physical_device_desc: "device: 0, name: GeForce GTX 1050 Ti, pci bus id: 0000:01:00.0, compute capability: 6.1"
, name: "/device:XLA_GPU:0"
device_type: "XLA_GPU"
memory_limit: 17179869184
locality {
}
incarnation: 2207722455070197847
physical_device_desc: "device: XLA_GPU device"
]
2.2.0
True
True
True
True
3.6.8 (tags/v3.6.8:3c6b436a57, Dec 24 2018, 00:16:47) [MSC v.1916 64 bit (AMD64)]
<WinDLL 'cudnn64_7.dll', handle 7ffe4b520000 at 0x256d1f56e80>
Num GPUs Available: 1
2020-05-25 15:09:59.955763: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_10.dll
2020-05-25 15:09:59.955935: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cufft64_10.dll
2020-05-25 15:09:59.956155: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library curand64_10.dll
2020-05-25 15:09:59.956357: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusolver64_10.dll
2020-05-25 15:09:59.956535: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusparse64_10.dll
2020-05-25 15:09:59.956719: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll
2020-05-25 15:09:59.957138: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0
Process finished with exit code 0