I was training my models when it felt like they were running very slowly. After some digging I noticed that device GPU 0 is type xla_cpu and is not going through my gpu. device xla_gpu is listed but when forcing tensforflow to use it just crashes saying it can't find ptaxs.
For environment information please scroll past the error block.
The is the crash report while using the line of code:
whith tf.device('/device:XLA_GPU:0'): model.fit(dataSetGenerator, epochs=1, steps_per_epoch=self.steps_per_epoch)
I get the following error
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]
About 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
For cudnn I have the following information
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)
I used the following python script to get hopefully more useful information to help debug this.
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')))
This gave me the following output.
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