>>> import tensorflow as tf
2020-07-08 17:10:50.005569: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
>>> tf.config.list_physical_devices('GPU')
2020-07-08 17:10:55.657489: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce GTX 1050 computeCapability: 6.1
coreClock: 1.493GHz coreCount: 5 deviceMemorySize: 4.00GiB deviceMemoryBandwidth: 104.43GiB/s
2020-07-08 17:10:55.701387: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0
[PhysicalDevice(name='/physical_device:GPU:0', device_type='GPU')]
in [1]: import tensorflow as tf
tf.config.list_physical_devices('GPU')
out[1]: []
in [1]: tf.__version__
out[1]: '2.2.0'
It needs to make new kernel for this env and select kernel form jupyter notebook
$ conda activate env_name
$ pip install ipykernel --user
$ python -m ipykernel install --user --name env_name --display-name env_name
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