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python - How to use my GPU when coding in Spyder (Anaconda in general) (Windows 10)?

I've recently tried to use my GPU in Windows 10 by following several instructions. Initially, I followed instructions given by Tensorflow (Tensorflow.org). I installed python 3.9.1, cuDNN 11.1, CUDA 11.1.1, NVIDIA GPU Driver based on my Graphic Card, and created new paths. Afterwards created a channel in Anaconda(1.10) called "Tensorflow", imported tensorflow in Spyder(4.1.5) running in this channel but when tried to test if any GPU was available, got "0" results (code provided below). Actually I was not sure if and how what I've previously installed were used.

In [1]: import tensorflow as tf
    2020-12-30 10:48:46.263644: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll

In [2]: print("Num GPUs Available: ", len(tf.config.experimental.list_physical_devices('GPU')))

2020-12-30 10:48:46.263644: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll
2020-12-30 10:48:54.941741: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
2020-12-30 10:48:54.945949: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library nvcuda.dll

2020-12-30 10:48:46.263644: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll
2020-12-30 10:48:54.941741: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
2020-12-30 10:48:54.945949: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library nvcuda.dll
2020-12-30 10:48:56.212215: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: 
pciBusID: 0000:01:00.0 name: GeForce GTX 1650 computeCapability: 7.5
coreClock: 1.56GHz coreCount: 16 deviceMemorySize: 4.00GiB deviceMemoryBandwidth: 119.24GiB/s
2020-12-30 10:48:56.215245: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll
2020-12-30 10:48:56.288545: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
2020-12-30 10:48:56.289169: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll
Num GPUs Available:  0

2020-12-30 10:48:46.263644: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll
2020-12-30 10:48:54.941741: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
2020-12-30 10:48:54.945949: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library nvcuda.dll
2020-12-30 10:48:56.212215: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: 
pciBusID: 0000:01:00.0 name: GeForce GTX 1650 computeCapability: 7.5
coreClock: 1.56GHz coreCount: 16 deviceMemorySize: 4.00GiB deviceMemoryBandwidth: 119.24GiB/s
2020-12-30 10:48:56.215245: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll
2020-12-30 10:48:56.288545: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
2020-12-30 10:48:56.289169: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll
2020-12-30 10:48:56.326345: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll
2020-12-30 10:48:56.336977: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll
2020-12-30 10:48:56.338808: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'cusolver64_10.dll'; dlerror: cusolver64_10.dll not found
2020-12-30 10:48:56.359937: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll
2020-12-30 10:48:56.363748: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll
2020-12-30 10:48:56.364357: W tensorflow/core/common_runtime/gpu/gpu_device.cc:1757] Cannot dlopen some GPU libraries. Please make sure the missing libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at https://www.tensorflow.org/install/gpu for how to download and setup the required libraries for your platform.
Skipping registering GPU devices...
In [3]: 

As a result I thought that I was still using CPU and decided to follow other instructions from similar questions here in Stackoverflow. I run as Administrator the Anaconda Prompt, created a new channel called "tf-gpu", installed tensorflow, keras and other packages with "pip". I installed Spyder in this channel from Anaconda, run Spyder and same code. I got the same results.

Nothing worked so far and I would like to take advantage of my GPU for saving some time, instead of using GoogleColab. I would be glad if any recommendation was given on how to use my GPU using Anaconda Spyder.

Thank you in advance.


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Are you sure you have the hardware requirements to use GPU? Because it says that there is no GPU available.


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