Create README.md

Signed-off-by: David Rotermund <54365609+davrot@users.noreply.github.com>

pytorch/layers/cuda/README.md

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+## Cuda
+{:.no_toc}
+
+<nav markdown="1" class="toc-class">
+* TOC
+{:toc}
+</nav>
+
+## The goal
+
+Convince PyTorch and Nvidia's GPUs working together. **I assume you installed the PyTorch and/or TensorFlow version for CUDA. (see Python installation instructions on thsi site...)**
+
+Questions to [David Rotermund](mailto:davrot@uni-bremen.de)
+
+## Windows
+
+* Download and install [CUDA driver](https://developer.nvidia.com/cuda-downloads)
+* Download and install [cuDNN toolkit](https://developer.nvidia.com/rdp/cudnn-download) (you will need to create an account :-( )
+
+## Test the PyTorch
+
+```python
+import torch
+torch.cuda.is_available()
+```
+
+Expected output:
+
+```python
+True
+```
+
+```python
+torch.cuda.is_available()
+```
+
+Expected output:
+
+```python
+True
+```
+
+```python
+torch.backends.cuda.is_built()
+```
+
+Expected output:
+
+```python
+True
+```
+
+```python
+torch.backends.cudnn.version()
+```
+
+Expected output (number depends on the GPU generation and may be different):
+
+```python
+8904
+```
+
+```python
+torch.backends.cudnn.enabled
+```
+
+Expected output:
+
+```python
+True
+```
+
+```python
+my_cuda_device = torch.device('cuda:0')
+print(torch.cuda.get_device_properties(my_cuda_device))
+```
+
+Expected output (values depend on the GPU generation):
+
+```python
+_CudaDeviceProperties(name='NVIDIA GeForce RTX 3060', major=8, minor=6, total_memory=12011MB, multi_processor_count=28)
+```