PyTorch will automatically use a GPU

GPU support for TensorFlow & amp; PyTorch

First of all, the 940M is unfortunately a kind of weak GPU for training. I suggest you use google colab for faster training but of course it would be faster than the CPU. So here are my answers to your four questions.

1-) Yes, if you install the requirements correctly then you can run on GPU. You can also manually place your data on your GPU. You can check implementations on TensorFlow. In PyTorch, you should specify the device you want to use. As you said, you should do then for models and data you should always call, then for models and data you should always Then it will automatically use GPU if available. call. Then it will automatically use GPU when available.

2-) PyTorch also needs additional installation (module) for GPU support. However, with the recent updates, both TF and PyTorch are easy to use for GPU compatible code.

3-) Both Tensorflow and PyTorch are based on cuDNN. You can use them without cuDNN but as far as I know it hurts performance but I'm not sure about this topic.

4-) No, they are still different packages. what they did with tf2, what making the tensorflow more like Keras. So it is more simplified then 1.15 or before. what they did with tf2 was make the tensor flow more like keras. So it's more simplified than 1.15 or earlier.