52 gpu utilization

[giorgiapitteri]

PR related to the issue #52

CUDA utilization now reaches 70% max. It still drops to 10% for some operations.

Changes made:

• The whole dataset is loaded into cuda.
• Covariance operations are done on cuda.
• Batch size increased to 128.

[giorgiapitteri]

Is this field "device" used somewhere?

[fariedabuzaid]

The class variable acts as a default value in case the someone accesses the device before calling to

obj = Flow(...)
obj.device

Since strings are immutable, the class variable cannot be changed and the instance variable "device" is created when someone sets the device variable. As soon as that happens the instance variable has precedence over the class variable.

In case that you are not familiar with class variables, have a look into this post

Anyway, this assumes that the initial location is always cpu. It is probably better to have it as another instantiation argument with default value "cpu". Then you can change the value in the config file.

[giorgiapitteri]

Thanks for the explanation. I was wondering indeed why then we need to pass it as an argument of the fit method. I get now that is the variable we set also in the config when creating the Flow object, if I am not mistaken.

[fariedabuzaid]

Looks good. I only saw that there where two potentially unnecessary casts to torch.Tensor. Could be that this causes some unnecessary copying.

[fariedabuzaid]

Thanks great improvement!

Summary:

• On MNIST3 with batch size of 128 GPU utilization
  • Mostly between 50% - 70%
  • Some sudden short drops to 1% (after epoch?)
• Hence, problem (mostly) solved