0.1.2: Fixing minor bugs

Fixing Double Counting Parameters #3 issue and PR Submodule can be None and should be ignored by hierarchical_summary #4

Thank you so much @daniel347x, @TortoiseHam and @jonashaag for the feedbacks

0.1.1

Making sure that weights and BN params won't be change during net str…

First improved version of `model summary` library

This is an Improved PyTorch library of modelsummary. Like in modelsummary, It does not care with number of Input parameter!

Improvements:

• For user defined pytorch layers, now summary can show layers inside it

  • some assumptions: when is an user defined layer, if any weight/params/bias is trainable, then it is assumed that this layer is trainable (but only trainable params are counted in Tr. Params #)

• Adding column counting only trainable parameters (it makes sense when there are user defined layers)

• Showing all input/output shapes, instead of showing only the first one

  • example: LSTM layer return a Tensor and a tuple (Tensor, Tensor), then output_shape has three set of values

• Printing: table width defined dynamically

• Adding option to add hierarchical summary in output

• Adding batch_size value (when provided) in table footer

• fix bugs