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Description
version: torchinfo 1.8.0 pyhd8ed1ab_0
Describe the solution you'd like
Add the Units alongside MB and GB and choose unit acoording to the best representation one can get.
In the following toy example having MB as unit is not of any help :
==========================================================================================
Layer (type:depth-idx) Output Shape Param #
==========================================================================================
LRBasedClassifier [10, 5] --
├─Linear: 1-1 [10, 5] 125
==========================================================================================
Total params: 125
Trainable params: 125
Non-trainable params: 0
Total mult-adds (Units.MEGABYTES): 0.00
==========================================================================================
Input size (MB): 0.00
Forward/backward pass size (MB): 0.00
Params size (MB): 0.00
Estimated Total Size (MB): 0.00
==========================================================================================
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