moduleprofiler v0.0.4

• Update documentation.
• Add ops estimation for torch.nn.BatchNorm1d and torch.nn.BatchNorm2d.
• Add exclude_from_ops option to ModuleProfiler.
• Fix NaN bit sizes and data types for modules without trainable or nontrainable parameters.

moduleprofiler v0.0.3

• Added torch.nn.LayerNorm reference.
• Update torch.nn.LSTM documentation.
• Fixed torch.nn.LayerNorm estimation.

moduleprofiler v0.0.2

• Updated documentation
• Fixed ConvTranspose1d and ConvTranspose2d overestimation of additions per filter.

moduleprofiler v0.0.1

First release of moduleprofiler, a fee open-source package to profile torch.nn.Module modules and obtain useful information to design a model that fits your needs and constraints at development time.

With moduleprofiler you can:

• Calculate the number of parameters of your model.
• Trace the input and output sizes of each component of your model.
• Estimate the number of operations your model performs in a forward pass.
• Calculate per module and total inference time.

All results can be obtained in one of the following formats:

• dict (default output format)
• pandas.DataFrame (to perform further calculations or filtering in your code)
• html (to export as webpage)
• LaTeX (to include in your publications)

[Online documentation | Tutorial ]