Automatic target layer resolution and support of IS-CAM

This release adds an implementation of IS-CAM and greatly improves interface.

Note: torchcam 0.1.2 requires PyTorch 1.1 or newer.

Highlights

CAMs

Implementation of CAM extractor
New

• Add an IS-CAM implementation #13 (@frgfm)
• Added automatic target layer resolution #32 (@frgfm)

Improvements

• Added support for submodule hooking #21 (@pkmandke)

Fixes

• Fixed hooking mechanism edge case #23 (@frgfm)

Test

Verifications of the package well-being before release
New

• Updated test for torchcam.cams #13, #30 (@frgfm)

Improvements

• Removed pretrained model loading in unittests #25 (@frgfm)
• Switched all models to eval, removed gradient when not required, and changed to simpler models #33 (@frgfm)

Documentation

Online resources for potential users
New

• Added entry for IS-CAM #13, #30 (@frgfm)

Fixes

• Fixed examples in docstrings of gradient-based CAMs #28, #33 (@frgfm)

Others

Other tools and implementations
New

• Added annotation typing to the codebase & mypy verification CI job #19 (@frgfm)
• Added package publishing verification jobs #12 (@frgfm)

Improvements

• Improved example script #15 (@frgfm)
• Optimized CI cache #20 (@frgfm)

Fixes

• Fixed coverage upload job #16 (@frgfm)
• Fixed doc deployment job #24 (@frgfm)
• Fixed conda recipe #29 (@frgfm)