CHANGES
=======

* Synops support for average pooling layers -> Synopcounter now works correctly when average pooling layers are used
* rename input tensor for gpu
* re-add unit-test for normalize\_weights
* add GPU tensor support for normalize\_weights method
* minor documentation typo fixes and some clarifications
* Added test to check on initialization with batch\_size
* wip
* move name\_list acquiring from plot\_comparison() into compare\_activations()
* Fix sinabs.network.Network.plot\_comparison() not work correctly for nested ANN and make it only plot Spiking layers' comparison-plot
* added test
* speeds up total power use using the new method
* added total synops counter that doesnt use pandas
* speeds up pandas use in synops count, big advantage
* Name convert\_torch\_ann
* necessary change in notebook
* updated docs
* added docs
* bug fixed
* synopcounter tests, changed network and from\_torch accordingly
* moved counter function
* SNNSynopCounter class
* Fix from\_torch method when model contains a ReLU that is not child of a Sequential
* m2r changed to m2r2
* swapped dimensions with batch, default batch None
* Documentation added and method name renamed to normalize\_weights
* Smart weight rescaling added
* fixed cuda issues on from torch, added test
* Changed aiCTX references to SynSense
* membrane reset implementation, removed layer name
* Equation rendering in docs fixed
* Doc front page changed to README
* Added documentation pipeline for testing doc generation
* Setup tools integration for sphinx documentation
* Martino added to authors
* Theme changed to rtd
* added a detach() call
* changed network removing no\_grad
* working bptt notebook
* twine deploy conditional on env variable
* Added condition on env variable to pypi\_deploy
* Add another pipeline that shouldn't execute
* WIP bptt notebook
* CI Lint corrections
* Added test for CI pipeline
* Link to contributing.md file fixed
* Description file content type updated
* Description file content type updated
* Update description type to markdown
* Update development status
* Updated Classifiers

v0.2.0
------

* Threshold gradient scaled by threshold (Bug fix)
* updated docs, removed exclude\_negative\_spikes from fromtorch (no effect)
* test requirements separated
* added coverage
* temporary solution for onnx
* temporary solution for onnxruntime
* amended test requirements to include onnxruntime
* trying to trigger CI
* Updated MNIST notebook
* Instructions for testing added
* \_\_version\_\_ specified from pbr
* Cleaned up setup.py and requirements with pbr
* added coverage tools
* removed network utilities not needed
* updated tests using pathlib
* added some network tests
* WIP on functional docstrings
* removed old stuff from network summary
* update gitignore
* notebook docs updated (WIP)
* fix docs for input shape in from\_torch, removed depency of Network on legacy layers
* removed deprecated arguments of from\_torch
* cleaned up keras in docs
* removed input shape from spiking which caused bugs, and output\_shape from inputlayer
* change dummy input to device, calculate layer-wise output size
* Updated URL
* Keras-related stuff all removed
* removed pandas from layers
* Unit test for adding spiking output in 'from\_model'
* Enable adding spiking layer to sequential model in from\_torch function
* Version bump
* removed bad choice
* removed unnecessary calls to print
* fixed bug in old version
* and again
* More updates to deepcopy
* Second deepcopy argument
* Added tentative deepcopy
* added ugly workaround to samna-torch crash problem
* bugfix: reset\_states in network
* Refactored keras\_model -> analog\_model
* Added tool to compute output shapes
* correct device for spiking layers
* added tentative synops support
* version number updated
* updated file paths in tests
* threshold methods updated, onnnx conversion works now
* wip:added test for equivalence
* fixed bug from\_torch was doing nothing
* model build method separately added
* changed default membrane subtract to Threshold, as in IAF. implemented in from\_torch
* updated documentation
* fixed bug in from\_torch; negative spikes no longer supported
* onnx support for threshold operation
* updated test; removed dummy input shape

0.2.0
-----

* install m2r with hotfix for new version of sphinx
* changed membrane\_subtract and reset defaults, some cleanup
* sumpool layer stride is None bug
* added conversion of flatten and linear to convolutions
* SpikingLayer attributes membrane\_subtract and membrane\_reset as properties to avoid that both are None at the same time
* bugfix related to sumpool
* added synopscount to master
* added documentation synopcounter and sumpool
* added new layers to docs
* Added analogue sumpool layer
* added two  layers by qian
* added synoploss and refactored
* added classifiers to setup.py
* fixed typos in setup.py
* updated setup file
* updated branch to master for pypi deployment
* fixed reference to rockpool in tag
* upload to pypi and tags in readme file
* version bump for test
* direct execute with twine
* typo fix
* added tags of the runner
* pypi build triggered on pip branch
* removed trailing line
* added rescaling of biases to from\_torch
* supported avgpool with different kernel sizes
* added some documentation, quantize now does nothing
* fix linear layer and add sumpool layer to from\_torch
* clean up maxpooling2d
* fix maxpooling spike\_count error
* load DynapSumPool and DynapConv2dSynop from pytorch
* added flag to exclude negative spikes
* added support for neuromorphicrelu
* fixes summary
* threshold management in from torch
* functionalities added to torch vonverter
* line-height fixed in h1
