CHANGES
=======

* 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
* removed and updated keras tests
* removed summary; device not determined automatically in from\_torch
* removed old tests
* Fixed relative imports
* Added deprecation warning
* Moved layers around, added deprecation
* Moved neuromorphicrelu, quantize, sumpool to separate files, functions to functional
* 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
* added warnings for unsupported operations
* Input shape optional and neurons dynamically allocated
* from\_torch completely rewritten (WIP)
* wip: from\_torch refractoring
* marked all torch layer wrappers to deprecated
* Depricated TorchLayer added
* merged master to bptt\_devel

0.2.0
-----

* install m2r with hotfix for new version of sphinx
* changed membrane\_subtract and reset defaults, some cleanup
* added test to compare iaf implementations
* added dummy test file intended for bptt layer
* sumpool layer stride is None bug
* updated version number
* added support for batch mode operation
* added conversion of flatten and linear to convolutions
* provided default implementation of iaf\_bptt to passthrough
* SpikingLayer with learning added to layers without default import
* SpikingLayer attributes membrane\_subtract and membrane\_reset as properties to avoid that both are None at the same time
* threshold function fix, bptt mnist example with spiking layer in notebook
* threshold functions used in forward iaf method for bptt
* added differentiable threshold functions
* 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
* updated summary function for iaf\_tc
* 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
* ci script to upload to test pypi
* wip: adding pip support for sinabs
* pew workon to pew ls
* added pew to documentation
* updated documentation structure and pipenv tutorial
* fixed missing module sinabs.from\_keras
* fixed tensorflow version 1.15
* fixed tensorflow version in ci script
* added tensorflow install to ci script
* typo fix
* force install torch
* updated documentation for from\_keras
* added pipfile
* moved all from keras methods to from\_keras.py
* added rescaling of biases to from\_torch
* updated notebook with a full run time output
* 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
* added intro to snns notebook documentation
* merge errors fixed in init file
* synops to cpu
* fixes needed for summary and synops
* removed detach()
* all self.spikes\_number are numbers only and detached now
* fixed incorrect variable name for weights
* added SpikingLinearLayer
* doc string corrections
* fixed test following small refactor
* fixed documentation
* allowed threshold\_low setting
* added documentation
* added YOLO layer and converted converter
* converter uses Sequential and Network instead of ModuleList
* merged latest version (PR) or no\_spike\_tracking
* iaf layers do not save spikes
* fixed loss return with flag
* added image to spike conversion layer
* added conv1d to the documentation
* added conv1d layer
* updated notebooks in examples
* conversion from markdown fixed
* added link to gitlab pages in readme
* documentation added to pages
* updated branch for testing and building
* fixed path to build folder
* pip upgrade command missing pip
* added gitlab CI script
* state to cuda device
* license notice updated in setup file
* layers submodule added to setupfile
* fixed calls to np load with allow\_pickle arg
* added contributing file
* added license text to readme
