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* [Bug] fix multiple bugs in JTNN example

* remove debug code

* clean commit

* oops forgot the most important files

* use einsum

* copy feature from frontier to block

* Revert "copy feature from frontier to block"

This reverts commit 5224ec963eb6a3ef1b6ab74d8ecbd44e4e42f285.

* temp fix

* unit test

* fix

* revert jtnn

* lint

* fix win64

* docstring fixes and doc indexing

* revert einsum in sparse bidecoder

* fix some examples

* lint

* fix due to some tediousness in remove_edges

* addresses comments

* fix

* more jtnn fixes

* fix

* jtnn and fixes

* make metagraph a method

* fix test

* fix

* Fix

* Update

* First commit

* Update

* Update splitters

* Update

* Update

* Update

* Update

* Update

* Update

* Migrate ACNN

* Fix

* Fix

* Update

* Update

* Update

* Update

* Update

* Update

* Finish classification

* Update

* Fix

* Update

* Update

* Update

* Fix

* Fix

* Fix

* Update

* Update

* Update

* trigger CI

* Fix CI

* Update

* Update

* Update

* Add default values

* Rename

* Update deprecation message

* Update

* Update

* Update

* Update

* Update

* jtnn model zoo

* poke ci

* fix line sep

* fix

* Fix import order

* fix render

* fix render

* revert

* fix

* Resolve conflict

* dix

* remove create_var

* refactor

* fix

* refactor

* readme

* format

* fix lint

* fix lint

* pylint

* lint

* fix lint

* fix lint

* add hint

* fix

* Remove vocab

* Add explanation for warning

* add directory

* Load model to cpu by default

* Update

* Update prerequisites of README

* dependencies for pytorch models

* dependencies for mxnet models

* minor

* cherry picking optimization from jtnn

* adding official code.  TODO: fix DGLMolTree

* updating to current api.  vae test still failing

* reverting to list stacking

* reverting to list stacking

* cleaning x flags (stupid windows)

* cleaning x flags (stupid windows)

* adding stats

* optimization

* updating dgl stats

* update again

* more optimization

* looks like computation is faster

* removing profiling code

* cleaning obsolete code

* remove comparison warning

* readme update

* official implementation got a lot faster

* minor fixes

* unbatch by slicing frames

* working around unbatch

* reduce pack

* oops

* support frame read/write with slices

* reverting back to readout as unbatch-by-slicing slows down backward

* reverting to unbatch by splitting; slicing is unfriendly to backward

* replacing lru cache with static object factory

* cherry picking optimization from jtnn

* unbatch by slicing frames

* reduce pack

* oops

* support frame read/write with slices

* reverting to unbatch by splitting; slicing is unfriendly to backward

* replacing lru cache with static object factory

* replacing Scheme object with namedtuple

* forgot the find edges interface

* subclassing namedtuple

* updating to the latest api spec

* bugfix

* bfs with edges

* dfs toy test case

* clean up

* style fix

* bugfix

* update to latest api; include traversal

* replacing with readout

* simplify decoder

* oops

* cleanup

* reducing number of sets

* more speed up

* profile results

* random fixes

* fixing tvmarray handling incontiguous dlpack input

* fancier dataloader

* fix a potential context mismatch

* todo: support pickling or using scipy in multiprocessing load

* pickling support

* resorting to suggested way of pickling

* custom attribute pickling check

* working around a weird pytorch pickling bug

* including partial frame case

* enabling multiprocessing dataloader

* pickling everything now

* really works

* oops

* updated profiling results

* cleanup

* fix as requested

* cleaning random blank lines

* removing profiler outputs

* starting decoding

* testing, WIP

* tree decoding

* graph decoding, WIP

* graph decoding works

* oops

* fixing legacy apis

* trimming number of candidate structures

* sampling cleanups

* removing comparison test

* updated description

* junction tree vae example

* added README and moved data to dropbox

* auto download; some fix in python3