GitLab

* 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

* WIP

* new at glance

* fix dgmg tutorial indentation

* bug in incidence_matrix docstring

* remove print

* rgcn tutorial

* data processing for rgcn

* many fix

* requirements for rgcn tutorial

* fix comments

* description of rgcn dataset

* author

* bug fix

* move all dataset to s3

* update dgl at a glance

* update title

* Update 1_first.py

* poke ci

* poke again

* force download data everytime

* move file from dropbox to s3

* fix ci and move sst to s3

* remove blank line

* change the signature of node/edge filter

* upd filter

* Support multi-dimension node feature in SPMV

* stable version

* hotfix

* upd tutorial

* upd README

* Fix dataset

* Track data APIs

* Docstring for udf

* Track udf docs

* Improve

* Improved

* Delete udf.py

* Improve

* Update doc

* Update batched_graph.py

* Fix

* Fix

* Fix

* Fix

* fix memory leak & Remove unnecessary initializer

* change confused name

* fix name

* Move func outside loop

* fix name inconsistency

* conda recipe

* switching to source build

* trying windows build

* wip

* windows build works

* DGMG with batch size 1

* Fix

* Adjustment

* Fix

* Fix

* Fix

* Fix

* Fix has_node and __contains__

* Batched implementation for DGMG

* Remove redundant dependency

* Adjustment

* Fix

* Add comments

* [Model]SBM hotfix

* [Model] remove backend in data

* add bdist_wheel build

* fix wheel build

* fix setup

* fix ci

* fix setup

* fix

* fix setup

* poke ci

* fix

* poke ci

* clean build

* fix ci

* addback the env

* Support multi-dimension node feature in SPMV

* fix as requested

* fix recv nodes are all 0deg; fix hybriddict does not through keyerror properly

* fallback to apply_nodes when all nodes are 0deg; WIP on pull spmv 0deg

* new 0deg behavior

* new 0deg behavior

* update mx utest for pull-0deg

* fix mx

* fix mx

* get rid of unnecessary sort-n-unique

* change the signature of node/edge filter

* upd filter

* executor api

* draft executor interface

* WIP

* revert changes to avoid conflict with api change

* core scheduling logic

* WIP: build graph adj

* incidence matrix for in edges

* support incidence matrix for partial recv nodes

* improve

* build adjmat in scheduler

* graph store

* get degree bucketing schedule

* connect to c++ degree bucketing

* conceptual executor creation code

* executor comments

* fix

* more executor comments

* WIP: full send_and_recv schedule

* most schedulers

* simplify scheduler

* executors

* runtime

* builtin function base class

* adj indices and shape

* completely refactor scheduler

* rename and move bundled out to function.py

* use_edge_feature in msg func

* rewrite scheduler

* node edge executor

* connect with graph api

* handle zero degree

* misc

* fix test cases

* fix a good many bugs...

* remove old scheduler

* push and pull

* fix send recv

* c++ lint

* fix batched send recv

* hot fix for mxnet

* typo

* write back executor

* apply node edge

* clean up, doc string

* fix as requested

* refactor

* fix

* WIP

* WIP

* ir draft

* more on ir

* WIP: spmv schedule

* WIP

* recv schedule

* refactor

* WIP

* snr degree bucketing

* snr scheduler

* move prog to graph.py; rename

* unittest for send/recv

* remove some legacy codes

* WIP: update_all

* pass test_basics

* passed all current utests

* more utests; fix mx utest

* WIP: fixing zero deg initial value

* some tests

* fix 0deg problem

* fix mx

* fix mx

* some notes

* fix as requested

* DGMG with batch size 1

* Fix

* Adjustment

* Fix

* Fix

* Fix

* Fix

* move initializer to column scheme; change num rows behavior

* poke mx ci

* fix mx utest in append

* fix bug in add edges

* utest for updating partial rows

* fix bug in from_networkx and from_scipy_matrix

* revert per-col initializer change

* fix pickle utest

* add spmv tests on mxnet.

* test backward.

* add tests for pull.

* use mxnet backend.

* address comment.

* add comments.

* add a test.

* move file.

* debug

* add degree normalization.

* it can converge now.

* remove hidden_data.

* use readonly graph index.

* use subgraph loader.

* refactor code and remove intermediate data.

* split inference.

* mix cpu and gpu training.

* fix mxnet sparse_matrix constructor.

* convert tensor context.

* set up the prediction model.

* load mxnet csr directly.

* add timing.

* move test_sse.py to sse_batch.py

* fix the tensor version of SSE.

* update README.

addresses issue #156

* minor fix

* jake's change

* pickling support

* resorting to suggested way of pickling

* custom attribute pickling check

* working around a weird pytorch pickling bug

* including partial frame case

* pickling everything now

* fix as requested