GitLab

* upd

* upd

* upd

* lint

* fix

* fix test

* fix

* fix

* upd

* upd

* upd

* upd

* upd

* upd

* upd

* upd

* upd

* upd

* upd tutorial

* upd

* upd

* fix kg

* upd doc organization

* refresh test

* upd

* refactor doc

* fix lint
Co-authored-by: Minjie Wang <minjie.wang@nyu.edu>

* 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

* upd

* upd

* upd

* upd

* lint

* upd

* upd

* upd

* upd
Co-authored-by: VoVAllen <VoVAllen@users.noreply.github.com>

* API change of kvstore

* add demo for kvstore

* update

* remove duplicated log

* change queue size

* update

* update

* update

* update

* update

* update

* update

* update

* update

* fix lint

* change name

* update

* fix lint

* update

* update

* update

* update

* change message queue size to a python argument

* change default queue size to 2GB

* OMP_NUM_THREADS=1

* add multiple NICs support for kvstore

* test

* fix lint

* update

* update

* update

* update

* update

* update

* update

* fix lint

* fix lint

* update

* update

* update

* update

* change ci image

* fix

* force bash

* fix

* fix python version

* fix

* fix

* fix

* update gpu

* cuda

* jenkins

* fix build sh

* fix

* Revert "fix"

This reverts commit 6b091914b3ef6b4300fa662ee375aa4b27944f5c.

* try fix

* fix

* Revert "fix"

This reverts commit e42c3035fa4974c6b197aaba0748f7b45113ddaa.

* try fix

* fix

* fix

* fix

* fix

* fix

* fix

* fix tests

* try fix

* fix

* fix

* fix

* fix

* fix

* fix

* fix ctx problem

* fix many tests

* fix typo

* add backend

* move to pytorch folder

* fix?

* fix ci

* try skip

* try false

* try?

* try?

* Revert to 7d9a52f

* fix various

* fix lint

* Revert Jenkinsfile

* revert env

* revert env

* address comment

* remove file

* upd

* damn it

* fuck

* fuck pylint

* fudge

* remove some comments about MXNet

* upd

* upd

* damn it

* damn it

* fuck

* fuck

* upd

* upd

* pylint bastard

* upd

* upd

* upd

* upd

* upd

* upd

* upd

* upd

* upd

* upd

* add test

* fix

* upd

* merge

* hotfix

* upd

* fix

* upd

* fig edgebatch edges

* add test

* trigger

* Update README.md for pytorch PinSage example.

Add noting that the PinSage model example under
example/pytorch/recommendation only work with Python 3.6+
as its dataset loader depends on stanfordnlp package
which work only with Python 3.6+.

* Provid a frame agnostic API to test nn modules on both CPU and CUDA side.

1. make dgl.nn.xxx frame agnostic
2. make test.backend include dgl.nn modules
3. modify test_edge_softmax of test/mxnet/test_nn.py and
    test/pytorch/test_nn.py work on both CPU and GPU

* Fix style

* Delete unused code

* Make agnostic test only related to tests/backend

1. clear all agnostic related code in dgl.nn
2. make test_graph_conv agnostic to cpu/gpu

* Fix code style

* fix

* doc

* Make all test code under tests.mxnet/pytorch.test_nn.py
work on both CPU and GPU.

* Fix syntex

* Remove rand

* Add TAGCN nn.module and example

* Now tagcn can run on CPU.

* Add unitest for TGConv

* Fix style

* For pubmed dataset, using --lr=0.005 can achieve better acc

* Fix style

* Fix some descriptions

* trigger

* Fix doc

* Add nn.TGConv and example

* Fix bug

* Update data in mxnet.tagcn test acc.

* Fix some comments and code

* delete useless code

* Fix namming

* Fix bug

* Fix bug

* Add test code for mxnet TAGCov

* Update some docs

* Fix some code

* Update docs dgl.nn.mxnet

* Update weight init

* Fix

* refactor

* upd mpnn

* gat

* upd

* upd sage

* upd

* upd

* upd

* upd

* upd

* add gmmconv

* upd ggnn

* upd

* upd

* upd

* upd

* add citation examples

* add README

* fix cheb

* improve doc

* formula

* upd

* trigger

* lint

* lint

* upd

* add test for transform

* add test

* check

* upd

* improve doc

* shape check

* upd

* densechebconv, currently not correct (?)

* fix cheb

* fix

* upd

* upd sgc-reddit

* upd

* trigger

* upd

* fig edgebatch edges

* add test

* trigger

* Update README.md for pytorch PinSage example.

Add noting that the PinSage model example under
example/pytorch/recommendation only work with Python 3.6+
as its dataset loader depends on stanfordnlp package
which work only with Python 3.6+.

* Provid a frame agnostic API to test nn modules on both CPU and CUDA side.

1. make dgl.nn.xxx frame agnostic
2. make test.backend include dgl.nn modules
3. modify test_edge_softmax of test/mxnet/test_nn.py and
    test/pytorch/test_nn.py work on both CPU and GPU

* Fix style

* Delete unused code

* Make agnostic test only related to tests/backend

1. clear all agnostic related code in dgl.nn
2. make test_graph_conv agnostic to cpu/gpu

* Fix code style

* fix

* doc

* Make all test code under tests.mxnet/pytorch.test_nn.py
work on both CPU and GPU.

* Fix syntex

* Remove rand

* Add TAGCN nn.module and example

* Now tagcn can run on CPU.

* Add unitest for TGConv

* Fix style

* For pubmed dataset, using --lr=0.005 can achieve better acc

* Fix style

* Fix some descriptions

* trigger

* Fix doc

* rgcn module

* support id input

* WIP: model codes

* use faster index select

* dropout

* self loop

* WIP: link prediction

* fix lint

* WIP: docs

* docstring

* docstring

* merge two child classes

* mxnet rgcn module

* fix lint

* fix lint

* fix rename bug

* add uniform edge sampler

* fix fn name

* docstring

* fix mxnet rgcn module

* fix mx rgcn

* enable test on cuda

* upd

* fig edgebatch edges

* add test

* trigger

* Update README.md for pytorch PinSage example.

Add noting that the PinSage model example under
example/pytorch/recommendation only work with Python 3.6+
as its dataset loader depends on stanfordnlp package
which work only with Python 3.6+.

* Provid a frame agnostic API to test nn modules on both CPU and CUDA side.

1. make dgl.nn.xxx frame agnostic
2. make test.backend include dgl.nn modules
3. modify test_edge_softmax of test/mxnet/test_nn.py and
    test/pytorch/test_nn.py work on both CPU and GPU

* Fix style

* Delete unused code

* Make agnostic test only related to tests/backend

1. clear all agnostic related code in dgl.nn
2. make test_graph_conv agnostic to cpu/gpu

* Fix code style

* fix

* doc

* Make all test code under tests.mxnet/pytorch.test_nn.py
work on both CPU and GPU.

* Fix syntex

* Remove rand

* removal doc

* glob

* upd

* rm knn

* add softmax

* upd

* upd

* add broadcast and s2s

* optimize max_on

* forsaken changes to heterograph

* upd

* upd

* upd

* upd

* upd

* bugfix

* upd

* upd

* upd

* upd

* format upd

* upd format

* upd doc

* upd

* import order

* upd

* rm warnings

* fix

* upd test

* upd

* upd

* fix device

* upd

* upd

* upd

* upd

* remove 1.1

* upd

* trigger

* trigger

* add more tests

* fix device

* upd

* upd

* refactor

* fix?

* fix

* upd docstring

* refactor

* upd

* fix

* upd

* upd

* upd

* fix

* upd docs

* add shape

* refactor & upd doc

* upd doc

* upd

* add local scope function

* fix lint

* fix docstring

* change local_scope to local_var; add context manager

* address comments

* upd

* Add stronger test

* Update test_nn.py

* Update test_nn.py

* trigger

* trigger

* trigger

* fix gat code to use latest edge softmax module

* avoid transpose

* update README

* use edge_softmax op

* mxnet edge softmax op

* mxnet gat

* update README

* fix unittest

* fix ci

* fix mxnet nn test; relax criteria for prod reducer

* [Kernel] Minigun integration and fused kernel support (#519)

* kernel interface

* add minigun

* Add cuda build

* functors

* working on binary elewise

* binary reduce

* change kernel interface

* WIP

* wip

* fix minigun

* compile

* binary reduce kernels

* compile

* simple test passed

* more reducers

* fix thrust problem

* fix cmake

* fix cmake; add proper guard for atomic

* WIP: bcast

* WIP

* bcast kernels

* update to new minigun pass-by-value practice

* broadcasting dim

* add copy src and copy edge

* fix linking

* fix none array problem

* fix copy edge

* add device_type and device_id to backend operator

* cache csr adj, remove cache for adjmat and incmat

* custom ops in backend and pytorch impl

* change dgl-mg kernel python interface

* add id_mapping var

* clean up plus v2e spmv schedule

* spmv schedule & clean up fall back

* symbolic message and reduce func, remove bundle func

* new executors

* new backend interface for dgl kernels and pytorch impl

* minor fix

* fix

* fix docstring, comments, func names

* nodeflow

* fix message id mapping and bugs...

* pytorch test case & fix

* backward binary reduce

* fix bug

* WIP: cusparse

* change to int32 csr for cusparse workaround

* disable cusparse

* change back to int64

* broadcasting backward

* cusparse; WIP: add rev_csr

* unit test for kernels

* pytorch backward with dgl kernel

* edge softmax

* fix backward

* improve softmax

* cache edge on device

* cache mappings on device

* fix partial forward code

* cusparse done

* copy_src_sum with cusparse

* rm id getter

* reduce grad for broadcast

* copy edge reduce backward

* kernel unit test for broadcasting

* full kernel unit test

* add cpu kernels

* edge softmax unit test

* missing ref

* fix compile and small bugs

* fix bug in bcast

* Add backward both

* fix torch utests

* expose infershape

* create out tensor in python

* fix c++ lint

* [Kernel] Add GPU utest and kernel utest (#524)

* fix gpu utest

* cuda utest runnable

* temp disable test nodeflow; unified test for kernel

* cuda test kernel done

* [Kernel] Update kernel branch (#550)

* [Model] add multiprocessing training with sampling. (#484)

* reorganize sampling code.

* add multi-process training.

* speed up gcn_cv

* fix graphsage_cv.

* add new API in graph store.

* update barrier impl.

* support both local and distributed training.

* fix multiprocess train.

* fix.

* fix barrier.

* add script for loading data.

* multiprocessing sampling.

* accel training.

* replace pull with spmv for speedup.

* nodeflow copy from parent with context.

* enable GPU.

* fix a bug in graph store.

* enable multi-GPU training.

* fix lint.

* add comments.

* rename to run_store_server.py

* fix gcn_cv.

* fix a minor bug in sampler.

* handle error better in graph store.

* improve graphsage_cv for distributed mode.

* update README.

* fix.

* update.

* [Tutorial] add sampling tutorial. (#522)

* add sampling tutorial.

* add readme

* update author list.

* fix indent in the code.

* rename the file.

* update tutorial.

* fix the last API.

* update image.

* [BUGFIX] fix the problems in the sampling tutorial. (#523)

* add index.

* update.

* update tutorial.

* fix gpu utest

* cuda utest runnable

* temp disable test nodeflow; unified test for kernel

* cuda test kernel done

* Fixing typo in JTNN after interface change (#536)

* [BugFix] Fix getting src and dst id of ALL edges in NodeFlow.apply_block (#515)

* [Bug Fix] Fix inplace op at backend (#546)

* Fix inplace operation

* fix line seprator

* [Feature] Add batch and unbatch for immutable graph (#539)

* Add batch and unbatch for immutable graph

* fix line seprator

* fix lintr

* remove unnecessary include

* fix code review

* [BUGFix] Improve multi-processing training (#526)

* fix.

* add comment.

* remove.

* temp fix.

* initialize for shared memory.

* fix graphsage.

* fix gcn.

* add more unit tests.

* add more tests.

* avoid creating shared-memory exclusively.

* redefine remote initializer.

* improve initializer.

* fix unit test.

* fix lint.

* fix lint.

* initialize data in the graph store server properly.

* fix test.

* fix test.

* fix test.

* small fix.

* add comments.

* cleanup server.

* test graph store with a random port.

* print.

* print to stderr.

* test1

* test2

* remove comment.

* adjust the initializer signature.

* [API] update graph store API. (#549)

* add init_ndata and init_edata in DGLGraph.

* adjust SharedMemoryGraph API.

* print warning.

* fix comment.

* update example

* fix.

* fix examples.

* add unit tests.

* add comments.

* [Refactor] Immutable graph index (#543)

* WIP

* header

* WIP .cc

* WIP

* transpose

* wip

* immutable graph .h and .cc

* WIP: nodeflow.cc

* compile

* remove all tmp dl managed ctx; they caused refcount issue

* one simple test

* WIP: testing

* test_graph

* fix graph index

* fix bug in sampler; pass pytorch utest

* WIP on mxnet

* fix lint

* fix mxnet unittest w/ unfortunate workaround

* fix msvc

* fix lint

* SliceRows and test_nodeflow

* resolve reviews

* resolve reviews

* try fix win ci

* try fix win ci

* poke win ci again

* poke

* lazy multigraph flag; stackoverflow error

* revert node subgraph test

* lazy object

* try fix win build

* try fix win build

* poke ci

* fix build script

* fix compile

* add a todo

* fix reviews

* fix compile

* [Kernel] Update kernel branch (#576)

* [Model] add multiprocessing training with sampling. (#484)

* reorganize sampling code.

* add multi-process training.

* speed up gcn_cv

* fix graphsage_cv.

* add new API in graph store.

* update barrier impl.

* support both local and distributed training.

* fix multiprocess train.

* fix.

* fix barrier.

* add script for loading data.

* multiprocessing sampling.

* accel training.

* replace pull with spmv for speedup.

* nodeflow copy from parent with context.

* enable GPU.

* fix a bug in graph store.

* enable multi-GPU training.

* fix lint.

* add comments.

* rename to run_store_server.py

* fix gcn_cv.

* fix a minor bug in sampler.

* handle error better in graph store.

* improve graphsage_cv for distributed mode.

* update README.

* fix.

* update.

* [Tutorial] add sampling tutorial. (#522)

* add sampling tutorial.

* add readme

* update author list.

* fix indent in the code.

* rename the file.

* update tutorial.

* fix the last API.

* update image.

* [BUGFIX] fix the problems in the sampling tutorial. (#523)

* add index.

* update.

* update tutorial.

* fix gpu utest

* cuda utest runnable

* temp disable test nodeflow; unified test for kernel

* cuda test kernel done

* Fixing typo in JTNN after interface change (#536)

* [BugFix] Fix getting src and dst id of ALL edges in NodeFlow.apply_block (#515)

* [Bug Fix] Fix inplace op at backend (#546)

* Fix inplace operation

* fix line seprator

* [Feature] Add batch and unbatch for immutable graph (#539)

* Add batch and unbatch for immutable graph

* fix line seprator

* fix lintr

* remove unnecessary include

* fix code review

* [BUGFix] Improve multi-processing training (#526)

* fix.

* add comment.

* remove.

* temp fix.

* initialize for shared memory.

* fix graphsage.

* fix gcn.

* add more unit tests.

* add more tests.

* avoid creating shared-memory exclusively.

* redefine remote initializer.

* improve initializer.

* fix unit test.

* fix lint.

* fix lint.

* initialize data in the graph store server properly.

* fix test.

* fix test.

* fix test.

* small fix.

* add comments.

* cleanup server.

* test graph store with a random port.

* print.

* print to stderr.

* test1

* test2

* remove comment.

* adjust the initializer signature.

* [API] update graph store API. (#549)

* add init_ndata and init_edata in DGLGraph.

* adjust SharedMemoryGraph API.

* print warning.

* fix comment.

* update example

* fix.

* fix examples.

* add unit tests.

* add comments.

* [Refactor] Immutable graph index (#543)

* WIP

* header

* WIP .cc

* WIP

* transpose

* wip

* immutable graph .h and .cc

* WIP: nodeflow.cc

* compile

* remove all tmp dl managed ctx; they caused refcount issue

* one simple test

* WIP: testing

* test_graph

* fix graph index

* fix bug in sampler; pass pytorch utest

* WIP on mxnet

* fix lint

* fix mxnet unittest w/ unfortunate workaround

* fix msvc

* fix lint

* SliceRows and test_nodeflow

* resolve reviews

* resolve reviews

* try fix win ci

* try fix win ci

* poke win ci again

* poke

* lazy multigraph flag; stackoverflow error

* revert node subgraph test

* lazy object

* try fix win build

* try fix win build

* poke ci

* fix build script

* fix compile

* add a todo

* fix reviews

* fix compile

* all demo use python-3 (#555)

* [DEMO] Reproduce numbers of distributed training in AMLC giant graph paper (#556)

* update

* update

* update

* update num_hops

* fix bug

* update

* report numbers of distributed training in AMLC giant graph paper

* [DEMO] Remove duplicate code for sampling (#557)

* update

* update

* re-use single-machine code

* update

* use relative path

* update

* update

* update

* add __init__.py

* add __init__.py

* import sys, os

* fix typo

* update

* [Perf] Improve performance of graph store. (#554)

* fix.

* use inplace.

* move to shared memory graph store.

* fix.

* add more unit tests.

* fix.

* fix test.

* fix test.

* disable test.

* fix.

* [BUGIFX] fix a bug in edge_ids (#560)

* add test.

* fix compute.

* fix test.

* turn on test.

* fix a bug.

* add test.

* fix.

* disable test.

* [DEMO] Add Pytorch demo for distributed sampler (#562)

* update

* update

* update

* add sender

* update

* remove duplicate cpde

* [Test] Add gtest to project (#547)

* add gtest module

* add gtest

* fix

* Update CMakeLists.txt

* Update README.md

* [Perf] lazily create msg_index. (#563)

* lazily create msg_index.

* update test.

* [BUGFIX] fix bugs for running GCN on giant graphs. (#561)

* load mxnet csr.

* enable load large csr.

* fix

* fix.

* fix int overflow.

* fix test.

* [BugFix] Fix error when bfs_level = 0 in Entity Classification with RGCN (#559)

* [DEMO] Update demo of distributed sampler (#564)

* update

* update

* update demo

* add network cpp test (#565)

* Add unittest for C++ RPC (#566)

* [CI] Fix CI for cpp test (#570)

* fix CI for cpp test

* update port number

* [Docker] update docker image (#575)

* update docker image

* specify lint version

* rm torch import from unified tests

* [Kernel][Scheduler][MXNet] Scheduler for DGL kernels and MXNet backend support (#541)

* [Model] add multiprocessing training with sampling. (#484)

* reorganize sampling code.

* add multi-process training.

* speed up gcn_cv

* fix graphsage_cv.

* add new API in graph store.

* update barrier impl.

* support both local and distributed training.

* fix multiprocess train.

* fix.

* fix barrier.

* add script for loading data.

* multiprocessing sampling.

* accel training.

* replace pull with spmv for speedup.

* nodeflow copy from parent with context.

* enable GPU.

* fix a bug in graph store.

* enable multi-GPU training.

* fix lint.

* add comments.

* rename to run_store_server.py

* fix gcn_cv.

* fix a minor bug in sampler.

* handle error better in graph store.

* improve graphsage_cv for distributed mode.

* update README.

* fix.

* update.

* [Tutorial] add sampling tutorial. (#522)

* add sampling tutorial.

* add readme

* update author list.

* fix indent in the code.

* rename the file.

* update tutorial.

* fix the last API.

* update image.

* [BUGFIX] fix the problems in the sampling tutorial. (#523)

* add index.

* update.

* update tutorial.

* fix gpu utest

* cuda utest runnable

* temp disable test nodeflow; unified test for kernel

* cuda test kernel done

* edge softmax module

* WIP

* Fixing typo in JTNN after interface change (#536)

* mxnet backend support

* improve reduce grad

* add max to unittest backend

* fix kernel unittest

* [BugFix] Fix getting src and dst id of ALL edges in NodeFlow.apply_block (#515)

* lint

* lint

* win build

* [Bug Fix] Fix inplace op at backend (#546)

* Fix inplace operation

* fix line seprator

* [Feature] Add batch and unbatch for immutable graph (#539)

* Add batch and unbatch for immutable graph

* fix line seprator

* fix lintr

* remove unnecessary include

* fix code review

* [BUGFix] Improve multi-processing training (#526)

* fix.

* add comment.

* remove.

* temp fix.

* initialize for shared memory.

* fix graphsage.

* fix gcn.

* add more unit tests.

* add more tests.

* avoid creating shared-memory exclusively.

* redefine remote initializer.

* improve initializer.

* fix unit test.

* fix lint.

* fix lint.

* initialize data in the graph store server properly.

* fix test.

* fix test.

* fix test.

* small fix.

* add comments.

* cleanup server.

* test graph store with a random port.

* print.

* print to stderr.

* test1

* test2

* remove comment.

* adjust the initializer signature.

* try

* fix

* fix

* fix

* fix

* fix

* try

* test

* test

* test

* try

* try

* try

* test

* fix

* try gen_target

* fix gen_target

* fix msvc var_args expand issue

* fix

* [API] update graph store API. (#549)

* add init_ndata and init_edata in DGLGraph.

* adjust SharedMemoryGraph API.

* print warning.

* fix comment.

* update example

* fix.

* fix examples.

* add unit tests.

* add comments.

* [Refactor] Immutable graph index (#543)

* WIP

* header

* WIP .cc

* WIP

* transpose

* wip

* immutable graph .h and .cc

* WIP: nodeflow.cc

* compile

* remove all tmp dl managed ctx; they caused refcount issue

* one simple test

* WIP: testing

* test_graph

* fix graph index

* fix bug in sampler; pass pytorch utest

* WIP on mxnet

* fix lint

* fix mxnet unittest w/ unfortunate workaround

* fix msvc

* fix lint

* SliceRows and test_nodeflow

* resolve reviews

* resolve reviews

* try fix win ci

* try fix win ci

* poke win ci again

* poke

* lazy multigraph flag; stackoverflow error

* revert node subgraph test

* lazy object

* try fix win build

* try fix win build

* poke ci

* fix build script

* fix compile

* add a todo

* fix reviews

* fix compile

* WIP

* WIP

* all demo use python-3 (#555)

* ToImmutable and CopyTo

* [DEMO] Reproduce numbers of distributed training in AMLC giant graph paper (#556)

* update

* update

* update

* update num_hops

* fix bug

* update

* report numbers of distributed training in AMLC giant graph paper

* [DEMO] Remove duplicate code for sampling (#557)

* update

* update

* re-use single-machine code

* update

* use relative path

* update

* update

* update

* add __init__.py

* add __init__.py

* import sys, os

* fix typo

* update

* [Perf] Improve performance of graph store. (#554)

* fix.

* use inplace.

* move to shared memory graph store.

* fix.

* add more unit tests.

* fix.

* fix test.

* fix test.

* disable test.

* fix.

* [BUGIFX] fix a bug in edge_ids (#560)

* add test.

* fix compute.

* fix test.

* turn on test.

* fix a bug.

* add test.

* fix.

* disable test.

* DGLRetValue DGLContext conversion

* [DEMO] Add Pytorch demo for distributed sampler (#562)

* update

* update

* update

* add sender

* update

* remove duplicate cpde

* [Test] Add gtest to project (#547)

* add gtest module

* add gtest

* fix

* Update CMakeLists.txt

* Update README.md

* Add support to convert immutable graph to 32 bits

* [Perf] lazily create msg_index. (#563)

* lazily create msg_index.

* update test.

* fix binary reduce following new minigun template

* enable both int64 and int32 kernels

* [BUGFIX] fix bugs for running GCN on giant graphs. (#561)

* load mxnet csr.

* enable load large csr.

* fix

* fix.

* fix int overflow.

* fix test.

* new kernel interface done for CPU

* docstring

* rename & docstring

* copy reduce and backward

* [BugFix] Fix error when bfs_level = 0 in Entity Classification with RGCN (#559)

* [DEMO] Update demo of distributed sampler (#564)

* update

* update

* update demo

* adapt cuda kernels to the new interface

* add network cpp test (#565)

* fix bug

* Add unittest for C++ RPC (#566)

* [CI] Fix CI for cpp test (#570)

* fix CI for cpp test

* update port number

* [Docker] update docker image (#575)

* update docker image

* specify lint version

* rm torch import from unified tests

* remove pytorch-specific test_function

* fix unittest

* fix

* fix unittest backend bug in converting tensor to numpy array

* fix

* mxnet version

* [BUGFIX] fix for MXNet 1.5. (#552)

* remove clone.

* turn on numpy compatible.

* Revert "remove clone."

This reverts commit 17bbf76ed72ff178df6b3f35addc428048672457.

* revert format changes

* fix mxnet api name

* revert mistakes in previous revert

* roll back CI to 20190523 build

* fix unittest

* disable test_shared_mem_store.py for now

* remove mxnet/test_specialization.py

* sync win64 test script

* fix lowercase

* missing backend in gpu unit test

* transpose to get forward graph

* pass update all

* add sanity check

* passing test_specialization.py

* fix and pass test_function

* fix check

* fix pytorch softmax

* mxnet kernels

* c++ lint

* pylint

* try

* win build

* fix

* win

* ci enable gpu build

* init submodule recursively

* backend docstring

* try

* test win dev

* doc string

* disable pytorch test_nn

* try to fix windows issue

* bug fixed, revert changes

* [Test] fix CI. (#586)

* disable unit test in mxnet tutorial.

* retry socket connection.

* roll back to set_np_compat

* try to fix multi-processing test hangs when it fails.

* fix test.

* fix.

* doc string

* doc string and clean up

* missing field in ctypes

* fix node flow schedule and unit test

* rename

* pylint

* copy from parent default context

* fix unit test script

* fix

* demo bug in nodeflow gpu test

* [Kernel][Bugfix] fix nodeflow bug (#604)

* fix nodeflow bug

* remove debug code

* add build gtest option

* fix cmake; fix graph index bug in spmv.py

* remove clone

* fix div rhs grad bug

* [Kernel] Support full builtin method, edge softmax and unit tests (#605)

* add full builtin support

* unit test

* unit test backend

* edge softmax

* apply edge with builtin

* fix kernel unit test

* disable mxnet test_shared_mem_store

* gen builtin reduce

* enable mxnet gpu unittest

* revert some changes

* docstring

* add note for the hack

* [Kernel][Unittest][CI] Fix MXNet GPU CI (#607)

* update docker image for MXNet GPU CI

* force all dgl graph input and output on CPU

* fix gpu unittest

* speedup compilation

* add some comments

* lint

* add more comments

* fix as requested

* add some comments

* comment

* lint

* lint

* update pylint

* fix as requested

* lint

* lint

* lint

* docstrings of python DGL kernel entries

* disable lint warnings on arguments in kernel.py

* fix docstring in scheduler

* fix some bug in unittest; try again

* Revert "Merge branch 'kernel' of github.com:zzhang-cn/dgl into kernel"

This reverts commit 1d2299e68b004182ea6130b088de1f1122b18a49, reversing
changes made to ddc97fbf1bec2b7815c0da7c74f7ecb2f428889b.

* Revert "fix some bug in unittest; try again"

This reverts commit ddc97fbf1bec2b7815c0da7c74f7ecb2f428889b.

* more comprehensive kernel test

* remove shape check in test_specialization

* fix bug in pickling

* fix lint

* refactor graph conv

* docs & tests

* fix lint

* fix lint

* fix lint

* fix lint script

* fix lint

* Update

* Style fix

* Fix style

* Fix style

* Fix gpu case

* Fix for gpu case

* Hotfix edgesoftmax docs

* Handle repeated features

* Add docstring

* Set default arguments

* Remove dropout from nn.conv

* Fix

* add util fn for renaming

* revert gcn_spmv.py

* mx folder

* fix wierd bug

* fix mx

* fix lint

* test basics

* batched graph & filter, mxnet filter fix

* frame and function; bugfix

* test graph adj and inc matrices

* fixing start = 0 for mxnet

* test index

* inplace update & line graph

* multi send recv

* more tests

* oops

* more tests

* removing old test files; readonly graphs for mxnet still kept

* modifying test scripts

* adding a placeholder for pytorch to reserve directory

* torch 0.4.1 compat fixes

* moving backend out of compute to avoid nose detection

* tests guide

* mx sparse-to-dense/sparse-to-numpy is buggy

* oops

* contribution guide for unit tests

* printing incmat

* printing dlpack

* small push

* typo

* fixing duplicate entries that causes undefined behavior

* move equal comparison to backend

* reverse a graph

* Reverse a graph

* Fix

* Revert "Fix"

This reverts commit 1728826b4f3a083b76dfc0fdecd2bbf943a971b2.

* Fix

* Fix

* Delete vcs.xml

* Delete Project_Default.xml

* Fix

* Fix

* Fix

* Remove outdated test

* Reorg transform and update reverse (#2)

* Reorg transform and update reverse

* Fix doc and test

* Update test

* Resolve conflict

* CI oriented fix

* Remove outdated import

* Fix import

* Fix import

* define __all__ for wildcard imports

* Fix import

* Address circular imports

* Fix

* Fix test case

* Fix

* Fix

* Remove unused import

* Fix

* Fix

* Fix

* fix lint for graph_index.py

* pylint for base.py

* pylint for batched_graph.py

* pylint for frame.py; simplify and fix bugs in frame when index is slice type

* pylint for graph.py

* pylint for immutable_graph_index.py

* pylint for init.py

* pylint for rest files in root package

* pylint for _ffi package

* pylint for function package

* pylint for runtime package

* pylint for runtime.ir package

* add pylint to ci

* fix mx tests

* fix lint errors

* fix ci

* fix as requested

* fix lint

* fix bug: frame append should check itself

* more test case

* fix multi-send-recv bug

* remv msg graph and clean up

* test cases

* more test case

* fix for batchedgraph

* fix bugs: converting from a graph with edges

* fix

* add more operators to utils.Index

* clear frame executor

* change message indicator to a graph level index

* fix test cases

* guard the case that mxnet does not support concat zero shape tensor

* fix bug: avoid convert full slice to numpy

* test multi-send-recv after conversion

* fix as request (partially)

* add dtype, ctx to full_1d

* add slice data to utils.Index

* fix

* more doc string

* fix as requested

* Jenkins build & test on Windows

* oops

* still running nohup on Windows slaves

* ooops again

* squishing vcvars and cmake

* another try

* reverting back

* --user

* switching to msbuild

* made the graph size in cache testing bigger

* put commands into script files

* oooops

* add cache to adj and incmat

* Fix bug in cached adj/inc

* mx gcn spmv runnable; acc debugging...

* fix bug in mx gcn that loss is not correctly calculated

* fix mx utest

* fix as requested

* use raw parameter tensors rather than dense layer

* fix dropout

* Add numbers in readme

* 0.1.2 release

* oops

* more fixes on windows

* [Bugfix] fix download dir (#275)

* fix download dir

* add doc for the env var

* windows 7 -> 10

* doc update

* [Bugfix] Fix conversion from networkx (#286)

* fix from_nx when no edge id available

* add test cases

* more detailed tests

* more comments

* [Bugfix] Switch to sparse_coo_matrix for torch 1.0+ (#282)

* switch to sparse_coo_matrix for torch 1.0+

* fix bug when the version is 0.4.1.post2

* change to distutils

* change Index.tolist -> Index.tonumpy; fix bug in traversal; remove dependencies in data

* fix import

* fix __all__ and some docstring

* copy feature to networkx

* fix to_network for multi-graph

* test case for nx conversion

* iterate over Index returns plain int instead of numpy.int64

* fix from_network multi-edge bug

* inplace write row op and executor

* update scheduler and graph to use inplace write

* fix

* fix bug

* test case for inplace

* fix bugs for inplace apply node/edge

* fix comments

* th.allclose -> U.allclose

* 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

* 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

addresses issue #156

* 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