GitLab

* fix

* fix

* fix

* fix

* fix

* 111

* fix

* fix

* fix

* test

* ff

* fix

* ff

* fix

* f

* merge

* fix

* add working scripts

* add frcnn training script

* remove redundent files

* refactor validation computation, will optimize sgdet and training

* validation finally finished

* f-rcnn training

* test reldn

* rm file

* update reldn training

* data preprocess to h5

* temp

* use coco json

* fix conflict

* new obj dataset for detection

* update training

* before cleanup

* remove abundant files

* add arg parse to train

* cleanup code file

* update

* fix

* add readme

* add ipynb as demo

* add demo pic

* update readme

* add demo script

* improve paths

* improve readme

* add docstrings

* fix args description

* update readme

* add models from s3

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

* add gin model

* convert dataset.py to data_ont_the_fly way and put it into dgl.data module

* convert dataset.py to data_ont_the_fly way and put it into dgl.data module
python code checked

* modified document and reference TUDataset; checked python part and bypass cpp part due to error

* change tensor to numpy in dataset and transform in collate@Dataloader

* Change minor format issue

Change minor format issue

* moved logging; adjusted tqdm etc

* fixing builtin src*edge shape mismatch

* bundled function refactor (?)

* fixing names

* readout prototype

* oops

* more fixes

* removing readout prototype

* sum_on() with SPMV, fixing batching with 0 edges

* readouts with segmented sum

* typo (??????)

* fixes NLTK dependency (#125)

* misc fixes including #126 (pushing again)

* sanity check for mxnet

* fixes NLTK dependency (#125) and #126

* reverting to sum_nodes/edges

* model code for generative graphs

* batched version for dynamic graph generation using padding

* renaming function train back to forward

* remove old util function for padding DGMG

* override networkx clear to reset state, add dgl.nn

* Dynamic graph without batching

* use relative import path

* load dataset, pad batch

* bug fix

* experimental batch and unbatch

* dgmg batched version

* minor tweak

* move preprocessing padding into data loading

* batch graph test code

* minor

* batched graph class and test cases

* make dgl.nn.gcn a simple layer plus minor fix

* update dgmg model

* test forward using attribute field

* use frame append, minor changes

* moving networkx operations out of forward

* revert some changes

* remove structural immutability check

* fix edge list order problem in cached graph.

* minor fix

* fix bug in edge iter

* SPMV works

* gcn spmv on CPU

* change gcn style

* fix cached graph performance; fixed gcn dataset bug

* reorg dir

* non-batch spmv; partial update problem with shape change

* fix reorder problem; finish gcn-batch impl

* pop API

* GPU context

Initial example file for ginipath