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Mufei Li e452179c88 [Deprecation] Dataset Attributes (#4666)
* Update from master (#4584)

* [Example][Refactor] Refactor graphsage multigpu and full-graph example (#4430)

* Add refactors for multi-gpu and full-graph example

* Fix format

* Update

* Update

* Update

* [Cleanup] Remove async_transferer (#4505)

* Remove async_transferer

* remove test

* Remove AsyncTransferer

Co-authored-by: Xin Yao <xiny@nvidia.com>
Co-authored-by: Xin Yao <yaox12@outlook.com>

* [Cleanup] Remove duplicate entries of CUB submodule   (issue# 4395) (#4499)

* remove third_part/cub

* remove from third_party

Co-authored-by: Israt Nisa <nisisrat@amazon.com>
Co-authored-by: Xin Yao <xiny@nvidia.com>

* [Bug] Enable turn on/off libxsmm at runtime (#4455)

* enable turn on/off libxsmm at runtime by adding a global config and related API


Co-authored-by: Ubuntu <ubuntu@ip-172-31-19-194.ap-northeast-1.compute.internal>

* [Feature] Unify the cuda stream used in core library (#4480)

* Use an internal cuda stream for CopyDataFromTo

* small fix white space

* Fix to compile

* Make stream optional in copydata for compile

* fix lint issue

* Update cub functions to use internal stream

* Lint check

* Update CopyTo/CopyFrom/CopyFromTo to use internal stream

* Address comments

* Fix backward CUDA stream

* Avoid overloading CopyFromTo()

* Minor comment update

* Overload copydatafromto in cuda device api

Co-authored-by: xiny <xiny@nvidia.com>

* [Feature] Added exclude_self and output_batch to knn graph construction (Issues #4323 #4316) (#4389)

* * Added "exclude_self" and "output_batch" options to knn_graph and segmented_knn_graph
* Updated out-of-date comments on remove_edges and remove_self_loop, since they now preserve batch information

* * Changed defaults on new knn_graph and segmented_knn_graph function parameters, for compatibility; pytorch/test_geometry.py was failing

* * Added test to ensure dgl.remove_self_loop function correctly updates batch information

* * Added new knn_graph and segmented_knn_graph parameters to dgl.nn.KNNGraph and dgl.nn.SegmentedKNNGraph

* * Formatting

* * Oops, I missed the one in segmented_knn_graph when I fixed the similar thing in knn_graph

* * Fixed edge case handling when invalid k specified, since it still needs to be handled consistently for tests to pass
* Fixed context of batch info, since it must match the context of the input position data for remove_self_loop to succeed

* * Fixed batch info resulting from knn_graph when output_batch is true, for case of 3D input tensor, representing multiple segments

* * Added testing of new exclude_self and output_batch parameters on knn_graph and segmented_knn_graph, and their wrappers, KNNGraph and SegmentedKNNGraph, into the test_knn_cuda test

* * Added doc comments for new parameters

* * Added correct handling for uncommon case of k or more coincident points when excluding self edges in knn_graph and segmented_knn_graph
* Added test cases for more than k coincident points

* * Updated doc comments for output_batch parameters for clarity

* * Linter formatting fixes

* * Extracted out common function for test_knn_cpu and test_knn_cuda, to add the new test cases to test_knn_cpu

* * Rewording in doc comments

* * Removed output_batch parameter from knn_graph and segmented_knn_graph, in favour of always setting the batch information, except in knn_graph if x is a 2D tensor

Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>

* [CI] only known devs are authorized to trigger CI (#4518)

* [CI] only known devs are authorized to trigger CI

* fix if author is null

* add comments

* [Readability] Auto fix setup.py and update-version.py (#4446)

* Auto fix update-version

* Auto fix setup.py

* Auto fix update-version

* Auto fix setup.py

* [Doc] Change random.py to random_partition.py in guide on distributed partition pipeline (#4438)

* Update distributed-preprocessing.rst

* Update

Co-authored-by: Ubuntu <ubuntu@ip-172-31-9-26.ap-northeast-1.compute.internal>

* fix unpinning when tensoradaptor is not available (#4450)

* [Doc] fix print issue in tutorial (#4459)

* [Example][Refactor] Refactor RGCN example (#4327)

* Refactor full graph entity classification

* Refactor rgcn with sampling

* README update

* Update

* Results update

* Respect default setting of self_loop=false in entity.py

* Update

* Update README

* Update for multi-gpu

* Update

* [doc] fix invalid link in user guide (#4468)

* [Example] directional_GSN for ogbg-molpcba (#4405)

* version-1

* version-2

* version-3

* update examples/README

* Update .gitignore

* update performance in README, delete scripts

* 1st approving review

* 2nd approving review

Co-authored-by: Mufei Li <mufeili1996@gmail.com>

* Clarify the message name, which is 'm'. (#4462)

Co-authored-by: Ubuntu <ubuntu@ip-172-31-34-29.ap-northeast-1.compute.internal>
Co-authored-by: Rhett Ying <85214957+Rhett-Ying@users.noreply.github.com>

* [Refactor] Auto fix view.py. (#4461)

Co-authored-by: Ubuntu <ubuntu@ip-172-31-34-29.ap-northeast-1.compute.internal>
Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>

* [Example] SEAL for OGBL (#4291)

* [Example] SEAL for OGBL

* update index

* update

* fix readme typo

* add seal sampler

* modify set ops

* prefetch

* efficiency test

* update

* optimize

* fix ScatterAdd dtype issue

* update sampler style

* update

Co-authored-by: Quan Gan <coin2028@hotmail.com>

* [CI] use https instead of http (#4488)

* [BugFix] fix crash due to incorrect dtype in dgl.to_block() (#4487)

* [BugFix] fix crash due to incorrect dtype in dgl.to_block()

* fix test failure in TF

* [Feature] Make TensorAdapter Stream Aware (#4472)

* Allocate tensors in DGL's current stream

* make tensoradaptor stream-aware

* replace TAemtpy with cpu allocator

* fix typo

* try fix cpu allocation

* clean header

* redirect AllocDataSpace as well

* resolve comments

* [Build][Doc] Specify the sphinx version (#4465)

Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>

* reformat

* reformat

* Auto fix update-version

* Auto fix setup.py

* reformat

* reformat

Co-authored-by: Ubuntu <ubuntu@ip-172-31-34-29.ap-northeast-1.compute.internal>
Co-authored-by: Rhett Ying <85214957+Rhett-Ying@users.noreply.github.com>
Co-authored-by: Mufei Li <mufeili1996@gmail.com>
Co-authored-by: Ubuntu <ubuntu@ip-172-31-9-26.ap-northeast-1.compute.internal>
Co-authored-by: Xin Yao <xiny@nvidia.com>
Co-authored-by: Chang Liu <chang.liu@utexas.edu>
Co-authored-by: Zhiteng Li <55398076+ZHITENGLI@users.noreply.github.com>
Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>
Co-authored-by: rudongyu <ru_dongyu@outlook.com>
Co-authored-by: Quan Gan <coin2028@hotmail.com>

* Move mock version of dgl_sparse library to DGL main repo (#4524)

* init

* Add api doc for sparse library

* support op btwn matrices with differnt sparsity

* Fixed docstring

* addresses comments

* lint check

* change keyword format to fmt

Co-authored-by: Israt Nisa <nisisrat@amazon.com>

* [DistPart] expose timeout config for process group (#4532)

* [DistPart] expose timeout config for process group

* refine code

* Update tools/distpartitioning/data_proc_pipeline.py

Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>

Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>

* [Feature] Import PyTorch's CUDA stream management (#4503)

* add set_stream

* add .record_stream for NDArray and HeteroGraph

* refactor dgl stream Python APIs

* test record_stream

* add unit test for record stream

* use pytorch's stream

* fix lint

* fix cpu build

* address comments

* address comments

* add record stream tests for dgl.graph

* record frames and update dataloder

* add docstring

* update frame

* add backend check for record_stream

* remove CUDAThreadEntry::stream

* record stream for newly created formats

* fix bug

* fix cpp test

* fix None c_void_p to c_handle

* [examples]educe memory consumption (#4558)

* [examples]educe memory consumption

* reffine help message

* refine

* [Feature][REVIEW] Enable DGL cugaph nightly CI  (#4525)

* Added cugraph nightly scripts

* Removed nvcr.io//nvidia/pytorch:22.04-py3 reference

Co-authored-by: Rhett Ying <85214957+Rhett-Ying@users.noreply.github.com>

* Revert "[Feature][REVIEW] Enable DGL cugaph nightly CI  (#4525)" (#4563)

This reverts commit ec171c648a.

* [Misc] Add flake8 lint workflow. (#4566)

* Add pyproject.toml for autopep8.

* Add pyproject.toml for autopep8.

* Add flake8 annotation in workflow.

* remove

* add

* clean up

Co-authored-by: Steve <ubuntu@ip-172-31-34-29.ap-northeast-1.compute.internal>

* [Misc] Try use official pylint workflow. (#4568)

* polish update_version

* update pylint workflow.

* add

* revert.

Co-authored-by: Steve <ubuntu@ip-172-31-34-29.ap-northeast-1.compute.internal>

* [CI] refine stage logic (#4565)

* [CI] refine stage logic

* refine

* refine

* remove (#4570)

Co-authored-by: Steve <ubuntu@ip-172-31-34-29.ap-northeast-1.compute.internal>

* Add Pylint workflow for flake8. (#4571)

* remove

* Add pylint.

Co-authored-by: Steve <ubuntu@ip-172-31-34-29.ap-northeast-1.compute.internal>

* [Misc] Update the python version in Pylint workflow for flake8. (#4572)

* remove

* Add pylint.

* Change the python version for pylint.

Co-authored-by: Steve <ubuntu@ip-172-31-34-29.ap-northeast-1.compute.internal>

* Update pylint. (#4574)

Co-authored-by: Steve <ubuntu@ip-172-31-34-29.ap-northeast-1.compute.internal>

* [Misc] Use another workflow. (#4575)

* Update pylint.

* Use another workflow.

Co-authored-by: Steve <ubuntu@ip-172-31-34-29.ap-northeast-1.compute.internal>

* Update pylint. (#4576)

Co-authored-by: Steve <ubuntu@ip-172-31-34-29.ap-northeast-1.compute.internal>

* Update pylint.yml

* Update pylint.yml

* Delete pylint.yml

* [Misc]Add pyproject.toml for autopep8 & black. (#4543)

* Add pyproject.toml for autopep8.

* Add pyproject.toml for autopep8.

Co-authored-by: Steve <ubuntu@ip-172-31-34-29.ap-northeast-1.compute.internal>

* [Feature] Bump DLPack to v0.7 and decouple DLPack from the core library (#4454)

* rename `DLContext` to `DGLContext`

* rename `kDLGPU` to `kDLCUDA`

* replace DLTensor with DGLArray

* fix linting

* Unify DGLType and DLDataType to DGLDataType

* Fix FFI

* rename DLDeviceType to DGLDeviceType

* decouple dlpack from the core library

* fix bug

* fix lint

* fix merge

* fix build

* address comments

* rename dl_converter to dlpack_convert

* remove redundant comments

Co-authored-by: Chang Liu <chang.liu@utexas.edu>
Co-authored-by: nv-dlasalle <63612878+nv-dlasalle@users.noreply.github.com>
Co-authored-by: Xin Yao <xiny@nvidia.com>
Co-authored-by: Xin Yao <yaox12@outlook.com>
Co-authored-by: Israt Nisa <neesha295@gmail.com>
Co-authored-by: Israt Nisa <nisisrat@amazon.com>
Co-authored-by: peizhou001 <110809584+peizhou001@users.noreply.github.com>
Co-authored-by: Ubuntu <ubuntu@ip-172-31-19-194.ap-northeast-1.compute.internal>
Co-authored-by: ndickson-nvidia <99772994+ndickson-nvidia@users.noreply.github.com>
Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>
Co-authored-by: Rhett Ying <85214957+Rhett-Ying@users.noreply.github.com>
Co-authored-by: Hongzhi (Steve), Chen <chenhongzhi.nkcs@gmail.com>
Co-authored-by: Ubuntu <ubuntu@ip-172-31-34-29.ap-northeast-1.compute.internal>
Co-authored-by: Ubuntu <ubuntu@ip-172-31-9-26.ap-northeast-1.compute.internal>
Co-authored-by: Zhiteng Li <55398076+ZHITENGLI@users.noreply.github.com>
Co-authored-by: rudongyu <ru_dongyu@outlook.com>
Co-authored-by: Quan Gan <coin2028@hotmail.com>
Co-authored-by: Vibhu Jawa <vibhujawa@gmail.com>

* [Deprecation] Dataset Attributes (#4546)

* Update

* CI

* CI

* Update

Co-authored-by: Ubuntu <ubuntu@ip-172-31-9-26.ap-northeast-1.compute.internal>

* [Example] Bug Fix (#4665)

* Update

* CI

* CI

* Update

* Update

Co-authored-by: Ubuntu <ubuntu@ip-172-31-9-26.ap-northeast-1.compute.internal>

* Update

Co-authored-by: Chang Liu <chang.liu@utexas.edu>
Co-authored-by: nv-dlasalle <63612878+nv-dlasalle@users.noreply.github.com>
Co-authored-by: Xin Yao <xiny@nvidia.com>
Co-authored-by: Xin Yao <yaox12@outlook.com>
Co-authored-by: Israt Nisa <neesha295@gmail.com>
Co-authored-by: Israt Nisa <nisisrat@amazon.com>
Co-authored-by: peizhou001 <110809584+peizhou001@users.noreply.github.com>
Co-authored-by: Ubuntu <ubuntu@ip-172-31-19-194.ap-northeast-1.compute.internal>
Co-authored-by: ndickson-nvidia <99772994+ndickson-nvidia@users.noreply.github.com>
Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>
Co-authored-by: Rhett Ying <85214957+Rhett-Ying@users.noreply.github.com>
Co-authored-by: Hongzhi (Steve), Chen <chenhongzhi.nkcs@gmail.com>
Co-authored-by: Ubuntu <ubuntu@ip-172-31-34-29.ap-northeast-1.compute.internal>
Co-authored-by: Ubuntu <ubuntu@ip-172-31-9-26.ap-northeast-1.compute.internal>
Co-authored-by: Zhiteng Li <55398076+ZHITENGLI@users.noreply.github.com>
Co-authored-by: rudongyu <ru_dongyu@outlook.com>
Co-authored-by: Quan Gan <coin2028@hotmail.com>
Co-authored-by: Vibhu Jawa <vibhujawa@gmail.com>
2022-10-13 11:12:45 +08:00

95 行
2.5 KiB
Python

"""KarateClub Dataset
"""
import numpy as np
import networkx as nx
from .. import backend as F
from .dgl_dataset import DGLDataset
from .utils import deprecate_property
from ..convert import from_networkx
__all__ = ['KarateClubDataset', 'KarateClub']
class KarateClubDataset(DGLDataset):
r""" Karate Club dataset for Node Classification
Zachary's karate club is a social network of a university
karate club, described in the paper "An Information Flow
Model for Conflict and Fission in Small Groups" by Wayne W. Zachary.
The network became a popular example of community structure in
networks after its use by Michelle Girvan and Mark Newman in 2002.
Official website: `<http://konect.cc/networks/ucidata-zachary/>`_
Karate Club dataset statistics:
- Nodes: 34
- Edges: 156
- Number of Classes: 2
Parameters
----------
transform : callable, optional
A transform that takes in a :class:`~dgl.DGLGraph` object and returns
a transformed version. The :class:`~dgl.DGLGraph` object will be
transformed before every access.
Attributes
----------
num_classes : int
Number of node classes
Examples
--------
>>> dataset = KarateClubDataset()
>>> num_classes = dataset.num_classes
>>> g = dataset[0]
>>> labels = g.ndata['label']
"""
def __init__(self, transform=None):
super(KarateClubDataset, self).__init__(name='karate_club', transform=transform)
def process(self):
kc_graph = nx.karate_club_graph()
label = np.asarray(
[kc_graph.nodes[i]['club'] != 'Mr. Hi' for i in kc_graph.nodes]).astype(np.int64)
label = F.tensor(label)
g = from_networkx(kc_graph)
g.ndata['label'] = label
self._graph = g
self._data = [g]
@property
def num_classes(self):
"""Number of classes."""
return 2
def __getitem__(self, idx):
r""" Get graph object
Parameters
----------
idx : int
Item index, KarateClubDataset has only one graph object
Returns
-------
:class:`dgl.DGLGraph`
graph structure and labels.
- ``ndata['label']``: ground truth labels
"""
assert idx == 0, "This dataset has only one graph"
if self._transform is None:
return self._graph
else:
return self._transform(self._graph)
def __len__(self):
r"""The number of graphs in the dataset."""
return 1
KarateClub = KarateClubDataset