Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

[CI] Move gpu docker binary to cuda10 #4229

Merged
merged 2 commits into from
Oct 31, 2019
Merged

[CI] Move gpu docker binary to cuda10 #4229

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
0de3762
[CI] Move gpu docker binary to cuda10
tqchen Oct 30, 2019
e80ea08
Fix the gcn tutorial
tqchen Oct 31, 2019
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion Jenkinsfile
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -45,7 +45,7 @@
//

ci_lint = "tvmai/ci-lint:v0.51"
ci_gpu = "tvmai/ci-gpu:v0.54"
ci_gpu = "tvmai/ci-gpu:v0.55"
ci_cpu = "tvmai/ci-cpu:v0.54"
ci_i386 = "tvmai/ci-i386:v0.52"

Expand Down
7 changes: 4 additions & 3 deletions tutorials/frontend/build_gcn.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -46,6 +46,7 @@
import torch.nn as nn
import torch.nn.functional as F
import dgl
import networkx as nx
from dgl.nn.pytorch import GraphConv

class GCN(nn.Module):
Expand Down Expand Up @@ -88,7 +89,7 @@ def load_dataset(dataset="cora"):

# Remove self-loops to avoid duplicate passing of a node's feature to itself
g = data.graph
g.remove_edges_from(g.selfloop_edges())
g.remove_edges_from(nx.selfloop_edges(g))
g.add_edges_from(zip(g.nodes, g.nodes))

return g, data
Expand All @@ -110,7 +111,7 @@ def evaluate(data, logits):
Parameters
----------
dataset: str
Name of dataset. You can choose from ['cora', 'citeseer', 'pubmed'].
Name of dataset. You can choose from ['cora', 'citeseer', 'pubmed'].

num_layer: int
number of hidden layers
Expand Down Expand Up @@ -251,7 +252,7 @@ def GraphConv(layer_name,
######################################################################
# Prepare the parameters needed in the GraphConv layers
# ------------------
#
#
import numpy as np
import networkx as nx

Expand Down