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Unverified Commit 895d6fff authored by Kay Liu's avatar Kay Liu Committed by GitHub
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[Doc] changing of output dimension (#2981) 


Co-authored-by: default avatarzhjwy9343 <6593865@qq.com>
parent e2a28a6c
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Showing with 6 additions and 6 deletions
docs/source/guide/message-efficient.rst
View file @ 895d6fff
...@@ -30,7 +30,7 @@ implementation would be like: ...@@ -30,7 +30,7 @@ implementation would be like:
import torch import torch
import torch.nn as nn import torch.nn as nn
linear = nn.Parameter(torch.FloatTensor(size=(node_feat_dim * 2, 1))) linear = nn.Parameter(torch.FloatTensor(size=(node_feat_dim * 2, out_dim)))
def concat_message_function(edges): def concat_message_function(edges):
return {'cat_feat': torch.cat([edges.src['feat'], edges.dst['feat']])} return {'cat_feat': torch.cat([edges.src['feat'], edges.dst['feat']])}
g.apply_edges(concat_message_function) g.apply_edges(concat_message_function)
...@@ -48,8 +48,8 @@ respectively: ...@@ -48,8 +48,8 @@ respectively:
import dgl.function as fn import dgl.function as fn
linear_src = nn.Parameter(torch.FloatTensor(size=(node_feat_dim, 1))) linear_src = nn.Parameter(torch.FloatTensor(size=(node_feat_dim, out_dim)))
linear_dst = nn.Parameter(torch.FloatTensor(size=(node_feat_dim, 1))) linear_dst = nn.Parameter(torch.FloatTensor(size=(node_feat_dim, out_dim)))
out_src = g.ndata['feat'] @ linear_src out_src = g.ndata['feat'] @ linear_src
out_dst = g.ndata['feat'] @ linear_dst out_dst = g.ndata['feat'] @ linear_dst
g.srcdata.update({'out_src': out_src}) g.srcdata.update({'out_src': out_src})
......
docs/source/guide_cn/message-efficient.rst
View file @ 895d6fff
...@@ -20,7 +20,7 @@ DGL建议用户尽量减少边的特征维数。 ...@@ -20,7 +20,7 @@ DGL建议用户尽量减少边的特征维数。
import torch import torch
import torch.nn as nn import torch.nn as nn
linear = nn.Parameter(torch.FloatTensor(size=(node_feat_dim * 2, 1))) linear = nn.Parameter(torch.FloatTensor(size=(node_feat_dim * 2, out_dim)))
def concat_message_function(edges): def concat_message_function(edges):
return {'cat_feat': torch.cat([edges.src.ndata['feat'], edges.dst.ndata['feat']])} return {'cat_feat': torch.cat([edges.src.ndata['feat'], edges.dst.ndata['feat']])}
g.apply_edges(concat_message_function) g.apply_edges(concat_message_function)
...@@ -35,8 +35,8 @@ DGL建议用户尽量减少边的特征维数。 ...@@ -35,8 +35,8 @@ DGL建议用户尽量减少边的特征维数。
import dgl.function as fn import dgl.function as fn
linear_src = nn.Parameter(torch.FloatTensor(size=(node_feat_dim, 1))) linear_src = nn.Parameter(torch.FloatTensor(size=(node_feat_dim, out_dim)))
linear_dst = nn.Parameter(torch.FloatTensor(size=(node_feat_dim, 1))) linear_dst = nn.Parameter(torch.FloatTensor(size=(node_feat_dim, out_dim)))
out_src = g.ndata['feat'] @ linear_src out_src = g.ndata['feat'] @ linear_src
out_dst = g.ndata['feat'] @ linear_dst out_dst = g.ndata['feat'] @ linear_dst
g.srcdata.update({'out_src': out_src}) g.srcdata.update({'out_src': out_src})
......
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