Skip to content

P
PGL

PaddlePaddle / PGL

通知 76
Star 4
Fork 0
P
PGL
提交 434be194 编写于 作者: S suweiyue
浏览文件
操作

1. fix mp_reader queue, 2. fix erniesagev2 biasattr

上级 5782fb81
隐藏空白更改
内联 并排
Showing with 25 addition and 12 deletion
examples/erniesage/models/erniesage_v2.py
浏览文件 @ 434be194
...@@ -48,6 +48,9 @@ class ErnieSageV2(BaseNet): ...@@ -48,6 +48,9 @@ class ErnieSageV2(BaseNet):
cls = L.fill_constant_batch_size_like(src_feat["term_ids"], [-1, 1, 1], "int64", 1) cls = L.fill_constant_batch_size_like(src_feat["term_ids"], [-1, 1, 1], "int64", 1)
src_ids = L.concat([cls, src_feat["term_ids"]], 1) src_ids = L.concat([cls, src_feat["term_ids"]], 1)
dst_ids = dst_feat["term_ids"] dst_ids = dst_feat["term_ids"]
# cls = L.fill_constant_batch_size_like(dst_feat["term_ids"], [-1, 1, 1], "int64", 1)
# src_ids = L.concat([cls, dst_feat["term_ids"]], 1)
# dst_ids = src_feat["term_ids"]
# sent_ids # sent_ids
sent_ids = L.concat([L.zeros_like(src_ids), L.ones_like(dst_ids)], 1) sent_ids = L.concat([L.zeros_like(src_ids), L.ones_like(dst_ids)], 1)
...@@ -81,14 +84,16 @@ class ErnieSageV2(BaseNet): ...@@ -81,14 +84,16 @@ class ErnieSageV2(BaseNet):
self_feature = L.fc(self_feature, self_feature = L.fc(self_feature,
hidden_size, hidden_size,
act=act, act=act,
param_attr=F.ParamAttr(name=name + "_l", param_attr=F.ParamAttr(name=name + "_l.w_0",
learning_rate=learning_rate), learning_rate=learning_rate),
bias_attr=name+"_l.b_0"
) )
neigh_feature = L.fc(neigh_feature, neigh_feature = L.fc(neigh_feature,
hidden_size, hidden_size,
act=act, act=act,
param_attr=F.ParamAttr(name=name + "_r", param_attr=F.ParamAttr(name=name + "_r.w_0",
learning_rate=learning_rate), learning_rate=learning_rate),
bias_attr=name+"_r.b_0"
) )
output = L.concat([self_feature, neigh_feature], axis=1) output = L.concat([self_feature, neigh_feature], axis=1)
output = L.l2_normalize(output, axis=1) output = L.l2_normalize(output, axis=1)
......
examples/erniesage/models/message_passing.py
浏览文件 @ 434be194
...@@ -57,14 +57,16 @@ def graphsage_sum(gw, feature, hidden_size, act, initializer, learning_rate, nam ...@@ -57,14 +57,16 @@ def graphsage_sum(gw, feature, hidden_size, act, initializer, learning_rate, nam
self_feature = fluid.layers.fc(self_feature, self_feature = fluid.layers.fc(self_feature,
hidden_size, hidden_size,
act=act, act=act,
param_attr=fluid.ParamAttr(name=name + "_l", initializer=initializer, param_attr=fluid.ParamAttr(name=name + "_l.w_0", initializer=initializer,
learning_rate=learning_rate), learning_rate=learning_rate),
bias_attr=name+"_l.b_0"
) )
neigh_feature = fluid.layers.fc(neigh_feature, neigh_feature = fluid.layers.fc(neigh_feature,
hidden_size, hidden_size,
act=act, act=act,
param_attr=fluid.ParamAttr(name=name + "_r", initializer=initializer, param_attr=fluid.ParamAttr(name=name + "_r.w_0", initializer=initializer,
learning_rate=learning_rate), learning_rate=learning_rate),
bias_attr=name+"_r.b_0"
) )
output = fluid.layers.concat([self_feature, neigh_feature], axis=1) output = fluid.layers.concat([self_feature, neigh_feature], axis=1)
output = fluid.layers.l2_normalize(output, axis=1) output = fluid.layers.l2_normalize(output, axis=1)
...@@ -79,14 +81,16 @@ def graphsage_mean(gw, feature, hidden_size, act, initializer, learning_rate, na ...@@ -79,14 +81,16 @@ def graphsage_mean(gw, feature, hidden_size, act, initializer, learning_rate, na
self_feature = fluid.layers.fc(self_feature, self_feature = fluid.layers.fc(self_feature,
hidden_size, hidden_size,
act=act, act=act,
param_attr=fluid.ParamAttr(name=name + "_l", initializer=initializer, param_attr=fluid.ParamAttr(name=name + "_l.w_0", initializer=initializer,
learning_rate=learning_rate), learning_rate=learning_rate),
bias_attr=name+"_l.b_0"
) )
neigh_feature = fluid.layers.fc(neigh_feature, neigh_feature = fluid.layers.fc(neigh_feature,
hidden_size, hidden_size,
act=act, act=act,
param_attr=fluid.ParamAttr(name=name + "_r", initializer=initializer, param_attr=fluid.ParamAttr(name=name + "_r.w_0", initializer=initializer,
learning_rate=learning_rate), learning_rate=learning_rate),
bias_attr=name+"_r.b_0"
) )
output = fluid.layers.concat([self_feature, neigh_feature], axis=1) output = fluid.layers.concat([self_feature, neigh_feature], axis=1)
output = fluid.layers.l2_normalize(output, axis=1) output = fluid.layers.l2_normalize(output, axis=1)
...@@ -101,14 +105,16 @@ def pinsage_mean(gw, feature, hidden_size, act, initializer, learning_rate, name ...@@ -101,14 +105,16 @@ def pinsage_mean(gw, feature, hidden_size, act, initializer, learning_rate, name
self_feature = fluid.layers.fc(self_feature, self_feature = fluid.layers.fc(self_feature,
hidden_size, hidden_size,
act=act, act=act,
param_attr=fluid.ParamAttr(name=name + "_l", initializer=initializer, param_attr=fluid.ParamAttr(name=name + "_l.w_0", initializer=initializer,
learning_rate=learning_rate), learning_rate=learning_rate),
bias_attr=name+"_l.b_0"
) )
neigh_feature = fluid.layers.fc(neigh_feature, neigh_feature = fluid.layers.fc(neigh_feature,
hidden_size, hidden_size,
act=act, act=act,
param_attr=fluid.ParamAttr(name=name + "_r", initializer=initializer, param_attr=fluid.ParamAttr(name=name + "_r.w_0", initializer=initializer,
learning_rate=learning_rate), learning_rate=learning_rate),
bias_attr=name+"_r.b_0"
) )
output = fluid.layers.concat([self_feature, neigh_feature], axis=1) output = fluid.layers.concat([self_feature, neigh_feature], axis=1)
output = fluid.layers.l2_normalize(output, axis=1) output = fluid.layers.l2_normalize(output, axis=1)
...@@ -123,14 +129,16 @@ def pinsage_sum(gw, feature, hidden_size, act, initializer, learning_rate, name) ...@@ -123,14 +129,16 @@ def pinsage_sum(gw, feature, hidden_size, act, initializer, learning_rate, name)
self_feature = fluid.layers.fc(self_feature, self_feature = fluid.layers.fc(self_feature,
hidden_size, hidden_size,
act=act, act=act,
param_attr=fluid.ParamAttr(name=name + "_l", initializer=initializer, param_attr=fluid.ParamAttr(name=name + "_l.w_0", initializer=initializer,
learning_rate=learning_rate), learning_rate=learning_rate),
bias_attr=name+"_l.b_0"
) )
neigh_feature = fluid.layers.fc(neigh_feature, neigh_feature = fluid.layers.fc(neigh_feature,
hidden_size, hidden_size,
act=act, act=act,
param_attr=fluid.ParamAttr(name=name + "_r", initializer=initializer, param_attr=fluid.ParamAttr(name=name + "_r.w_0", initializer=initializer,
learning_rate=learning_rate), learning_rate=learning_rate),
bias_attr=name+"_r.b_0"
) )
output = fluid.layers.concat([self_feature, neigh_feature], axis=1) output = fluid.layers.concat([self_feature, neigh_feature], axis=1)
output = fluid.layers.l2_normalize(output, axis=1) output = fluid.layers.l2_normalize(output, axis=1)
......
pgl/utils/mp_reader.py
浏览文件 @ 434be194
...@@ -25,7 +25,7 @@ except: ...@@ -25,7 +25,7 @@ except:
import numpy as np import numpy as np
import time import time
import paddle.fluid as fluid import paddle.fluid as fluid
from queue import Queue from multiprocessing import Queue
import threading import threading
......
Markdown is supported
0% 或 .
You are about to add 0 people to the discussion. Proceed with caution.
先完成此消息的编辑！
想要评论请 注册 或