forked from shenweichen/DeepCTR
-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy path__init__.py
41 lines (39 loc) · 1.85 KB
/
__init__.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
import tensorflow as tf
from .activation import Dice
from .core import DNN, LocalActivationUnit, PredictionLayer
from .interaction import (CIN, FM, AFMLayer, BiInteractionPooling, CrossNet,
InnerProductLayer, InteractingLayer,
OutterProductLayer, FGCNNLayer,SENETLayer,BilinearInteraction)
from .normalization import LayerNormalization
from .sequence import (AttentionSequencePoolingLayer, BiasEncoding, BiLSTM,
KMaxPooling, SequencePoolingLayer,
Transformer, DynamicGRU)
from .utils import NoMask, Hash,Linear
custom_objects = {'tf': tf,
'InnerProductLayer': InnerProductLayer,
'OutterProductLayer': OutterProductLayer,
'DNN': DNN,
'PredictionLayer': PredictionLayer,
'FM': FM,
'AFMLayer': AFMLayer,
'CrossNet': CrossNet,
'BiInteractionPooling': BiInteractionPooling,
'LocalActivationUnit': LocalActivationUnit,
'Dice': Dice,
'SequencePoolingLayer': SequencePoolingLayer,
'AttentionSequencePoolingLayer': AttentionSequencePoolingLayer,
'CIN': CIN,
'InteractingLayer': InteractingLayer,
'LayerNormalization': LayerNormalization,
'BiLSTM': BiLSTM,
'Transformer': Transformer,
'NoMask': NoMask,
'BiasEncoding': BiasEncoding,
'KMaxPooling': KMaxPooling,
'FGCNNLayer': FGCNNLayer,
'Hash': Hash,
'Linear':Linear,
'DynamicGRU': DynamicGRU,
'SENETLayer':SENETLayer,
'BilinearInteraction':BilinearInteraction,
}