-
Notifications
You must be signed in to change notification settings - Fork 726
/
config_bigdata.yaml
executable file
·55 lines (52 loc) · 1.92 KB
/
config_bigdata.yaml
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
42
43
44
45
46
47
48
49
50
51
52
53
54
55
# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# global settings
runner:
#train_data_dir: "data/slot_train_data_full"
train_data_dir: "../../../datasets/criteo/slot_train_data_full"
train_reader_path: "criteo_reader" # importlib format
use_gpu: True
use_xpu: False # Enable this option only if you have an xpu device
use_auc: True
train_batch_size: 512
epochs: 4
print_interval: 10
#model_init_path: "output_model/0" # init model
model_save_path: "output_model_all_wide_deep"
test_data_dir: "../../../datasets/criteo/slot_test_data_full"
infer_reader_path: "criteo_reader" # importlib format
infer_batch_size: 512
infer_load_path: "output_model_all_wide_deep"
infer_start_epoch: 3
infer_end_epoch: 4
#use inference save model
use_inference: False
save_inference_feed_varnames: ["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","dense_input"]
save_inference_fetch_varnames: ["sigmoid_0.tmp_0"]
#use fleet
use_fleet: False
# hyper parameters of user-defined network
hyper_parameters:
# optimizer config
optimizer:
class: Adam
learning_rate: 0.001
strategy: async
# user-defined <key, value> pairs
sparse_inputs_slots: 27
sparse_feature_number: 1000001
sparse_feature_dim: 9
dense_input_dim: 13
fc_sizes: [512, 256, 128, 32]
distributed_embedding: 0