config.yaml

# 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.

workspace: "./"

# list of dataset
dataset:
- name: dataset_train # name of dataset to distinguish different datasets
  batch_size: 128
  type: DataLoader 
  data_path: "{workspace}/data/train"
  sparse_slots: "logid time userid gender age occupation movieid title genres label"
  dense_slots: ""

# 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_feature_number: 60000000
  sparse_feature_dim: 9
  dense_input_dim: 13
  fc_sizes: [512, 256, 128, 32]

# train
mode: runner_train
runner:
- name: runner_train
  class: train
  save_checkpoint_interval: 1 # save model interval of epochs
  save_checkpoint_path: "increment_recall" # save checkpoint path
  epochs: 10
  device: cpu

#train
phase:
- name: phase1
  model: "{workspace}/recall/model.py" # user-defined model
  dataset_name: dataset_train # select dataset by name
  thread_num: 4