config.yaml 1.9 KB

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  1. # Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
  2. #
  3. # Licensed under the Apache License, Version 2.0 (the "License");
  4. # you may not use this file except in compliance with the License.
  5. # You may obtain a copy of the License at
  6. #
  7. # http://www.apache.org/licenses/LICENSE-2.0
  8. #
  9. # Unless required by applicable law or agreed to in writing, software
  10. # distributed under the License is distributed on an "AS IS" BASIS,
  11. # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  12. # See the License for the specific language governing permissions and
  13. # limitations under the License.
  14. # workspace
  15. #workspace: "models/rank/dnn"
  16. runner:
  17. train_data_dir: "data/sample_data/train"
  18. train_reader_path: "criteo_reader" # importlib format
  19. use_gpu: False
  20. use_auc: True
  21. train_batch_size: 2
  22. epochs: 1
  23. print_interval: 2
  24. model_save_path: "output_model_dnn"
  25. infer_batch_size: 2
  26. infer_reader_path: "criteo_reader" # importlib format
  27. test_data_dir: "data/sample_data/train"
  28. infer_load_path: "output_model_dnn"
  29. infer_start_epoch: 0
  30. infer_end_epoch: 3
  31. num_workers: 0
  32. #use inference save model
  33. # model_init_path: "output_model_dnn/2" # init model
  34. use_inference: True
  35. 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"]
  36. save_inference_fetch_varnames: ["label", "SparseFeatFactors"]
  37. # distribute_config
  38. sync_mode: "async"
  39. split_file_list: False
  40. thread_num: 1
  41. upload_oss: True
  42. oss_object_name: "dyp/dnn.tar.gz"
  43. # hyper parameters of user-defined network
  44. hyper_parameters:
  45. # optimizer config
  46. optimizer:
  47. class: Adam
  48. learning_rate: 0.001
  49. strategy: async
  50. # user-defined <key, value> pairs
  51. sparse_inputs_slots: 27
  52. sparse_feature_number: 1000001
  53. sparse_feature_dim: 9
  54. dense_input_dim: 13
  55. fc_sizes: [256, 256, 128]
  56. distributed_embedding: 0