add dygraph to static

Author: frankwhzhang

models/rank/dnn/config.yaml

@@ -22,7 +22,7 @@ runner:
   use_gpu: False
   use_auc: True
   train_batch_size: 2
-  epochs: 3
+  epochs: 1
   print_interval: 2
   model_save_path: "output_model_dnn"
   infer_batch_size: 2

models/rank/dnn/config_to_static.yaml

@@ -0,0 +1,55 @@
+# 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.
+
+# workspace
+#workspace: "models/rank/dnn"
+
+
+runner:
+  train_data_dir: "data/sample_data/train"
+  train_reader_path: "criteo_reader" # importlib format
+  model_init_path: "output_model_dnn/0" # model_init
+  use_gpu: False
+  use_auc: True
+  train_batch_size: 2
+  epochs: 1
+  print_interval: 2
+  model_save_path: "output_model_dnn2" # save path
+  infer_batch_size: 2
+  infer_reader_path: "criteo_reader" # importlib format
+  test_data_dir: "data/sample_data/train"
+  infer_load_path: "output_model_dnn"
+  infer_start_epoch: 0
+  infer_end_epoch: 3
+
+  # distribute_config
+  sync_mode: "async"
+  split_file_list: False
+  thread_num: 1
+
+
+# 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

tools/utils/save_load.py

@@ -30,6 +30,14 @@ def save_model(net, optimizer, model_path, epoch_id, prefix='rec'):
     logger.info("Already save model in {}".format(model_path))
 
 
+def save_jit_model(net, model_path, prefix='tostatic'):
+    _mkdir_if_not_exist(model_path)
+    model_prefix = os.path.join(model_path, prefix)
+    #paddle.save(net.state_dict(), model_prefix + ".pdparams")
+    paddle.jit.save(net, model_prefix)
+    logger.info("Already save jit model in {}".format(model_path))
+
+
 def load_model(model_path, net, prefix='rec'):
     logger.info("start load model from {}".format(model_path))
     model_prefix = os.path.join(model_path, prefix)