add log hint for local cluster training

demo/ctr-dnn_train.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.
-
-train:
-  trainer:
-    # for cluster training
-    strategy: "async"
-
-  epochs: 10
-  workspace: "fleetrec.models.rank.dnn"
-
-  reader:
-    batch_size: 2
-    class: "{workspace}/../criteo_reader.py"
-    train_data_path: "{workspace}/data/train"
-
-  model:
-    models: "{workspace}/model.py"
-    hyper_parameters:
-      sparse_inputs_slots: 27
-      sparse_feature_number: 1000001
-      sparse_feature_dim: 9
-      dense_input_dim: 13
-      fc_sizes: [512, 256, 128, 32]
-      learning_rate: 0.001
-      optimizer: adam
-
-  save:
-    increment:
-      dirname: "increment"
-      epoch_interval: 2
-      save_last: True
-    inference:
-      dirname: "inference"
-      epoch_interval: 4
-      save_last: True

demo/user_define_trainer.py

-# 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.
-
-import paddle.fluid as fluid
-
-from fleetrec.core.trainers.transpiler_trainer import TranspileTrainer
-from fleetrec.core.utils import envs
-
-
-class UserDefineTrainer(TranspileTrainer):
-    def __init__(self, config=None):
-        TranspileTrainer.__init__(self, config)
-        print("this is a demo about how to use user define trainer in fleet-rec")
-
-    def processor_register(self):
-        self.regist_context_processor('uninit', self.instance)
-        self.regist_context_processor('init_pass', self.init)
-        self.regist_context_processor('train_pass', self.train)
-
-    def init(self, context):
-        self.model.train_net()
-        optimizer = self.model.optimizer()
-        optimizer.minimize((self.model.get_cost_op()))
-
-        self.fetch_vars = []
-        self.fetch_alias = []
-        self.fetch_period = self.model.get_fetch_period()
-
-        metrics = self.model.get_metrics()
-        if metrics:
-            self.fetch_vars = metrics.values()
-            self.fetch_alias = metrics.keys()
-        context['status'] = 'train_pass'
-
-    def train(self, context):
-        # run startup program at once
-        self._exe.run(fluid.default_startup_program())
-
-        dataset = self._get_dataset()
-
-        epochs = envs.get_global_env("train.epochs")
-
-        for i in range(epochs):
-            self._exe.train_from_dataset(program=fluid.default_main_program(),
-                                         dataset=dataset,
-                                         fetch_list=self.fetch_vars,
-                                         fetch_info=self.fetch_alias,
-                                         print_period=self.fetch_period)
-
-        context['is_exit'] = True

readme.md

@@ -26,22 +26,20 @@ python setup.py install
 
 
 ## ctr-dnn示例使用
-目前框架内置了ctr-dnn模型，后续会加入更多模型
-
-示例代码位于FleetRec/demo/下， 当前支持单机训练和本地1*1模拟训练
+目前框架内置了多个模型，简单的命令即可使用内置模型开始单机训练和本地1*1模拟训练
 
 ### 单机训练
 ```bash
 cd FleetRec
 
 python -m fleetrec.run \
-       -m demo/ctr-dnn_train.yaml \
+       -m fleetrec.models.rank.dnn \
        -d cpu \
        -e single 
 
 # 使用GPU资源进行训练
 python -m fleetrec.run \
-       -m demo/ctr-dnn_train.yaml \
+       -m fleetrec.models.rank.dnn \
        -d gpu \
        -e single
 ```
@@ -52,7 +50,7 @@ python -m fleetrec.run \
 cd FleetRec
 # 使用CPU资源进行训练
 python -m fleetrec.run \
-       -m demo/ctr-dnn_train.yaml \
+       -m fleetrec.models.rank.dnn \
        -d cpu \
        -e local_cluster
 ```
@@ -63,7 +61,7 @@ python -m fleetrec.run \
 cd FleetRec
 
 python -m fleetrec.run \
-       -m demo/ctr-dnn_train.yaml \
+       -m fleetrec.models.rank.dnn \
        -d cpu \
        -e cluster
 ```