From db5e61147468f370a6ac71139dcf9c96a6de4588 Mon Sep 17 00:00:00 2001
From: Germey <cqc@cuiqingcai.com>
Date: Thu, 11 Oct 2018 00:09:11 +0800
Subject: [PATCH] change examples

---
 examples/evaluate.py |  4 ----
 examples/infer.py    | 15 +++++----------
 examples/model.py    |  1 +
 examples/train.py    | 18 +++++++-----------
 4 files changed, 13 insertions(+), 25 deletions(-)

diff --git a/examples/evaluate.py b/examples/evaluate.py
index 5507463..5a83f0e 100644
--- a/examples/evaluate.py
+++ b/examples/evaluate.py
@@ -1,4 +1,3 @@
-from model import BostonHousingModel
 from model_zoo.evaluater import BaseEvaluater
 import tensorflow as tf
 
@@ -6,9 +5,6 @@
 
 
 class Evaluater(BaseEvaluater):
-    def __init__(self):
-        BaseEvaluater.__init__(self)
-        self.model_class = BostonHousingModel
     
     def prepare_data(self):
         from tensorflow.python.keras.datasets import boston_housing
diff --git a/examples/infer.py b/examples/infer.py
index b8b1112..b78f339 100644
--- a/examples/infer.py
+++ b/examples/infer.py
@@ -1,21 +1,16 @@
-from model import BostonHousingModel
 from model_zoo.inferer import BaseInferer
+from model_zoo.preprocess import standardize
 import tensorflow as tf
-from tensorflow.python.keras.datasets import boston_housing
-from sklearn.preprocessing import StandardScaler
 
-tf.flags.DEFINE_string('checkpoint_name', 'model.ckpt-38', help='Model name')
+tf.flags.DEFINE_string('checkpoint_name', 'model.ckpt-20', help='Model name')
+
 
 class Inferer(BaseInferer):
-    def __init__(self):
-        BaseInferer.__init__(self)
-        self.model_class = BostonHousingModel
     
     def prepare_data(self):
+        from tensorflow.python.keras.datasets import boston_housing
         (x_train, y_train), (x_test, y_test) = boston_housing.load_data()
-        ss = StandardScaler()
-        ss.fit(x_train)
-        x_test = ss.transform(x_test)
+        _, x_test = standardize(x_train, x_test)
         return x_test
 
 
diff --git a/examples/model.py b/examples/model.py
index 08110e2..6b1b7e2 100644
--- a/examples/model.py
+++ b/examples/model.py
@@ -1,6 +1,7 @@
 from model_zoo.model import BaseModel
 import tensorflow as tf
 
+
 class BostonHousingModel(BaseModel):
     def __init__(self, config):
         super(BostonHousingModel, self).__init__(config)
diff --git a/examples/train.py b/examples/train.py
index e5b96e9..fb301a9 100644
--- a/examples/train.py
+++ b/examples/train.py
@@ -1,23 +1,19 @@
-from model import BostonHousingModel
+import tensorflow as tf
 from model_zoo.trainer import BaseTrainer
-from tensorflow.python.keras.datasets import boston_housing
-from sklearn.preprocessing import StandardScaler
+from model_zoo.preprocess import standardize
+
+tf.flags.DEFINE_integer('epochs', 20, 'Max epochs')
+tf.flags.DEFINE_string('model_class', 'BostonHousingModel', 'Model class name')
 
 
 class Trainer(BaseTrainer):
     
-    def __init__(self):
-        BaseTrainer.__init__(self)
-        self.model_class = BostonHousingModel
-    
     def prepare_data(self):
+        from tensorflow.python.keras.datasets import boston_housing
         (x_train, y_train), (x_eval, y_eval) = boston_housing.load_data()
-        ss = StandardScaler()
-        ss.fit(x_train)
-        x_train, x_eval = ss.transform(x_train), ss.transform(x_eval)
+        x_train, x_eval = standardize(x_train, x_eval)
         train_data, eval_data = (x_train, y_train), (x_eval, y_eval)
         return train_data, eval_data
 
-
 if __name__ == '__main__':
     Trainer().run()