From bfcd53da55fc8dbd67c1d304a8f288588faca0cf Mon Sep 17 00:00:00 2001
From: tangwei <tangwei12@baidu.com>
Date: Fri, 10 Apr 2020 12:34:31 +0800
Subject: [PATCH] code fix

---
 fleetrec/models/base.py | 91 ++++++++++++++++++++---------------------
 1 file changed, 45 insertions(+), 46 deletions(-)

diff --git a/fleetrec/models/base.py b/fleetrec/models/base.py
index a309d37f..22cedc06 100644
--- a/fleetrec/models/base.py
+++ b/fleetrec/models/base.py
@@ -75,13 +75,6 @@ class Model(object):
     def __init__(self, config):
         """R
         """
-        self._config = config
-        self._name = config['name']
-        f = open(config['layer_file'], 'r')
-        self._build_nodes = yaml.safe_load(f.read())
-        self._build_phase = ['input', 'param', 'summary', 'layer']
-        self._build_param = {'layer': {}, 'inner_layer': {}, 'layer_extend': {}, 'model': {}}
-        self._inference_meta = {'dependency': {}, 'params': {}}
         self._cost = None
         self._metrics = {}
         self._data_var = []
@@ -130,44 +123,6 @@ class Model(object):
         """
         pass
 
-    def inference_params(self, inference_layer):
-        """
-        get params name for inference_layer
-        Args:
-            inference_layer(str): layer for inference
-        Return:
-            params(list): params name list that for inference layer
-        """
-        layer = inference_layer
-        if layer in self._inference_meta['params']:
-            return self._inference_meta['params'][layer]
-
-        self._inference_meta['params'][layer] = []
-        self._inference_meta['dependency'][layer] = self.get_dependency(self._build_param['inner_layer'], layer)
-        for node in self._build_nodes['layer']:
-            if node['name'] not in self._inference_meta['dependency'][layer]:
-                continue
-            if 'inference_param' in self._build_param['layer_extend'][node['name']]:
-                self._inference_meta['params'][layer] += \
-                    self._build_param['layer_extend'][node['name']]['inference_param']['params']
-        return self._inference_meta['params'][layer]
-
-    def get_dependency(self, layer_graph, dest_layer):
-        """
-        get model of dest_layer depends on
-        Args:
-            layer_graph(dict) : all model in graph
-        Return:
-            depend_layers(list) : sub-graph model for calculate dest_layer
-        """
-        dependency_list = []
-        if dest_layer in layer_graph:
-            dependencys = copy.deepcopy(layer_graph[dest_layer]['input'])
-            dependency_list = copy.deepcopy(dependencys)
-            for dependency in dependencys:
-                dependency_list = dependency_list + self.get_dependency(layer_graph, dependency)
-        return list(set(dependency_list))
-
 
 class YamlModel(Model):
     """R
@@ -177,7 +132,13 @@ class YamlModel(Model):
         """R
         """
         Model.__init__(self, config)
-        pass
+        self._config = config
+        self._name = config['name']
+        f = open(config['layer_file'], 'r')
+        self._build_nodes = yaml.safe_load(f.read())
+        self._build_phase = ['input', 'param', 'summary', 'layer']
+        self._build_param = {'layer': {}, 'inner_layer': {}, 'layer_extend': {}, 'model': {}}
+        self._inference_meta = {'dependency': {}, 'params': {}}
 
     def build_model(self):
         """R
@@ -289,3 +250,41 @@ class YamlModel(Model):
                                        program, vars=params_var_list, filename=params_file_name)
                 else:
                     fluid.io.save_vars(executor, params_file_name, program, vars=params_var_list)
+
+    def inference_params(self, inference_layer):
+        """
+        get params name for inference_layer
+        Args:
+            inference_layer(str): layer for inference
+        Return:
+            params(list): params name list that for inference layer
+        """
+        layer = inference_layer
+        if layer in self._inference_meta['params']:
+            return self._inference_meta['params'][layer]
+
+        self._inference_meta['params'][layer] = []
+        self._inference_meta['dependency'][layer] = self.get_dependency(self._build_param['inner_layer'], layer)
+        for node in self._build_nodes['layer']:
+            if node['name'] not in self._inference_meta['dependency'][layer]:
+                continue
+            if 'inference_param' in self._build_param['layer_extend'][node['name']]:
+                self._inference_meta['params'][layer] += \
+                    self._build_param['layer_extend'][node['name']]['inference_param']['params']
+        return self._inference_meta['params'][layer]
+
+    def get_dependency(self, layer_graph, dest_layer):
+        """
+        get model of dest_layer depends on
+        Args:
+            layer_graph(dict) : all model in graph
+        Return:
+            depend_layers(list) : sub-graph model for calculate dest_layer
+        """
+        dependency_list = []
+        if dest_layer in layer_graph:
+            dependencys = copy.deepcopy(layer_graph[dest_layer]['input'])
+            dependency_list = copy.deepcopy(dependencys)
+            for dependency in dependencys:
+                dependency_list = dependency_list + self.get_dependency(layer_graph, dependency)
+        return list(set(dependency_list))
\ No newline at end of file
-- 
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