add evaluate only choice

core/trainers/single_trainer.py

@@ -55,6 +55,11 @@ class SingleTrainer(TranspileTrainer):
         if metrics:
             self.fetch_vars = metrics.values()
             self.fetch_alias = metrics.keys()
+        evaluate_only = envs.get_global_env(
+            'evaluate_only', False, namespace='evaluate')
+        if evaluate_only:
+            context['status'] = 'infer_pass'
+        else:
             context['status'] = 'startup_pass'
 
     def startup(self, context):

core/trainers/transpiler_trainer.py

@@ -229,8 +229,17 @@ class TranspileTrainer(Trainer):
         metrics_format = ", ".join(metrics_format)
         self._exe.run(startup_program)
 
-        for (epoch, model_dir) in self.increment_models:
-            print("Begin to infer epoch {}, model_dir: {}".format(epoch, model_dir))
+        model_list = self.increment_models
+
+        evaluate_only = envs.get_global_env(
+            'evaluate_only', False, namespace='evaluate')
+        if evaluate_only:
+            model_list = [(0, envs.get_global_env(
+                'evaluate_model_path', "", namespace='evaluate'))]
+
+        for (epoch, model_dir) in model_list:
+            print("Begin to infer No.{} model, model_dir: {}".format(
+                epoch, model_dir))
             program = infer_program.clone()
             fluid.io.load_persistables(self._exe, model_dir, program)
             reader.start()

models/recall/word2vec/config.yaml

@@ -13,6 +13,10 @@
 # limitations under the License.
 evaluate:
   workspace: "paddlerec.models.recall.word2vec" 
+
+  evaluate_only: False
+  evaluate_model_path: ""
+  
   reader:
     batch_size: 50
     class: "{workspace}/w2v_evaluate_reader.py"