From 5090515b8d9ab8ceba082c88ec46162a9039f3ed Mon Sep 17 00:00:00 2001
From: xjqbest <173596896@qq.com>
Date: Thu, 28 May 2020 12:07:36 +0800
Subject: [PATCH] fix

---
 core/trainers/single_trainer.py | 10 ++++++----
 1 file changed, 6 insertions(+), 4 deletions(-)

diff --git a/core/trainers/single_trainer.py b/core/trainers/single_trainer.py
index db1bc8ef..d39d48f3 100755
--- a/core/trainers/single_trainer.py
+++ b/core/trainers/single_trainer.py
@@ -210,7 +210,7 @@ class SingleTrainer(TranspileTrainer):
                         train_prog = self._model[model_dict["name"]][0]
                         startup_prog = self._model[model_dict["name"]][1]
                         with fluid.program_guard(train_prog, startup_prog):
-                            self.load(j)
+                            self.load()
                 reader_name = model_dict["dataset_name"]
                 name = "dataset." + reader_name + "."
                 begin_time = time.time()
@@ -283,7 +283,7 @@ class SingleTrainer(TranspileTrainer):
         metrics_format = []
         fetch_period = 20
         metrics_format.append("{}: {{}}".format("batch"))
-        for name, var in model_class.get_metrics().items():
+        for name, var in metrics.items():
             metrics_varnames.append(var.name)
             metrics_format.append("{}: {{}}".format(name))
         metrics_format = ", ".join(metrics_format)
@@ -313,6 +313,7 @@ class SingleTrainer(TranspileTrainer):
         dirname = envs.get_global_env("epoch.init_model_path", None)
         if dirname is None:
             return
+        print("going to load ", dirname)
         if is_fleet:
             fleet.load_persistables(self._exe, dirname)
         else:
@@ -334,7 +335,7 @@ class SingleTrainer(TranspileTrainer):
                 return
             feed_varnames = envs.get_global_env("epoch.save_inference_feed_varnames", None)
             fetch_varnames = envs.get_global_env("epoch.save_inference_fetch_varnames", None)
-            if feed_varnames is None or fetch_varnames is None:
+            if feed_varnames is None or fetch_varnames is None or feed_varnames == "":
                 return
             fetch_vars = [
                 fluid.default_main_program().global_block().vars[varname]
@@ -358,7 +359,8 @@ class SingleTrainer(TranspileTrainer):
             if not need_save(epoch_id, save_interval, False):
                 return
             dirname = envs.get_global_env("epoch.save_checkpoint_path", None)
-            assert dirname is not None
+            if dirname is None or dirname == "":
+                return
             dirname = os.path.join(dirname, str(epoch_id))
             if is_fleet:
                 fleet.save_persistables(self._exe, dirname)
-- 
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