From ad15a6456990545f3be27ef951974d1b60bcc7f6 Mon Sep 17 00:00:00 2001
From: tink2123 <y_tink@163.com>
Date: Sun, 7 Feb 2021 07:31:24 +0000
Subject: [PATCH] polish code for srn eval

---
 tools/program.py | 18 +++++++++++++-----
 1 file changed, 13 insertions(+), 5 deletions(-)

diff --git a/tools/program.py b/tools/program.py
index 99a37432..3dc85500 100755
--- a/tools/program.py
+++ b/tools/program.py
@@ -177,6 +177,8 @@ def train(config,
     model_average = False
     model.train()
 
+    use_srn = config['Architecture']['algorithm'] == "SRN"
+
     if 'start_epoch' in best_model_dict:
         start_epoch = best_model_dict['start_epoch']
     else:
@@ -195,7 +197,7 @@ def train(config,
                 break
             lr = optimizer.get_lr()
             images = batch[0]
-            if config['Architecture']['algorithm'] == "SRN":
+            if use_srn:
                 others = batch[-4:]
                 preds = model(images, others)
                 model_average = True
@@ -251,8 +253,12 @@ def train(config,
                         min_average_window=10000,
                         max_average_window=15625)
                     Model_Average.apply()
-                cur_metric = eval(model, valid_dataloader, post_process_class,
-                                  eval_class)
+                cur_metric = eval(
+                    model,
+                    valid_dataloader,
+                    post_process_class,
+                    eval_class,
+                    use_srn=use_srn)
                 cur_metric_str = 'cur metric, {}'.format(', '.join(
                     ['{}: {}'.format(k, v) for k, v in cur_metric.items()]))
                 logger.info(cur_metric_str)
@@ -316,7 +322,8 @@ def train(config,
     return
 
 
-def eval(model, valid_dataloader, post_process_class, eval_class):
+def eval(model, valid_dataloader, post_process_class, eval_class,
+         use_srn=False):
     model.eval()
     with paddle.no_grad():
         total_frame = 0.0
@@ -327,7 +334,8 @@ def eval(model, valid_dataloader, post_process_class, eval_class):
                 break
             images = batch[0]
             start = time.time()
-            if "SRN" in str(model.head):
+
+            if use_srn:
                 others = batch[-4:]
                 preds = model(images, others)
             else:
-- 
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