Init PaddleClas

ppcls/utils/config.py

@@ -89,8 +89,8 @@ def print_config(config):
         config: configs
     """
 
-    copyright = "PaddleCLS is powered by PaddlePaddle"
-    ad = "https://github.com/PaddlePaddle/PaddleCLS"
+    copyright = "PaddleClas is powered by PaddlePaddle"
+    ad = "https://github.com/PaddlePaddle/PaddleClas"
 
     logger.info("\n" * 2)
     logger.info(copyright)
@@ -193,9 +193,11 @@ def get_config(fname, overrides=[], show=True):
     assert os.path.exists(fname), \
             ('config file({}) is not exist'.format(fname))
     config = parse_config(fname)
-    if show: print_config(config)
+    if show:
+        print_config(config)
     if len(overrides) > 0:
         override_config(config, overrides)
-        print_config(config)
+        if show:
+            print_config(config)
     check_config(config)
     return config

ppcls/utils/save_load.py

@@ -30,7 +30,7 @@ __all__ = ['init_model', 'save_model']
 
 def _mkdir_if_not_exist(path):
     """
-        mkdir if not exists
+    mkdir if not exists
     """
     if not os.path.exists(os.path.join(path)):
         os.makedirs(os.path.join(path))
@@ -97,25 +97,27 @@ def load_params(exe, prog, path, ignore_params=[]):
     fluid.io.set_program_state(prog, state)
 
 
-def init_model(config, program, exe):
+def init_model(config, program, exe, prefix="ppcls"):
     """
-        load model from checkpoint or pretrained_model
+    load model from checkpoint or pretrained_model
     """
     checkpoints = config.get('checkpoints')
-    if checkpoints and os.path.exists(checkpoints):
-        fluid.load(program, checkpoints, exe)
-        logger.info("Finish initing model from {}".format(checkpoints))
+    if checkpoints:
+        path = os.path.join(checkpoints, prefix)
+        fluid.load(program, path, exe)
+        logger.info("Finish initing model from {}".format(path))
         return
 
     pretrained_model = config.get('pretrained_model')
-    if pretrained_model and os.path.exists(pretrained_model):
-        load_params(exe, program, pretrained_model)
-        logger.info("Finish initing model from {}".format(pretrained_model))
+    if pretrained_model:
+        path = os.path.join(pretrained_model, prefix)
+        load_params(exe, program, path)
+        logger.info("Finish initing model from {}".format(path))
 
 
 def save_model(program, model_path, epoch_id, prefix='ppcls'):
     """
-        save model to the target path
+    save model to the target path
     """
     model_path = os.path.join(model_path, str(epoch_id))
     _mkdir_if_not_exist(model_path)

tools/program.py

@@ -357,6 +357,8 @@ def run(dataloader, exe, program, fetchs, epoch=0, mode='train'):
     """
     fetch_list = [f[0] for f in fetchs.values()]
     metric_list = [f[1] for f in fetchs.values()]
+    for m in metric_list:
+        m.reset()
     batch_time = AverageMeter('cost', ':6.3f')
     tic = time.time()
     for idx, batch in enumerate(dataloader()):