Fix train+eval in PaddleDetection(#2847)

configs/faster_rcnn_r50_fpn_1x.yml

@@ -9,7 +9,7 @@ log_smooth_window: 20
 save_dir: output
 pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_cos_pretrained.tar
 metric: COCO
-weights: output/fpn/faster_rcnn_r50_fpn_1x/model_final
+weights: output/faster_rcnn_r50_fpn_1x/model_final
 num_classes: 81
 
 FasterRCNN:

ppdet/modeling/architectures/mask_rcnn.py

@@ -149,7 +149,11 @@ class MaskRCNN(object):
             cond = fluid.layers.less_than(x=bbox_size, y=size)
 
             mask_pred = fluid.layers.create_global_var(
-                shape=[1], value=0.0, dtype='float32', persistable=False)
+                shape=[1],
+                value=0.0,
+                dtype='float32',
+                persistable=False,
+                name='mask_pred')
 
             with fluid.layers.control_flow.Switch() as switch:
                 with switch.case(cond):

tools/train.py

@@ -86,7 +86,6 @@ def main():
     place = fluid.CUDAPlace(0) if cfg.use_gpu else fluid.CPUPlace()
     exe = fluid.Executor(place)
 
-    model = create(main_arch)
     lr_builder = create('LearningRate')
     optim_builder = create('OptimizerBuilder')
 
@@ -95,6 +94,7 @@ def main():
     train_prog = fluid.Program()
     with fluid.program_guard(train_prog, startup_prog):
         with fluid.unique_name.guard():
+            model = create(main_arch)
             train_pyreader, feed_vars = create_feed(train_feed)
             train_fetches = model.train(feed_vars)
             loss = train_fetches['loss']
@@ -113,6 +113,7 @@ def main():
         eval_prog = fluid.Program()
         with fluid.program_guard(eval_prog, startup_prog):
             with fluid.unique_name.guard():
+                model = create(main_arch)
                 eval_pyreader, feed_vars = create_feed(eval_feed)
                 fetches = model.eval(feed_vars)
         eval_prog = eval_prog.clone(True)
@@ -120,8 +121,9 @@ def main():
         eval_reader = create_reader(eval_feed)
         eval_pyreader.decorate_sample_list_generator(eval_reader, place)
 
-        # parse train fetches
-        extra_keys = ['im_info', 'im_id'] if cfg.metric == 'COCO' else []
+        # parse eval fetches
+        extra_keys = ['im_info', 'im_id',
+                      'im_shape'] if cfg.metric == 'COCO' else []
         eval_keys, eval_values, eval_cls = parse_fetches(fetches, eval_prog,
                                                          extra_keys)
 
@@ -132,7 +134,7 @@ def main():
     sync_bn = getattr(model.backbone, 'norm_type', None) == 'sync_bn'
     # only enable sync_bn in multi GPU devices
     build_strategy.sync_batch_norm = sync_bn and devices_num > 1 \
-				     and cfg.use_gpu
+         and cfg.use_gpu
     train_compile_program = fluid.compiler.CompiledProgram(
         train_prog).with_data_parallel(
             loss_name=loss.name, build_strategy=build_strategy)