Fix load checkpoint (PaddlePaddle#250)

an1018 · Feb 22, 2020 · 3849c17 · 3849c17
1 parent 61a8b0e
commit 3849c17
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Showing 4 changed files with 13 additions and 249 deletions.
diff --git a/slim/quantization/README.md b/slim/quantization/README.md
@@ -76,7 +76,7 @@ python slim/quantization/train.py --not_quant_pattern yolo_output \
 
 
 通过`python slim/quantization/train.py --help`查看可配置参数。
-通过`python .tools/configure.py ${option_name} help`查看如何通过命令行覆盖配置文件中的参数。
+通过`python ./tools/configure.py help ${option_name}`查看如何通过命令行覆盖配置文件中的参数。
 
 
 

diff --git a/slim/quantization/export_model.py b/slim/quantization/export_model.py
@@ -21,7 +21,6 @@
 from paddle import fluid
 
 from ppdet.core.workspace import load_config, merge_config, create
-from ppdet.modeling.model_input import create_feed
 from ppdet.utils.cli import ArgsParser
 import ppdet.utils.checkpoint as checkpoint
 from tools.export_model import prune_feed_vars

diff --git a/slim/quantization/freeze.py b/slim/quantization/freeze.py
diff --git a/slim/quantization/train.py b/slim/quantization/train.py
@@ -166,14 +166,15 @@ def main():
 
     fuse_bn = getattr(model.backbone, 'norm_type', None) == 'affine_channel'
 
-    if FLAGS.resume_checkpoint:
-        checkpoint.load_checkpoint(exe, train_prog, FLAGS.resume_checkpoint)
-        start_iter = checkpoint.global_step()
-    elif cfg.pretrain_weights and fuse_bn and not ignore_params:
-        checkpoint.load_and_fusebn(exe, train_prog, cfg.pretrain_weights)
-    elif cfg.pretrain_weights:
-        checkpoint.load_params(
-            exe, train_prog, cfg.pretrain_weights, ignore_params=ignore_params)
+    if not FLAGS.resume_checkpoint:
+        if cfg.pretrain_weights and fuse_bn and not ignore_params:
+            checkpoint.load_and_fusebn(exe, train_prog, cfg.pretrain_weights)
+        elif cfg.pretrain_weights:
+            checkpoint.load_params(
+                exe,
+                train_prog,
+                cfg.pretrain_weights,
+                ignore_params=ignore_params)
     # insert quantize op in train_prog, return type is CompiledProgram
     train_prog = quant_aware(train_prog, place, config, for_test=False)
 
@@ -189,6 +190,9 @@ def main():
         compiled_eval_prog = fluid.compiler.CompiledProgram(eval_prog)
 
     start_iter = 0
+    if FLAGS.resume_checkpoint:
+        checkpoint.load_checkpoint(exe, eval_prog, FLAGS.resume_checkpoint)
+        start_iter = checkpoint.global_step()
 
     train_reader = create_reader(cfg.TrainReader,
                                  (cfg.max_iters - start_iter) * devices_num)