diff --git a/paddleslim/auto_compression/compressor.py b/paddleslim/auto_compression/compressor.py
index b7a86f08864e60bd73feff76cca3c3d84ef7cf50..df764017adc425847c28625fb8d63b88707954b6 100644
--- a/paddleslim/auto_compression/compressor.py
+++ b/paddleslim/auto_compression/compressor.py
@@ -248,6 +248,8 @@ class AutoCompression:
         if train_config.amp_config is not None:
             strategy.amp = True
             strategy.amp_configs = { ** train_config.amp_config}
+        if train_config.asp_config is not None:
+            strategy.asp = True
         return strategy
 
     def _prepare_program(self, program, feed_target_names, fetch_targets,
diff --git a/paddleslim/auto_compression/create_compressed_program.py b/paddleslim/auto_compression/create_compressed_program.py
index aae9f3ea2191fdb4d6d27c9e27c5daf805dbba56..5df2fdc029e406555172ddbd111c5556abf0d432 100644
--- a/paddleslim/auto_compression/create_compressed_program.py
+++ b/paddleslim/auto_compression/create_compressed_program.py
@@ -278,7 +278,8 @@ def build_distill_program(executor,
             loss.stop_gradient = False
 
             if 'prune_algo' in config:  ### prune & asp
-                if config['prune_algo'] == 'asp':
+                if config['prune_algo'] == 'asp' and not train_config.get(
+                        'use_fleet'):
                     optimizer = pruner.decorate(optimizer)
                 optimizer.minimize(loss)
             elif 'prune_strategy' in config:  ###unstructure prune
@@ -414,6 +415,8 @@ def build_prune_program(executor,
                         'prune_params_name'] is not None and param.name not in config[
                             'prune_params_name']:
                     excluded_params_name.append(param.name)
+                if "teacher_" in param.name:
+                    excluded_params_name.append(param.name)
             pruner.set_excluded_layers(train_program_info.program,
                                        excluded_params_name)
         elif config['prune_algo'] == 'transformer_pruner':