lazy import smac (#1361)

paddleslim/quant/__init__.py

@@ -35,7 +35,7 @@ try:
 except Exception as e:
     _logger.warning(e)
     _logger.warning(
-        f"If you want to use training-aware and post-training quantization, "
-        "please use Paddle >= {min_paddle_version} or develop version")
+        "If you want to use training-aware and post-training quantization, "
+        "please use Paddle >= {} or develop version".format(min_paddle_version))
 
 from .quant_embedding import quant_embedding

paddleslim/quant/post_quant_hpo.py

@@ -29,13 +29,7 @@ import shutil
 import glob
 from scipy.stats import wasserstein_distance
 
-# smac
-from ConfigSpace.hyperparameters import CategoricalHyperparameter, \
-    UniformFloatHyperparameter, UniformIntegerHyperparameter
-from smac.configspace import ConfigurationSpace
-from smac.facade.smac_hpo_facade import SMAC4HPO
-from smac.scenario.scenario import Scenario
-
+import pkg_resources as pkg
 from paddleslim.common import get_logger
 from paddleslim.quant import quant_post
 
@@ -417,6 +411,18 @@ def quant_post_hpo(
         None
     """
 
+    try:
+        pkg.require('smac')
+    except:
+        from pip._internal import main
+        main(['install', 'smac'])
+    # smac
+    from ConfigSpace.hyperparameters import CategoricalHyperparameter, \
+        UniformFloatHyperparameter, UniformIntegerHyperparameter
+    from smac.configspace import ConfigurationSpace
+    from smac.facade.smac_hpo_facade import SMAC4HPO
+    from smac.scenario.scenario import Scenario
+
     global g_quant_config
     g_quant_config = QuantConfig(
         executor, place, model_dir, quantize_model_path, algo, hist_percent,

requirements.txt

@@ -4,4 +4,3 @@ matplotlib
 pillow 
 pyyaml
 scikit-learn
-smac