Fix bug of loading saved model and tests. (#1744)

* fix bug of loading saved model.

* fix distill demo.

* fix flops.py.

* fix tests.

Author: zzjjay

demo/distillation/distill.py

@@ -97,8 +97,8 @@ def compress(args):
         raise ValueError("{} is not supported.".format(args.data))
     image_shape = [int(m) for m in image_shape.split(",")]
 
-    assert args.model in model_list, "{} is not in lists: {}".format(args.model,
-                                                                     model_list)
+    assert args.model in model_list, "{} is not in lists: {}".format(
+        args.model, model_list)
     student_program = paddle.static.Program()
     s_startup = paddle.static.Program()
     places = paddle.static.cuda_places(
@@ -202,7 +202,7 @@ def if_exist(var):
                 _logger.info(
                     "train_epoch {} step {} lr {:.6f}, loss {:.6f}, class loss {:.6f}, distill loss {:.6f}".
                     format(epoch_id, step_id,
-                           lr.get_lr(), loss_1[0], loss_2[0], loss_3[0]))
+                           lr.get_lr(), loss_1, loss_2, loss_3))
             lr.step()
         val_acc1s = []
         val_acc5s = []
@@ -216,8 +216,7 @@ def if_exist(var):
             if step_id % args.log_period == 0:
                 _logger.info(
                     "valid_epoch {} step {} loss {:.6f}, top1 {:.6f}, top5 {:.6f}".
-                    format(epoch_id, step_id, val_loss[0], val_acc1[0],
-                           val_acc5[0]))
+                    format(epoch_id, step_id, val_loss, val_acc1, val_acc5))
         if args.save_inference:
             paddle.static.save_inference_model(
                 os.path.join("./saved_models", str(epoch_id)), [image], [out],

paddleslim/analysis/flops.py

@@ -84,7 +84,8 @@ def _graph_flops(graph, only_conv=True, detail=False):
             output_shape = op.outputs("Out")[0].shape()
             _, c_out, h_out, w_out = output_shape
             k_size = op.attr("ksize")
-            flops += h_out * w_out * c_out * (k_size[0]**2)
+            if op.attr('pooling_type') == 'avg':
+                flops += (h_out * w_out * c_out * (k_size[0]**2) * 2)
 
         elif op.type() in ['mul', 'matmul', 'matmul_v2']:
             x_shape = list(op.inputs("X")[0].shape())
@@ -101,7 +102,11 @@ def _graph_flops(graph, only_conv=True, detail=False):
             input_shape = list(op.inputs("X")[0].shape())
             if input_shape[0] == -1:
                 input_shape[0] = 1
-            flops += np.product(input_shape)
+            if op.type() == 'batch_norm':
+                op_flops = np.product(input_shape) * 2
+            else:
+                op_flops = np.product(input_shape)
+            flops += op_flops
 
     if detail:
         return flops, params2flops

paddleslim/auto_compression/compressor.py

@@ -570,7 +570,7 @@ def create_tmp_dir(self, base_dir, prefix="tmp"):
         tmp_base_name = "_".join([prefix, str(os.getppid()), s_datetime])
         tmp_dir = os.path.join(base_dir, tmp_base_name)
         if not os.path.exists(tmp_dir):
-            os.makedirs(tmp_dir)
+            os.makedirs(tmp_dir, exist_ok=True)
         return tmp_dir
 
     def compress(self):
@@ -609,10 +609,17 @@ def compress(self):
             shutil.rmtree(self.tmp_dir)
 
             if self.eval_function is not None and self.final_metric < 0.0:
+                model_filename = None
+                if self.model_filename is None:
+                    model_filename = "model.pdmodel"
+                elif self.model_filename.endswith(".pdmodel"):
+                    model_filename = self.model_filename
+                else:
+                    model_filename = self.model_filename + '.pdmodel'
+
                 [inference_program, feed_target_names, fetch_targets]= load_inference_model( \
                     final_model_path, \
-                    model_filename=self.model_filename, params_filename=self.params_filename,
-                    executor=self._exe)
+                    model_filename=model_filename, executor=self._exe)
                 self.final_metric = self.eval_function(
                     self._exe, inference_program, feed_target_names,
                     fetch_targets)

tests/dygraph/test_flops.py

@@ -73,9 +73,8 @@ def runTest(self):
 
 def add_cases(suite):
     suite.addTest(
-        TestFlops(
-            net=paddle.vision.models.mobilenet_v1, gt=11792896.0))
-    suite.addTest(TestFlops(net=paddle.vision.models.resnet50, gt=83872768.0))
+        TestFlops(net=paddle.vision.models.mobilenet_v1, gt=12920832.0))
+    suite.addTest(TestFlops(net=paddle.vision.models.resnet50, gt=86112768.0))
     suite.addTest(TestFLOPsCase1())
     suite.addTest(TestFLOPsCase2())