Fix TF OOB 200 EfficientDet regression on TFnewAPI (#1066)

Author: zehao-intel

examples/tensorflow/oob_models/quantization/ptq/model_detail.py

@@ -364,6 +364,26 @@
                   'input/item_onehot':np.array([[0] * 3706] * 10, dtype='float32')
                   },
         'output': ['evaluation/TopKV2',]
-    }
+    },
+    # EfficientDet-D2-768x768
+    {
+        'model_name': 'EfficientDet-D2-768x768',
+        'input': {'input': generate_data([768, 768, 3]),},
+        'output': ['class_net/class-predict_1/BiasAdd', 'class_net/class-predict_2/BiasAdd', 
+        'class_net/class-predict_3/BiasAdd', 'class_net/class-predict_4/BiasAdd', 'box_net/box-predict_1/BiasAdd', 
+        'box_net/box-predict_2/BiasAdd', 'box_net/box-predict_3/BiasAdd', 'box_net/box-predict_4/BiasAdd'],
+        'low': -1.0,
+        'high': 1.0
+    },
+    # EfficientDet-D4-1024x1024
+    {
+        'model_name': 'EfficientDet-D4-1024x1024',
+        'input': {'input': generate_data([1024, 1024, 3]),},
+        'output': ['class_net/class-predict_1/BiasAdd', 'class_net/class-predict_2/BiasAdd', 
+        'class_net/class-predict_3/BiasAdd', 'class_net/class-predict_4/BiasAdd', 'box_net/box-predict_1/BiasAdd', 
+        'box_net/box-predict_2/BiasAdd', 'box_net/box-predict_3/BiasAdd', 'box_net/box-predict_4/BiasAdd'],
+        'low': -1.0,
+        'high': 1.0
+    },
 ]
 

examples/tensorflow/oob_models/quantization/ptq/run_tuning.sh

@@ -81,6 +81,8 @@ function set_args {
   NeuMF
   PRNet
   DIEN_Deep-Interest-Evolution-Network
+  EfficientDet-D2-768x768
+  EfficientDet-D4-1024x1024
   --------
   )
 

examples/tensorflow/oob_models/quantization/ptq/tf_benchmark.py

@@ -242,6 +242,9 @@ def __iter__(self):
     args = parser.parse_args()
 
 
+    # the range of dummy data
+    low = 1.0
+    high = 20.0
     # benchmark PB model directly
     find_graph_def = tf_v1.GraphDef()
     if args.model_path and not args.model_name:
@@ -290,6 +293,10 @@ def __iter__(self):
                 model_detail = model
                 model_detail['model_dir'] = args.model_path
                 model_detail['ckpt'] = args.is_meta
+                if 'low' in model_detail.keys():
+                    low = model_detail['low']
+                if 'high' in model_detail.keys():
+                    high = model_detail['high']
                 break
         if not model_detail:
             logger.error("Model undefined.")
@@ -336,7 +343,7 @@ def __iter__(self):
         else:
             dataset = quantizer.dataset(dataset_type='dummy',
                                         shape=inputs_shape,
-                                        low=1.0, high=20.0,
+                                        low=low, high=high,
                                         dtype=inputs_dtype,
                                         label=True)
             dataloader_dict = {'wide_deep': WidedeepDataloader}