fix blazeface nas (#5241)

static/slim/nas/blazeface.yml

@@ -93,3 +93,20 @@ EvalReader:
     mean: [104, 117, 123]
     std: [127.502231, 127.502231, 127.502231]
   batch_size: 1
+
+TestReader:
+  inputs_def:
+    fields: ['image', 'im_id', 'im_shape']
+  dataset:
+    !ImageFolder
+    use_default_label: true
+  sample_transforms:
+  - !DecodeImage
+    to_rgb: true
+  - !NormalizeImage
+    is_channel_first: false
+    is_scale: false
+    mean: [123, 117, 104]
+    std: [127.502231, 127.502231, 127.502231]
+  - !Permute {}
+  batch_size: 1

static/slim/nas/search_space/blazefacespace_nas.py

@@ -33,7 +33,9 @@ class BlazeFaceNasSpace(SearchSpaceBase):
         self.mid_filter_num = np.array([8, 12, 16, 20, 24, 32])
         self.double_filter_num = np.array(
             [8, 12, 16, 24, 32, 40, 48, 64, 72, 80, 88, 96])
-        self.use_5x5kernel = np.array([0, 1])
+        self.use_5x5kernel = np.array(
+            [0]
+        )  ### if constraint is latency, use 3x3 kernel, otherwise self.use_5x5kernel = np.array([0, 1])
 
     def init_tokens(self):
         return [2, 1, 3, 8, 2, 1, 2, 1, 1]
@@ -74,7 +76,8 @@ class BlazeFaceNasSpace(SearchSpaceBase):
             self.double_filter_num[tokens[3]]
         ]]
 
-        is_5x5kernel = True if self.use_5x5kernel[tokens[8]] else False
+        ### if constraint is latency, use 3x3 kernel, otherwise is_5x5kernel = True if self.use_5x5kernel[tokens[8]] else False
+        is_5x5kernel = False  ###True if self.use_5x5kernel[tokens[8]] else False
         return blaze_filters, double_blaze_filters, is_5x5kernel
 
     def token2arch(self, tokens=None):

static/slim/nas/train_nas.py

@@ -62,6 +62,8 @@ except ImportError as e:
 
 from paddleslim.analysis import flops, TableLatencyEvaluator
 from paddleslim.nas import SANAS
+### register search space to paddleslim
+import search_space
 
 
 @register