Post_training_quantizaion supports min_max methon (#23078)

* Post_training_quantizaion supports min_max methon

python/paddle/fluid/contrib/slim/tests/test_post_training_quantization_mobilenetv1.py

@@ -264,7 +264,7 @@ class TestPostTrainingQuantization(unittest.TestCase):
         ptq.save_quantized_model(self.int8_model)
 
     def run_test(self, model, algo, data_urls, data_md5s, quantizable_op_type,
-                 is_full_quantize, is_use_cache_file):
+                 is_full_quantize, is_use_cache_file, diff_threshold):
         infer_iterations = self.infer_iterations
         batch_size = self.batch_size
         sample_iterations = self.sample_iterations
@@ -296,11 +296,11 @@ class TestPostTrainingQuantization(unittest.TestCase):
         sys.stdout.flush()
 
         delta_value = fp32_acc1 - int8_acc1
-        self.assertLess(delta_value, 0.025)
+        self.assertLess(delta_value, diff_threshold)
 
 
-class TestPostTrainingForMobilenetv1(TestPostTrainingQuantization):
-    def test_post_training_mobilenetv1(self):
+class TestPostTrainingKLForMobilenetv1(TestPostTrainingQuantization):
+    def test_post_training_kl_mobilenetv1(self):
         model = "MobileNet-V1"
         algo = "KL"
         data_urls = [
@@ -310,10 +310,29 @@ class TestPostTrainingForMobilenetv1(TestPostTrainingQuantization):
         quantizable_op_type = [
             "conv2d", "depthwise_conv2d", "mul", "pool2d", "elementwise_add"
         ]
-        is_full_quantize = True
+        is_full_quantize = False
         is_use_cache_file = False
+        diff_threshold = 0.025
         self.run_test(model, algo, data_urls, data_md5s, quantizable_op_type,
-                      is_full_quantize, is_use_cache_file)
+                      is_full_quantize, is_use_cache_file, diff_threshold)
+
+
+class TestPostTrainingAbsMaxForMobilenetv1(TestPostTrainingQuantization):
+    def test_post_training_abs_max_mobilenetv1(self):
+        model = "MobileNet-V1"
+        algo = "abs_max"
+        data_urls = [
+            'http://paddle-inference-dist.bj.bcebos.com/int8/mobilenetv1_int8_model.tar.gz'
+        ]
+        data_md5s = ['13892b0716d26443a8cdea15b3c6438b']
+        quantizable_op_type = [
+            "conv2d", "depthwise_conv2d", "mul", "pool2d", "elementwise_add"
+        ]
+        is_full_quantize = False
+        is_use_cache_file = False
+        diff_threshold = 0.05
+        self.run_test(model, algo, data_urls, data_md5s, quantizable_op_type,
+                      is_full_quantize, is_use_cache_file, diff_threshold)
 
 
 if __name__ == '__main__':

python/paddle/fluid/contrib/slim/tests/test_post_training_quantization_resnet50.py

@@ -20,7 +20,7 @@ from test_post_training_quantization_mobilenetv1 import TestPostTrainingQuantiza
 class TestPostTrainingForResnet50(TestPostTrainingQuantization):
     def test_post_training_resnet50(self):
         model = "ResNet-50"
-        algo = "direct"
+        algo = "min_max"
         data_urls = [
             'http://paddle-inference-dist.bj.bcebos.com/int8/resnet50_int8_model.tar.gz'
         ]
@@ -28,8 +28,9 @@ class TestPostTrainingForResnet50(TestPostTrainingQuantization):
         quantizable_op_type = ["conv2d", "mul"]
         is_full_quantize = False
         is_use_cache_file = False
+        diff_threshold = 0.025
         self.run_test(model, algo, data_urls, data_md5s, quantizable_op_type,
-                      is_full_quantize, is_use_cache_file)
+                      is_full_quantize, is_use_cache_file, diff_threshold)
 
 
 if __name__ == '__main__':