Reduce test_calibration test time by using large batchsize

test=develop

python/paddle/fluid/contrib/tests/test_calibration.py

@@ -147,10 +147,11 @@ class TestCalibrationForResnet50(unittest.TestCase):
                                                    self.data_cache_folder)
         os.system(cmd)
 
-        self.batch_size = 1
-        self.sample_iterations = 50
+        self.batch_size = 1 if os.environ.get('DATASET') == 'full' else 50
+        self.sample_iterations = 50 if os.environ.get(
+            'DATASET') == 'full' else 1
         self.infer_iterations = 50000 if os.environ.get(
-            'DATASET') == 'full' else 50
+            'DATASET') == 'full' else 1
 
     def cache_unzipping(self, target_folder, zip_path):
         if not os.path.exists(target_folder):
@@ -279,15 +280,15 @@ class TestCalibrationForResnet50(unittest.TestCase):
     def test_calibration(self):
         self.download_model()
         print("Start FP32 inference for {0} on {1} images ...").format(
-            self.model, self.infer_iterations)
+            self.model, self.infer_iterations * self.batch_size)
         (fp32_throughput, fp32_latency,
          fp32_acc1) = self.run_program(self.model_cache_folder + "/model")
         print("Start INT8 calibration for {0} on {1} images ...").format(
-            self.model, self.sample_iterations)
+            self.model, self.sample_iterations * self.batch_size)
         self.run_program(
             self.model_cache_folder + "/model", True, algo=self.algo)
         print("Start INT8 inference for {0} on {1} images ...").format(
-            self.model, self.infer_iterations)
+            self.model, self.infer_iterations * self.batch_size)
         (int8_throughput, int8_latency,
          int8_acc1) = self.run_program("calibration_out")
         delta_value = fp32_acc1 - int8_acc1