polish code with new pre-commit rule (#2923)

test/operators/test_rejection_top_p_sampling.py

@@ -13,17 +13,20 @@
 # limitations under the License.
 
 import unittest
+
 import numpy as np
 import paddle
+
 from fastdeploy.model_executor.ops.gpu import rejection_top_p_sampling
 
+
 class TestRejectionTopPSampling(unittest.TestCase):
     def setUp(self):
         """Initialize common test data"""
         self.batch_size = 10
         self.vocab_size = 103424
         paddle.seed(2023)
-        
+
         # Generate test data once for all tests
         self.pre_norm_prob_np = np.random.rand(self.batch_size, self.vocab_size).astype(np.float32)
         self.paddle_pre_norm_prob = paddle.to_tensor(self.pre_norm_prob_np)
@@ -32,12 +35,12 @@ class TestRejectionTopPSampling(unittest.TestCase):
     def test_top_p_sampling_reject_case1(self):
         """Test with fixed top_p=0.8 and different random seeds"""
         top_p_paddle = paddle.full((self.batch_size,), 0.8)
-        
+
         # Test with different seeds
         for seed in [1024, 2033, 2033]:
             samples = rejection_top_p_sampling(self.paddle_norm_prob, top_p_paddle, seed)
             self._validate_samples(samples)
-            
+
             # Basic validation
             self.assertTrue(paddle.all(samples >= 0))
             self.assertTrue(paddle.all(samples < self.vocab_size))
@@ -46,9 +49,9 @@ class TestRejectionTopPSampling(unittest.TestCase):
         """Test with varying top_p values across batch"""
         top_p_paddle = paddle.uniform(shape=[self.batch_size], min=0.1, max=1.0)
         samples = rejection_top_p_sampling(self.paddle_norm_prob, top_p_paddle, -1)
-        
+
         self._validate_samples(samples)
-        
+
         # Additional check that we're getting different results for different top_p
         unique_samples = len(paddle.unique(samples))
         print(f"Unique samples: {unique_samples}")
@@ -58,9 +61,10 @@ class TestRejectionTopPSampling(unittest.TestCase):
         """Common validation for all test cases"""
         self.assertTrue(paddle.all(samples >= 0))
         self.assertTrue(paddle.all(samples < self.vocab_size))
-        
+
         # Check dtype
         self.assertEqual(samples.dtype, paddle.int64)
 
+
 if __name__ == "__main__":
-    unittest.main()
+    unittest.main()