【Hackathon 9th No.49】add test_pre_cache_len_concat

tests/operators/test_pre_cache_len_concat.py

@@ -0,0 +1,42 @@
+import unittest
+
+import numpy as np
+import paddle
+
+from fastdeploy.model_executor.ops.gpu import pre_cache_len_concat
+
+
+class TestPreCacheLenConcat(unittest.TestCase):
+    def setUp(self):
+        paddle.set_device("gpu")
+
+    def test_basic_functionality(self):
+        batch_size = 3
+        max_dec_len, block_size = 16, 4
+
+        seq_lens_decoder_np = np.array([8, 4, 2], dtype=np.int32)
+        seq_lens_this_time_np = np.array([2, 3, 1], dtype=np.int32)
+
+        seq_lens_decoder = paddle.to_tensor(seq_lens_decoder_np, dtype="int32")
+        seq_lens_this_time = paddle.to_tensor(seq_lens_this_time_np, dtype="int32")
+
+        outputs = pre_cache_len_concat(seq_lens_decoder, seq_lens_this_time, max_dec_len, block_size)
+        cu_seqlens_k, batch_ids, tile_ids, num_blocks, kv_token_num = [out.numpy() for out in outputs]
+
+        # Shape checks
+        self.assertEqual(cu_seqlens_k.shape[0], batch_size + 1)
+        self.assertEqual(batch_ids.shape, tile_ids.shape)
+        self.assertEqual(num_blocks.shape, (1,))
+        self.assertEqual(kv_token_num.shape, (1,))
+
+        # Basic value checks
+        self.assertTrue(np.all(np.diff(cu_seqlens_k) >= 0))
+        self.assertGreaterEqual(num_blocks[0], 0)
+        self.assertGreaterEqual(kv_token_num[0], 0)
+
+        # # kv_token_num equals cu_seqlens_k[-1]
+        self.assertEqual(kv_token_num[0], cu_seqlens_k[-1])
+
+
+if __name__ == "__main__":
+    unittest.main()