[Refactor]Refactor sampler (#2050)

Refactor Sampler implementation from patch way to inherit from vLLM
Sampler interface.

Next step: Make the op `TopKTopPSampler` in vLLM support custom ops
register mechanism

- vLLM version: v0.10.0
- vLLM main:
61a6905ab0

Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>

tests/ut/sample/test_sampler.py

@@ -0,0 +1,32 @@
+from unittest import mock
+
+import torch
+
+from tests.ut.base import TestBase
+from vllm_ascend.sample.sampler import AscendSampler, AscendTopKTopPSampler
+
+
+class TestAscendSampler(TestBase):
+
+    def test_init_with_raw_logprobs(self):
+        sampler = AscendSampler(logprobs_mode="raw_logprobs")
+        self.assertEqual(sampler.logprobs_mode, "raw_logprobs")
+        self.assertTrue(hasattr(sampler, 'topk_topp_sampler'))
+        self.assertIsInstance(sampler.topk_topp_sampler, AscendTopKTopPSampler)
+
+
+class TestAscendTopKTopPSampler(TestBase):
+
+    @mock.patch("torch_npu.npu_top_k_top_p")
+    def test_npu_topk_topp_called_when_optimized(self, mock_npu_op):
+        mock_npu_op.return_value = (torch.randn(1, 3))
+        sampler = AscendTopKTopPSampler()
+
+        logits = torch.tensor([[1.0, 2.0, 3.0]])
+        k = torch.tensor([2])
+        p = torch.tensor([0.9])
+        generators = {0: torch.Generator()}
+        generators[0].manual_seed(42)
+
+        sampler.forward_native(logits, generators, k, p)
+        mock_npu_op.assert_called_once_with(logits, p, k)