9b67c87b14
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>
33 lines
1.0 KiB
Python
33 lines
1.0 KiB
Python
from unittest import mock
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import torch
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from tests.ut.base import TestBase
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from vllm_ascend.sample.sampler import AscendSampler, AscendTopKTopPSampler
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class TestAscendSampler(TestBase):
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def test_init_with_raw_logprobs(self):
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sampler = AscendSampler(logprobs_mode="raw_logprobs")
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self.assertEqual(sampler.logprobs_mode, "raw_logprobs")
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self.assertTrue(hasattr(sampler, 'topk_topp_sampler'))
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self.assertIsInstance(sampler.topk_topp_sampler, AscendTopKTopPSampler)
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class TestAscendTopKTopPSampler(TestBase):
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@mock.patch("torch_npu.npu_top_k_top_p")
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def test_npu_topk_topp_called_when_optimized(self, mock_npu_op):
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mock_npu_op.return_value = (torch.randn(1, 3))
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sampler = AscendTopKTopPSampler()
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logits = torch.tensor([[1.0, 2.0, 3.0]])
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k = torch.tensor([2])
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p = torch.tensor([0.9])
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generators = {0: torch.Generator()}
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generators[0].manual_seed(42)
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sampler.forward_native(logits, generators, k, p)
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mock_npu_op.assert_called_once_with(logits, p, k)
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