forked from EngineX-Ascend/enginex-ascend-910-vllm
init v0.11.0rc0
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@@ -5,8 +5,8 @@ import torch
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from tests.ut.base import TestBase
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from vllm_ascend.attention.attention_v1 import AscendAttentionState
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from vllm_ascend.ops.layers.experts_selector import (_native_grouped_topk,
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select_experts)
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from vllm_ascend.ops.moe.experts_selector import (_native_grouped_topk,
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select_experts)
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from vllm_ascend.quantization.w8a8 import (AscendC8KVCacheMethod,
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AscendW8A8FusedMoEMethod,
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AscendW8A8LinearMethod,
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@@ -784,7 +784,7 @@ class TestSelectExperts(TestBase):
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self.assertEqual(ids.shape, (self.num_tokens, self.top_k))
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self.assertEqual(ids.dtype, torch.int32)
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@patch('vllm_ascend.ops.layers.experts_selector._native_grouped_topk')
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@patch('vllm_ascend.ops.moe.experts_selector._native_grouped_topk')
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def test_grouped_topk_with_correction_bias(self, mock_grouped_topk):
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"""Test grouped topk with expert score correction bias"""
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mock_grouped_topk.return_value = torch.ones(self.num_tokens,
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