23524f2ca4
### What this PR does / why we need it?
This pull request focuses on a significant refactoring effort within the
vllm-ascend project, specifically targeting operations optimized for the
Ascend 310P hardware. The changes aim to streamline the implementation
of core components like quantization and multi-head attention, making
the codebase more maintainable and robust. Concurrently, new unit tests
have been introduced to ensure the correctness and reliability of these
refactored modules.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
E2E test with qwen3-32b w8a8
- vLLM version: v0.15.0
- vLLM main:
d7e17aaacd
---------
Signed-off-by: pu-zhe <zpuaa@outlook.com>
68 lines
3.3 KiB
Python
68 lines
3.3 KiB
Python
from unittest.mock import MagicMock, patch
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from vllm.model_executor.layers.fused_moe import FusedMoE
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from vllm.model_executor.layers.fused_moe.config import FusedMoEConfig
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from vllm.model_executor.layers.linear import LinearBase
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from tests.ut.base import TestBase
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from vllm_ascend._310p.quantization.modelslim_config import AscendModelSlimConfig310
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from vllm_ascend.ops.linear import AscendUnquantizedLinearMethod
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class TestAscendModelSlimConfig310(TestBase):
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def setUp(self):
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self.sample_config = {
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"weight": "INT8",
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"layer1.weight": "INT8",
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"layer2.weight": "FLOAT",
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"fused_layer.weight": "FLOAT",
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"fused_layer.shard1.weight": "FLOAT",
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"fused_layer.shard2.weight": "FLOAT",
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"shard1.weight": "FLOAT",
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"shard2.weight": "FLOAT",
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}
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self.ascend_config = AscendModelSlimConfig310(self.sample_config)
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self.ascend_config.packed_modules_mapping = None
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def test_get_quant_method_for_linear_310(self):
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mock_config = MagicMock()
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mock_config.model_config.hf_config.model_type = None
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linear_layer = MagicMock(spec=LinearBase)
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# Test skipped layer
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with (
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patch("vllm_ascend._310p.quantization.modelslim_config.get_current_vllm_config", return_value=mock_config),
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patch.object(self.ascend_config, "is_layer_skipped_ascend", return_value=True)
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):
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method = self.ascend_config.get_quant_method(linear_layer, ".attn")
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self.assertIsInstance(method, AscendUnquantizedLinearMethod)
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# Test quantized layer
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mock_scheme = MagicMock()
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with (
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patch.object(self.ascend_config, "is_layer_skipped_ascend", return_value=False),
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patch("vllm_ascend._310p.quantization.modelslim_config.get_current_vllm_config", return_value=mock_config),
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patch("vllm_ascend._310p.quantization.modelslim_config.create_scheme_for_layer", return_value=mock_scheme),
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patch(
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"vllm_ascend._310p.quantization.modelslim_config.AscendLinearMethod", return_value=MagicMock()
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) as mock_ascend_linear,
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):
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method = self.ascend_config.get_quant_method(linear_layer, ".attn")
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self.assertIs(method, mock_ascend_linear.return_value)
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mock_ascend_linear.assert_called_once_with(mock_scheme)
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def test_get_quant_method_for_fused_moe_310(self):
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fused_moe_layer = MagicMock(spec=FusedMoE)
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fused_moe_layer.moe = MagicMock(spec=FusedMoEConfig)
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fused_moe_layer.moe_config = MagicMock(spec=FusedMoEConfig)
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mock_config = MagicMock()
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mock_config.model_config.hf_config.model_type = None
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mock_scheme = MagicMock()
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with (
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patch.object(self.ascend_config, "is_layer_skipped_ascend", return_value=False),
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patch("vllm_ascend._310p.quantization.modelslim_config.get_current_vllm_config", return_value=mock_config),
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patch("vllm_ascend._310p.quantization.modelslim_config.create_scheme_for_layer", return_value=mock_scheme),
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patch("vllm_ascend._310p.quantization.modelslim_config.AscendLinearMethod", return_value=MagicMock()),
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self.assertRaises(NotImplementedError),
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):
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self.ascend_config.get_quant_method(fused_moe_layer, "moe_layer")
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