[1/N][Refactor][Quantization] remove redundant quantizer class (#2680)
### What this PR does / why we need it?
AscendQuantizer/LLMQuantizer class is used to select quant method based
on quant config and some other arguments,
but it is more simple and clean replacing these classes with map. So i
remove them.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
ut and e2e test
- vLLM version: v0.10.1.1
- vLLM main:
6997a25ac6
Signed-off-by: 22dimensions <waitingwind@foxmail.com>
This commit is contained in:
22dimensions
@@ -156,33 +156,22 @@ class TestAscendKVCacheMethod(TestBase):
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def setUp(self):
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# Setup common test fixtures
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self.mock_quant_config = MagicMock(spec=AscendQuantConfig)
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self.mock_quant_config.quant_description = {"some_config": "value"}
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self.prefix = "attention_layer"
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self.mock_quant_config.quant_description = {"kv_quant_type": "C8"}
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self.prefix = "layer.attn"
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# Mock the quantizer and quant_method
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self.mock_quantizer = MagicMock()
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# Mock quant_method
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self.mock_quant_method = MagicMock()
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# Patch the AscendQuantizer
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self.quantizer_patcher = patch(
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'vllm_ascend.quantization.quant_config.AscendQuantizer.get_quantizer',
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return_value=self.mock_quantizer)
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self.mock_get_quantizer = self.quantizer_patcher.start()
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self.mock_quantizer.build_attention_method.return_value = self.mock_quant_method
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self.patcher = patch(
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'vllm_ascend.quantization.quant_config.get_quant_method')
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self.mock_get_quant_method = self.patcher.start()
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self.mock_get_quant_method.return_value = self.mock_quant_method
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# Create instance
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self.kv_cache_method = AscendKVCacheMethod(self.mock_quant_config,
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self.prefix)
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def tearDown(self):
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self.quantizer_patcher.stop()
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def test_init(self):
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"""Test initialization with proper quantizer setup."""
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self.mock_get_quantizer.assert_called_once_with(
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self.mock_quant_config.quant_description, self.prefix)
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self.mock_quantizer.build_attention_method.assert_called_once()
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self.patcher.stop()
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def test_create_weights(self):
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"""Test create_weights delegates to quant_method."""
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@@ -1,145 +0,0 @@
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from unittest.mock import MagicMock, patch
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from tests.ut.base import TestBase
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from vllm_ascend.quantization.quant_config import AscendQuantConfig
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from vllm_ascend.quantization.quantizer import (VLLMAscendQuantizer,
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W4A8DYNAMICQuantizer,
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W8A8Quantizer)
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SUPPORT_ASCEND_QUANTIZER_TYPE = {"test": "1"}
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class TestGetQuantizer(TestBase):
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def setUp(self):
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# Setup common test fixtures
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self.supported_types = {
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'INT8': MagicMock(_instance=None),
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'FP16': MagicMock(_instance=None),
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'C8': MagicMock(_instance=None)
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}
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self.original_supported_types = SUPPORT_ASCEND_QUANTIZER_TYPE.copy()
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SUPPORT_ASCEND_QUANTIZER_TYPE.update(self.supported_types)
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self.mock_quant_config = MagicMock(spec=AscendQuantConfig)
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self.mock_quant_config.quant_description = {"some_config": "value"}
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def tearDown(self):
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# Restore original supported types
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SUPPORT_ASCEND_QUANTIZER_TYPE.clear()
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SUPPORT_ASCEND_QUANTIZER_TYPE.update(self.original_supported_types)
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def test_get_quantizer_fa(self):
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"""Test successful quantizer retrieval for different cases."""
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# Setup
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quant_description = {'fa_quant_type': 'C8'}
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prefix = '.attn'
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expected_type = 'C8'
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with patch.dict(
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'vllm_ascend.quantization.quantizer.SUPPORT_ASCEND_QUANTIZER_TYPE',
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SUPPORT_ASCEND_QUANTIZER_TYPE):
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result = VLLMAscendQuantizer.get_quantizer(
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quant_description,
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prefix,
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packed_modules_mapping={"some": "mapping"})
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# Verify
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self.assertIsNotNone(result)
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self.assertEqual(result,
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self.supported_types[expected_type]._instance)
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self.supported_types[expected_type].assert_called_once_with(
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quant_description)
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def test_get_quantizer_kv(self):
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"""Test successful quantizer retrieval for different cases."""
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# Setup
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quant_description = {'kv_quant_type': 'C8'}
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prefix = '.attn'
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expected_type = 'C8'
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with patch.dict(
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'vllm_ascend.quantization.quantizer.SUPPORT_ASCEND_QUANTIZER_TYPE',
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SUPPORT_ASCEND_QUANTIZER_TYPE):
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result = VLLMAscendQuantizer.get_quantizer(
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quant_description,
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prefix,
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packed_modules_mapping={"some": "mapping"})
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# Verify
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self.assertIsNotNone(result)
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self.assertEqual(result,
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self.supported_types[expected_type]._instance)
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self.supported_types[expected_type].assert_called_once_with(
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quant_description)
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def test_get_quantizer_linear(self):
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"""Test successful quantizer retrieval for different cases."""
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# Setup
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quant_description = {'linear_type': 'INT8'}
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prefix = 'nothing'
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expected_type = 'INT8'
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with patch('vllm_ascend.quantization.quantizer.VLLMAscendQuantizer.get_linear_quant_type',
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return_value=expected_type), \
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patch.dict('vllm_ascend.quantization.quantizer.SUPPORT_ASCEND_QUANTIZER_TYPE', SUPPORT_ASCEND_QUANTIZER_TYPE):
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result = VLLMAscendQuantizer.get_quantizer(
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quant_description,
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prefix,
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packed_modules_mapping={"some": "mapping"})
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# Verify
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self.assertIsNotNone(result)
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self.assertEqual(result,
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self.supported_types[expected_type]._instance)
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self.supported_types[expected_type].assert_called_once_with(
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quant_description)
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class TestW8A8Quantizer(TestBase):
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def setUp(self):
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self.quantizer = W8A8Quantizer(quant_description={})
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def test_build_linear_method(self):
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with patch('vllm_ascend.quantization.quantizer.AscendW8A8LinearMethod',
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return_value=MagicMock()) as mock_linear:
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result = self.quantizer.build_linear_method()
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mock_linear.assert_called_once_with()
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self.assertIsInstance(result, MagicMock)
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def test_build_moe_method(self):
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with patch(
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'vllm_ascend.quantization.quantizer.AscendW8A8FusedMoEMethod',
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return_value=MagicMock()) as mock_linear:
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result = self.quantizer.build_moe_method()
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mock_linear.assert_called_once_with()
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self.assertIsInstance(result, MagicMock)
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def test_build_attention_method(self):
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with patch('vllm_ascend.quantization.quantizer.AscendC8KVCacheMethod',
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return_value=MagicMock()) as mock_linear:
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result = self.quantizer.build_attention_method()
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mock_linear.assert_called_once_with()
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self.assertIsInstance(result, MagicMock)
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class TestW4A8DYNAMICQuantizer(TestBase):
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def setUp(self):
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self.quantizer = W4A8DYNAMICQuantizer(quant_description={})
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def test_build_linear_method(self):
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with patch(
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'vllm_ascend.quantization.quantizer.AscendW4A8DynamicLinearMethod',
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return_value=MagicMock()) as mock_linear:
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result = self.quantizer.build_linear_method()
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mock_linear.assert_called_once_with()
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self.assertIsInstance(result, MagicMock)
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def test_build_moe_method(self):
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with patch(
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'vllm_ascend.quantization.quantizer.AscendW4A8DynamicFusedMoEMethod',
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return_value=MagicMock()) as mock_fused_moe:
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result = self.quantizer.build_moe_method()
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mock_fused_moe.assert_called_once_with()
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self.assertIsInstance(result, MagicMock)
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62
tests/ut/quantization/test_utils.py
Normal file
62
tests/ut/quantization/test_utils.py
Normal file
@@ -0,0 +1,62 @@
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import types
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from tests.ut.base import TestBase
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from vllm_ascend.quantization.utils import (ASCEND_QUANTIZATION_METHOD_MAP,
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get_quant_method)
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class TestGetQuantMethod(TestBase):
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def setUp(self):
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self.original_quantization_method_map = ASCEND_QUANTIZATION_METHOD_MAP.copy(
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)
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for quant_type, layer_map in ASCEND_QUANTIZATION_METHOD_MAP.items():
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for layer_type in layer_map.keys():
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ASCEND_QUANTIZATION_METHOD_MAP[quant_type][
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layer_type] = types.new_class(f"{quant_type}_{layer_type}")
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def tearDown(self):
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# Restore original map
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ASCEND_QUANTIZATION_METHOD_MAP.clear()
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ASCEND_QUANTIZATION_METHOD_MAP.update(
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self.original_quantization_method_map)
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def test_linear_quant_methods(self):
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for quant_type, layer_map in ASCEND_QUANTIZATION_METHOD_MAP.items():
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if "linear" in layer_map.keys():
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prefix = "linear_layer"
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cls = layer_map["linear"]
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method = get_quant_method({"linear_layer.weight": quant_type},
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prefix, "linear")
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self.assertIsInstance(method, cls)
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def test_moe_quant_methods(self):
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for quant_type, layer_map in ASCEND_QUANTIZATION_METHOD_MAP.items():
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if "moe" in layer_map.keys():
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prefix = "layer"
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cls = layer_map["moe"]
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method = get_quant_method({"layer.weight": quant_type}, prefix,
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"moe")
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self.assertIsInstance(method, cls)
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def test_with_fa_quant_type(self):
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quant_description = {"fa_quant_type": "C8"}
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method = get_quant_method(quant_description, ".attn", "attention")
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self.assertIsInstance(
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method, ASCEND_QUANTIZATION_METHOD_MAP["C8"]["attention"])
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def test_with_kv_quant_type(self):
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quant_description = {"kv_quant_type": "C8"}
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method = get_quant_method(quant_description, ".attn", "attention")
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self.assertIsInstance(
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method, ASCEND_QUANTIZATION_METHOD_MAP["C8"]["attention"])
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def test_invalid_layer_type(self):
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quant_description = {"linear_layer.weight": "W8A8"}
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with self.assertRaises(NotImplementedError):
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get_quant_method(quant_description, "linear_layer", "unsupported")
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def test_invalid_quant_type(self):
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quant_description = {"linear_layer.weight": "UNKNOWN"}
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with self.assertRaises(NotImplementedError):
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get_quant_method(quant_description, "linear_layer", "linear")
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