[Rebase] Rebase to vLLM 0.30.0 (#7820)
Signed-off-by: tzhouam <tzhouam@connect.ust.hk> Signed-off-by: Gao Han <hgaoaf@connect.ust.hk> Co-authored-by: Claude Opus 5 (1M context) <noreply@anthropic.com> Co-authored-by: Gao Han <hgaoaf@connect.ust.hk>
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@@ -178,7 +178,13 @@ class TestGlmImageAdaLayerNormZeroQuantization:
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def test_accepts_quant_config_parameter(self, mocker: MockerFixture):
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"""Verify the class accepts quant_config parameter."""
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# vLLM 0.30 resolves online quantization in resolve_quant_method():
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# a non-None online_quantization_config whose resolve_quant_method_cls()
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# returns a target raises on a checkpoint-quantized layer. A bare
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# MagicMock satisfies both, so declare no online quantization -- these
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# tests only assert the layer accepts and stores a quant_config.
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mock_quant_config = mocker.MagicMock()
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mock_quant_config.online_quantization_config = None
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layer = GlmImageAdaLayerNormZero(
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embedding_dim=512,
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dim=2560,
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@@ -220,7 +226,13 @@ class TestGlmImageAdaLayerNormContinuousQuantization:
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def test_accepts_quant_config_parameter(self, mocker: MockerFixture):
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"""Verify the class accepts quant_config parameter."""
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# vLLM 0.30 resolves online quantization in resolve_quant_method():
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# a non-None online_quantization_config whose resolve_quant_method_cls()
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# returns a target raises on a checkpoint-quantized layer. A bare
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# MagicMock satisfies both, so declare no online quantization -- these
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# tests only assert the layer accepts and stores a quant_config.
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mock_quant_config = mocker.MagicMock()
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mock_quant_config.online_quantization_config = None
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layer = GlmImageAdaLayerNormContinuous(
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embedding_dim=2560,
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conditioning_embedding_dim=512,
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@@ -260,7 +272,13 @@ class TestGlmImageAttentionQuantization:
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def test_accepts_quant_config_parameter(self, mocker: MockerFixture):
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"""Verify GlmImageAttention accepts quant_config parameter."""
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# vLLM 0.30 resolves online quantization in resolve_quant_method():
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# a non-None online_quantization_config whose resolve_quant_method_cls()
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# returns a target raises on a checkpoint-quantized layer. A bare
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# MagicMock satisfies both, so declare no online quantization -- these
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# tests only assert the layer accepts and stores a quant_config.
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mock_quant_config = mocker.MagicMock()
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mock_quant_config.online_quantization_config = None
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attn = GlmImageAttention(
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dim=2560,
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num_heads=64,
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@@ -286,7 +304,13 @@ class TestColumnParallelModulesQuantization:
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def test_column_parallel_gelu_accepts_quant_config(self, mocker: MockerFixture):
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"""Verify ColumnParallelGELU accepts quant_config."""
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# vLLM 0.30 resolves online quantization in resolve_quant_method():
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# a non-None online_quantization_config whose resolve_quant_method_cls()
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# returns a target raises on a checkpoint-quantized layer. A bare
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# MagicMock satisfies both, so declare no online quantization -- these
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# tests only assert the layer accepts and stores a quant_config.
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mock_quant_config = mocker.MagicMock()
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mock_quant_config.online_quantization_config = None
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layer = ColumnParallelGELU(
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dim_in=2560,
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dim_out=10240,
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@@ -297,7 +321,13 @@ class TestColumnParallelModulesQuantization:
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def test_column_parallel_silu_accepts_quant_config(self, mocker: MockerFixture):
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"""Verify ColumnParallelSiLU accepts quant_config."""
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# vLLM 0.30 resolves online quantization in resolve_quant_method():
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# a non-None online_quantization_config whose resolve_quant_method_cls()
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# returns a target raises on a checkpoint-quantized layer. A bare
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# MagicMock satisfies both, so declare no online quantization -- these
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# tests only assert the layer accepts and stores a quant_config.
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mock_quant_config = mocker.MagicMock()
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mock_quant_config.online_quantization_config = None
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layer = ColumnParallelSiLU(
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dim_in=2560,
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dim_out=10240,
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@@ -312,7 +342,13 @@ class TestGlmImageFeedForwardQuantization:
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def test_accepts_quant_config_parameter(self, mocker: MockerFixture):
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"""Verify GlmImageFeedForward accepts quant_config parameter."""
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# vLLM 0.30 resolves online quantization in resolve_quant_method():
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# a non-None online_quantization_config whose resolve_quant_method_cls()
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# returns a target raises on a checkpoint-quantized layer. A bare
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# MagicMock satisfies both, so declare no online quantization -- these
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# tests only assert the layer accepts and stores a quant_config.
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mock_quant_config = mocker.MagicMock()
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mock_quant_config.online_quantization_config = None
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ff = GlmImageFeedForward(
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dim=2560,
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dim_out=2560,
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@@ -358,7 +394,13 @@ class TestGlmImageTransformerBlockQuantization:
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def test_accepts_quant_config_parameter(self, mocker: MockerFixture):
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"""Verify GlmImageTransformerBlock accepts quant_config parameter."""
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# vLLM 0.30 resolves online quantization in resolve_quant_method():
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# a non-None online_quantization_config whose resolve_quant_method_cls()
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# returns a target raises on a checkpoint-quantized layer. A bare
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# MagicMock satisfies both, so declare no online quantization -- these
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# tests only assert the layer accepts and stores a quant_config.
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mock_quant_config = mocker.MagicMock()
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mock_quant_config.online_quantization_config = None
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parallel_config = DiffusionParallelConfig(
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tensor_parallel_size=1,
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sequence_parallel_size=1,
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@@ -534,7 +576,13 @@ class TestGlmImageTransformer2DModelQuantization:
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"""Verify the model accepts quant_config parameter."""
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from vllm_omni.diffusion.data import OmniDiffusionConfig
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# vLLM 0.30 resolves online quantization in resolve_quant_method():
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# a non-None online_quantization_config whose resolve_quant_method_cls()
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# returns a target raises on a checkpoint-quantized layer. A bare
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# MagicMock satisfies both, so declare no online quantization -- these
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# tests only assert the layer accepts and stores a quant_config.
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mock_quant_config = mocker.MagicMock()
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mock_quant_config.online_quantization_config = None
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parallel_config = DiffusionParallelConfig(
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tensor_parallel_size=1,
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sequence_parallel_size=1,
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@@ -607,7 +655,13 @@ class TestGlmImageTransformer2DModelQuantization:
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"""Verify norm_out (output layer) does NOT use quantization to preserve precision."""
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from vllm_omni.diffusion.data import OmniDiffusionConfig
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# vLLM 0.30 resolves online quantization in resolve_quant_method():
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# a non-None online_quantization_config whose resolve_quant_method_cls()
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# returns a target raises on a checkpoint-quantized layer. A bare
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# MagicMock satisfies both, so declare no online quantization -- these
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# tests only assert the layer accepts and stores a quant_config.
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mock_quant_config = mocker.MagicMock()
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mock_quant_config.online_quantization_config = None
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parallel_config = DiffusionParallelConfig(
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tensor_parallel_size=1,
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sequence_parallel_size=1,
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@@ -1380,6 +1380,8 @@ def test_text_encoder_linear_delegates_quantization_to_vllm_factory():
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method = UnquantizedLinearMethod()
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quant_config = Mock()
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quant_config.get_quant_method.return_value = method
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# vLLM 0.30: no online quantization for this checkpoint-quantized layer
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quant_config.online_quantization_config = None
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prefix = "text_encoder.text_model.layers.0.mlp.gate_up_proj"
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with (
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@@ -1396,7 +1398,9 @@ def test_text_encoder_linear_delegates_quantization_to_vllm_factory():
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)
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assert linear.quant_method is method
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quant_config.get_quant_method.assert_called_once_with(linear, prefix=prefix)
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# vLLM 0.30 resolves the method through resolve_quant_method(), which calls
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# get_quant_method(layer, prefix) POSITIONALLY; 0.29 passed prefix= by keyword.
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quant_config.get_quant_method.assert_called_once_with(linear, prefix)
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def test_distributed_layerwise_offload_stages_vae_component():
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