de0526f668
Signed-off-by: kewang-xlnx <kewang@xilinx.com> Signed-off-by: kewang2 <kewang2@amd.com> Co-authored-by: kewang2 <kewang2@amd.com> Co-authored-by: Michael Goin <michael@neuralmagic.com>
31 lines
1.1 KiB
Python
31 lines
1.1 KiB
Python
"""Test model set-up and weight loading for quark-quantized models.
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Run `pytest tests/quantization/test_quark.py`.
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"""
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import torch
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from vllm.model_executor.layers.quantization.quark.quark import ( # noqa: E501
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QuarkLinearMethod, QuarkW8A8Fp8)
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def test_quark_fp8(vllm_runner):
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model_path = "amd/Llama-3.1-8B-Instruct-FP8-KV-Quark-test"
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with vllm_runner(model_path) as llm:
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model = llm.model.llm_engine.model_executor.driver_worker.model_runner.model # noqa: E501
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layer = model.model.layers[0]
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qkv_proj = layer.self_attn.qkv_proj
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assert isinstance(qkv_proj.quant_method, QuarkLinearMethod)
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assert isinstance(qkv_proj.scheme, QuarkW8A8Fp8)
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if isinstance(qkv_proj.scheme, QuarkW8A8Fp8):
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assert len(qkv_proj.input_scale.shape) == 0
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assert qkv_proj.weight.dtype is torch.float8_e4m3fn
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#assert qkv_proj.weight.dtype is torch.float8_e4m3fnuz
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assert len(qkv_proj.weight_scale.shape) == 0
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output = llm.generate_greedy("Hello my name is", max_tokens=20)
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assert output
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