d4d93db2c5
Signed-off-by: rshaw@neuralmagic.com <rshaw@neuralmagic.com> Co-authored-by: rshaw@neuralmagic.com <rshaw@neuralmagic.com> Co-authored-by: Nicolò Lucchesi <nlucches@redhat.com> Co-authored-by: Tyler Michael Smith <tyler@neuralmagic.com> Co-authored-by: Michael Goin <michael@neuralmagic.com>
37 lines
1.2 KiB
Python
37 lines
1.2 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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"""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, monkeypatch):
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# vllm_runner.apply_model() relies on V0 internals.
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monkeypatch.setenv("VLLM_USE_V1", "0")
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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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def check_model(model):
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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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llm.apply_model(check_model)
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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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