e489ad7a21
- **Add SPDX license headers to python source files**
- **Check for SPDX headers using pre-commit**
commit 9d7ef44c3cfb72ca4c32e1c677d99259d10d4745
Author: Russell Bryant <rbryant@redhat.com>
Date: Fri Jan 31 14:18:24 2025 -0500
Add SPDX license headers to python source files
This commit adds SPDX license headers to python source files as
recommended to
the project by the Linux Foundation. These headers provide a concise way
that is
both human and machine readable for communicating license information
for each
source file. It helps avoid any ambiguity about the license of the code
and can
also be easily used by tools to help manage license compliance.
The Linux Foundation runs license scans against the codebase to help
ensure
we are in compliance with the licenses of the code we use, including
dependencies. Having these headers in place helps that tool do its job.
More information can be found on the SPDX site:
- https://spdx.dev/learn/handling-license-info/
Signed-off-by: Russell Bryant <rbryant@redhat.com>
commit 5a1cf1cb3b80759131c73f6a9dddebccac039dea
Author: Russell Bryant <rbryant@redhat.com>
Date: Fri Jan 31 14:36:32 2025 -0500
Check for SPDX headers using pre-commit
Signed-off-by: Russell Bryant <rbryant@redhat.com>
---------
Signed-off-by: Russell Bryant <rbryant@redhat.com>
86 lines
2.8 KiB
Python
86 lines
2.8 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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"""Compares the outputs of gptq vs gptq_marlin
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Note: GPTQ and Marlin do not have bitwise correctness.
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As a result, in this test, we just confirm that the top selected tokens of the
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Marlin/GPTQ models are in the top 5 selections of each other.
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Note: Marlin internally uses locks to synchronize the threads. This can
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result in very slight nondeterminism for Marlin. As a result, we re-run the test
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up to 3 times to see if we pass.
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Run `pytest tests/models/test_gptq_marlin.py`.
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"""
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import os
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import pytest
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from tests.quantization.utils import is_quant_method_supported
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from vllm.model_executor.layers.rotary_embedding import _ROPE_DICT
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from ...utils import check_logprobs_close
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os.environ["TOKENIZERS_PARALLELISM"] = "true"
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MAX_MODEL_LEN = 1024
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MODELS = [
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# act_order==True, group_size=128
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("TheBloke/TinyLlama-1.1B-Chat-v1.0-GPTQ", "main"),
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# 8-bit, act_order==True, group_size=channelwise
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("TheBloke/TinyLlama-1.1B-Chat-v1.0-GPTQ", "gptq-8bit--1g-actorder_True"),
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# 4-bit, act_order==True, group_size=128
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("TechxGenus/gemma-1.1-2b-it-GPTQ", "main")
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]
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@pytest.mark.quant_model
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@pytest.mark.flaky(reruns=3)
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@pytest.mark.skipif(not is_quant_method_supported("gptq_marlin"),
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reason="gptq_marlin is not supported on this GPU type.")
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@pytest.mark.parametrize("model", MODELS)
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@pytest.mark.parametrize("dtype", ["half", "bfloat16"])
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@pytest.mark.parametrize("max_tokens", [32])
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@pytest.mark.parametrize("num_logprobs", [5])
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def test_models(
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vllm_runner,
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example_prompts,
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model,
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dtype: str,
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max_tokens: int,
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num_logprobs: int,
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) -> None:
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model_name, revision = model
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# Run marlin.
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with vllm_runner(model_name=model_name,
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revision=revision,
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dtype=dtype,
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quantization="marlin",
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max_model_len=MAX_MODEL_LEN,
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tensor_parallel_size=1) as gptq_marlin_model:
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gptq_marlin_outputs = gptq_marlin_model.generate_greedy_logprobs(
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example_prompts[:-1], max_tokens, num_logprobs)
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_ROPE_DICT.clear() # clear rope cache to avoid rope dtype error
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# Run gptq.
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# The naive gptq kernel doesn't support bf16 yet.
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# Here we always compare fp16/bf16 gpt marlin kernel
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# to fp16 gptq kernel.
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with vllm_runner(model_name=model_name,
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revision=revision,
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dtype="half",
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quantization="gptq",
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max_model_len=MAX_MODEL_LEN,
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tensor_parallel_size=1) as gptq_model:
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gptq_outputs = gptq_model.generate_greedy_logprobs(
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example_prompts[:-1], max_tokens, num_logprobs)
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check_logprobs_close(
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outputs_0_lst=gptq_outputs,
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outputs_1_lst=gptq_marlin_outputs,
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name_0="gptq",
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name_1="gptq_marlin",
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)
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