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65 lines
1.8 KiB
Python
65 lines
1.8 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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"""Compare the outputs of a GPTQ model to a bitblas model.
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Note: GPTQ and bitblas 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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bitblas/GPTQ models are in the top 3 selections of each other.
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Note: bitblas internally uses locks to synchronize the threads. This can
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result in very slight nondeterminism for bitblas. As a result, we re-run the
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test up to 3 times to see if we pass.
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"""
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from dataclasses import dataclass
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import pytest
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from ..utils import check_logprobs_close
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@dataclass
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class ModelPair:
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model_gptq: str
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model_pairs = [
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ModelPair(model_gptq="hxbgsyxh/opt-125m-4bit-128g"),
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]
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@pytest.mark.flaky(reruns=2)
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@pytest.mark.skipif(True, reason="BitBLAS takes too much time for tuning.")
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@pytest.mark.parametrize("model_pair", model_pairs)
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@pytest.mark.parametrize("dtype", ["half"])
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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_pair: ModelPair,
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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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with vllm_runner(
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model_pair.model_gptq, dtype=dtype, quantization="bitblas"
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) as bitblas_model:
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bitblas_outputs = bitblas_model.generate_greedy_logprobs(
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example_prompts, max_tokens, num_logprobs
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)
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with vllm_runner(
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model_pair.model_gptq, dtype=dtype, quantization="gptq"
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) as gptq_model:
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gptq_outputs = gptq_model.generate_greedy_logprobs(
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example_prompts, max_tokens, num_logprobs
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)
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check_logprobs_close(
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outputs_0_lst=gptq_outputs,
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outputs_1_lst=bitblas_outputs,
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name_0="gptq",
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name_1="gptq_bitblas",
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)
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