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[Quantization][Deprecation] Remove BitBlas (#32683)

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Signed-off-by: Robert Shaw <robshaw@redhat.com>
Signed-off-by: Robert Shaw <114415538+robertgshaw2-redhat@users.noreply.github.com>
Co-authored-by: Robert Shaw <robshaw@redhat.com>
This commit is contained in:
Robert Shaw
2026-01-28 03:06:22 -08:00
committed by GitHub
parent ecb4f82209
commit 247d1a32ea
15 changed files with 2 additions and 2030 deletions
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68
tests/models/quantization/test_bitblas.py
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@@ -1,68 +0,0 @@
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
"""Compare the outputs of a GPTQ model to a bitblas model.
Note: GPTQ and bitblas do not have bitwise correctness.
As a result, in this test, we just confirm that the top selected tokens of the
bitblas/GPTQ models are in the top 3 selections of each other.
Note: bitblas internally uses locks to synchronize the threads. This can
result in very slight nondeterminism for bitblas. As a result, we re-run the
test up to 3 times to see if we pass.
"""
from dataclasses import dataclass
import pytest
from ..utils import check_logprobs_close
@dataclass
class ModelPair:
model_bitblas: str
model_gptq: str
model_pairs = [
ModelPair(
model_bitblas="hxbgsyxh/opt-125m-4bit-128g-bitblas",
model_gptq="hxbgsyxh/opt-125m-4bit-128g",
),
]
@pytest.mark.flaky(reruns=2)
@pytest.mark.skipif(True, reason="BitBLAS takes too much time for tuning.")
@pytest.mark.parametrize("model_pair", model_pairs)
@pytest.mark.parametrize("dtype", ["half"])
@pytest.mark.parametrize("max_tokens", [32])
@pytest.mark.parametrize("num_logprobs", [5])
def test_models(
vllm_runner,
example_prompts,
model_pair: ModelPair,
dtype: str,
max_tokens: int,
num_logprobs: int,
) -> None:
with vllm_runner(
model_pair.model_bitblas, dtype=dtype, quantization="bitblas"
) as bitblas_model:
bitblas_outputs = bitblas_model.generate_greedy_logprobs(
example_prompts, max_tokens, num_logprobs
)
with vllm_runner(
model_pair.model_gptq, dtype=dtype, quantization="gptq"
) as gptq_model:
gptq_outputs = gptq_model.generate_greedy_logprobs(
example_prompts, max_tokens, num_logprobs
)
check_logprobs_close(
outputs_0_lst=gptq_outputs,
outputs_1_lst=bitblas_outputs,
name_0="gptq",
name_1="bitblas",
)

64
tests/models/quantization/test_gptq_bitblas.py
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@@ -1,64 +0,0 @@
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
"""Compare the outputs of a GPTQ model to a bitblas model.
Note: GPTQ and bitblas do not have bitwise correctness.
As a result, in this test, we just confirm that the top selected tokens of the
bitblas/GPTQ models are in the top 3 selections of each other.
Note: bitblas internally uses locks to synchronize the threads. This can
result in very slight nondeterminism for bitblas. As a result, we re-run the
test up to 3 times to see if we pass.
"""
from dataclasses import dataclass
import pytest
from ..utils import check_logprobs_close
@dataclass
class ModelPair:
model_gptq: str
model_pairs = [
ModelPair(model_gptq="hxbgsyxh/opt-125m-4bit-128g"),
]
@pytest.mark.flaky(reruns=2)
@pytest.mark.skipif(True, reason="BitBLAS takes too much time for tuning.")
@pytest.mark.parametrize("model_pair", model_pairs)
@pytest.mark.parametrize("dtype", ["half"])
@pytest.mark.parametrize("max_tokens", [32])
@pytest.mark.parametrize("num_logprobs", [5])
def test_models(
vllm_runner,
example_prompts,
model_pair: ModelPair,
dtype: str,
max_tokens: int,
num_logprobs: int,
) -> None:
with vllm_runner(
model_pair.model_gptq, dtype=dtype, quantization="bitblas"
) as bitblas_model:
bitblas_outputs = bitblas_model.generate_greedy_logprobs(
example_prompts, max_tokens, num_logprobs
)
with vllm_runner(
model_pair.model_gptq, dtype=dtype, quantization="gptq"
) as gptq_model:
gptq_outputs = gptq_model.generate_greedy_logprobs(
example_prompts, max_tokens, num_logprobs
)
check_logprobs_close(
outputs_0_lst=gptq_outputs,
outputs_1_lst=bitblas_outputs,
name_0="gptq",
name_1="gptq_bitblas",
)