Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Refine HQQ UTs #1888

Merged
merged 3 commits into from
Jul 2, 2024
Merged

Refine HQQ UTs #1888

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
3 commits
Select commit Hold shift + click to select a range
363b9ac
refine hqq test
yiliu30 Jun 28, 2024
9b6a51a
remove cuda
yiliu30 Jun 28, 2024
c9db050
correct name
yiliu30 Jun 28, 2024
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
130 changes: 0 additions & 130 deletions test/3x/torch/quantization/weight_only/hqq/test_hqq_cuda.py
View file
Open in desktop

This file was deleted.

30 changes: 23 additions & 7 deletions ...ntization/weight_only/hqq/test_hqq_cpu.py → ...orch/quantization/weight_only/test_hqq.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -6,6 +6,7 @@
import transformers
from transformers import AutoModelForCausalLM

from neural_compressor.common.utils import logger
from neural_compressor.torch.algorithms.weight_only.hqq.config import HQQModuleConfig, QTensorConfig, hqq_global_option
from neural_compressor.torch.algorithms.weight_only.hqq.core import HQQLinear
from neural_compressor.torch.quantization import HQQConfig, convert, get_default_hqq_config, prepare, quantize
Expand All @@ -14,7 +15,9 @@
device = accelerator.current_device_name()


def _common_cpu_test(nbits=4, group_size=64, quant_zero=True, quant_scale=False, scale_quant_group_size=128):
def _common_hqq_test(
nbits=4, group_size=64, quant_zero=True, quant_scale=False, scale_quant_group_size=128, device=None
):
# Parse config
weight_qconfig = QTensorConfig(
nbits=nbits, channel_wise=True, group_size=group_size, optimize=True, round_zero=True if nbits == 4 else False
Expand All @@ -26,15 +29,14 @@ def _common_cpu_test(nbits=4, group_size=64, quant_zero=True, quant_scale=False,
if quant_scale:
scale_qconfig = QTensorConfig(nbits=8, channel_wise=True, group_size=scale_quant_group_size, optimize=False)
hqq_quant_config = HQQModuleConfig(weight=weight_qconfig, scale=scale_qconfig, zero=zero_qconfig)
device = "cpu"

# Create HQQ Linear
bs = 4
in_features = 64
out_features = 128
float_linear = torch.nn.Linear(in_features=in_features, out_features=out_features)
if hqq_global_option.use_half:
print(f"hqq_global_option use half: {hqq_global_option.use_half}")
logger.info(f"hqq_global_option use half: {hqq_global_option.use_half}")
float_linear = float_linear.half()
float_linear.to(device)
float_linear_copy = deepcopy(float_linear)
Expand All @@ -54,7 +56,7 @@ def _common_cpu_test(nbits=4, group_size=64, quant_zero=True, quant_scale=False,
del float_output, hqq_output, hqq_output_2


class TestHQQCPU:
class TestHQQ:

@classmethod
def setup_class(cls):
Expand Down Expand Up @@ -137,6 +139,7 @@ def test_quant_lm_head(self, force_use_cpu, force_not_half):
id(model.model.decoder.embed_tokens.weight) == lm_head_id
), "The tied lm_head weight is not deep copied, please check!"

@pytest.mark.parametrize("device_name", ["cuda", "cpu"])
@pytest.mark.parametrize(
"nbits, group_size, quant_zero, quant_scale, scale_quant_group_size",
[
Expand All @@ -155,13 +158,26 @@ def test_quant_lm_head(self, force_use_cpu, force_not_half):
(4, -1, False, True, 64),
],
)
def test_hqq_module_cpu(
self, force_use_cpu, force_not_half, nbits, group_size, quant_zero, quant_scale, scale_quant_group_size
def test_hqq_module(
self,
nbits,
group_size,
quant_zero,
quant_scale,
scale_quant_group_size,
device_name,
):
_common_cpu_test(
if device_name == "cuda" and not torch.cuda.is_available():
pytest.skip("Skipping CUDA test because cuda is not available")
if device_name == "cpu":
os.environ["FORCE_DEVICE"] = "cpu"
hqq_global_option.use_half = False

_common_hqq_test(
nbits=nbits,
group_size=group_size,
quant_zero=quant_zero,
quant_scale=quant_scale,
scale_quant_group_size=scale_quant_group_size,
device=torch.device(device_name),
)
Loading