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Accelerate bug in specific versions #1007

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merged 3 commits into from
Aug 28, 2023
Merged

Accelerate bug in specific versions #1007

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0236131
Exclude accelerate versions with unwrap_model bug
BenjaminBossan Aug 14, 2023
941ea5e
Be more precise about the versions
BenjaminBossan Aug 14, 2023
8a27860
Use accelerate>=0.22.0
BenjaminBossan Aug 28, 2023
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2 changes: 1 addition & 1 deletion requirements-dev.txt
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Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
accelerate>=0.11.0
accelerate>=0.22.0
fire
flaky
future>=0.17.1
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22 changes: 22 additions & 0 deletions skorch/tests/test_hf.py
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Expand Up @@ -660,10 +660,32 @@ def test_mixed_precision_save_load_params(
accelerator = accelerator_cls(mixed_precision=mixed_precision)
net = net_cls(accelerator=accelerator)
net.initialize()

filename = tmp_path / 'accel-net-params.pth'
net.save_params(f_params=filename)
net.load_params(f_params=filename)

@pytest.mark.parametrize('mixed_precision', ['fp16', 'bf16', 'no'])
def test_mixed_precision_inference(
self, net_cls, accelerator_cls, data, mixed_precision, tmp_path
):
from accelerate.utils import is_bf16_available

if (mixed_precision != 'no') and not torch.cuda.is_available():
pytest.skip('skipping AMP test because device does not support it')
if (mixed_precision == 'bf16') and not is_bf16_available():
pytest.skip('skipping bf16 test because device does not support it')

X, y = data
accelerator = accelerator_cls(mixed_precision=mixed_precision)
net = net_cls(accelerator=accelerator)
net.fit(X, y)
net.predict(X)
net.predict_proba(X)

Xt = torch.from_numpy(X).to(net.device)
net.forward(Xt)

def test_force_cpu(self, net_cls, accelerator_cls, data):
accelerator = accelerator_cls(device_placement=False, cpu=True)
net = net_cls(accelerator=accelerator)
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