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Add ruff, remove black, isort, flake8, pylint (#3092)

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* black, isort, flake8 -> ruff

* remove unused

* add back needed import

* fix
This commit is contained in:
Dan Saunders
2025-08-23 23:37:33 -04:00
committed by GitHub
parent eea7a006e1
commit 79ddaebe9a
286 changed files with 10979 additions and 11435 deletions
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26
tests/e2e/test_quantization.py
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@@ -131,7 +131,7 @@ class TestQuantization:
@require_torch_2_6_0
def test_prepare_model_for_qat(
self, model, weight_dtype, activation_dtype, group_size, quantize_embedding
): # pylint: disable=redefined-outer-name
):
prepare_model_for_qat(
model, weight_dtype, group_size, activation_dtype, quantize_embedding
)
@@ -175,7 +175,7 @@ class TestQuantization:
group_size,
quantize_embedding,
expected_exception,
): # pylint: disable=redefined-outer-name
):
if expected_exception:
with pytest.raises(expected_exception):
quantize_model_for_ptq(
@@ -198,11 +198,13 @@ class TestQuantization:
if activation_dtype:
assert isinstance(
child.weight, LinearActivationQuantizedTensor
), "Linear weight should be quantized with activation quantization"
), (
"Linear weight should be quantized with activation quantization"
)
else:
assert isinstance(
child.weight, AffineQuantizedTensor
), "Linear weight should be quantized without activation quantization"
assert isinstance(child.weight, AffineQuantizedTensor), (
"Linear weight should be quantized without activation quantization"
)
class TestQuantizationCallback:
@@ -217,9 +219,7 @@ class TestQuantizationCallback:
)
@require_torch_2_6_0
def test_qat_callback_fake_quant_after_n_steps(
self, model, trainer_state
): # pylint: disable=redefined-outer-name
def test_qat_callback_fake_quant_after_n_steps(self, model, trainer_state):
cfg = QATConfig(
weight_dtype="int8",
activation_dtype="int8",
@@ -269,9 +269,7 @@ class TestQuantizationCallback:
assert model.lm_head.weight_fake_quantizer.enabled
@require_torch_2_6_0
def test_qat_callback_fake_quant_after_n_steps_is_none(
self, model, trainer_state
): # pylint: disable=redefined-outer-name
def test_qat_callback_fake_quant_after_n_steps_is_none(self, model, trainer_state):
cfg = QATConfig(
weight_dtype="int8",
activation_dtype="int8",
@@ -314,9 +312,7 @@ class TestConvertQATModelForPTQ:
"""
@require_torch_2_6_0
def test_convert_qat_model_for_ptq(
self, model
): # pylint: disable=redefined-outer-name
def test_convert_qat_model_for_ptq(self, model):
config = QATConfig(
weight_dtype="int8",
activation_dtype="int8",