-
Notifications
You must be signed in to change notification settings - Fork 197
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
Feat (tests): add new tests for proxy
- Loading branch information
Showing
3 changed files
with
91 additions
and
1 deletion.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,82 @@ | ||
import pytest | ||
|
||
from brevitas.nn import QuantLinear | ||
from brevitas.nn.quant_activation import QuantReLU | ||
from brevitas.quant.scaled_int import Int8AccumulatorAwareWeightQuant | ||
from brevitas.quant.scaled_int import Int8BiasPerTensorFloatInternalScaling | ||
from brevitas.quant.scaled_int import Int8WeightPerChannelFloatDecoupled | ||
from brevitas.quant.scaled_int import Int8WeightPerTensorFloat | ||
from brevitas_examples.common.generative.quantizers import Int8DynamicActPerTensorFloat | ||
from tests.marker import jit_disabled_for_dynamic_quant_act | ||
|
||
|
||
class TestProxy: | ||
|
||
def test_bias_proxy(self): | ||
model = QuantLinear(10, 5, bias_quant=Int8BiasPerTensorFloatInternalScaling) | ||
assert model.bias_quant.scale() is not None | ||
assert model.bias_quant.zero_point() is not None | ||
assert model.bias_quant.bit_width() is not None | ||
|
||
model.bias_quant.disable_quant = True | ||
assert model.bias_quant.scale() is None | ||
assert model.bias_quant.zero_point() is None | ||
assert model.bias_quant.bit_width() is None | ||
|
||
def test_weight_proxy(self): | ||
model = QuantLinear(10, 5, weight_quant=Int8WeightPerTensorFloat) | ||
assert model.weight_quant.scale() is not None | ||
assert model.weight_quant.zero_point() is not None | ||
assert model.weight_quant.bit_width() is not None | ||
|
||
model.weight_quant.disable_quant = True | ||
assert model.weight_quant.scale() is None | ||
assert model.weight_quant.zero_point() is None | ||
assert model.weight_quant.bit_width() is None | ||
|
||
def test_weight_decoupled_proxy(self): | ||
model = QuantLinear(10, 5, weight_quant=Int8WeightPerChannelFloatDecoupled) | ||
assert model.weight_quant.pre_scale() is not None | ||
assert model.weight_quant.pre_zero_point() is not None | ||
|
||
model.weight_quant.disable_quant = True | ||
assert model.weight_quant.pre_scale() is None | ||
assert model.weight_quant.pre_zero_point() is None | ||
|
||
def test_weight_decoupled_with_input_proxy(self): | ||
model = QuantLinear(10, 5, weight_quant=Int8AccumulatorAwareWeightQuant) | ||
with pytest.raises(NotImplementedError): | ||
model.weight_quant.scale() | ||
with pytest.raises(NotImplementedError): | ||
model.weight_quant.zero_point() | ||
|
||
with pytest.raises(NotImplementedError): | ||
model.weight_quant.pre_scale() | ||
with pytest.raises(NotImplementedError): | ||
model.weight_quant.pre_zero_point() | ||
|
||
def test_act_proxy(self): | ||
model = QuantReLU() | ||
assert model.act_quant.scale() is not None | ||
assert model.act_quant.zero_point() is not None | ||
assert model.act_quant.bit_width() is not None | ||
|
||
model.act_quant.disable_quant = True | ||
assert model.act_quant.scale() is None | ||
assert model.act_quant.zero_point() is None | ||
assert model.act_quant.bit_width() is None | ||
|
||
@jit_disabled_for_dynamic_quant_act() | ||
def test_dynamic_act_proxy(self): | ||
model = QuantReLU(Int8DynamicActPerTensorFloat) | ||
|
||
with pytest.raises(RuntimeError, match="Scale for Dynamic Act Quant is input-dependant"): | ||
model.act_quant.scale() | ||
with pytest.raises(RuntimeError, | ||
match="Zero point for Dynamic Act Quant is input-dependant"): | ||
model.act_quant.zero_point() | ||
|
||
assert model.act_quant.bit_width() is not None | ||
|
||
model.act_quant.disable_quant = True | ||
assert model.act_quant.bit_width() is None |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters