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Feat (tests): add new tests for proxy
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import pytest | ||
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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 | ||
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class TestProxy: | ||
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def test_bias_proxy(self): | ||
model = QuantLinear(10, 5, bias_quant=Int8BiasPerTensorFloatInternalScaling) | ||
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 | ||
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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 | ||
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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 | ||
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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 | ||
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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 | ||
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model.weight_quant.disable_quant = True | ||
assert model.weight_quant.pre_scale() is None | ||
assert model.weight_quant.pre_zero_point() is None | ||
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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() | ||
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with pytest.raises(NotImplementedError): | ||
model.weight_quant.pre_scale() | ||
with pytest.raises(NotImplementedError): | ||
model.weight_quant.pre_zero_point() | ||
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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 | ||
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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 | ||
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def test_act_proxy(self): | ||
model = QuantReLU(Int8DynamicActPerTensorFloat) | ||
with pytest.raises(NotImplementedError): | ||
model.weight_quant.scale() | ||
with pytest.raises(NotImplementedError): | ||
model.weight_quant.zero_point() | ||
assert model.act_quant.bit_width() is not None | ||
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model.act_quant.disable_quant = True | ||
assert model.act_quant.bit_width() is None |
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