def test_import_from_8bit_with_bias(self):
# QuantizationMode dynamic
exporter = QuantizedLinear(10, 5, mode='dynamic')
exporter.eval()
exporter.mode_8bit = True
state_dict = exporter.state_dict()
exporter.mode_8bit = False
importer = QuantizedLinear(10, 5, mode='dynamic')
self.assertTrue((exporter.weight != importer.weight).any())
self.assertTrue((exporter.bias != importer.bias).any())
importer.eval()
importer.load_state_dict(state_dict, strict=False)
x = torch.randn(3, 10)
self.assertTrue((exporter(x) == importer(x)).all())
# QuantizationMode ema
exporter = QuantizedLinear(10, 5, requantize_output=False, mode='ema')
x = torch.randn(3, 10)
exporter(x)
self.assertTrue(exporter.input_thresh != 0.)
exporter.eval()
exporter.mode_8bit = True
state_dict = exporter.state_dict()
exporter.mode_8bit = False
importer = QuantizedLinear(10, 5, requantize_output=False, mode='ema')
self.assertTrue((exporter.weight != importer.weight).any())
self.assertTrue((exporter.bias != importer.bias).any())
importer.eval()
importer.load_state_dict(state_dict, strict=False)
self.assertTrue((exporter(x) == importer(x)).all())
def test_export_to_8bit_with_bias(self):
qlinear = QuantizedLinear(10, 5, mode='EMA')
qlinear.eval()
state_dict = qlinear.state_dict()
self.assertTrue('weight' in state_dict)
self.assertTrue('bias' in state_dict)
self.assertTrue('quantized_weight' not in state_dict)
self.assertTrue('_quantized_bias' not in state_dict)
self.assertTrue('bias_scale' not in state_dict)
qlinear.mode_8bit = True
state_dict = qlinear.state_dict()
self.assertTrue('weight' not in state_dict)
self.assertTrue('bias' not in state_dict)
self.assertTrue('quantized_weight' in state_dict)
self.assertTrue(state_dict['quantized_weight'].dtype == torch.int8)
self.assertTrue('_quantized_bias' in state_dict)
self.assertTrue(state_dict['_quantized_bias'].dtype == torch.int32)
self.assertTrue('bias_scale' in state_dict)
qlinear.mode_8bit = False
state_dict = qlinear.state_dict()
self.assertTrue('weight' in state_dict)
self.assertTrue('bias' in state_dict)
self.assertTrue('quantized_weight' not in state_dict)
self.assertTrue('_quantized_bias' not in state_dict)
self.assertTrue('bias_scale' not in state_dict)
def test_export_to_8bit_with_bias(self):
qlinear = QuantizedLinear(10, 5, mode="EMA")
qlinear.eval()
state_dict = qlinear.state_dict()
self.assertTrue("weight" in state_dict)
self.assertTrue("bias" in state_dict)
self.assertTrue("quantized_weight" not in state_dict)
self.assertTrue("_quantized_bias" not in state_dict)
self.assertTrue("bias_scale" not in state_dict)
qlinear.mode_8bit = True
state_dict = qlinear.state_dict()
self.assertTrue("weight" not in state_dict)
self.assertTrue("bias" not in state_dict)
self.assertTrue("quantized_weight" in state_dict)
self.assertTrue(state_dict["quantized_weight"].dtype == torch.int8)
self.assertTrue("_quantized_bias" in state_dict)
self.assertTrue(state_dict["_quantized_bias"].dtype == torch.int32)
self.assertTrue("bias_scale" in state_dict)
qlinear.mode_8bit = False
state_dict = qlinear.state_dict()
self.assertTrue("weight" in state_dict)
self.assertTrue("bias" in state_dict)
self.assertTrue("quantized_weight" not in state_dict)
self.assertTrue("_quantized_bias" not in state_dict)
self.assertTrue("bias_scale" not in state_dict)
def test_import_from_8bit_without_bias(self):
exporter = QuantizedLinear(10, 5, bias=False, mode='dynamic')
exporter.eval()
exporter.mode_8bit = True
state_dict = exporter.state_dict()
exporter.mode_8bit = False
importer = QuantizedLinear(10, 5, bias=False, mode='dynamic')
self.assertTrue((exporter.weight != importer.weight).any())
importer.eval()
importer.load_state_dict(state_dict, strict=False)
x = torch.randn(3, 10)
self.assertTrue((exporter(x) == importer(x)).all())
def test_restrict_loading_to_train_model(self):
exporter = QuantizedLinear(10, 5, mode='dynamic')
exporter.eval()
exporter.mode_8bit = True
state_dict = exporter.state_dict()
importer = QuantizedLinear(10, 5, mode='dynamic')
with self.assertRaises(RuntimeError):
importer.load_state_dict(state_dict, strict=False)
def test_train_block_when_loading_quantized_model(self):
exporter = QuantizedLinear(10, 5, mode="dynamic")
exporter.eval()
exporter.mode_8bit = True
state_dict = exporter.state_dict()
importer = QuantizedLinear(10, 5, mode="dynamic")
importer.eval()
importer.load_state_dict(state_dict, strict=False)
with self.assertRaises(RuntimeError):
importer.train()