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_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()
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())