fix(mge/quantization): fix `quantize` and `quantize_qat`'s `set_expand_structure` arguments

GitOrigin-RevId: c61633095d

imperative/python/megengine/quantization/quantize.py

@@ -80,7 +80,7 @@ def quantize(module: Module, inplace: bool = True, mapping: dict = None):
         module._flatten(with_key=True, with_parent=True, predicate=is_qat)
     ):
         new_mod = convert_dict[type(submodule)].from_qat_module(submodule)
-        set_expand_structure(parent, key, new_mod)
+        set_expand_structure(module, key, new_mod)
 
     return module
 
@@ -123,7 +123,7 @@ def quantize_qat(
             continue
 
         new_mod = convert_dict[type(submodule)].from_float_module(submodule)
-        set_expand_structure(parent, key, new_mod)
+        set_expand_structure(module, key, new_mod)
 
     propagate_qconfig(module, qconfig)
     return module

imperative/python/test/unit/quantization/test_quantize.py

@@ -37,9 +37,10 @@ class FloatNet(Float.Module):
     def __init__(self):
         super().__init__()
         self.quant = Float.QuantStub()
-        self.linear = Float.Linear(3, 3)
+        self.linear = Float.Sequential(Float.Linear(3, 3), Float.Linear(3, 3))
         self.dequant = Float.DequantStub()
-        self.linear.bias[...] = Parameter(np.random.rand(3))
+        self.linear[0].bias[...] = Parameter(np.random.rand(3))
+        self.linear[1].bias[...] = Parameter(np.random.rand(3))
 
     def forward(self, x):
         x = self.quant(x)
@@ -52,9 +53,10 @@ class QATNet(Float.Module):
     def __init__(self):
         super().__init__()
         self.quant = QAT.QuantStub()
-        self.linear = QAT.Linear(3, 3)
+        self.linear = Float.Sequential(QAT.Linear(3, 3), QAT.Linear(3, 3))
         self.dequant = QAT.DequantStub()
-        self.linear.bias[...] = Parameter(np.random.rand(3))
+        self.linear[0].bias[...] = Parameter(np.random.rand(3))
+        self.linear[1].bias[...] = Parameter(np.random.rand(3))
 
     def forward(self, x):
         x = self.quant(x)
@@ -72,10 +74,14 @@ def test_propagate_qconfig():
             net.quant.weight_fake_quant is None,
             isinstance(net.quant.act_observer, MinMaxObserver),
             isinstance(net.quant.act_fake_quant, FakeQuantize),
-            isinstance(net.linear.weight_observer, MinMaxObserver),
-            isinstance(net.linear.weight_fake_quant, FakeQuantize),
-            isinstance(net.linear.act_observer, MinMaxObserver),
-            isinstance(net.linear.act_fake_quant, FakeQuantize),
+            isinstance(net.linear[0].weight_observer, MinMaxObserver),
+            isinstance(net.linear[0].weight_fake_quant, FakeQuantize),
+            isinstance(net.linear[0].act_observer, MinMaxObserver),
+            isinstance(net.linear[0].act_fake_quant, FakeQuantize),
+            isinstance(net.linear[1].weight_observer, MinMaxObserver),
+            isinstance(net.linear[1].weight_fake_quant, FakeQuantize),
+            isinstance(net.linear[1].act_observer, MinMaxObserver),
+            isinstance(net.linear[1].act_fake_quant, FakeQuantize),
             net.dequant.weight_observer is None,
             net.dequant.weight_fake_quant is None,
             net.dequant.act_observer is None,
@@ -91,10 +97,14 @@ def init_qat_net():
     max_val = np.random.randint(1, 127, size=(3,))
     net.quant.act_observer.min_val[...] = Parameter(min_val[0])
     net.quant.act_observer.max_val[...] = Parameter(max_val[0])
-    net.linear.weight_observer.min_val[...] = Parameter(min_val[1])
-    net.linear.weight_observer.max_val[...] = Parameter(max_val[1])
-    net.linear.act_observer.min_val[...] = Parameter(min_val[2])
-    net.linear.act_observer.max_val[...] = Parameter(max_val[2])
+    net.linear[0].weight_observer.min_val[...] = Parameter(min_val[1])
+    net.linear[0].weight_observer.max_val[...] = Parameter(max_val[1])
+    net.linear[0].act_observer.min_val[...] = Parameter(min_val[2])
+    net.linear[0].act_observer.max_val[...] = Parameter(max_val[2])
+    net.linear[1].weight_observer.min_val[...] = Parameter(min_val[1])
+    net.linear[1].weight_observer.max_val[...] = Parameter(max_val[1])
+    net.linear[1].act_observer.min_val[...] = Parameter(min_val[2])
+    net.linear[1].act_observer.max_val[...] = Parameter(max_val[2])
     return net
 
 
@@ -102,11 +112,20 @@ def test_reset_qconfig():
     qat_net = init_qat_net()
     new_qat_net = reset_qconfig(qat_net, passive_qconfig)
     assert (
-        new_qat_net.linear.get_weight_qparams() == qat_net.linear.get_weight_qparams()
+        new_qat_net.linear[0].get_weight_qparams()
+        == qat_net.linear[0].get_weight_qparams()
     )
     assert (
-        new_qat_net.linear.get_activation_qparams()
-        == qat_net.linear.get_activation_qparams()
+        new_qat_net.linear[0].get_activation_qparams()
+        == qat_net.linear[0].get_activation_qparams()
+    )
+    assert (
+        new_qat_net.linear[1].get_weight_qparams()
+        == qat_net.linear[1].get_weight_qparams()
+    )
+    assert (
+        new_qat_net.linear[1].get_activation_qparams()
+        == qat_net.linear[1].get_activation_qparams()
     )
 
 
@@ -114,24 +133,32 @@ def test_enable_and_disable_observer():
     net = init_qat_net()
     enable_observer(net)
     assert net.quant.act_observer.enabled is True
-    assert net.linear.weight_observer.enabled is True
-    assert net.linear.act_observer.enabled is True
+    assert net.linear[0].weight_observer.enabled is True
+    assert net.linear[0].act_observer.enabled is True
+    assert net.linear[1].weight_observer.enabled is True
+    assert net.linear[1].act_observer.enabled is True
     disable_observer(net)
     assert net.quant.act_observer.enabled is False
-    assert net.linear.weight_observer.enabled is False
-    assert net.linear.act_observer.enabled is False
+    assert net.linear[0].weight_observer.enabled is False
+    assert net.linear[0].weight_observer.enabled is False
+    assert net.linear[1].act_observer.enabled is False
+    assert net.linear[1].act_observer.enabled is False
 
 
 def test_enable_and_disable_fake_quant():
     net = init_qat_net()
     disable_fake_quant(net)
     assert net.quant.act_fake_quant.enabled is False
-    assert net.linear.weight_fake_quant.enabled is False
-    assert net.linear.act_fake_quant.enabled is False
+    assert net.linear[0].weight_fake_quant.enabled is False
+    assert net.linear[0].act_fake_quant.enabled is False
+    assert net.linear[1].weight_fake_quant.enabled is False
+    assert net.linear[1].act_fake_quant.enabled is False
     enable_fake_quant(net)
     assert net.quant.act_fake_quant.enabled is True
-    assert net.linear.weight_fake_quant.enabled is True
-    assert net.linear.act_fake_quant.enabled is True
+    assert net.linear[0].weight_fake_quant.enabled is True
+    assert net.linear[0].act_fake_quant.enabled is True
+    assert net.linear[1].weight_fake_quant.enabled is True
+    assert net.linear[1].act_fake_quant.enabled is True
 
 
 def init_observer(module, data):
@@ -165,7 +192,8 @@ def test_quantize_qat():
     net = FloatNet()
     qat_net = quantize_qat(net, inplace=False, qconfig=min_max_fakequant_qconfig)
     assert isinstance(qat_net.quant, QAT.QuantStub)
-    assert isinstance(qat_net.linear, QAT.Linear)
+    assert isinstance(qat_net.linear[0], QAT.Linear)
+    assert isinstance(qat_net.linear[1], QAT.Linear)
     assert isinstance(qat_net.dequant, QAT.DequantStub)
 
 
@@ -173,7 +201,8 @@ def test_quantize():
     qat_net = init_qat_net()
     q_net = quantize(qat_net, inplace=False)
     assert isinstance(q_net.quant, Q.QuantStub)
-    assert isinstance(q_net.linear, Q.Linear)
+    assert isinstance(q_net.linear[0], Q.Linear)
+    assert isinstance(q_net.linear[1], Q.Linear)
     assert isinstance(q_net.dequant, Q.DequantStub)
 
 
@@ -183,8 +212,10 @@ def test_apply_easy_quant():
     eq_net = reset_qconfig(qat_net, passive_qconfig, inplace=False)
     apply_easy_quant(eq_net, data, 0.9, 1.1, 10)
     assert isinstance(eq_net.quant.act_observer, PassiveObserver)
-    assert isinstance(eq_net.linear.weight_observer, PassiveObserver)
-    assert isinstance(eq_net.linear.act_observer, PassiveObserver)
+    assert isinstance(eq_net.linear[0].weight_observer, PassiveObserver)
+    assert isinstance(eq_net.linear[0].act_observer, PassiveObserver)
+    assert isinstance(eq_net.linear[1].weight_observer, PassiveObserver)
+    assert isinstance(eq_net.linear[1].act_observer, PassiveObserver)
     assert eq_net.dequant.act_observer is None
 
 
@@ -192,8 +223,10 @@ def test_apply_tqt():
     qat_net = init_qat_net()
     tqt_net = reset_qconfig(qat_net, tqt_qconfig, inplace=False)
     assert isinstance(tqt_net.quant.act_fake_quant, TQT)
-    assert isinstance(tqt_net.linear.weight_fake_quant, TQT)
-    assert isinstance(tqt_net.linear.act_fake_quant, TQT)
+    assert isinstance(tqt_net.linear[0].weight_fake_quant, TQT)
+    assert isinstance(tqt_net.linear[0].act_fake_quant, TQT)
+    assert isinstance(tqt_net.linear[1].weight_fake_quant, TQT)
+    assert isinstance(tqt_net.linear[1].act_fake_quant, TQT)
     assert tqt_net.dequant.act_fake_quant is None