fix(mge/utils): use static infer manager to get value of network.varnode

GitOrigin-RevId: ecc47edab8334e3f41a409020db2a9090db62147

imperative/python/megengine/utils/network_node.py

@@ -18,7 +18,6 @@ from ..core._trace_option import use_symbolic_shape
 from ..core._wrap import Device
 from ..core.ops import builtin
 from ..core.tensor.array_method import ArrayMethodMixin
-from ..core.tensor.megbrain_graph import OutputNode
 from .comp_graph_tools import replace_vars
 from .module_stats import (
     preprocess_receptive_field,
@@ -106,9 +105,7 @@ class VarNode(NetworkNode, SymbolVar, ArrayMethodMixin, metaclass=VarNodeMeta):
         return id(self)
 
     def numpy(self):
-        o = OutputNode(self.var)
-        self.graph.compile(o.outputs).execute()
-        return o.get_value().numpy()
+        return super().numpy()
 
     def _reset(self, other):
         if not isinstance(other, VarNode):
@@ -141,15 +138,13 @@ class OpNode(NetworkNode):
 
     @property
     def id(self):
-        if self._opr is not None:
-            return self._opr.id
         return id(self)
 
     @property
     def priority(self):
         if self._opr is not None:
-            return self._opr.priority
-        return 0
+            return (self._opr.priority, self._opr.id)
+        return (0, 0)
 
     @classmethod
     def load(cls, opr):

imperative/python/test/helpers/utils.py

@@ -5,6 +5,7 @@ import numpy as np
 import megengine.core.tensor.megbrain_graph as G
 import megengine.utils.comp_graph_tools as cgtools
 from megengine import tensor
+from megengine.core.tensor.megbrain_graph import OutputNode
 from megengine.jit import trace
 from megengine.utils.network_node import VarNode
 
@@ -12,8 +13,10 @@ from megengine.utils.network_node import VarNode
 def _default_compare_fn(x, y):
     if isinstance(x, np.ndarray):
         np.testing.assert_allclose(x, y, rtol=1e-6)
-    else:
+    elif isinstance(x, tensor):
         np.testing.assert_allclose(x.numpy(), y, rtol=1e-6)
+    else:
+        np.testing.assert_allclose(get_var_value(x), y, rtol=1e-6)
 
 
 def make_tensor(x, network=None, device=None):
@@ -25,6 +28,15 @@ def make_tensor(x, network=None, device=None):
         return tensor(x, device=device)
 
 
+def get_var_value(x):
+    try:
+        o = OutputNode(x.var)
+        o.graph.compile(o.outputs).execute()
+        return o.get_value().numpy()
+    except RuntimeError:
+        raise ValueError("value invalid!")
+
+
 def opr_test(
     cases,
     func,

imperative/python/test/unit/core/test_tensor_wrapper.py

@@ -10,7 +10,7 @@ import copy
 
 import numpy as np
 import pytest
-from utils import make_tensor
+from utils import get_var_value, make_tensor
 
 from megengine.core.tensor.dtype import get_scale, get_zero_point, qint8, quint8
 from megengine.tensor import Parameter, Tensor
@@ -55,7 +55,12 @@ def test_matmul(is_varnode):
     A = make_tensor(np.random.rand(5, 7).astype("float32"), network)
     B = make_tensor(np.random.rand(7, 10).astype("float32"), network)
     C = A @ B
-    np.testing.assert_almost_equal(C.numpy(), A.numpy() @ B.numpy(), decimal=6)
+    if is_varnode:
+        np.testing.assert_almost_equal(
+            get_var_value(C), get_var_value(A) @ get_var_value(B), decimal=6
+        )
+    else:
+        np.testing.assert_almost_equal(C.numpy(), A.numpy() @ B.numpy(), decimal=6)
 
 
 @pytest.mark.parametrize("is_varnode", [True, False])
@@ -116,11 +121,17 @@ def test_set_subtensor(is_varnode):
 
     x = make_tensor([1, 2, 3], network)
     x[:] = [1, 1, 1]
-    np.testing.assert_almost_equal(x.numpy(), [1, 1, 1], decimal=6)
+    np.testing.assert_almost_equal(
+        get_var_value(x) if is_varnode else x.numpy(), [1, 1, 1], decimal=6
+    )
     x[[0, 2]] = [3, 2]
-    np.testing.assert_almost_equal(x.numpy(), [3, 1, 2], decimal=6)
+    np.testing.assert_almost_equal(
+        get_var_value(x) if is_varnode else x.numpy(), [3, 1, 2], decimal=6
+    )
     x[1:3] = [4, 5]
-    np.testing.assert_almost_equal(x.numpy(), [3, 4, 5], decimal=6)
+    np.testing.assert_almost_equal(
+        get_var_value(x) if is_varnode else x.numpy(), [3, 4, 5], decimal=6
+    )
 
 
 def test_computing_with_numpy_array():

imperative/python/test/unit/functional/test_tensor.py

@@ -11,7 +11,7 @@ import platform
 
 import numpy as np
 import pytest
-from utils import make_tensor, opr_test
+from utils import get_var_value, make_tensor, opr_test
 
 import megengine.functional as F
 from megengine import tensor
@@ -75,8 +75,12 @@ def test_condtake(is_varnode):
     xx = make_tensor(x, network)
     yy = make_tensor(y, network)
     val, idx = F.cond_take(yy, xx)
-    np.testing.assert_equal(val.numpy(), x[y])
-    np.testing.assert_equal(idx.numpy(), np.where(y.reshape(-1))[0])
+    if is_varnode:
+        np.testing.assert_equal(get_var_value(val), x[y])
+        np.testing.assert_equal(get_var_value(idx), np.where(y.reshape(-1))[0])
+    else:
+        np.testing.assert_equal(val.numpy(), x[y])
+        np.testing.assert_equal(idx.numpy(), np.where(y.reshape(-1))[0])
 
 
 @pytest.mark.parametrize("is_varnode", [True, False])