address spec in lpnorm

Author: titaiwangms

onnx/backend/test/case/node/lpnormalization.py

@@ -21,7 +21,8 @@ def export_l2normalization_axis_0() -> None:
             dtype=np.float32,
         )
         l2_norm_axis_0 = np.sqrt(np.sum(x**2, axis=0, keepdims=True))
-        y = x / l2_norm_axis_0
+        # When norm is 0, output is 0 (0/0 = 0)
+        y = np.where(l2_norm_axis_0 == 0, 0, x / l2_norm_axis_0)
         expect(node, inputs=[x], outputs=[y], name="test_l2normalization_axis_0")
 
     @staticmethod

onnx/defs/doc_strings.cc

@@ -609,6 +609,9 @@ is applied to the tensor elementwise.
 
 const char kDoc_LpNormalization_ver1[] = R"DOC(
 Given a matrix, apply Lp-normalization along the provided axis.
+The output is computed as: `output = input / Lp_norm(input, axis)`.
+When the Lp norm is zero (i.e., all elements along the axis are zero),
+the output is defined to be zero to avoid division by zero.
 )DOC";
 
 const char kDoc_Erf_ver9[] = R"DOC(

onnx/reference/ops/op_lp_normalization.py

@@ -14,4 +14,6 @@ def _run(self, x, axis=None, p=None):
         p = p or self.p
         norm = np.power(np.power(x, p).sum(axis=axis), 1.0 / p)
         norm = np.expand_dims(norm, axis)
-        return ((x / norm).astype(x.dtype),)
+        # When norm is 0, return 0 instead of NaN (0/0 = 0)
+        result = np.where(norm == 0, 0, x / norm)
+        return (result.astype(x.dtype),)