I am done

rl/Lib/site-packages/onnx/reference/ops/op_min.py

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+# Copyright (c) ONNX Project Contributors
+
+# SPDX-License-Identifier: Apache-2.0
+from __future__ import annotations
+
+import numpy as np
+
+from onnx.reference.ops._op import OpRunBinaryNumpy
+
+
+class Min(OpRunBinaryNumpy):
+    def __init__(self, onnx_node, run_params):  # type: ignore
+        OpRunBinaryNumpy.__init__(self, np.minimum, onnx_node, run_params)
+
+    def run(self, *data):  # type: ignore
+        if len(data) == 2:
+            return OpRunBinaryNumpy.run(self, *data)
+        if len(data) == 1:
+            return (data[0].copy(),)
+        if len(data) > 2:
+            a = data[0]
+            for i in range(1, len(data)):
+                a = np.minimum(a, data[i])
+            return (a,)
+        raise RuntimeError("Unexpected turn of events.")