I am done

rl/Lib/site-packages/onnx/reference/ops/op_pad.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.op_run import OpRun
+
+
+def _pad_impl(data, raw_pads, mode, constant_values=0.0, axes=None):  # type: ignore
+    input_rank = data.ndim
+    if axes is None:
+        axes = list(range(input_rank))
+    else:
+        axes = [axis if axis >= 0 else axis + input_rank for axis in axes]
+    num_axes = len(axes)
+    if num_axes * 2 != len(raw_pads):
+        raise RuntimeError(
+            "The number of elements in raw_pads should be 2 times the number of axes"
+        )
+
+    pad_width = [(0, 0)] * input_rank
+    for i, axis in enumerate(axes):
+        pad_begin = raw_pads[i]
+        pad_end = raw_pads[num_axes + i]
+        pad_width[axis] = (pad_begin, pad_end)
+
+    if mode == "constant":
+        return np.pad(
+            data, pad_width=pad_width, mode=mode, constant_values=constant_values
+        ).astype(data.dtype)
+    return np.pad(data, pad_width=pad_width, mode=mode).astype(data.dtype)
+
+
+class Pad_1(OpRun):
+    def _run(self, data, paddings=None, mode=None, value=None):  # type: ignore
+        if value is None:
+            value = 0
+        return (_pad_impl(data, paddings, mode=mode, constant_values=value),)
+
+
+class Pad_2(OpRun):
+    def _run(self, data, pads=None, mode=None, value=None):  # type: ignore
+        if value is None:
+            value = 0
+        return (_pad_impl(data, pads, mode=mode, constant_values=value),)
+
+
+class Pad_11(OpRun):
+    def _run(self, data, pads, constant_value=None, mode=None):  # type: ignore
+        if constant_value is None:
+            constant_value = 0
+        return (
+            _pad_impl(data, pads, mode=mode, constant_values=constant_value, axes=None),
+        )
+
+
+class Pad_18(OpRun):
+    def _run(self, data, pads, constant_value=None, axes=None, mode=None):  # type: ignore
+        if constant_value is None:
+            constant_value = 0
+        return (
+            _pad_impl(data, pads, mode=mode, constant_values=constant_value, axes=axes),
+        )