ReflectPadding Parse Error

Environment
- NVIDIA A10
- TensorRT 8.4GA
- CUDA 11.6
- CuDNN 8.4.0
- CUBLAS 11.9.2
- NVIDIA Driver 510.73.08

Reproduction Steps

CASE

unit.py: Generate ONNX graph with a Pad layer with reflect mode.

import torch
import torch.nn as nn
import torch.nn.functional as F

class ReflectPad(nn.Module):
  def __init__(self):
      super(ReflectPad, self).__init__()

  def forward(self, input):
      out = F.pad(input, (0, 1, 0, 2), "reflect")
      return out

input = torch.arange(9, dtype=torch.float).reshape(1, 1, 3, 3).cuda()
print(input)
rp = ReflectPad().cuda()
out = rp(input)
print(out)

torch.onnx.export(rp,
                input,
                "unit.onnx",
                input_names=["input"],
                output_names=["output"],
                verbose=True,
                keep_initializers_as_inputs=True,
                opset_version=13,
                dynamic_axes={"input": {0: "batch_size"}})

parse.sh: parse the onnx graph generated

#!/usr/bin/env bash
python3 unit.py

trtexec \
      --onnx=unit.onnx \
      --explicitBatch \
      --minShapes=lr:1x3x64x64 \
      --optShapes=lr:1x3x80x80 \
      --maxShapes=lr:1x3x120x120 \
      --saveEngine=unit.plan \
      --workspace=40960 \
      --buildOnly \
      --noTF32 \
      --verbose \

Run this case:

bash parse.sh

Expected Behavior
- Reffered from [Release TensorRT OSS v8.2.0 EA](https://github.com/NVIDIA/TensorRT/releases/tag/8.2.0-EA), TensorRT parser supported Pad layer in ONNX, especially ND padding, along with reflect padding mode.
- So that this case can parse the graph and generate a TensorRT plan successfully.

Actual Behavior

Error occurred:

[06/27/2022-11:15:47] [E] [TRT] ModelImporter.cpp:776: --- End node ---
[06/27/2022-11:15:47] [E] [TRT] ModelImporter.cpp:779: ERROR: ModelImporter.cpp:180 In function parseGraph:
[6] Invalid Node - Pad_13
[shuffleNode.cpp::symbolicExecute::392] Error Code 4: Internal Error (Reshape_3: IShuffleLayer applied to shape tensor must have 0 or 1 reshape dimensions: dimensions were [-1,2])
[06/27/2022-11:15:47] [E] Failed to parse onnx file
[06/27/2022-11:15:47] [I] Finish parsing network model
[06/27/2022-11:15:47] [E] Parsing model failed
[06/27/2022-11:15:47] [E] Failed to create engine from model or file.
[06/27/2022-11:15:47] [E] Engine set up failed
&&&& FAILED TensorRT.trtexec [TensorRT v8401] # trtexec --onnx=unit.onnx --explicitBatch --minShapes=lr:1x3x64x64 --optShapes=lr:1x3x80x80 --maxShapes=lr:1x3x120x120 --saveEngine=unit.plan --workspace=40960 --buildOnly --noTF32 --verbose

Additional Notes
- After I propose this problem, NVDIA give a workaround can be used to solve this problem temporally: [padNode-war](https://github.com/NVIDIA/trt-samples-for-hackathon-cn/tree/master/cookbook/06-PluginAndParser/pyTorch-PadNode) .
- There are many existing posts with this problem need help:
- [Reflect padding in TensorRT - Deep Learning (Training & Inference) / TensorRT - NVIDIA Developer Forums](https://forums.developer.nvidia.com/t/reflect-padding-in-tensorrt/187326)
- [Pad opset 11 not supported · Issue #378 · onnx/onnx-tensorrt (github.com)](https://github.com/onnx/onnx-tensorrt/issues/378)

NVIDIA / trt-samples-for-hackathon-cn

ReflectPadding Parse Error #34