[Feature]: Add onnx evaluation tool

[RunningLeon]

This PR includes:

• Add a tool to evaluate ONNX models with ONNXRuntime backend.
• Align metrics of models between PyTorch and ONNXRuntime.
• Update the document.

Results and Models

Model	Config	Dataset	Metric	PyTorch	ONNX Runtime
ESRGAN	esrgan_x4c64b23g32_g1_400k_div2k.py	Set5	PSNR	28.2700	28.2619
			SSIM	0.7778	0.7784
		Set14	PSNR	24.6328	24.6290
			SSIM	0.6491	0.6494
		DIV2K	PSNR	26.6531	26.6532
			SSIM	0.7340	0.7340
ESRGAN	esrgan_psnr_x4c64b23g32_g1_1000k_div2k.py	Set5	PSNR	30.6428	30.6307
			SSIM	0.8559	0.8565
		Set14	PSNR	27.0543	27.0422
			SSIM	0.7447	0.7450
		DIV2K	PSNR	29.3354	29.3354
			SSIM	0.8263	0.8263
SRCNN	srcnn_x4k915_g1_1000k_div2k.py	Set5	PSNR	28.4316	28.4120
			SSIM	0.8099	0.8106
		Set14	PSNR	25.6486	25.6367
			SSIM	0.7014	0.7015
		DIV2K	PSNR	27.7460	27.7460
			SSIM	0.7854	0.78543

Notes:

• All ONNX models are evaluated with dynamic shape on the datasets and images are preprocessed according to the original config file.
• This tool is still experimental, and we only support restorer for now.

[codecov]

Codecov Report

Merging #279 (6b3cf88) into master (293b513) will increase coverage by 0.55%.
The diff coverage is 88.63%.

@@            Coverage Diff             @@
##           master     #279      +/-   ##
==========================================
+ Coverage   79.99%   80.54%   +0.55%     
==========================================
  Files         160      162       +2     
  Lines        8003     8091      +88     
  Branches     1185     1192       +7     
==========================================
+ Hits         6402     6517     +115     
+ Misses       1456     1429      -27     
  Partials      145      145              

Flag	Coverage Δ
unittests	80.54% <88.63%> (+0.55%)	⬆️

Flags with carried forward coverage won't be shown. Click here to find out more.

Impacted Files	Coverage Δ
mmedit/core/export/wrappers.py	88.37% <88.37%> (ø)
mmedit/core/export/__init__.py	100.00% <100.00%> (ø)
mmedit/models/mattors/dim.py	82.69% <0.00%> (+1.92%)	⬆️
mmedit/models/mattors/base_mattor.py	85.41% <0.00%> (+3.12%)	⬆️
.../models/backbones/encoder_decoders/encoders/vgg.py	98.33% <0.00%> (+5.00%)	⬆️
...ckbones/encoder_decoders/decoders/plain_decoder.py	100.00% <0.00%> (+33.70%)	⬆️

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[Yshuo-Li]

Fine.

[innerlee]

Please add some unit tests for functions and classes in mmedit/core/export/wrappers.py

[grimoire]

@innerlee can we just ignore these functions and classes in Codecov since it is hard to test without a real ONNX model.

[innerlee]

a real ONNX model.

A dummy model contains a single conv or fc is good enough.

[innerlee]

If the onnx runtime is not available at CI, you can edit the config similar to this line https://github.com/open-mmlab/mmediting/blob/master/.github/workflows/build.yml#L54