chore: add support for quantized versions of CV models CLIP, Style Transfer, EfficientNetV2, SSDLite

[barhanc]

Description

Adds support for quantized versions of CV models CLIP, Style Transfer, EfficientNetV2, SSDLite and updates paths to non-quantized models exported with ExecuTorch v1.1.0.

Introduces a breaking change?

• Yes
• No

Type of change

• Bug fix (change which fixes an issue)
• New feature (change which adds functionality)
• Documentation update (improves or adds clarity to existing documentation)
• Other (chores, tests, code style improvements etc.)

Tested on

• iOS
• Android

Testing instructions

1. Run the Computer Vision example app:
   • Object detection with model set to:
     • SSDLITE_320_MOBILENET_V3_LARGE
   • Classification with model set to:
     • EFFICIENTNET_V2_S,
     • EFFICIENTNET_V2_S_QUANTIZED
   • Style transfer with model set to:
     • STYLE_TRANSFER_CANDY,
     • STYLE_TRANSFER_MOSAIC,
     • STYLE_TRANSFER_UDNIE,
     • STYLE_TRANSFER_RAIN_PRINCESS,
     • STYLE_TRANSFER_CANDY_QUANTIZED,
     • STYLE_TRANSFER_MOSAIC_QUANTIZED,
     • STYLE_TRANSFER_UDNIE_QUANTIZED,
     • STYLE_TRANSFER_RAIN_PRINCESS_QUANTIZED,
2. Run the Text Embeddings example app:
   • CLIP embeddings with image model set to:
     • CLIP_VIT_BASE_PATCH32_IMAGE,
     • CLIP_VIT_BASE_PATCH32_IMAGE_QUANTIZED
3. Check HF pages for updated models:
   • https://huggingface.co/software-mansion/react-native-executorch-style-transfer-candy
   • https://huggingface.co/software-mansion/react-native-executorch-style-transfer-mosaic
   • https://huggingface.co/software-mansion/react-native-executorch-style-transfer-rain-princess
   • https://huggingface.co/software-mansion/react-native-executorch-style-transfer-udnie
   • https://huggingface.co/software-mansion/react-native-executorch-efficientnet-v2-s
   • https://huggingface.co/software-mansion/react-native-executorch-ssdlite320-mobilenet-v3-large
   • https://huggingface.co/software-mansion/react-native-executorch-clip-vit-base-patch32

Screenshots

Related issues

Closes #719

Checklist

• I have performed a self-review of my code
• I have commented my code, particularly in hard-to-understand areas
• I have updated the documentation accordingly
• My changes generate no new warnings

Additional notes

[NorbertKlockiewicz]

I will run the new models later today to see if they work. I think you should also benchmark them and add the results to our docs.

You can ask @IgorSwat for the tips about benchmarking ;D

[IgorSwat]

@barhanc Did you profile the added XNNPACK models following these instructions?

I guess they should be fine considering that those are only a quantized versions of already profiled models, but it's always nice to check if everything is alright with export.

[barhanc]

I've added the profiling results to the corresponding READMEs in the internal exports gitlab. They all look fine to me (>80% delegated ops), but you can also take a look to make sure everything is correct.

[NorbertKlockiewicz]

Please change examples in demo apps to use quantized models by default.

[NorbertKlockiewicz]

Suggested change

	export const EFFICIENTNET_V2_S_QUANTIZED = {
	modelSource: EFFICIENTNET_V2_S_QUANTIZED_MODEL,
	};
	export const EFFICIENTNET_V2_S_QUANTIZED = {
	modelName: "efficientnet-v2-s-quantized"
	modelSource: EFFICIENTNET_V2_S_QUANTIZED_MODEL,
	};

Please add modelName to each new model

[barhanc]

Done