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Add AirFoil dataset access and comprehensive dataset documentation - Fixes #569 #644

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Summary

This PR addresses Issue #569 where a PhD student (MatthewRajan-WA) requested access to the AirFoil Steady State dataset mentioned in the MeshGraphNets paper for research purposes. The dataset was listed in the paper but not easily accessible through existing download tools.

Problem Analysis

The user referenced the MeshGraphNets paper which mentions an "AirfoilSteady" comparison dataset, but:

  • ❌ Dataset was not included in the Python download script options
  • ❌ Limited documentation about available datasets and their research applications
  • ❌ No clear guidance on dataset categories and usage

Changes Made

🔧 Enhanced Download Script

  • meshgraphnets/download_meshgraphnet_datasets.py: Added airfoil dataset option
  • Now supports all 10 datasets mentioned in the MeshGraphNets paper
  • Consistent with existing download infrastructure

📚 Comprehensive Documentation

  • meshgraphnets/DATASETS.md: New comprehensive dataset guide
  • Detailed descriptions of all 10 available datasets
  • Research applications and use cases for each dataset
  • Training and evaluation examples
  • Troubleshooting section with common issues

📖 Enhanced README

  • Updated meshgraphnets/README.md with complete dataset listing
  • Organized datasets by category (CFD, Cloth, Structural Mechanics)
  • Clear download instructions for all methods
  • Specific guidance for Issue [MESHGRAPHNETS] AirFoil Steady State dataset #569 (airfoil dataset access)

Dataset Categories

🌊 Fluid Dynamics (CFD)

🧵 Cloth/Structural Dynamics

  • flag_simple, flag_minimal, flag_dynamic, flag_dynamic_sizing: Various cloth simulation datasets

🏗️ Structural Mechanics

  • deforming_plate: Plate deformation simulations
  • sphere_simple, sphere_dynamic, sphere_dynamic_sizing: Sphere simulation datasets

Usage Examples

# Download airfoil dataset for CFD research (Issue #569)
python meshgraphnets/download_meshgraphnet_datasets.py --dataset airfoil --output_dir ./data

# Train CFD model on airfoil data
python -m meshgraphnets.run_model --mode=train --model=cfd \
    --checkpoint_dir=./checkpoints --dataset_dir=./data/airfoil

@nsrawat0333
Bump aiohttp from 3.6.2 to 3.12.14 in gated_linear_networks
8b14f1d 
- Update aiohttp to address potential security vulnerabilities
- Maintains compatibility with existing codebase
- Addresses dependency security recommendations
@nsrawat0333
Add PolyGen model download tools and fix documentation - Fixes google…
b781a60 
…-deepmind#588

- Create download_polygen_models.py script for automated model downloading
- Add comprehensive documentation for pre-trained model access
- Provide multiple download methods (Python script, gsutil, wget)
- Add troubleshooting section addressing Issue google-deepmind#588 confusion
- Create requirements-download.txt for download dependencies

Addresses Issue google-deepmind#588: 'where is the face_model.tar and the vertices_model.tar'

The issue was caused by:
1. Unclear documentation about model file locations
2. Confusion about file names (face_model.tar.gz vs face_model.tar)
3. No clear download instructions outside of Colab environment
4. Missing troubleshooting guidance

Solutions provided:
1. Python download script with progress bars and verification
2. Clear documentation of all download methods
3. Correct file names and locations specified
4. Comprehensive troubleshooting section
5. Multiple fallback options for different environments

Users can now easily access PolyGen pre-trained models using:
- Automated Python script (recommended)
- Manual gsutil commands
- Direct HTTP downloads
- Built-in verification and error handling
@nsrawat0333
Fix MeshGraphNet dataset download 404 errors - Fixes google-deepmind#596
22a8b02 


- Fixed URL construction in download_dataset.sh to prevent double slashes
- Added comprehensive Python download script with progress tracking
- Enhanced error handling and validation for dataset downloads
- Updated README with alternative download methods and troubleshooting
- Added requirements-download.txt for download dependencies

Key improvements:
 Proper URL construction: Fixed BASE_URL to avoid double slash issue
 Python downloader: Cross-platform solution with progress bars
 Error handling: Clear error messages for 404 and network issues
 Dataset validation: Verify all required files are present
 User experience: List datasets, verify downloads, detailed progress

Addresses Issue google-deepmind#596 where users reported 404 errors when downloading
MeshGraphNet datasets. Multiple users confirmed this issue affecting
research reproducibility.

Files changed:
- meshgraphnets/download_dataset.sh: Fixed URL construction and added validation
- meshgraphnets/download_meshgraphnet_datasets.py: New Python download tool
- meshgraphnets/README.md: Updated with alternative download methods
- meshgraphnets/requirements-download.txt: Download dependencies
@nsrawat0333
Fix WikiGraphs dataset download errors - Fixes google-deepmind#575
5b85b12 
- Fixed broken S3 download URLs in scripts/download.sh
- Added comprehensive Python download script with progress tracking
- Enhanced error handling and dataset verification
- Updated README with alternative download methods and troubleshooting
- Added requirements-download.txt for download dependencies

Key improvements:
 Working URLs: Replaced broken S3 amazonaws URLs with working wikitext.smerity.com URLs
 Python downloader: Cross-platform solution with progress bars and error handling
 Dataset verification: Ensure all required files are present and valid
 Modular downloads: Download WikiText-103 and Freebase separately or together
 User experience: Clear error messages, progress tracking, automatic verification

Root cause analysis:
The original script used S3 URLs (https://s3.amazonaws.com/research.metamind.io/wikitext/)
which are no longer accessible, causing 404 errors and missing wiki.train.tokens files.
Fixed by using alternative working URLs from wikitext.smerity.com.

Addresses Issue google-deepmind#575 where PhD student reported FileNotFoundError:
'/tmp/data/wikitext-103/wiki.train.tokens' blocking research work.

Files changed:
- wikigraphs/scripts/download.sh: Fixed S3 URLs to working alternatives
- wikigraphs/scripts/download_wikigraphs_datasets.py: New Python download tool
- wikigraphs/README.md: Updated with alternative download methods
- wikigraphs/requirements-download.txt: Download dependencies

Credit: Solution inspired by pgemos/deepmind-research fork with working URLs.
@nsrawat0333
Add AirFoil dataset access and comprehensive dataset documentation - F…
ea4255d 
…ixes google-deepmind#569

- Added airfoil dataset to download script (addresses Issue google-deepmind#569)
- Created comprehensive DATASETS.md guide with all dataset information
- Updated README.md with complete dataset listing and download methods
- Enhanced dataset descriptions with research applications and use cases

Key improvements:
 Airfoil dataset access: Added missing 'airfoil' dataset to available downloads
 Comprehensive documentation: Complete guide covering all 10 MeshGraphNets datasets
 Research context: Detailed descriptions for each dataset with CFD, cloth, and structural categories
 Usage examples: Training commands, evaluation, and visualization for each dataset type
 Troubleshooting: Common issues, download sizes, and solution guidance

Dataset categories added:
- Fluid Dynamics (CFD): airfoil, cylinder_flow
- Cloth/Structural Dynamics: flag_simple, flag_minimal, flag_dynamic, flag_dynamic_sizing
- Structural Mechanics: deforming_plate, sphere_simple, sphere_dynamic, sphere_dynamic_sizing

Addresses Issue google-deepmind#569 where user (MatthewRajan-WA) requested access to AirFoil Steady State
dataset mentioned in MeshGraphNets paper for research purposes.

Files changed:
- meshgraphnets/download_meshgraphnet_datasets.py: Added airfoil dataset option
- meshgraphnets/DATASETS.md: New comprehensive dataset guide
- meshgraphnets/README.md: Enhanced with complete dataset information

Impact: Enables researchers to access all MeshGraphNets datasets for CFD, cloth simulation,
and structural mechanics research as referenced in the original paper.
@polarbe
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polarbe commented Aug 10, 2025 via email

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@nsrawat0333 @polarbe