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license: apache-2.0 |
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# ML4TSP Pretrained Files 2024-02-02 |
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**This repository primarily stores the pretrained files for ML4TSP.** |
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**All the files in this repository have a last update date prior to 2024-02-02.** |
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## 1. Dataset |
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#### 1.1 Supervised Learning Training Dataset |
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**File Naming Convention:** tsp{nodes_num}\_{distribution}\_{solver(params)}\_{size}.txt |
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| Problem Scale | Train File | |
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|:-------------:|:----------:| |
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| TSP50 | [tsp50_uniform_lkh_5k_1.28m.txt](https://huggingface.co/datasets/ML4CO/ML4TSPDataset/blob/main/tsp50_uniform_lkh_5k_1.28m.txt) | LKH-5K | |
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| TSP100 | [tsp100_uniform_lkh_5k_1.28m.txt](https://huggingface.co/datasets/ML4CO/ML4TSPDataset/blob/main/tsp100_uniform_lkh_5k_1.28m.txt) | LKH-5K | |
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| TSP500 | [tsp500_uniform_lkh_50k_128k.txt](https://huggingface.co/datasets/ML4CO/ML4TSPDataset/blob/main/tsp500_uniform_lkh_50k_128k.txt) | LKH-50k | |
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| TSP1000 | [tsp1000_uniform_lkh_100k_64k.txt](https://huggingface.co/datasets/ML4CO/ML4TSPDataset/blob/main/tsp1000_uniform_lkh_100k_64k.txt) | LKH-100k | |
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#### 1.2 Test Dataset (Uniform) |
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**File Naming Convention:** tsp{nodes_num}\_{solver(params)}\_{avg_length}.txt |
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| Problem Scale | Test | Distribution | Size | |
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|:-------------:|:----:|:------------:|:----:| |
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| TSP50 | [tsp50_concorde_5.68759.txt](https://huggingface.co/datasets/ML4CO/TSPUniformDataset/blob/main/tsp_uniform/tsp50_concorde_5.68759.txt) | uniform | 1280 | |
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| TSP100 | [tsp100_concorde_7.75585.txt](https://huggingface.co/datasets/ML4CO/TSPUniformDataset/blob/main/tsp_uniform/tsp100_concorde_7.75585.txt) | uniform | 1280 | |
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| TSP500 | [tsp500_concorde_16.54581.txt](https://huggingface.co/datasets/ML4CO/TSPUniformDataset/blob/main/tsp_uniform/tsp500_concorde_16.54581.txt) | uniform | 128 | |
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| TSP1000 | [tsp1000_concorde_23.11812.txt](https://huggingface.co/datasets/ML4CO/TSPUniformDataset/blob/main/tsp_uniform/tsp1000_concorde_23.11812.txt) | uniform | 128 | |
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| TSP10000 | [tsp10000_concorde_large_71.84185.txt](https://huggingface.co/datasets/ML4CO/TSPUniformDataset/blob/main/tsp_uniform/tsp10000_concorde_large_71.84185.txt) | uniform | 16 | |
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## 2. Model Parameters |
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#### 2.1 NAR Model Parameters |
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| Pretrained File | Net Type | Layer | Embed | Hidden | Out | Epoch(select)| |
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|:----------------|:--------:|:-----:|:-----:|:------:|:---:|:------------:| |
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| tsp50_diffusion.pt | gnn | 12 | 128 | 256 | 2 | 100(?) | |
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| tsp50_dimes.pt | gnn | 12 | 128 | 256 | 2 | 405/500step | |
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| tsp50_gnn.pt | gnn | 12 | 128 | 256 | 2 | 100(96) | |
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| tsp50_gnn_wise.pt | gnn | 12 | 128 | 256 | 2 | 100(76) | |
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| tsp50_gnn4reg.pt | gnn | 12 | 128 | 256 | 2 | 100(62) | |
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| tsp50_us.pt | sag | 3 | 64 | 64 | 50 | 100(3) | |
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| tsp100_diffusion.pt | gnn | 12 | 128 | 256 | 2 | 50(?) | |
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| tsp100_dimes.pt | gnn | 12 | 128 | 256 | 2 | 240/250step | |
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| tsp100_gnn.pt | gnn | 12 | 128 | 256 | 2 | 50(50) | |
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| tsp100_gnn_wise.pt | gnn | 12 | 128 | 256 | 2 | 50(48) | |
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| tsp100_gnn4reg.pt | gnn | 12 | 128 | 256 | 2 | 50(18) | |
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| tsp100_us.pt | sag | 3 | 64 | 64 | 50 | 50(3) | |
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| tsp500_diffusion.pt | gnn | 12 | 128 | 256 | 2 | 50(?) | |
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| tsp500_dimes.pt | gnn | 12 | 128 | 256 | 2 | 66/100step | |
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| tsp500_gnn.pt | gnn | 12 | 128 | 256 | 2 | 50(22) | |
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| tsp500_gnn_wise.pt | gnn | 12 | 128 | 256 | 2 | 50(14) | |
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| tsp1000_diffusion.pt | gnn | 12 | 128 | 256 | 2 | 50(?) | |
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| tsp1000_gnn_wise.pt | gnn | 12 | 128 | 256 | 2 | 50(44) | |
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#### 2.2 AR Model Parameters |
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| Pretrained File | Net Type | Layer | Embed | Heads | Baseline | Epoch(select)| |
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|:----------------|:--------:|:-----:|:-----:|:-----:|:--------:|:------------:| |
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| tsp50_am.pt | gat | 3 | 128 | 8 | rollout | 360(360) | |
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| tsp50_pomo.pt | gat | 3 | 128 | 8 | shared | 360(360) | |
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| tsp50_symnco.pt | gat | 3 | 128 | 8 | no | 360(360) | |
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| tsp100_am.pt | gat | 3 | 128 | 8 | rollout | 500(500) | |
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| tsp100_pomo.pt | gat | 3 | 128 | 8 | shared | 100(100) | |
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| tsp100_symnco.pt | gat | 3 | 128 | 8 | no | 330(329) | |
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## 3. Training Details |
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### 3.1 NAR Model |
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* lr_scheduler: "cosine-decay" (torch.optim.lr_scheduler.CosineAnnealingLR) |
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* learning-rate: 0.003(initial) |
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* optimizer: "AdamW" (torch.optim.AdamW) |
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### 3.2 AR Model |
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* lr_scheduler: None |
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* learning-rate: 0.0001(fix) |
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* optimizer: "Adam" (torch.optim.Adam) |
