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.DS_Store ADDED
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README.md ADDED
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1
+ ---
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+ base_model:
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+ - facebook/convnext-base-224
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+ library_name: transformers
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+ tags:
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+ - fusion-bench
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+ - merge
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+ ---
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+ # Deep Model Fusion
10
+
11
+ Fine-tuned ResNet model on dataset dtd.
12
+
13
+ ## Models Merged
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+
15
+ This is a merged model created using [fusion-bench](https://github.com/tanganke/fusion_bench).
16
+
17
+ The following models were included in the merge:
18
+
19
+
20
+ - base model: facebook/convnext-base-224
21
+
22
+
23
+ ## Configuration
24
+
25
+ The following YAML configuration was used to produce this model:
26
+
27
+ ### Algorithm Configuration
28
+
29
+ ```yaml
30
+ _recursive_: false
31
+ _target_: fusion_bench.method.classification.image_classification_finetune.ImageClassificationFineTuning
32
+ _usage_: null
33
+ _version_: 0.2.31.dev0
34
+ dataloader_kwargs:
35
+ batch_size: 64
36
+ num_workers: 8
37
+ pin_memory: true
38
+ label_smoothing: 0
39
+ lr_scheduler: null
40
+ max_epochs: -1
41
+ max_steps: 4000
42
+ optimizer:
43
+ _target_: torch.optim.SGD
44
+ lr: 0.01
45
+ momentum: 0.9
46
+ weight_decay: 0.0001
47
+ save_interval: 1000
48
+ save_on_train_epoch_end: false
49
+ save_top_k: -1
50
+ training_data_ratio: null
51
+ ```
52
+
53
+ ### Model Pool Configuration
54
+
55
+ ```yaml
56
+ _recursive_: false
57
+ _target_: fusion_bench.modelpool.convnext_for_image_classification.ConvNextForImageClassificationPool
58
+ _usage_: null
59
+ _version_: 0.2.31.dev0
60
+ models:
61
+ _pretrained_:
62
+ config_path: facebook/convnext-base-224
63
+ dataset_name: dtd
64
+ pretrained: true
65
+ test_datasets: null
66
+ train_datasets:
67
+ dtd:
68
+ _target_: datasets.load_dataset
69
+ path: tanganke/dtd
70
+ split: train
71
+ val_datasets:
72
+ dtd:
73
+ _target_: datasets.load_dataset
74
+ path: tanganke/dtd
75
+ split: test
76
+ ```
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+
cli.log ADDED
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+ [2026-01-08 04:49:05,782][fusion_bench.programs.fusion_program][INFO] - Running the model fusion program.
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+ [2026-01-08 04:49:05,785][fusion_bench.programs.fusion_program][INFO] - loading model pool
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+ [2026-01-08 04:49:08,035][fusion_bench.programs.fusion_program][INFO] - loading method
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+ [2026-01-08 04:49:08,098][fusion_bench.method.classification.image_classification_finetune][INFO] - Training interval: step
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+ [2026-01-08 04:49:08,098][fusion_bench.method.classification.image_classification_finetune][INFO] - Max epochs: -1, max steps: 4000
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+ [2026-01-08 04:49:08,099][fusion_bench.programs.fusion_program][INFO] - loading task pool
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+ [2026-01-08 04:49:09,773][fusion_bench.method.classification.image_classification_finetune][INFO] - Number of classes for dataset dtd: 47
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+ [2026-01-08 04:49:09,786][datasets.load][WARNING] - Using the latest cached version of the dataset since tanganke/dtd couldn't be found on the Hugging Face Hub (offline mode is enabled).
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+ [2026-01-08 04:49:09,795][datasets.packaged_modules.cache.cache][WARNING] - Found the latest cached dataset configuration 'default' at /data/dataset/datasets/tanganke___dtd/default/0.0.0/d2afa97d9f335b1a6b3b09c637aef667f98f966e (last modified on Mon Jan 5 04:22:16 2026).
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+ [2026-01-08 04:49:09,972][fusion_bench.method.classification.image_classification_finetune][INFO] - Training dataset size: 3760
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+ [2026-01-08 04:49:10,003][datasets.load][WARNING] - Using the latest cached version of the dataset since tanganke/dtd couldn't be found on the Hugging Face Hub (offline mode is enabled).
12
+ [2026-01-08 04:49:10,010][datasets.packaged_modules.cache.cache][WARNING] - Found the latest cached dataset configuration 'default' at /data/dataset/datasets/tanganke___dtd/default/0.0.0/d2afa97d9f335b1a6b3b09c637aef667f98f966e (last modified on Mon Jan 5 04:22:16 2026).
13
+ [2026-01-08 04:49:10,060][fusion_bench.method.classification.image_classification_finetune][INFO] - optimizer:
14
+ SGD (
15
+ Parameter Group 0
16
+ dampening: 0
17
+ differentiable: False
18
+ foreach: None
19
+ fused: None
20
+ lr: 0.01
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+ maximize: False
22
+ momentum: 0.9
23
+ nesterov: False
24
+ weight_decay: 0.0001
25
+ )
26
+ [2026-01-08 05:15:05,827][fusion_bench.method.classification.image_classification_finetune][INFO] - Saving the final model to outputs/convnext-base-224/dtd/batch_size=64,lr=0.01/raw_checkpoints/final
config.json ADDED
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1
+ {
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+ "architectures": [
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+ "ConvNextForImageClassification"
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+ ],
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+ "depths": [
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+ 3,
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+ 3,
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+ 27,
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+ 3
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+ ],
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+ "drop_path_rate": 0.0,
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+ "dtype": "float32",
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+ "hidden_act": "gelu",
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+ "hidden_sizes": [
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+ 128,
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+ 256,
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+ 512,
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+ 1024
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+ ],
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+ "id2label": {
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+ "0": "banded",
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+ "1": "blotchy",
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+ "2": "braided",
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+ "3": "bubbly",
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+ "4": "bumpy",
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+ "5": "chequered",
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+ "6": "cobwebbed",
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+ "7": "cracked",
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+ "8": "crosshatched",
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+ "9": "crystalline",
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+ "10": "dotted",
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+ "11": "fibrous",
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+ "12": "flecked",
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+ "13": "freckled",
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+ "14": "frilly",
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+ "15": "gauzy",
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+ "16": "grid",
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+ "17": "grooved",
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+ "18": "honeycombed",
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+ "19": "interlaced",
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+ "20": "knitted",
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+ "21": "lacelike",
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+ "22": "lined",
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+ "23": "marbled",
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+ "24": "matted",
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+ "25": "meshed",
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+ "26": "paisley",
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+ "27": "perforated",
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+ "28": "pitted",
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+ "29": "pleated",
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+ "30": "polka-dotted",
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+ "31": "porous",
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+ "32": "potholed",
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+ "33": "scaly",
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+ "34": "smeared",
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+ "35": "spiralled",
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+ "36": "sprinkled",
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+ "37": "stained",
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+ "38": "stratified",
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+ "39": "striped",
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+ "40": "studded",
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+ "41": "swirly",
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+ "42": "veined",
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+ "43": "waffled",
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+ "44": "woven",
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+ "45": "wrinkled",
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+ "46": "zigzagged"
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+ },
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+ "image_size": 224,
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+ "initializer_range": 0.02,
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+ "label2id": {
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+ "banded": 0,
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+ "blotchy": 1,
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+ "braided": 2,
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+ "bubbly": 3,
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+ "bumpy": 4,
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+ "chequered": 5,
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+ "cobwebbed": 6,
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+ "cracked": 7,
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+ "crosshatched": 8,
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+ "crystalline": 9,
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+ "dotted": 10,
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+ "fibrous": 11,
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+ "flecked": 12,
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+ "freckled": 13,
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+ "frilly": 14,
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+ "gauzy": 15,
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+ "grid": 16,
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+ "grooved": 17,
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+ "honeycombed": 18,
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+ "interlaced": 19,
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+ "knitted": 20,
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+ "lacelike": 21,
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+ "lined": 22,
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+ "marbled": 23,
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+ "matted": 24,
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+ "meshed": 25,
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+ "paisley": 26,
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+ "perforated": 27,
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+ "pitted": 28,
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+ "pleated": 29,
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+ "polka-dotted": 30,
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+ "porous": 31,
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+ "potholed": 32,
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+ "scaly": 33,
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+ "smeared": 34,
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+ "spiralled": 35,
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+ "sprinkled": 36,
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+ "stained": 37,
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+ "stratified": 38,
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+ "striped": 39,
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+ "studded": 40,
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+ "swirly": 41,
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+ "veined": 42,
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+ "waffled": 43,
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+ "woven": 44,
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+ "wrinkled": 45,
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+ "zigzagged": 46
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+ },
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+ "layer_norm_eps": 1e-12,
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+ "layer_scale_init_value": 1e-06,
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+ "model_type": "convnext",
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+ "num_channels": 3,
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+ "num_stages": 4,
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+ "out_features": [
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+ "stage4"
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+ ],
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+ "out_indices": [
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+ 4
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+ ],
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+ "patch_size": 4,
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+ "stage_names": [
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+ "stem",
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+ "stage1",
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+ "stage2",
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+ "stage3",
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+ "stage4"
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+ ],
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+ "transformers_version": "4.57.3"
140
+ }
config.yaml ADDED
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1
+ path:
2
+ root_dir: ${oc.env:FUSION_BENCH_PROJECT_ROOT,"."}
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+ output_dir: ${.root_dir}/outputs
4
+ data_dir: ${oc.env:FUSION_BENCH_DATA_DIR,${.root_dir}/data}
5
+ cache_dir: ${oc.env:FUSION_BENCH_CACHE_DIR,${.output_dir}/cache}
6
+ log_dir: outputs/convnext-base-224/dtd/batch_size=64,lr=0.01
7
+ work_dir: ${hydra:runtime.cwd}
8
+ modelpool:
9
+ _target_: fusion_bench.modelpool.ConvNextForImageClassificationPool
10
+ _recursive_: false
11
+ models:
12
+ _pretrained_:
13
+ config_path: facebook/convnext-base-224
14
+ pretrained: true
15
+ dataset_name: dtd
16
+ train_datasets:
17
+ dtd:
18
+ _target_: datasets.load_dataset
19
+ path: tanganke/dtd
20
+ split: train
21
+ val_datasets:
22
+ dtd:
23
+ _target_: datasets.load_dataset
24
+ path: tanganke/dtd
25
+ split: test
26
+ test_datasets: null
27
+ method:
28
+ _target_: fusion_bench.method.classification.ImageClassificationFineTuning
29
+ max_epochs: -1
30
+ max_steps: 4000
31
+ save_top_k: -1
32
+ save_interval: 1000
33
+ save_on_train_epoch_end: false
34
+ training_data_ratio: null
35
+ label_smoothing: 0
36
+ optimizer:
37
+ _target_: torch.optim.SGD
38
+ lr: 0.01
39
+ momentum: 0.9
40
+ weight_decay: 0.0001
41
+ lr_scheduler: null
42
+ dataloader_kwargs:
43
+ batch_size: 64
44
+ num_workers: 8
45
+ pin_memory: true
46
+ taskpool:
47
+ _target_: fusion_bench.taskpool.DummyTaskPool
48
+ model_save_path: null
49
+ _target_: fusion_bench.programs.ModelFusionProgram
50
+ _recursive_: false
51
+ seed: 0
52
+ fast_dev_run: false
53
+ dry_run: false
54
+ print_config: true
55
+ print_function_call: true
56
+ merged_model_save_path: null
57
+ merged_model_save_kwargs: null
58
+ report_save_path: '{log_dir}/program_report.json'
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+ {}
hydra.yaml ADDED
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1
+ hydra:
2
+ run:
3
+ dir: ${path.log_dir}
4
+ sweep:
5
+ dir: ${oc.env:FUSION_BENCH_PROJECT_ROOT,"."}/outputs/multirun/${hydra.job.config_name}/${now:%Y-%m-%d_%H-%M-%S}
6
+ subdir: ${hydra.job.num}
7
+ launcher:
8
+ _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
9
+ sweeper:
10
+ _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
11
+ max_batch_size: null
12
+ params: null
13
+ help:
14
+ app_name: fusion_bench
15
+ header: == ${hydra.help.app_name} ==
16
+ footer: 'Powered by Hydra (https://hydra.cc)
17
+
18
+ Use --hydra-help to view Hydra specific help'
19
+ template: '${hydra.help.header}
20
+
21
+
22
+ fusion_bench is the command line interface for running model fusion benchmarks
23
+ in the FusionBench project.
24
+
25
+ It provides a flexible way to configure and execute various fusion algorithms
26
+ on different model pools and evaluate them across multiple tasks.
27
+
28
+
29
+ == Configuration groups ==
30
+
31
+ Compose your configuration from these groups (method, modelpool, taskpool are
32
+ the most important):
33
+
34
+
35
+ $APP_CONFIG_GROUPS
36
+
37
+
38
+ == Config ==
39
+
40
+ You can override options, for example:
41
+
42
+ fusion_bench method=task_arithmetic modelpool=clip-vit-base-patch32_svhn_and_mnist
43
+ taskpool=clip-vit-base-patch32_svhn_and_mnist
44
+
45
+
46
+ == Basic usage ==
47
+
48
+ fusion_bench [--config-path CONFIG_PATH] [--config-name CONFIG_NAME] OPTION_1=VALUE_1
49
+ OPTION_2=VALUE_2 ...
50
+
51
+
52
+ == Key options ==
53
+
54
+ --help, -h : Print this help message and exit
55
+
56
+ --hydra-help : Hydra''s help
57
+
58
+ --cfg, -c : Show config instead of running [job|hydra|all]
59
+
60
+ --config-path, -cp : Overrides the config_path
61
+
62
+ --config-name, -cn : Overrides the config_name
63
+
64
+ --shell-completion, -sc : Install or Uninstall shell completion
65
+
66
+
67
+ For more detailed information on options and usage, please refer to the online
68
+ documentation:
69
+
70
+ https://tanganke.github.io/fusion_bench/cli/fusion_bench/
71
+
72
+
73
+ ${hydra.help.footer}'
74
+ hydra_help:
75
+ template: 'Hydra (${hydra.runtime.version})
76
+
77
+ See https://hydra.cc for more info.
78
+
79
+
80
+ == Flags ==
81
+
82
+ $FLAGS_HELP
83
+
84
+
85
+ == Configuration groups ==
86
+
87
+ Compose your configuration from those groups (For example, append hydra/job_logging=disabled
88
+ to command line)
89
+
90
+
91
+ $HYDRA_CONFIG_GROUPS
92
+
93
+
94
+ Use ''--cfg hydra'' to Show the Hydra config.
95
+
96
+ '
97
+ hydra_help: ???
98
+ hydra_logging:
99
+ version: 1
100
+ formatters:
101
+ simple:
102
+ format: '[%(asctime)s][HYDRA] %(message)s'
103
+ handlers:
104
+ console:
105
+ class: logging.StreamHandler
106
+ formatter: simple
107
+ stream: ext://sys.stdout
108
+ root:
109
+ level: INFO
110
+ handlers:
111
+ - console
112
+ loggers:
113
+ logging_example:
114
+ level: DEBUG
115
+ disable_existing_loggers: false
116
+ job_logging:
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+ version: 1
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+ formatters:
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+ simple:
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+ format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
121
+ rich_handler:
122
+ format: '%(message)s'
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+ handlers:
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+ console:
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+ class: rich.logging.RichHandler
126
+ formatter: rich_handler
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+ file:
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+ class: logging.FileHandler
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+ formatter: simple
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+ filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
131
+ root:
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+ level: INFO
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+ handlers:
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+ - console
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+ - file
136
+ disable_existing_loggers: false
137
+ env: {}
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+ mode: RUN
139
+ searchpath: []
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+ callbacks: {}
141
+ output_subdir: ''
142
+ overrides:
143
+ hydra:
144
+ - hydra.mode=RUN
145
+ task:
146
+ - path.log_dir="outputs/convnext-base-224/dtd/batch_size=64,lr=0.01"
147
+ - seed=0
148
+ - method=classification/image_classification_finetune
149
+ - method.max_epochs=-1
150
+ - method.max_steps=4000
151
+ - method.save_top_k=-1
152
+ - method.save_interval=1000
153
+ - method.save_on_train_epoch_end=false
154
+ - method.optimizer.lr=0.01
155
+ - method.lr_scheduler=null
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+ - method.dataloader_kwargs.batch_size=64
157
+ - modelpool=ConvNextForImageClassification/convnext-base-224
158
+ - modelpool.models._pretrained_.dataset_name=dtd
159
+ - +dataset/image_classification/train@modelpool.train_datasets=dtd
160
+ - +dataset/image_classification/test@modelpool.val_datasets=dtd
161
+ job:
162
+ name: cli
163
+ chdir: null
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+ override_dirname: +dataset/image_classification/test@modelpool.val_datasets=dtd,+dataset/image_classification/train@modelpool.train_datasets=dtd,method.dataloader_kwargs.batch_size=64,method.lr_scheduler=null,method.max_epochs=-1,method.max_steps=4000,method.optimizer.lr=0.01,method.save_interval=1000,method.save_on_train_epoch_end=false,method.save_top_k=-1,method=classification/image_classification_finetune,modelpool.models._pretrained_.dataset_name=dtd,modelpool=ConvNextForImageClassification/convnext-base-224,path.log_dir="outputs/convnext-base-224/dtd/batch_size=64,lr=0.01",seed=0
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+ id: ???
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+ num: ???
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+ config_name: model_fusion
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+ env_set:
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+ HYDRA_FULL_ERROR: ${oc.env:HYDRA_FULL_ERROR,1}
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+ env_copy: []
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+ config:
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+ override_dirname:
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+ kv_sep: '='
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+ item_sep: ','
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+ exclude_keys: []
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+ runtime:
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+ version: 1.3.2
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+ version_base: '1.3'
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+ cwd: /data/users/anke/fusion_bench
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+ config_sources:
181
+ - path: hydra.conf
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+ schema: pkg
183
+ provider: hydra
184
+ - path: /data/users/anke/fusion_bench/config
185
+ schema: file
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+ provider: main
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+ - path: ''
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+ schema: structured
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+ provider: schema
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+ output_dir: /data/users/anke/fusion_bench/outputs/convnext-base-224/dtd/batch_size=64,lr=0.01
191
+ choices:
192
+ dataset/image_classification/test@modelpool.val_datasets: dtd
193
+ dataset/image_classification/train@modelpool.train_datasets: dtd
194
+ taskpool: dummy
195
+ method: classification/image_classification_finetune
196
+ modelpool: ConvNextForImageClassification/convnext-base-224
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+ path: default
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+ hydra: default
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+ hydra/env: default
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+ hydra/callbacks: null
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+ hydra/job_logging: rich_logging
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+ hydra/hydra_logging: default
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+ hydra/hydra_help: default
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+ hydra/help: fusion_bench_help
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+ hydra/sweeper: basic
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+ hydra/launcher: basic
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+ hydra/output: default
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+ verbose: false
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@@ -0,0 +1,15 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ - path.log_dir="outputs/convnext-base-224/dtd/batch_size=64,lr=0.01"
2
+ - seed=0
3
+ - method=classification/image_classification_finetune
4
+ - method.max_epochs=-1
5
+ - method.max_steps=4000
6
+ - method.save_top_k=-1
7
+ - method.save_interval=1000
8
+ - method.save_on_train_epoch_end=false
9
+ - method.optimizer.lr=0.01
10
+ - method.lr_scheduler=null
11
+ - method.dataloader_kwargs.batch_size=64
12
+ - modelpool=ConvNextForImageClassification/convnext-base-224
13
+ - modelpool.models._pretrained_.dataset_name=dtd
14
+ - +dataset/image_classification/train@modelpool.train_datasets=dtd
15
+ - +dataset/image_classification/test@modelpool.val_datasets=dtd
preprocessor_config.json ADDED
@@ -0,0 +1,22 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "crop_pct": 0.875,
3
+ "do_normalize": true,
4
+ "do_rescale": true,
5
+ "do_resize": true,
6
+ "image_mean": [
7
+ 0.485,
8
+ 0.456,
9
+ 0.406
10
+ ],
11
+ "image_processor_type": "ConvNextImageProcessor",
12
+ "image_std": [
13
+ 0.229,
14
+ 0.224,
15
+ 0.225
16
+ ],
17
+ "resample": 3,
18
+ "rescale_factor": 0.00392156862745098,
19
+ "size": {
20
+ "shortest_edge": 224
21
+ }
22
+ }
program_report.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"model_info": {"trainable_params": 87614639, "all_params": 87614639, "trainable_percentage": 1.0}}