Publish Digital baseline checkpoints and loading instructions
Browse files- README.md +59 -18
- baseline_manifest.json +291 -0
- checkpoint_manifest.json +381 -95
- cifar100/standard/mid/artifact_validation.json +47 -0
- cifar100/standard/mid/config.json +14 -0
- cifar100/standard/mid/model.pt +3 -0
- cifar100/standard/small/artifact_validation.json +47 -0
- cifar100/standard/small/config.json +14 -0
- cifar100/standard/small/model.pt +3 -0
- cifar100/standard/tiny/artifact_validation.json +47 -0
- cifar100/standard/tiny/config.json +14 -0
- cifar100/standard/tiny/model.pt +3 -0
- imagenet200/standard/mid/artifact_validation.json +47 -0
- imagenet200/standard/mid/config.json +14 -0
- imagenet200/standard/mid/model.pt +3 -0
- imagenet200/standard/small/artifact_validation.json +47 -0
- imagenet200/standard/small/config.json +14 -0
- imagenet200/standard/small/model.pt +3 -0
- imagenet200/standard/tiny/artifact_validation.json +47 -0
- imagenet200/standard/tiny/config.json +14 -0
- imagenet200/standard/tiny/model.pt +3 -0
- release_validation.json +12 -5
README.md
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@@ -9,37 +9,78 @@ tags:
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# ISA Vision checkpoints
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Model-only PyTorch checkpoints for
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I(V,V_{th}) = I_S\frac{\operatorname{softplus}^2\!\left(\frac{V-V_{th}}{2nU_T}\right)-\operatorname{softplus}^2\!\left(\frac{V-V_{th}-V_D}{2nU_T}\right)}{1+V/V_{sat}}.
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\]
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The checkpoint tensors already contain the fitted threshold and TIA parameters required by this operator.
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## Layout
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```text
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{cifar100,imagenet200}/{hybrid,physical}/{tiny,mid,small}/model.pt
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```
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```python
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import torch
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from huggingface_hub import hf_hub_download
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)
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model.load_state_dict(checkpoint["model"], strict=True)
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model.eval()
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```
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# ISA Vision checkpoints
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Model-only PyTorch checkpoints for CIFAR-100 and ImageNet-200. The collection
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contains **18 checkpoints**: two datasets, three model scales (tiny, mid and
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small), and three variants:
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- `standard`: the Digital baseline with ordinary digital FFNs;
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- `hybrid`: a physical Flash-transistor up projection and a digital down projection;
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- `physical`: physical Flash-transistor up and down projections.
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Source code and experiment configurations: [ISA on GitHub](https://github.com/Vigilanceee/ISA-).
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Related collections: [language Transformers](https://huggingface.co/Viligance/ISA-Language)
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and [five-device MLP/VGG8 studies](https://huggingface.co/Viligance/ISA-Device-Checkpoints).
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## Layout
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```text
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{cifar100,imagenet200}/{standard,hybrid,physical}/{tiny,mid,small}/model.pt
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```
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Digital baselines additionally have a matching `config.json` and
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`artifact_validation.json`. Vision embedding dimensions are 192/256/384 for
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tiny/mid/small. Use the actual checkpoint configuration when constructing a model.
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## Load a Digital baseline
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Install the ISA source package, then use the stored configuration and strict loading:
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```python
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import torch
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from huggingface_hub import HfApi, hf_hub_download
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from isa.vision.config import ModelConfig
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from isa.vision.models import StandardViT
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repo_id = "Viligance/ISA-Vision"
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revision = HfApi().model_info(repo_id).sha
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path = hf_hub_download(repo_id, "cifar100/standard/tiny/model.pt", revision=revision)
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checkpoint = torch.load(path, map_location="cpu", weights_only=True)
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model = StandardViT(ModelConfig(**checkpoint["model_config"]))
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model.load_state_dict(checkpoint["model"], strict=True)
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model.eval()
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print("Hugging Face revision:", revision)
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```
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For repeatable downloads, retain that immutable revision and pass it to subsequent
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`hf_hub_download` calls. Hybrid and Physical checkpoints also use the `model`
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state-dictionary key; construct the corresponding ISA model and experiment
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configuration before strictly loading it. Their threshold and TIA parameters are
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already stored in the tensors.
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## Physical device equation
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For Hybrid and Physical projections, the fitted Flash-transistor operator evaluates
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\[
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I(V,V_{th}) = I_S\frac{\operatorname{softplus}^2\!\left(\frac{V-V_{th}}{2nU_T}\right)-\operatorname{softplus}^2\!\left(\frac{V-V_{th}-V_D}{2nU_T}\right)}{1+V/V_{sat}}.
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\]
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This device equation does not apply to the Digital baseline FFNs.
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## Digital baseline records
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| Dataset | Tiny | Mid | Small |
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|---|---:|---:|---:|
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| CIFAR-100 | 67.98% | 69.45% | 69.30% |
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| ImageNet-200 | 72.43% | 72.57% | 73.64% |
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These are recorded training-validation/checkpoint-selection accuracies, not new
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full-dataset evaluations performed during publication. The model-only baseline
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artifacts preserve all source model tensors exactly and pass finite-value checks,
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strict loading, and a CPU forward check. Optimizer and scheduler state are not
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required for inference and are not part of these model-only artifacts.
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`checkpoint_manifest.json` covers all 18 weights with file sizes, SHA256 digests
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and validation metadata. `baseline_manifest.json` records the six Digital
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baselines and their configurations. `release_validation.json` distinguishes
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physical-parameter verification from Digital baseline artifact checks.
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baseline_manifest.json
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{
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"artifact_type": "model-only Digital baseline checkpoints",
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"checkpoints": [
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{
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"bytes": 21563722,
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"dataset": "cifar100",
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"domain": "vision",
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"file": "cifar100/standard/tiny/model.pt",
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"model_config": {
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"attn_drop_rate": 0.0,
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"depth": 12,
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"drop_path_rate": 0.05,
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"drop_rate": 0.0,
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"embed_dim": 192,
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"img_size": 32,
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"in_chans": 3,
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"mlp_ratio": 4.0,
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"num_classes": 100,
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"num_heads": 3,
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"patch_size": 4,
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"voltage_max": 4.0
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},
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"model_type": "standard",
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| 24 |
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"parameter_count": 5380132,
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"parameterized_layers": 0,
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"recorded_metrics": {
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"best_acc": 67.97999999999999,
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"epoch": 284
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},
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"scale": "tiny",
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+
"sha256": "ee7b9c569349d62b9bf6dd2c9b6a334d61f907119fa02b56607eb3b1e785c24e",
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+
"tensor_count": 152,
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"validation": {
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"artifact": {
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"cpu_forward_finite": true,
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"cpu_forward_shape": [
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1,
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100
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],
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"finite_tensor_count": 152,
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| 41 |
+
"full_dataset_reevaluation_performed": false,
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| 42 |
+
"model_config_plain_dict": true,
|
| 43 |
+
"parameter_count": 5380132,
|
| 44 |
+
"reload_ok": true,
|
| 45 |
+
"source_model_tensor_equality": true,
|
| 46 |
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"state_key": "model",
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| 47 |
+
"tensor_count": 152
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| 48 |
+
}
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}
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},
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{
|
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+
"bytes": 38174538,
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"dataset": "cifar100",
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| 54 |
+
"domain": "vision",
|
| 55 |
+
"file": "cifar100/standard/mid/model.pt",
|
| 56 |
+
"model_config": {
|
| 57 |
+
"attn_drop_rate": 0.0,
|
| 58 |
+
"depth": 12,
|
| 59 |
+
"drop_path_rate": 0.05,
|
| 60 |
+
"drop_rate": 0.0,
|
| 61 |
+
"embed_dim": 256,
|
| 62 |
+
"img_size": 32,
|
| 63 |
+
"in_chans": 3,
|
| 64 |
+
"mlp_ratio": 4.0,
|
| 65 |
+
"num_classes": 100,
|
| 66 |
+
"num_heads": 4,
|
| 67 |
+
"patch_size": 4,
|
| 68 |
+
"voltage_max": 4.0
|
| 69 |
+
},
|
| 70 |
+
"model_type": "standard",
|
| 71 |
+
"parameter_count": 9532772,
|
| 72 |
+
"parameterized_layers": 0,
|
| 73 |
+
"recorded_metrics": {
|
| 74 |
+
"best_acc": 69.45,
|
| 75 |
+
"epoch": 290
|
| 76 |
+
},
|
| 77 |
+
"scale": "mid",
|
| 78 |
+
"sha256": "3f71184e4fa24939371a462c3fe0f09c9fae2f029abd52778f742b83e5bc7be7",
|
| 79 |
+
"tensor_count": 152,
|
| 80 |
+
"validation": {
|
| 81 |
+
"artifact": {
|
| 82 |
+
"cpu_forward_finite": true,
|
| 83 |
+
"cpu_forward_shape": [
|
| 84 |
+
1,
|
| 85 |
+
100
|
| 86 |
+
],
|
| 87 |
+
"finite_tensor_count": 152,
|
| 88 |
+
"full_dataset_reevaluation_performed": false,
|
| 89 |
+
"model_config_plain_dict": true,
|
| 90 |
+
"parameter_count": 9532772,
|
| 91 |
+
"reload_ok": true,
|
| 92 |
+
"source_model_tensor_equality": true,
|
| 93 |
+
"state_key": "model",
|
| 94 |
+
"tensor_count": 152
|
| 95 |
+
}
|
| 96 |
+
}
|
| 97 |
+
},
|
| 98 |
+
{
|
| 99 |
+
"bytes": 85551434,
|
| 100 |
+
"dataset": "cifar100",
|
| 101 |
+
"domain": "vision",
|
| 102 |
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"file": "cifar100/standard/small/model.pt",
|
| 103 |
+
"model_config": {
|
| 104 |
+
"attn_drop_rate": 0.0,
|
| 105 |
+
"depth": 12,
|
| 106 |
+
"drop_path_rate": 0.05,
|
| 107 |
+
"drop_rate": 0.0,
|
| 108 |
+
"embed_dim": 384,
|
| 109 |
+
"img_size": 32,
|
| 110 |
+
"in_chans": 3,
|
| 111 |
+
"mlp_ratio": 4.0,
|
| 112 |
+
"num_classes": 100,
|
| 113 |
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checkpoint_manifest.json
CHANGED
|
@@ -30,79 +30,79 @@
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| 30 |
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| 31 |
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| 32 |
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| 33 |
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| 64 |
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|
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| 106 |
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|
| 107 |
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|
| 108 |
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|
@@ -110,38 +110,38 @@
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|
| 110 |
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|
| 111 |
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|
| 112 |
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|
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|
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|
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|
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| 136 |
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|
| 137 |
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|
| 138 |
-
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|
| 139 |
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|
| 140 |
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|
| 141 |
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|
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|
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|
| 144 |
-
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|
| 145 |
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|
| 146 |
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|
| 147 |
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|
|
@@ -174,6 +174,147 @@
|
|
| 174 |
}
|
| 175 |
}
|
| 176 |
},
|
|
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|
| 177 |
{
|
| 178 |
"bytes": 51708446,
|
| 179 |
"dataset": "imagenet200",
|
|
@@ -204,50 +345,50 @@
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|
| 204 |
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|
| 205 |
},
|
| 206 |
{
|
| 207 |
-
"bytes":
|
| 208 |
"dataset": "imagenet200",
|
| 209 |
"domain": "vision",
|
| 210 |
-
"file": "imagenet200/
|
| 211 |
-
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|
| 212 |
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|
| 213 |
-
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|
| 214 |
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| 215 |
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|
| 216 |
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|
| 217 |
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|
| 218 |
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|
| 219 |
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|
| 220 |
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|
| 221 |
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| 222 |
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|
| 223 |
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|
| 224 |
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|
| 225 |
-
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| 226 |
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|
| 227 |
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|
| 228 |
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|
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|
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|
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|
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| 235 |
{
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| 236 |
-
"bytes":
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| 237 |
"dataset": "imagenet200",
|
| 238 |
"domain": "vision",
|
| 239 |
-
"file": "imagenet200/hybrid/
|
| 240 |
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|
| 241 |
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|
| 242 |
-
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| 243 |
-
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| 244 |
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| 245 |
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|
| 246 |
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|
| 247 |
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|
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|
| 252 |
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| 253 |
"state_key": "model",
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|
@@ -255,28 +396,28 @@
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|
| 255 |
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| 256 |
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cifar100/standard/mid/model.pt
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cifar100/standard/small/artifact_validation.json
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|
| 11 |
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|
| 12 |
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|
| 13 |
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|
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|
| 15 |
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|
| 16 |
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|
| 17 |
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|
| 18 |
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|
| 19 |
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| 20 |
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|
| 21 |
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|
| 22 |
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|
| 23 |
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|
| 24 |
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|
| 25 |
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|
| 26 |
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| 27 |
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|
| 28 |
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|
| 29 |
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|
| 30 |
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|
| 31 |
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|
| 32 |
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|
| 33 |
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|
| 34 |
+
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|
| 35 |
+
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|
| 36 |
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|
| 37 |
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|
| 38 |
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|
| 39 |
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|
| 40 |
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|
| 41 |
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| 42 |
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|
| 43 |
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|
| 44 |
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|
| 45 |
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|
| 46 |
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}
|
| 47 |
+
}
|
cifar100/standard/small/config.json
ADDED
|
@@ -0,0 +1,14 @@
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
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|
|
|
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|
|
|
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|
|
|
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|
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|
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|
|
| 1 |
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|
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|
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|
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| 6 |
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|
| 7 |
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|
| 8 |
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|
| 9 |
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| 10 |
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| 11 |
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|
| 12 |
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|
| 13 |
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|
| 14 |
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|
cifar100/standard/small/model.pt
ADDED
|
@@ -0,0 +1,3 @@
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|
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| 1 |
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version https://git-lfs.github.com/spec/v1
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| 3 |
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size 85551434
|
cifar100/standard/tiny/artifact_validation.json
ADDED
|
@@ -0,0 +1,47 @@
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|
| 1 |
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{
|
| 2 |
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"bytes": 21563722,
|
| 3 |
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"dataset": "cifar100",
|
| 4 |
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|
| 5 |
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|
| 6 |
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| 7 |
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|
| 8 |
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|
| 9 |
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|
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|
| 11 |
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|
| 12 |
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|
| 13 |
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|
| 14 |
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|
| 15 |
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|
| 16 |
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|
| 17 |
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|
| 18 |
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|
| 19 |
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|
| 20 |
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|
| 21 |
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|
| 22 |
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|
| 23 |
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|
| 24 |
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|
| 25 |
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|
| 26 |
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|
| 27 |
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|
| 28 |
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|
| 29 |
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|
| 30 |
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|
| 31 |
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|
| 32 |
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|
| 33 |
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|
| 34 |
+
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|
| 35 |
+
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|
| 36 |
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|
| 37 |
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|
| 38 |
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|
| 39 |
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|
| 40 |
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|
| 41 |
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|
| 42 |
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|
| 43 |
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|
| 44 |
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|
| 45 |
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}
|
| 46 |
+
}
|
| 47 |
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}
|
cifar100/standard/tiny/config.json
ADDED
|
@@ -0,0 +1,14 @@
|
|
|
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|
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|
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| 8 |
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|
| 13 |
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|
| 14 |
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|
cifar100/standard/tiny/model.pt
ADDED
|
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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size 21563722
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imagenet200/standard/mid/artifact_validation.json
ADDED
|
@@ -0,0 +1,47 @@
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|
| 3 |
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|
| 4 |
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|
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|
| 6 |
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|
| 8 |
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| 11 |
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|
| 12 |
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|
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|
| 14 |
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|
| 15 |
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|
| 16 |
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|
| 18 |
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|
| 19 |
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| 20 |
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|
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|
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| 34 |
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| 35 |
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|
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|
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|
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|
| 41 |
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|
| 43 |
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|
| 44 |
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|
| 45 |
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|
| 46 |
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|
| 47 |
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|
imagenet200/standard/mid/config.json
ADDED
|
@@ -0,0 +1,14 @@
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|
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|
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|
| 13 |
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|
| 14 |
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|
imagenet200/standard/mid/model.pt
ADDED
|
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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| 3 |
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size 39149834
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imagenet200/standard/small/artifact_validation.json
ADDED
|
@@ -0,0 +1,47 @@
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|
| 1 |
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{
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"bytes": 87014154,
|
| 3 |
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|
| 4 |
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|
| 5 |
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|
| 6 |
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|
| 7 |
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|
| 8 |
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|
| 9 |
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|
| 10 |
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|
| 11 |
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|
| 12 |
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|
| 13 |
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|
| 14 |
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|
| 15 |
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|
| 16 |
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|
| 17 |
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|
| 18 |
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|
| 19 |
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| 20 |
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|
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|
| 22 |
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|
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|
| 24 |
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|
| 25 |
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|
| 26 |
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|
| 28 |
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| 29 |
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|
| 30 |
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|
| 31 |
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|
| 32 |
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|
| 33 |
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|
| 34 |
+
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|
| 35 |
+
200
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| 36 |
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|
| 37 |
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|
| 38 |
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|
| 39 |
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|
| 40 |
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|
| 41 |
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|
| 42 |
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|
| 43 |
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|
| 44 |
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|
| 45 |
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|
| 46 |
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|
| 47 |
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}
|
imagenet200/standard/small/config.json
ADDED
|
@@ -0,0 +1,14 @@
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|
|
|
|
|
|
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|
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|
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|
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|
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|
| 6 |
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|
| 7 |
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|
| 8 |
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|
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|
| 10 |
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|
| 11 |
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|
| 12 |
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|
| 13 |
+
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|
| 14 |
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}
|
imagenet200/standard/small/model.pt
ADDED
|
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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| 3 |
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size 87014154
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imagenet200/standard/tiny/artifact_validation.json
ADDED
|
@@ -0,0 +1,47 @@
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|
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|
| 5 |
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"file": "imagenet200/standard/tiny/model.pt",
|
| 6 |
+
"model_config": {
|
| 7 |
+
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|
| 8 |
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"depth": 12,
|
| 9 |
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|
| 10 |
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|
| 11 |
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|
| 12 |
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|
| 13 |
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|
| 14 |
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|
| 15 |
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|
| 16 |
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|
| 17 |
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"patch_size": 16,
|
| 18 |
+
"voltage_max": 4.0
|
| 19 |
+
},
|
| 20 |
+
"model_type": "standard",
|
| 21 |
+
"parameter_count": 5563016,
|
| 22 |
+
"parameterized_layers": 0,
|
| 23 |
+
"recorded_metrics": {
|
| 24 |
+
"best_acc": 72.43,
|
| 25 |
+
"epoch": 295
|
| 26 |
+
},
|
| 27 |
+
"scale": "tiny",
|
| 28 |
+
"sha256": "0f15e7d660a9a03fc10eb4c53ff133ebc6806703e783c6cf69c08882fcc1d5b4",
|
| 29 |
+
"tensor_count": 152,
|
| 30 |
+
"validation": {
|
| 31 |
+
"artifact": {
|
| 32 |
+
"cpu_forward_finite": true,
|
| 33 |
+
"cpu_forward_shape": [
|
| 34 |
+
1,
|
| 35 |
+
200
|
| 36 |
+
],
|
| 37 |
+
"finite_tensor_count": 152,
|
| 38 |
+
"full_dataset_reevaluation_performed": false,
|
| 39 |
+
"model_config_plain_dict": true,
|
| 40 |
+
"parameter_count": 5563016,
|
| 41 |
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"reload_ok": true,
|
| 42 |
+
"source_model_tensor_equality": true,
|
| 43 |
+
"state_key": "model",
|
| 44 |
+
"tensor_count": 152
|
| 45 |
+
}
|
| 46 |
+
}
|
| 47 |
+
}
|
imagenet200/standard/tiny/config.json
ADDED
|
@@ -0,0 +1,14 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"attn_drop_rate": 0.0,
|
| 3 |
+
"depth": 12,
|
| 4 |
+
"drop_path_rate": 0.05,
|
| 5 |
+
"drop_rate": 0.0,
|
| 6 |
+
"embed_dim": 192,
|
| 7 |
+
"img_size": 224,
|
| 8 |
+
"in_chans": 3,
|
| 9 |
+
"mlp_ratio": 4.0,
|
| 10 |
+
"num_classes": 200,
|
| 11 |
+
"num_heads": 3,
|
| 12 |
+
"patch_size": 16,
|
| 13 |
+
"voltage_max": 4.0
|
| 14 |
+
}
|
imagenet200/standard/tiny/model.pt
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:0f15e7d660a9a03fc10eb4c53ff133ebc6806703e783c6cf69c08882fcc1d5b4
|
| 3 |
+
size 22295242
|
release_validation.json
CHANGED
|
@@ -1,10 +1,17 @@
|
|
| 1 |
{
|
| 2 |
-
"checkpoint_count":
|
|
|
|
|
|
|
| 3 |
"embedded_parameter_verified": 12,
|
| 4 |
-
"finite_state_verified":
|
| 5 |
"format_version": 1,
|
| 6 |
"formula": "I=I_S*(softplus((V-Vth)/(2*n*U_T))^2-softplus((V-Vth-V_D)/(2*n*U_T))^2)/(1+V/V_sat)",
|
| 7 |
-
"
|
| 8 |
-
|
| 9 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 10 |
}
|
|
|
|
| 1 |
{
|
| 2 |
+
"checkpoint_count": 18,
|
| 3 |
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"cpu_forward_verified_digital_baselines": 6,
|
| 4 |
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"digital_baseline_count": 6,
|
| 5 |
"embedded_parameter_verified": 12,
|
| 6 |
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"finite_state_verified": 18,
|
| 7 |
"format_version": 1,
|
| 8 |
"formula": "I=I_S*(softplus((V-Vth)/(2*n*U_T))^2-softplus((V-Vth-V_D)/(2*n*U_T))^2)/(1+V/V_sat)",
|
| 9 |
+
"formula_applies_to_model_types": [
|
| 10 |
+
"hybrid",
|
| 11 |
+
"physical"
|
| 12 |
+
],
|
| 13 |
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"reload_verified": 18,
|
| 14 |
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"sha256_verified": 18,
|
| 15 |
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"source_tensor_equality_verified_digital_baselines": 6,
|
| 16 |
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"total_bytes": 1168910020
|
| 17 |
}
|