add example Jupyter Notebook
This commit is contained in:
rmaphoh
@@ -48,20 +48,10 @@
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"execution_count": null,
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"id": "7cbf5e93-6ca0-4401-88e6-64e39968e7cd",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Project root: /home/jupyter/RETFound\n",
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"sys.executable: /opt/conda/envs/retfound/bin/python\n",
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"torch version: 2.4.1+cu118\n"
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]
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}
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],
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"outputs": [],
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"source": [
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"import sys, torch\n",
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"from pathlib import Path\n",
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@@ -99,20 +89,10 @@
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"execution_count": null,
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"id": "5f675843",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"DATA_PATH: /home/jupyter/RETFound/MESSIDOR2\n",
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"TASK: retfound_dinov2_MESSIDOR2_finetune\n",
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"OUTPUT_DIR: /home/jupyter/RETFound/output_dir/retfound_dinov2_MESSIDOR2_finetune\n"
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]
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}
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],
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"outputs": [],
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"source": [
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"from pathlib import Path\n",
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"ADAPTATION='finetune'\n",
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@@ -143,118 +123,12 @@
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"execution_count": null,
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"id": "d23ff751",
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"metadata": {
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"scrolled": true
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Not using distributed mode\n",
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"[12:55:12.463648] job dir: /home/jupyter/RETFound\n",
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"[12:55:12.463731] Namespace(batch_size=24,\n",
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"epochs=50,\n",
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"accum_iter=1,\n",
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"model='RETFound_dinov2',\n",
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"model_arch='retfound_dinov2',\n",
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"input_size=224,\n",
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"drop_path=0.2,\n",
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"global_pool=True,\n",
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"clip_grad=None,\n",
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"weight_decay=0.05,\n",
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"lr=None,\n",
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"blr=0.005,\n",
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"layer_decay=0.65,\n",
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"min_lr=1e-06,\n",
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"warmup_epochs=10,\n",
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"color_jitter=None,\n",
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"aa='rand-m9-mstd0.5-inc1',\n",
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"smoothing=0.1,\n",
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"reprob=0.25,\n",
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"remode='pixel',\n",
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"recount=1,\n",
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"resplit=False,\n",
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"mixup=0.0,\n",
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"cutmix=0.0,\n",
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"cutmix_minmax=None,\n",
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"mixup_prob=1.0,\n",
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"mixup_switch_prob=0.5,\n",
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"mixup_mode='batch',\n",
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"finetune='RETFound_dinov2_meh',\n",
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"task='retfound_dinov2_MESSIDOR2_finetune',\n",
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"adaptation='finetune',\n",
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"data_path='/home/jupyter/RETFound/MESSIDOR2',\n",
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"nb_classes=5,\n",
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"output_dir='./output_dir',\n",
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"log_dir='./output_logs',\n",
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"dataratio='1.0',\n",
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"stratified=False,\n",
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"device='cuda',\n",
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"seed=0,\n",
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"resume='',\n",
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"start_epoch=0,\n",
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"eval=False,\n",
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"dist_eval=False,\n",
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"num_workers=10,\n",
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"pin_mem=True,\n",
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"world_size=1,\n",
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"local_rank=-1,\n",
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"dist_on_itp=False,\n",
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"dist_url='env://',\n",
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"savemodel=True,\n",
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"norm='IMAGENET',\n",
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"enhance=False,\n",
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"datasets_seed=2026,\n",
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"distributed=False)\n",
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"^C\n",
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"Traceback (most recent call last):\n",
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" File \"/home/jupyter/RETFound/main_finetune.py\", line 448, in <module>\n",
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" main(args, criterion)\n",
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" File \"/home/jupyter/RETFound/main_finetune.py\", line 173, in main\n",
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" model = models.__dict__[args.model](\n",
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" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
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" File \"/home/jupyter/RETFound/models_vit.py\", line 80, in RETFound_dinov2\n",
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" model = timm.create_model(\n",
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" ^^^^^^^^^^^^^^^^^^\n",
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" File \"/opt/conda/envs/retfound/lib/python3.11/site-packages/timm/models/_factory.py\", line 117, in create_model\n",
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" model = create_fn(\n",
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" ^^^^^^^^^^\n",
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" File \"/opt/conda/envs/retfound/lib/python3.11/site-packages/timm/models/vision_transformer.py\", line 2462, in vit_large_patch14_dinov2\n",
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" model = _create_vision_transformer(\n",
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" ^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
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" File \"/opt/conda/envs/retfound/lib/python3.11/site-packages/timm/models/vision_transformer.py\", line 1781, in _create_vision_transformer\n",
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" return build_model_with_cfg(\n",
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" ^^^^^^^^^^^^^^^^^^^^^\n",
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" File \"/opt/conda/envs/retfound/lib/python3.11/site-packages/timm/models/_builder.py\", line 398, in build_model_with_cfg\n",
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" model = model_cls(**kwargs)\n",
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" ^^^^^^^^^^^^^^^^^^^\n",
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" File \"/opt/conda/envs/retfound/lib/python3.11/site-packages/timm/models/vision_transformer.py\", line 540, in __init__\n",
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" self.init_weights(weight_init)\n",
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" File \"/opt/conda/envs/retfound/lib/python3.11/site-packages/timm/models/vision_transformer.py\", line 558, in init_weights\n",
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" named_apply(get_init_weights_vit(mode, head_bias), self)\n",
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" File \"/opt/conda/envs/retfound/lib/python3.11/site-packages/timm/models/_manipulate.py\", line 34, in named_apply\n",
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" named_apply(fn=fn, module=child_module, name=child_name, depth_first=depth_first, include_root=True)\n",
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" File \"/opt/conda/envs/retfound/lib/python3.11/site-packages/timm/models/_manipulate.py\", line 34, in named_apply\n",
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" named_apply(fn=fn, module=child_module, name=child_name, depth_first=depth_first, include_root=True)\n",
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" File \"/opt/conda/envs/retfound/lib/python3.11/site-packages/timm/models/_manipulate.py\", line 34, in named_apply\n",
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" named_apply(fn=fn, module=child_module, name=child_name, depth_first=depth_first, include_root=True)\n",
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" [Previous line repeated 1 more time]\n",
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" File \"/opt/conda/envs/retfound/lib/python3.11/site-packages/timm/models/_manipulate.py\", line 36, in named_apply\n",
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" fn(module=module, name=name)\n",
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" File \"/opt/conda/envs/retfound/lib/python3.11/site-packages/timm/models/vision_transformer.py\", line 712, in init_weights_vit_timm\n",
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" trunc_normal_(module.weight, std=.02)\n",
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" File \"/opt/conda/envs/retfound/lib/python3.11/site-packages/timm/layers/weight_init.py\", line 67, in trunc_normal_\n",
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" return _trunc_normal_(tensor, mean, std, a, b)\n",
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" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
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" File \"/opt/conda/envs/retfound/lib/python3.11/site-packages/timm/layers/weight_init.py\", line 28, in _trunc_normal_\n",
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" tensor.uniform_(2 * l - 1, 2 * u - 1)\n",
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"KeyboardInterrupt\n"
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]
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}
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],
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"outputs": [],
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"source": [
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"import sys\n",
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"\n",
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@@ -283,94 +157,12 @@
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"execution_count": null,
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"id": "0af0f8a7",
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"metadata": {
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"scrolled": true
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Not using distributed mode\n",
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"[13:01:56.741693] job dir: /home/jupyter/RETFound\n",
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"[13:01:56.741757] Namespace(batch_size=128,\n",
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"epochs=50,\n",
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"accum_iter=1,\n",
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"model='RETFound_dinov2',\n",
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"model_arch='retfound_dinov2',\n",
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"input_size=224,\n",
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"drop_path=0.2,\n",
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"global_pool=True,\n",
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"clip_grad=None,\n",
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"weight_decay=0.05,\n",
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"lr=None,\n",
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"blr=0.005,\n",
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"layer_decay=0.65,\n",
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"min_lr=1e-06,\n",
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"warmup_epochs=10,\n",
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"color_jitter=None,\n",
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"aa='rand-m9-mstd0.5-inc1',\n",
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"smoothing=0.1,\n",
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"reprob=0.25,\n",
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"remode='pixel',\n",
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"recount=1,\n",
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"resplit=False,\n",
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"mixup=0.0,\n",
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"cutmix=0.0,\n",
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"cutmix_minmax=None,\n",
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"mixup_prob=1.0,\n",
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"mixup_switch_prob=0.5,\n",
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"mixup_mode='batch',\n",
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"finetune='RETFound_dinov2_meh',\n",
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"task='retfound_dinov2_MESSIDOR2_finetune',\n",
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"adaptation='finetune',\n",
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"data_path='/home/jupyter/RETFound/MESSIDOR2',\n",
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"nb_classes=5,\n",
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"output_dir='./output_dir',\n",
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"log_dir='./output_logs',\n",
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"dataratio='1.0',\n",
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"stratified=False,\n",
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"device='cuda',\n",
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"seed=0,\n",
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"resume='/home/jupyter/RETFound/output_dir/retfound_dinov2_MESSIDOR2_finetune/checkpoint-best.pth',\n",
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"start_epoch=0,\n",
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"eval=True,\n",
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"dist_eval=False,\n",
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"num_workers=10,\n",
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"pin_mem=True,\n",
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"world_size=1,\n",
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"local_rank=-1,\n",
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"dist_on_itp=False,\n",
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"dist_url='env://',\n",
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"savemodel=True,\n",
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"norm='IMAGENET',\n",
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"enhance=False,\n",
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"datasets_seed=2026,\n",
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"distributed=False)\n",
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"/opt/conda/envs/retfound/lib/python3.11/site-packages/torch/utils/data/dataloader.py:557: UserWarning: This DataLoader will create 10 worker processes in total. Our suggested max number of worker in current system is 8, which is smaller than what this DataLoader is going to create. Please be aware that excessive worker creation might get DataLoader running slow or even freeze, lower the worker number to avoid potential slowness/freeze if necessary.\n",
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" warnings.warn(_create_warning_msg(\n",
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"[13:02:01.795301] Load checkpoint for eval from: /home/jupyter/RETFound/output_dir/retfound_dinov2_MESSIDOR2_finetune/checkpoint-best.pth\n",
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"[13:02:02.683863] [Adaptation] Full fine-tuning: training all parameters.\n",
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"[13:02:02.685617] number of trainable params (M): 303.23\n",
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"[13:02:02.685682] base lr: 5.00e-03\n",
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"[13:02:02.685697] actual lr: 2.50e-03\n",
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"[13:02:02.685710] accumulate grad iterations: 1\n",
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"[13:02:02.685722] effective batch size: 128\n",
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"[13:02:02.690046] criterion = CrossEntropyLoss()\n",
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"[13:02:03.513582] Resume checkpoint /home/jupyter/RETFound/output_dir/retfound_dinov2_MESSIDOR2_finetune/checkpoint-best.pth\n",
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"[13:02:03.514238] Test with the best model at epoch = 12\n",
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"[13:02:11.667583] test: [0/5] eta: 0:00:40 loss: 0.6644 (0.6644) time: 8.1504 data: 5.8343 max mem: 2841\n",
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"[13:02:15.546902] test: [4/5] eta: 0:00:02 loss: 0.7874 (0.9476) time: 2.4058 data: 1.2244 max mem: 2841\n",
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"[13:02:15.598723] test: Total time: 0:00:12 (2.4165 s / it)\n",
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"[13:02:15.622190] val loss: 0.9476207017898559\n",
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"[13:02:15.622238] Accuracy: 0.7091, F1 Score: 0.6078, ROC AUC: 0.9037, Hamming Loss: 0.1163,\n",
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" Jaccard Score: 0.4613, Precision: 0.7244, Recall: 0.5616,\n",
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" Average Precision: 0.6863, Kappa: 0.5141, Score: 0.6752\n"
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]
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}
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],
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"outputs": [],
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"source": [
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"import sys\n",
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"\n",
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