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+[2025-08-14 13:09:01,525][INFO] Args: {
+    "accelerator": "auto",
+    "batch_size": 32,
+    "callbacks": null,
+    "checkpoint": null,
+    "data": "data/kyucapsule",
+    "devices": "auto",
+    "embed_dim": null,
+    "epochs": 300,
+    "loader_args": null,
+    "loggers": {
+        "wandb": {
+            "project": "ent-endoscopy-ssl"
+        }
+    },
+    "method": "dino",
+    "method_args": null,
+    "model": "VisionTransformer",
+    "model_args": null,
+    "num_nodes": 1,
+    "num_workers": "auto",
+    "optim": "auto",
+    "optim_args": null,
+    "out": "outputs/ssl_dino/vit16s",
+    "overwrite": true,
+    "precision": "32-true",
+    "resume": false,
+    "seed": 0,
+    "strategy": "auto",
+    "trainer_args": null,
+    "transform_args": {
+        "image_size": [
+            224,
+            224
+        ]
+    }
+}
+[2025-08-14 13:09:01,525][INFO] Using output directory '/home/duckq1u/Documents/workspace/cuong/ent-labotary/outputs/ssl_dino/vit16s'.
+[2025-08-14 13:09:01,630][DEBUG] '/home/duckq1u/miniconda3/envs/ent-lab/lib/python3.11/site-packages/lightly_train' is not a git repository.
+[2025-08-14 13:09:01,634][DEBUG] Platform: Linux-6.16.0-zen1-1-zen-x86_64-with-glibc2.42
+[2025-08-14 13:09:01,634][DEBUG] Python: 3.11.13
+[2025-08-14 13:09:01,634][DEBUG] LightlyTrain: 0.6.1
+[2025-08-14 13:09:01,634][DEBUG] LightlyTrain Git Information:
+[2025-08-14 13:09:01,634][DEBUG]  LightlyTrain is not installed from a git repository.
+[2025-08-14 13:09:01,634][DEBUG] Run directory Git Information:
+[2025-08-14 13:09:01,634][DEBUG]  Branch: feat/ssl
+[2025-08-14 13:09:01,634][DEBUG]  Commit: 61f4482b9df47dedf1dd991b89913f2e5962454c
+[2025-08-14 13:09:01,634][DEBUG]  Uncommitted changes: None
+[2025-08-14 13:09:01,634][DEBUG] Dependencies:
+[2025-08-14 13:09:01,634][DEBUG]  - torch                2.9.0.dev20250806+cu128
+[2025-08-14 13:09:01,634][DEBUG]  - torchvision          0.24.0.dev20250806+cu128
+[2025-08-14 13:09:01,634][DEBUG]  - pytorch-lightning           2.5.2
+[2025-08-14 13:09:01,634][DEBUG]  - Pillow                     11.3.0
+[2025-08-14 13:09:01,634][DEBUG]  - pillow-simd                     x
+[2025-08-14 13:09:01,634][DEBUG] Optional dependencies:
+[2025-08-14 13:09:01,634][DEBUG]  - super-gradients                 x
+[2025-08-14 13:09:01,634][DEBUG]  - timm                       1.0.19
+[2025-08-14 13:09:01,634][DEBUG]  - ultralytics                     x
+[2025-08-14 13:09:01,634][DEBUG]  - wandb                      0.21.1
+[2025-08-14 13:09:01,634][DEBUG] CPUs: 6
+[2025-08-14 13:09:01,635][DEBUG] GPUs: 1
+[2025-08-14 13:09:01,635][DEBUG]  - NVIDIA GeForce RTX 5060 Ti 12.0 (16612917248)
+[2025-08-14 13:09:01,635][DEBUG] Environment variables:
+[2025-08-14 13:09:01,641][DEBUG] Getting transform args for method 'dino'.
+[2025-08-14 13:09:01,641][DEBUG] Using additional transform arguments {'image_size': (224, 224)}.
+[2025-08-14 13:09:01,641][DEBUG] Getting transform for method 'dino'.
+[2025-08-14 13:09:01,648][DEBUG] Making sure data directory '/home/duckq1u/Documents/workspace/cuong/ent-labotary/data/kyucapsule' exists and is not empty.
+[2025-08-14 13:09:01,648][INFO] Initializing dataset from '/home/duckq1u/Documents/workspace/cuong/ent-labotary/data/kyucapsule'.
+[2025-08-14 13:09:01,649][DEBUG] Writing filenames to '/tmp/tmpiaccn5q5' (chunk_size=10000)
+[2025-08-14 13:09:01,899][DEBUG] Creating memory mapped sequence with 18481 'filenames'.
+[2025-08-14 13:09:01,899][DEBUG] Found dataset size 18481.
+[2025-08-14 13:09:01,900][DEBUG] Getting embedding model with embedding dimension None.
+[2025-08-14 13:09:01,900][WARNING] Could not find pooling layer on the model, defaulting to AdaptiveAvgPool2d
+[2025-08-14 13:09:01,900][DEBUG] Using jsonl logger with args flush_logs_every_n_steps=100
+[2025-08-14 13:09:01,902][DEBUG] Using tensorboard logger with args name='' version='' log_graph=False default_hp_metric=True prefix='' sub_dir=None
+[2025-08-14 13:09:01,903][DEBUG] Using wandb logger with args name=None version=None offline=False anonymous=None project='ent-endoscopy-ssl' log_model=False prefix='' checkpoint_name=None
+[2025-08-14 13:09:01,903][DEBUG] Using loggers ['JSONLLogger', 'TensorBoardLogger', 'WandbLogger'].
+[2025-08-14 13:09:01,907][DEBUG] Getting accelerator for 'auto'.
+[2025-08-14 13:09:01,907][DEBUG] CUDA is available, defaulting to CUDA.
+[2025-08-14 13:09:01,907][DEBUG] Detected 1 devices.
+[2025-08-14 13:09:01,907][DEBUG] Using strategy 'auto'.
+[2025-08-14 13:09:01,907][DEBUG] Getting trainer.
+[2025-08-14 13:09:01,907][DEBUG] Using sync_batchnorm 'True'.
+[2025-08-14 13:09:01,913][INFO] GPU available: True (cuda), used: True
+[2025-08-14 13:09:01,913][INFO] TPU available: False, using: 0 TPU cores
+[2025-08-14 13:09:01,914][INFO] HPU available: False, using: 0 HPUs
+[2025-08-14 13:09:01,914][DEBUG] Detected 1 nodes and 1 devices per node.
+[2025-08-14 13:09:01,914][DEBUG] Total number of devices: 1.
+[2025-08-14 13:09:01,914][DEBUG] Detected dataset size 18481.
+[2025-08-14 13:09:01,914][DEBUG] Using batch size per device 32.
+[2025-08-14 13:09:01,914][DEBUG] Using optimizer 'OptimizerType.SGD'.
+[2025-08-14 13:09:01,914][DEBUG] Getting method args for 'DINO'
+[2025-08-14 13:09:01,914][DEBUG] Getting method for 'DINO'
+[2025-08-14 13:09:01,966][WARNING] /home/duckq1u/miniconda3/envs/ent-lab/lib/python3.11/site-packages/torch/nn/utils/weight_norm.py:144: FutureWarning: `torch.nn.utils.weight_norm` is deprecated in favor of `torch.nn.utils.parametrizations.weight_norm`.
+  WeightNorm.apply(module, name, dim)
+
+[2025-08-14 13:09:02,074][INFO] Resolved configuration:
+{
+    "accelerator": "CUDAAccelerator",
+    "batch_size": 32,
+    "callbacks": {
+        "device_stats_monitor": {},
+        "early_stopping": {
+            "check_finite": true,
+            "monitor": "train_loss",
+            "patience": 1000000000000
+        },
+        "learning_rate_monitor": {},
+        "model_checkpoint": {
+            "enable_version_counter": false,
+            "every_n_epochs": null,
+            "save_last": true,
+            "save_top_k": 1
+        }
+    },
+    "checkpoint": null,
+    "data": "data/kyucapsule",
+    "devices": 1,
+    "embed_dim": null,
+    "epochs": 300,
+    "loader_args": null,
+    "loggers": {
+        "jsonl": {
+            "flush_logs_every_n_steps": 100
+        },
+        "tensorboard": {
+            "default_hp_metric": true,
+            "log_graph": false,
+            "name": "",
+            "prefix": "",
+            "sub_dir": null,
+            "version": ""
+        },
+        "wandb": {
+            "anonymous": null,
+            "checkpoint_name": null,
+            "log_model": false,
+            "name": null,
+            "offline": false,
+            "prefix": "",
+            "project": "ent-endoscopy-ssl",
+            "version": null
+        }
+    },
+    "method": "dino",
+    "method_args": {
+        "batch_norm": false,
+        "bottleneck_dim": 256,
+        "center_momentum": 0.9,
+        "hidden_dim": 2048,
+        "momentum_end": 1.0,
+        "momentum_start": 0.99,
+        "norm_last_layer": true,
+        "output_dim": 1024,
+        "student_freeze_last_layer_epochs": 1,
+        "student_temp": 0.1,
+        "teacher_temp": 0.02,
+        "warmup_teacher_temp": 0.02,
+        "warmup_teacher_temp_epochs": 30,
+        "weight_decay_end": 0.0001,
+        "weight_decay_start": 0.0001
+    },
+    "model": "VisionTransformer",
+    "model_args": null,
+    "num_nodes": 1,
+    "num_workers": 5,
+    "optim": "sgd",
+    "optim_args": {
+        "lr": 0.03,
+        "momentum": 0.9,
+        "weight_decay": 0.0001
+    },
+    "out": "outputs/ssl_dino/vit16s",
+    "overwrite": true,
+    "precision": "32-true",
+    "resume": false,
+    "seed": 0,
+    "strategy": "SingleDeviceStrategy",
+    "trainer_args": null,
+    "transform_args": {
+        "color_jitter": {
+            "brightness": 0.8,
+            "contrast": 0.8,
+            "hue": 0.2,
+            "prob": 0.8,
+            "saturation": 0.4,
+            "strength": 0.5
+        },
+        "gaussian_blur": {
+            "blur_limit": 0,
+            "prob": 1.0,
+            "sigmas": [
+                0.1,
+                2.0
+            ]
+        },
+        "global_view_1": {
+            "gaussian_blur": {
+                "blur_limit": 0,
+                "prob": 0.1,
+                "sigmas": [
+                    0.1,
+                    2.0
+                ]
+            },
+            "solarize": {
+                "prob": 0.2,
+                "threshold": 0.5
+            }
+        },
+        "image_size": [
+            224,
+            224
+        ],
+        "local_view": {
+            "gaussian_blur": {
+                "blur_limit": 0,
+                "prob": 0.5,
+                "sigmas": [
+                    0.1,
+                    2.0
+                ]
+            },
+            "num_views": 6,
+            "random_resize": {
+                "max_scale": 0.14,
+                "min_scale": 0.05
+            },
+            "view_size": [
+                96,
+                96
+            ]
+        },
+        "normalize": {
+            "mean": [
+                0.485,
+                0.456,
+                0.406
+            ],
+            "std": [
+                0.229,
+                0.224,
+                0.225
+            ]
+        },
+        "random_flip": {
+            "horizontal_prob": 0.5,
+            "vertical_prob": 0.0
+        },
+        "random_gray_scale": 0.2,
+        "random_resize": {
+            "max_scale": 1.0,
+            "min_scale": 0.14
+        },
+        "random_rotation": null,
+        "solarize": null
+    }
+}
+[2025-08-14 13:09:04,586][WARNING] /home/duckq1u/miniconda3/envs/ent-lab/lib/python3.11/site-packages/torch/__init__.py:1539: UserWarning: Please use the new API settings to control TF32 behavior, such as torch.backends.cudnn.conv.fp32_precision = 'tf32' or torch.backends.cuda.matmul.fp32_precision = 'ieee'. Old settings, e.g, torch.backends.cuda.matmul.allow_tf32 = True, torch.backends.cudnn.allow_tf32 = True, allowTF32CuDNN() and allowTF32CuBLAS() will be deprecated after Pytorch 2.9. Please see https://pytorch.org/docs/main/notes/cuda.html#tensorfloat-32-tf32-on-ampere-and-later-devices (Triggered internally at /pytorch/aten/src/ATen/Context.cpp:80.)
+  return _C._get_float32_matmul_precision()
+
+[2025-08-14 13:09:04,586][INFO] You are using a CUDA device ('NVIDIA GeForce RTX 5060 Ti') that has Tensor Cores. To properly utilize them, you should set `torch.set_float32_matmul_precision('medium' | 'high')` which will trade-off precision for performance. For more details, read https://pytorch.org/docs/stable/generated/torch.set_float32_matmul_precision.html#torch.set_float32_matmul_precision
+[2025-08-14 13:09:04,817][INFO] LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
+[2025-08-14 13:09:04,894][INFO] Loading `train_dataloader` to estimate number of stepping batches.
+[2025-08-14 13:09:05,027][INFO] 
+  | Name                    | Type               | Params | Mode 
+-----------------------------------------------------------------------
+0 | teacher_embedding_model | EmbeddingModel     | 30.1 M | train
+1 | teacher_projection_head | DINOProjectionHead | 5.8 M  | train
+2 | student_embedding_model | EmbeddingModel     | 30.1 M | train
+3 | student_projection_head | DINOProjectionHead | 5.8 M  | train
+4 | flatten                 | Flatten            | 0      | train
+5 | criterion               | DINOLoss           | 0      | train
+-----------------------------------------------------------------------
+71.7 M    Trainable params
+2.0 K     Non-trainable params
+71.7 M    Total params
+286.782   Total estimated model params size (MB)
+578       Modules in train mode
+0         Modules in eval mode
+[2025-08-15 07:08:42,748][INFO] Args: {
+    "accelerator": "auto",
+    "batch_size": 32,
+    "callbacks": null,
+    "checkpoint": null,
+    "data": "data/kyucapsule",
+    "devices": "auto",
+    "embed_dim": null,
+    "epochs": 300,
+    "loader_args": null,
+    "loggers": {
+        "wandb": {
+            "project": "ent-endoscopy-ssl"
+        }
+    },
+    "method": "dino",
+    "method_args": null,
+    "model": "VisionTransformer",
+    "model_args": null,
+    "num_nodes": 1,
+    "num_workers": "auto",
+    "optim": "auto",
+    "optim_args": null,
+    "out": "outputs/ssl_dino/vit16s",
+    "overwrite": true,
+    "precision": "32-true",
+    "resume": true,
+    "seed": 0,
+    "strategy": "auto",
+    "trainer_args": null,
+    "transform_args": {
+        "image_size": [
+            224,
+            224
+        ]
+    }
+}
+[2025-08-15 07:08:42,749][INFO] Using output directory '/home/duckq1u/Documents/workspace/cuong/ent-labotary/outputs/ssl_dino/vit16s'.
+[2025-08-15 07:08:42,945][DEBUG] '/home/duckq1u/miniconda3/envs/ent-lab/lib/python3.11/site-packages/lightly_train' is not a git repository.
+[2025-08-15 07:08:42,948][DEBUG] Platform: Linux-6.16.0-zen1-1-zen-x86_64-with-glibc2.42
+[2025-08-15 07:08:42,948][DEBUG] Python: 3.11.13
+[2025-08-15 07:08:42,949][DEBUG] LightlyTrain: 0.6.1
+[2025-08-15 07:08:42,949][DEBUG] LightlyTrain Git Information:
+[2025-08-15 07:08:42,949][DEBUG]  LightlyTrain is not installed from a git repository.
+[2025-08-15 07:08:42,949][DEBUG] Run directory Git Information:
+[2025-08-15 07:08:42,949][DEBUG]  Branch: feat/ssl
+[2025-08-15 07:08:42,949][DEBUG]  Commit: 61f4482b9df47dedf1dd991b89913f2e5962454c
+[2025-08-15 07:08:42,949][DEBUG]  Uncommitted changes: M src/experiment/ssl_dino.py
+[2025-08-15 07:08:42,949][DEBUG] Dependencies:
+[2025-08-15 07:08:42,949][DEBUG]  - torch                2.9.0.dev20250806+cu128
+[2025-08-15 07:08:42,949][DEBUG]  - torchvision          0.24.0.dev20250806+cu128
+[2025-08-15 07:08:42,949][DEBUG]  - pytorch-lightning           2.5.2
+[2025-08-15 07:08:42,949][DEBUG]  - Pillow                     11.3.0
+[2025-08-15 07:08:42,949][DEBUG]  - pillow-simd                     x
+[2025-08-15 07:08:42,949][DEBUG] Optional dependencies:
+[2025-08-15 07:08:42,949][DEBUG]  - super-gradients                 x
+[2025-08-15 07:08:42,949][DEBUG]  - timm                       1.0.19
+[2025-08-15 07:08:42,949][DEBUG]  - ultralytics                     x
+[2025-08-15 07:08:42,949][DEBUG]  - wandb                      0.21.1
+[2025-08-15 07:08:42,949][DEBUG] CPUs: 6
+[2025-08-15 07:08:42,949][DEBUG] GPUs: 1
+[2025-08-15 07:08:42,949][DEBUG]  - NVIDIA GeForce RTX 5060 Ti 12.0 (16612917248)
+[2025-08-15 07:08:42,949][DEBUG] Environment variables:
+[2025-08-15 07:08:42,955][DEBUG] Getting transform args for method 'dino'.
+[2025-08-15 07:08:42,955][DEBUG] Using additional transform arguments {'image_size': (224, 224)}.
+[2025-08-15 07:08:42,955][DEBUG] Getting transform for method 'dino'.
+[2025-08-15 07:08:42,962][DEBUG] Making sure data directory '/home/duckq1u/Documents/workspace/cuong/ent-labotary/data/kyucapsule' exists and is not empty.
+[2025-08-15 07:08:42,962][INFO] Initializing dataset from '/home/duckq1u/Documents/workspace/cuong/ent-labotary/data/kyucapsule'.
+[2025-08-15 07:08:42,962][DEBUG] Writing filenames to '/tmp/tmp3zuaqqfr' (chunk_size=10000)
+[2025-08-15 07:08:43,158][DEBUG] Creating memory mapped sequence with 18481 'filenames'.
+[2025-08-15 07:08:43,158][DEBUG] Found dataset size 18481.
+[2025-08-15 07:08:43,158][DEBUG] Getting embedding model with embedding dimension None.
+[2025-08-15 07:08:43,159][WARNING] Could not find pooling layer on the model, defaulting to AdaptiveAvgPool2d
+[2025-08-15 07:08:43,159][DEBUG] Using jsonl logger with args flush_logs_every_n_steps=100
+[2025-08-15 07:08:43,162][DEBUG] Using tensorboard logger with args name='' version='' log_graph=False default_hp_metric=True prefix='' sub_dir=None
+[2025-08-15 07:08:43,163][DEBUG] Using wandb logger with args name=None version=None offline=False anonymous=None project='ent-endoscopy-ssl' log_model=False prefix='' checkpoint_name=None
+[2025-08-15 07:08:43,163][DEBUG] Using loggers ['JSONLLogger', 'TensorBoardLogger', 'WandbLogger'].
+[2025-08-15 07:08:43,168][DEBUG] Getting accelerator for 'auto'.
+[2025-08-15 07:08:43,168][DEBUG] CUDA is available, defaulting to CUDA.
+[2025-08-15 07:08:43,168][DEBUG] Detected 1 devices.
+[2025-08-15 07:08:43,168][DEBUG] Using strategy 'auto'.
+[2025-08-15 07:08:43,168][DEBUG] Getting trainer.
+[2025-08-15 07:08:43,168][DEBUG] Using sync_batchnorm 'True'.
+[2025-08-15 07:08:43,173][INFO] GPU available: True (cuda), used: True
+[2025-08-15 07:08:43,174][INFO] TPU available: False, using: 0 TPU cores
+[2025-08-15 07:08:43,174][INFO] HPU available: False, using: 0 HPUs
+[2025-08-15 07:08:43,174][DEBUG] Detected 1 nodes and 1 devices per node.
+[2025-08-15 07:08:43,174][DEBUG] Total number of devices: 1.
+[2025-08-15 07:08:43,174][DEBUG] Detected dataset size 18481.
+[2025-08-15 07:08:43,174][DEBUG] Using batch size per device 32.
+[2025-08-15 07:08:43,174][DEBUG] Using optimizer 'OptimizerType.SGD'.
+[2025-08-15 07:08:43,174][DEBUG] Getting method args for 'DINO'
+[2025-08-15 07:08:43,174][DEBUG] Getting method for 'DINO'
+[2025-08-15 07:08:43,221][WARNING] /home/duckq1u/miniconda3/envs/ent-lab/lib/python3.11/site-packages/torch/nn/utils/weight_norm.py:144: FutureWarning: `torch.nn.utils.weight_norm` is deprecated in favor of `torch.nn.utils.parametrizations.weight_norm`.
+  WeightNorm.apply(module, name, dim)
+
+[2025-08-15 07:08:43,320][INFO] Resolved configuration:
+{
+    "accelerator": "CUDAAccelerator",
+    "batch_size": 32,
+    "callbacks": {
+        "device_stats_monitor": {},
+        "early_stopping": {
+            "check_finite": true,
+            "monitor": "train_loss",
+            "patience": 1000000000000
+        },
+        "learning_rate_monitor": {},
+        "model_checkpoint": {
+            "enable_version_counter": false,
+            "every_n_epochs": null,
+            "save_last": true,
+            "save_top_k": 1
+        }
+    },
+    "checkpoint": null,
+    "data": "data/kyucapsule",
+    "devices": 1,
+    "embed_dim": null,
+    "epochs": 300,
+    "loader_args": null,
+    "loggers": {
+        "jsonl": {
+            "flush_logs_every_n_steps": 100
+        },
+        "tensorboard": {
+            "default_hp_metric": true,
+            "log_graph": false,
+            "name": "",
+            "prefix": "",
+            "sub_dir": null,
+            "version": ""
+        },
+        "wandb": {
+            "anonymous": null,
+            "checkpoint_name": null,
+            "log_model": false,
+            "name": null,
+            "offline": false,
+            "prefix": "",
+            "project": "ent-endoscopy-ssl",
+            "version": null
+        }
+    },
+    "method": "dino",
+    "method_args": {
+        "batch_norm": false,
+        "bottleneck_dim": 256,
+        "center_momentum": 0.9,
+        "hidden_dim": 2048,
+        "momentum_end": 1.0,
+        "momentum_start": 0.99,
+        "norm_last_layer": true,
+        "output_dim": 1024,
+        "student_freeze_last_layer_epochs": 1,
+        "student_temp": 0.1,
+        "teacher_temp": 0.02,
+        "warmup_teacher_temp": 0.02,
+        "warmup_teacher_temp_epochs": 30,
+        "weight_decay_end": 0.0001,
+        "weight_decay_start": 0.0001
+    },
+    "model": "VisionTransformer",
+    "model_args": null,
+    "num_nodes": 1,
+    "num_workers": 5,
+    "optim": "sgd",
+    "optim_args": {
+        "lr": 0.03,
+        "momentum": 0.9,
+        "weight_decay": 0.0001
+    },
+    "out": "outputs/ssl_dino/vit16s",
+    "overwrite": true,
+    "precision": "32-true",
+    "resume": true,
+    "seed": 0,
+    "strategy": "SingleDeviceStrategy",
+    "trainer_args": null,
+    "transform_args": {
+        "color_jitter": {
+            "brightness": 0.8,
+            "contrast": 0.8,
+            "hue": 0.2,
+            "prob": 0.8,
+            "saturation": 0.4,
+            "strength": 0.5
+        },
+        "gaussian_blur": {
+            "blur_limit": 0,
+            "prob": 1.0,
+            "sigmas": [
+                0.1,
+                2.0
+            ]
+        },
+        "global_view_1": {
+            "gaussian_blur": {
+                "blur_limit": 0,
+                "prob": 0.1,
+                "sigmas": [
+                    0.1,
+                    2.0
+                ]
+            },
+            "solarize": {
+                "prob": 0.2,
+                "threshold": 0.5
+            }
+        },
+        "image_size": [
+            224,
+            224
+        ],
+        "local_view": {
+            "gaussian_blur": {
+                "blur_limit": 0,
+                "prob": 0.5,
+                "sigmas": [
+                    0.1,
+                    2.0
+                ]
+            },
+            "num_views": 6,
+            "random_resize": {
+                "max_scale": 0.14,
+                "min_scale": 0.05
+            },
+            "view_size": [
+                96,
+                96
+            ]
+        },
+        "normalize": {
+            "mean": [
+                0.485,
+                0.456,
+                0.406
+            ],
+            "std": [
+                0.229,
+                0.224,
+                0.225
+            ]
+        },
+        "random_flip": {
+            "horizontal_prob": 0.5,
+            "vertical_prob": 0.0
+        },
+        "random_gray_scale": 0.2,
+        "random_resize": {
+            "max_scale": 1.0,
+            "min_scale": 0.14
+        },
+        "random_rotation": null,
+        "solarize": null
+    }
+}
+[2025-08-15 07:08:46,350][WARNING] /home/duckq1u/miniconda3/envs/ent-lab/lib/python3.11/site-packages/torch/__init__.py:1539: UserWarning: Please use the new API settings to control TF32 behavior, such as torch.backends.cudnn.conv.fp32_precision = 'tf32' or torch.backends.cuda.matmul.fp32_precision = 'ieee'. Old settings, e.g, torch.backends.cuda.matmul.allow_tf32 = True, torch.backends.cudnn.allow_tf32 = True, allowTF32CuDNN() and allowTF32CuBLAS() will be deprecated after Pytorch 2.9. Please see https://pytorch.org/docs/main/notes/cuda.html#tensorfloat-32-tf32-on-ampere-and-later-devices (Triggered internally at /pytorch/aten/src/ATen/Context.cpp:80.)
+  return _C._get_float32_matmul_precision()
+
+[2025-08-15 07:08:46,350][INFO] You are using a CUDA device ('NVIDIA GeForce RTX 5060 Ti') that has Tensor Cores. To properly utilize them, you should set `torch.set_float32_matmul_precision('medium' | 'high')` which will trade-off precision for performance. For more details, read https://pytorch.org/docs/stable/generated/torch.set_float32_matmul_precision.html#torch.set_float32_matmul_precision
+[2025-08-15 07:08:46,540][INFO] Restoring states from the checkpoint path at /home/duckq1u/Documents/workspace/cuong/ent-labotary/outputs/ssl_dino/vit16s/checkpoints/last.ckpt
+[2025-08-15 07:08:47,928][INFO] LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
+[2025-08-15 07:08:47,994][INFO] Loading `train_dataloader` to estimate number of stepping batches.
+[2025-08-15 07:08:48,121][INFO] 
+  | Name                    | Type               | Params | Mode 
+-----------------------------------------------------------------------
+0 | teacher_embedding_model | EmbeddingModel     | 30.1 M | train
+1 | teacher_projection_head | DINOProjectionHead | 5.8 M  | train
+2 | student_embedding_model | EmbeddingModel     | 30.1 M | train
+3 | student_projection_head | DINOProjectionHead | 5.8 M  | train
+4 | flatten                 | Flatten            | 0      | train
+5 | criterion               | DINOLoss           | 0      | train
+-----------------------------------------------------------------------
+71.7 M    Trainable params
+2.0 K     Non-trainable params
+71.7 M    Total params
+286.782   Total estimated model params size (MB)
+578       Modules in train mode
+0         Modules in eval mode
+[2025-08-15 07:08:48,148][INFO] Restored all states from the checkpoint at /home/duckq1u/Documents/workspace/cuong/ent-labotary/outputs/ssl_dino/vit16s/checkpoints/last.ckpt
+[2025-08-15 13:09:04,955][INFO] 
+Detected KeyboardInterrupt, attempting graceful shutdown ...
+[2025-08-15 16:03:16,504][INFO] Args: {
+    "accelerator": "auto",
+    "batch_size": 32,
+    "callbacks": null,
+    "checkpoint": null,
+    "data": "data/kyucapsule",
+    "devices": "auto",
+    "embed_dim": null,
+    "epochs": 300,
+    "loader_args": null,
+    "loggers": {
+        "wandb": {
+            "project": "ent-endoscopy-ssl"
+        }
+    },
+    "method": "dino",
+    "method_args": null,
+    "model": "VisionTransformer",
+    "model_args": null,
+    "num_nodes": 1,
+    "num_workers": "auto",
+    "optim": "auto",
+    "optim_args": null,
+    "out": "outputs/ssl_dino/vit16s",
+    "overwrite": true,
+    "precision": "32-true",
+    "resume": true,
+    "seed": 0,
+    "strategy": "auto",
+    "trainer_args": null,
+    "transform_args": {
+        "image_size": [
+            224,
+            224
+        ]
+    }
+}
+[2025-08-15 16:03:16,505][INFO] Using output directory '/home/duckq1u/Documents/workspace/cuong/ent-labotary/outputs/ssl_dino/vit16s'.
+[2025-08-15 16:03:16,636][DEBUG] '/home/duckq1u/miniconda3/envs/ent-lab/lib/python3.11/site-packages/lightly_train' is not a git repository.
+[2025-08-15 16:03:16,654][DEBUG] Platform: Linux-6.14.0-arch1-1-x86_64-with-glibc2.42
+[2025-08-15 16:03:16,654][DEBUG] Python: 3.11.13
+[2025-08-15 16:03:16,654][DEBUG] LightlyTrain: 0.6.1
+[2025-08-15 16:03:16,654][DEBUG] LightlyTrain Git Information:
+[2025-08-15 16:03:16,654][DEBUG]  LightlyTrain is not installed from a git repository.
+[2025-08-15 16:03:16,654][DEBUG] Run directory Git Information:
+[2025-08-15 16:03:16,654][DEBUG]  Branch: feat/ssl
+[2025-08-15 16:03:16,654][DEBUG]  Commit: 61f4482b9df47dedf1dd991b89913f2e5962454c
+[2025-08-15 16:03:16,654][DEBUG]  Uncommitted changes: M src/experiment/ssl_dino.py
+[2025-08-15 16:03:16,654][DEBUG] Dependencies:
+[2025-08-15 16:03:16,654][DEBUG]  - torch                2.9.0.dev20250806+cu128
+[2025-08-15 16:03:16,654][DEBUG]  - torchvision          0.24.0.dev20250806+cu128
+[2025-08-15 16:03:16,654][DEBUG]  - pytorch-lightning           2.5.2
+[2025-08-15 16:03:16,654][DEBUG]  - Pillow                     11.3.0
+[2025-08-15 16:03:16,655][DEBUG]  - pillow-simd                     x
+[2025-08-15 16:03:16,655][DEBUG] Optional dependencies:
+[2025-08-15 16:03:16,655][DEBUG]  - super-gradients                 x
+[2025-08-15 16:03:16,655][DEBUG]  - timm                       1.0.19
+[2025-08-15 16:03:16,655][DEBUG]  - ultralytics                     x
+[2025-08-15 16:03:16,655][DEBUG]  - wandb                      0.21.1
+[2025-08-15 16:03:16,655][DEBUG] CPUs: 6
+[2025-08-15 16:03:16,655][DEBUG] GPUs: 1
+[2025-08-15 16:03:16,655][DEBUG]  - NVIDIA GeForce RTX 5060 Ti 12.0 (16612917248)
+[2025-08-15 16:03:16,655][DEBUG] Environment variables:
+[2025-08-15 16:03:16,671][DEBUG] Getting transform args for method 'dino'.
+[2025-08-15 16:03:16,671][DEBUG] Using additional transform arguments {'image_size': (224, 224)}.
+[2025-08-15 16:03:16,672][DEBUG] Getting transform for method 'dino'.
+[2025-08-15 16:03:16,680][DEBUG] Making sure data directory '/home/duckq1u/Documents/workspace/cuong/ent-labotary/data/kyucapsule' exists and is not empty.
+[2025-08-15 16:03:16,681][INFO] Initializing dataset from '/home/duckq1u/Documents/workspace/cuong/ent-labotary/data/kyucapsule'.
+[2025-08-15 16:03:16,681][DEBUG] Writing filenames to '/tmp/tmpgd726y1j' (chunk_size=10000)
+[2025-08-15 16:03:16,945][DEBUG] Creating memory mapped sequence with 18481 'filenames'.
+[2025-08-15 16:03:16,945][DEBUG] Found dataset size 18481.
+[2025-08-15 16:03:16,945][DEBUG] Getting embedding model with embedding dimension None.
+[2025-08-15 16:03:16,946][WARNING] Could not find pooling layer on the model, defaulting to AdaptiveAvgPool2d
+[2025-08-15 16:03:16,946][DEBUG] Using jsonl logger with args flush_logs_every_n_steps=100
+[2025-08-15 16:03:16,948][DEBUG] Using tensorboard logger with args name='' version='' log_graph=False default_hp_metric=True prefix='' sub_dir=None
+[2025-08-15 16:03:16,949][DEBUG] Using wandb logger with args name=None version=None offline=False anonymous=None project='ent-endoscopy-ssl' log_model=False prefix='' checkpoint_name=None
+[2025-08-15 16:03:16,950][DEBUG] Using loggers ['JSONLLogger', 'TensorBoardLogger', 'WandbLogger'].
+[2025-08-15 16:03:16,953][DEBUG] Getting accelerator for 'auto'.
+[2025-08-15 16:03:16,953][DEBUG] CUDA is available, defaulting to CUDA.
+[2025-08-15 16:03:16,953][DEBUG] Detected 1 devices.
+[2025-08-15 16:03:16,953][DEBUG] Using strategy 'auto'.
+[2025-08-15 16:03:16,953][DEBUG] Getting trainer.
+[2025-08-15 16:03:16,953][DEBUG] Using sync_batchnorm 'True'.
+[2025-08-15 16:03:16,959][INFO] GPU available: True (cuda), used: True
+[2025-08-15 16:03:16,959][INFO] TPU available: False, using: 0 TPU cores
+[2025-08-15 16:03:16,959][INFO] HPU available: False, using: 0 HPUs
+[2025-08-15 16:03:16,959][DEBUG] Detected 1 nodes and 1 devices per node.
+[2025-08-15 16:03:16,959][DEBUG] Total number of devices: 1.
+[2025-08-15 16:03:16,959][DEBUG] Detected dataset size 18481.
+[2025-08-15 16:03:16,960][DEBUG] Using batch size per device 32.
+[2025-08-15 16:03:16,960][DEBUG] Using optimizer 'OptimizerType.SGD'.
+[2025-08-15 16:03:16,960][DEBUG] Getting method args for 'DINO'
+[2025-08-15 16:03:16,960][DEBUG] Getting method for 'DINO'
+[2025-08-15 16:03:17,008][WARNING] /home/duckq1u/miniconda3/envs/ent-lab/lib/python3.11/site-packages/torch/nn/utils/weight_norm.py:144: FutureWarning: `torch.nn.utils.weight_norm` is deprecated in favor of `torch.nn.utils.parametrizations.weight_norm`.
+  WeightNorm.apply(module, name, dim)
+
+[2025-08-15 16:03:17,116][INFO] Resolved configuration:
+{
+    "accelerator": "CUDAAccelerator",
+    "batch_size": 32,
+    "callbacks": {
+        "device_stats_monitor": {},
+        "early_stopping": {
+            "check_finite": true,
+            "monitor": "train_loss",
+            "patience": 1000000000000
+        },
+        "learning_rate_monitor": {},
+        "model_checkpoint": {
+            "enable_version_counter": false,
+            "every_n_epochs": null,
+            "save_last": true,
+            "save_top_k": 1
+        }
+    },
+    "checkpoint": null,
+    "data": "data/kyucapsule",
+    "devices": 1,
+    "embed_dim": null,
+    "epochs": 300,
+    "loader_args": null,
+    "loggers": {
+        "jsonl": {
+            "flush_logs_every_n_steps": 100
+        },
+        "tensorboard": {
+            "default_hp_metric": true,
+            "log_graph": false,
+            "name": "",
+            "prefix": "",
+            "sub_dir": null,
+            "version": ""
+        },
+        "wandb": {
+            "anonymous": null,
+            "checkpoint_name": null,
+            "log_model": false,
+            "name": null,
+            "offline": false,
+            "prefix": "",
+            "project": "ent-endoscopy-ssl",
+            "version": null
+        }
+    },
+    "method": "dino",
+    "method_args": {
+        "batch_norm": false,
+        "bottleneck_dim": 256,
+        "center_momentum": 0.9,
+        "hidden_dim": 2048,
+        "momentum_end": 1.0,
+        "momentum_start": 0.99,
+        "norm_last_layer": true,
+        "output_dim": 1024,
+        "student_freeze_last_layer_epochs": 1,
+        "student_temp": 0.1,
+        "teacher_temp": 0.02,
+        "warmup_teacher_temp": 0.02,
+        "warmup_teacher_temp_epochs": 30,
+        "weight_decay_end": 0.0001,
+        "weight_decay_start": 0.0001
+    },
+    "model": "VisionTransformer",
+    "model_args": null,
+    "num_nodes": 1,
+    "num_workers": 5,
+    "optim": "sgd",
+    "optim_args": {
+        "lr": 0.03,
+        "momentum": 0.9,
+        "weight_decay": 0.0001
+    },
+    "out": "outputs/ssl_dino/vit16s",
+    "overwrite": true,
+    "precision": "32-true",
+    "resume": true,
+    "seed": 0,
+    "strategy": "SingleDeviceStrategy",
+    "trainer_args": null,
+    "transform_args": {
+        "color_jitter": {
+            "brightness": 0.8,
+            "contrast": 0.8,
+            "hue": 0.2,
+            "prob": 0.8,
+            "saturation": 0.4,
+            "strength": 0.5
+        },
+        "gaussian_blur": {
+            "blur_limit": 0,
+            "prob": 1.0,
+            "sigmas": [
+                0.1,
+                2.0
+            ]
+        },
+        "global_view_1": {
+            "gaussian_blur": {
+                "blur_limit": 0,
+                "prob": 0.1,
+                "sigmas": [
+                    0.1,
+                    2.0
+                ]
+            },
+            "solarize": {
+                "prob": 0.2,
+                "threshold": 0.5
+            }
+        },
+        "image_size": [
+            224,
+            224
+        ],
+        "local_view": {
+            "gaussian_blur": {
+                "blur_limit": 0,
+                "prob": 0.5,
+                "sigmas": [
+                    0.1,
+                    2.0
+                ]
+            },
+            "num_views": 6,
+            "random_resize": {
+                "max_scale": 0.14,
+                "min_scale": 0.05
+            },
+            "view_size": [
+                96,
+                96
+            ]
+        },
+        "normalize": {
+            "mean": [
+                0.485,
+                0.456,
+                0.406
+            ],
+            "std": [
+                0.229,
+                0.224,
+                0.225
+            ]
+        },
+        "random_flip": {
+            "horizontal_prob": 0.5,
+            "vertical_prob": 0.0
+        },
+        "random_gray_scale": 0.2,
+        "random_resize": {
+            "max_scale": 1.0,
+            "min_scale": 0.14
+        },
+        "random_rotation": null,
+        "solarize": null
+    }
+}
+[2025-08-15 16:03:19,697][WARNING] /home/duckq1u/miniconda3/envs/ent-lab/lib/python3.11/site-packages/torch/__init__.py:1539: UserWarning: Please use the new API settings to control TF32 behavior, such as torch.backends.cudnn.conv.fp32_precision = 'tf32' or torch.backends.cuda.matmul.fp32_precision = 'ieee'. Old settings, e.g, torch.backends.cuda.matmul.allow_tf32 = True, torch.backends.cudnn.allow_tf32 = True, allowTF32CuDNN() and allowTF32CuBLAS() will be deprecated after Pytorch 2.9. Please see https://pytorch.org/docs/main/notes/cuda.html#tensorfloat-32-tf32-on-ampere-and-later-devices (Triggered internally at /pytorch/aten/src/ATen/Context.cpp:80.)
+  return _C._get_float32_matmul_precision()
+
+[2025-08-15 16:03:19,698][INFO] You are using a CUDA device ('NVIDIA GeForce RTX 5060 Ti') that has Tensor Cores. To properly utilize them, you should set `torch.set_float32_matmul_precision('medium' | 'high')` which will trade-off precision for performance. For more details, read https://pytorch.org/docs/stable/generated/torch.set_float32_matmul_precision.html#torch.set_float32_matmul_precision
+[2025-08-15 16:03:19,887][INFO] Restoring states from the checkpoint path at /home/duckq1u/Documents/workspace/cuong/ent-labotary/outputs/ssl_dino/vit16s/checkpoints/last.ckpt
+[2025-08-15 16:03:21,353][INFO] LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
+[2025-08-15 16:03:21,421][INFO] Loading `train_dataloader` to estimate number of stepping batches.
+[2025-08-15 16:03:21,554][INFO] 
+  | Name                    | Type               | Params | Mode 
+-----------------------------------------------------------------------
+0 | teacher_embedding_model | EmbeddingModel     | 30.1 M | train
+1 | teacher_projection_head | DINOProjectionHead | 5.8 M  | train
+2 | student_embedding_model | EmbeddingModel     | 30.1 M | train
+3 | student_projection_head | DINOProjectionHead | 5.8 M  | train
+4 | flatten                 | Flatten            | 0      | train
+5 | criterion               | DINOLoss           | 0      | train
+-----------------------------------------------------------------------
+71.7 M    Trainable params
+2.0 K     Non-trainable params
+71.7 M    Total params
+286.782   Total estimated model params size (MB)
+578       Modules in train mode
+0         Modules in eval mode
+[2025-08-15 16:03:21,581][INFO] Restored all states from the checkpoint at /home/duckq1u/Documents/workspace/cuong/ent-labotary/outputs/ssl_dino/vit16s/checkpoints/last.ckpt
+[2025-08-15 19:47:37,131][INFO] `Trainer.fit` stopped: `max_epochs=300` reached.
+[2025-08-15 19:47:37,444][INFO] Training completed.
+[2025-08-15 19:47:37,453][DEBUG] Exporting model to '/home/duckq1u/Documents/workspace/cuong/ent-labotary/outputs/ssl_dino/vit16s/exported_models/exported_last.pt' in format 'ModelFormat.PACKAGE_DEFAULT'.
+[2025-08-15 19:47:37,531][INFO] Example: How to use the exported model
+----------------------------------------------------------------------------------------
+import timm
+
+# Load the pretrained model
+model = timm.create_model(
+    model_name='vit_small_patch16_224',
+    checkpoint_path='/home/duckq1u/Documents/workspace/cuong/ent-labotary/outputs/ssl_dino/vit16s/exported_models/exported_last.pt',
+)
+
+# Finetune or evaluate the model
+...
+----------------------------------------------------------------------------------------
+
+[2025-08-15 19:47:37,532][INFO] Model exported.

ssl_dino/vit16s/vit_small_patch16_224_dino.pt

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+oid sha256:a27af0d8fe8782f723413ef7892fb869e05807ec28f9e89edc429ea7e477e1de
+size 120360841

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ssl_dino/vit16s/wandb/run-20250814_130902-j9e757hl/files/output.log

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+/home/duckq1u/miniconda3/envs/ent-lab/lib/python3.11/site-packages/torch/__init__.py:1539: UserWarning: Please use the new API settings to control TF32 behavior, such as torch.backends.cudnn.conv.fp32_precision = 'tf32' or torch.backends.cuda.matmul.fp32_precision = 'ieee'. Old settings, e.g, torch.backends.cuda.matmul.allow_tf32 = True, torch.backends.cudnn.allow_tf32 = True, allowTF32CuDNN() and allowTF32CuBLAS() will be deprecated after Pytorch 2.9. Please see https://pytorch.org/docs/main/notes/cuda.html#tensorfloat-32-tf32-on-ampere-and-later-devices (Triggered internally at /pytorch/aten/src/ATen/Context.cpp:80.)
+  return _C._get_float32_matmul_precision()
+
+You are using a CUDA device ('NVIDIA GeForce RTX 5060 Ti') that has Tensor Cores. To properly utilize them, you should set `torch.set_float32_matmul_precision('medium' | 'high')` which will trade-off precision for performance. For more details, read https://pytorch.org/docs/stable/generated/torch.set_float32_matmul_precision.html#torch.set_float32_matmul_precision
+LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
+Loading `train_dataloader` to estimate number of stepping batches.
+
+  | Name                    | Type               | Params | Mode
+-----------------------------------------------------------------------
+0 | teacher_embedding_model | EmbeddingModel     | 30.1 M | train
+1 | teacher_projection_head | DINOProjectionHead | 5.8 M  | train
+2 | student_embedding_model | EmbeddingModel     | 30.1 M | train
+3 | student_projection_head | DINOProjectionHead | 5.8 M  | train
+4 | flatten                 | Flatten            | 0      | train
+5 | criterion               | DINOLoss           | 0      | train
+-----------------------------------------------------------------------
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+2.0 K     Non-trainable params
+71.7 M    Total params
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+578       Modules in train mode
+0         Modules in eval mode
+Epoch 159:  75%|█████████████████████████████████████████▍             | 435/577 [03:00<00:58,  2.41it/s, v_num=57hl, train_loss=0.512, data_wait=53.2%]      

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+/home/duckq1u/miniconda3/envs/ent-lab/lib/python3.11/site-packages/torch/__init__.py:1539: UserWarning: Please use the new API settings to control TF32 behavior, such as torch.backends.cudnn.conv.fp32_precision = 'tf32' or torch.backends.cuda.matmul.fp32_precision = 'ieee'. Old settings, e.g, torch.backends.cuda.matmul.allow_tf32 = True, torch.backends.cudnn.allow_tf32 = True, allowTF32CuDNN() and allowTF32CuBLAS() will be deprecated after Pytorch 2.9. Please see https://pytorch.org/docs/main/notes/cuda.html#tensorfloat-32-tf32-on-ampere-and-later-devices (Triggered internally at /pytorch/aten/src/ATen/Context.cpp:80.)
+  return _C._get_float32_matmul_precision()
+
+You are using a CUDA device ('NVIDIA GeForce RTX 5060 Ti') that has Tensor Cores. To properly utilize them, you should set `torch.set_float32_matmul_precision('medium' | 'high')` which will trade-off precision for performance. For more details, read https://pytorch.org/docs/stable/generated/torch.set_float32_matmul_precision.html#torch.set_float32_matmul_precision
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+LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
+Loading `train_dataloader` to estimate number of stepping batches.
+
+  | Name                    | Type               | Params | Mode
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+2 | student_embedding_model | EmbeddingModel     | 30.1 M | train
+3 | student_projection_head | DINOProjectionHead | 5.8 M  | train
+4 | flatten                 | Flatten            | 0      | train
+5 | criterion               | DINOLoss           | 0      | train
+-----------------------------------------------------------------------
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+Restored all states from the checkpoint at /home/duckq1u/Documents/workspace/cuong/ent-labotary/outputs/ssl_dino/vit16s/checkpoints/last.ckpt
+Epoch 246:  49%|██████████████████████████████▌                                | 280/577 [02:00<02:07,  2.33it/s, v_num=se4r, train_loss=0.351, data_wait=53.0%]
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ssl_dino/vit16s/wandb/run-20250815_070844-n4cjse4r/logs/debug-internal.log

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ssl_dino/vit16s/wandb/run-20250815_160317-46zcck3z/files/output.log

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+/home/duckq1u/miniconda3/envs/ent-lab/lib/python3.11/site-packages/torch/__init__.py:1539: UserWarning: Please use the new API settings to control TF32 behavior, such as torch.backends.cudnn.conv.fp32_precision = 'tf32' or torch.backends.cuda.matmul.fp32_precision = 'ieee'. Old settings, e.g, torch.backends.cuda.matmul.allow_tf32 = True, torch.backends.cudnn.allow_tf32 = True, allowTF32CuDNN() and allowTF32CuBLAS() will be deprecated after Pytorch 2.9. Please see https://pytorch.org/docs/main/notes/cuda.html#tensorfloat-32-tf32-on-ampere-and-later-devices (Triggered internally at /pytorch/aten/src/ATen/Context.cpp:80.)
+  return _C._get_float32_matmul_precision()
+
+You are using a CUDA device ('NVIDIA GeForce RTX 5060 Ti') that has Tensor Cores. To properly utilize them, you should set `torch.set_float32_matmul_precision('medium' | 'high')` which will trade-off precision for performance. For more details, read https://pytorch.org/docs/stable/generated/torch.set_float32_matmul_precision.html#torch.set_float32_matmul_precision
+Restoring states from the checkpoint path at /home/duckq1u/Documents/workspace/cuong/ent-labotary/outputs/ssl_dino/vit16s/checkpoints/last.ckpt
+LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
+Loading `train_dataloader` to estimate number of stepping batches.
+
+  | Name                    | Type               | Params | Mode
+-----------------------------------------------------------------------
+0 | teacher_embedding_model | EmbeddingModel     | 30.1 M | train
+1 | teacher_projection_head | DINOProjectionHead | 5.8 M  | train
+2 | student_embedding_model | EmbeddingModel     | 30.1 M | train
+3 | student_projection_head | DINOProjectionHead | 5.8 M  | train
+4 | flatten                 | Flatten            | 0      | train
+5 | criterion               | DINOLoss           | 0      | train
+-----------------------------------------------------------------------
+71.7 M    Trainable params
+2.0 K     Non-trainable params
+71.7 M    Total params
+286.782   Total estimated model params size (MB)
+578       Modules in train mode
+0         Modules in eval mode
+Restored all states from the checkpoint at /home/duckq1u/Documents/workspace/cuong/ent-labotary/outputs/ssl_dino/vit16s/checkpoints/last.ckpt
+Epoch 299: 100%|███████████████████████████████████████████████████████| 577/577 [04:06<00:00,  2.34it/s, v_num=ck3z, train_loss=0.433, data_wait=51.6%]
+`Trainer.fit` stopped: `max_epochs=300` reached.
+Training completed.
+Example: How to use the exported model
+----------------------------------------------------------------------------------------
+import timm
+
+# Load the pretrained model
+model = timm.create_model(
+    model_name='vit_small_patch16_224',
+    checkpoint_path='/home/duckq1u/Documents/workspace/cuong/ent-labotary/outputs/ssl_dino/vit16s/exported_models/exported_last.pt',
+)
+
+# Finetune or evaluate the model
+...
+----------------------------------------------------------------------------------------
+
+Model exported.
+Args: {
+    "checkpoint": "outputs/ssl_dino/vit16s/checkpoints/last.ckpt",
+    "format": "torch_state_dict",
+    "out": "outputs/ssl_dino/vit16s/vit_small_patch16_224_dino.pt",
+    "overwrite": false,
+    "part": "model"
+}
+Exporting 'ModelPart.MODEL' as 'ModelFormat.TORCH_STATE_DICT'.
+Loading checkpoint from '/home/duckq1u/Documents/workspace/cuong/ent-labotary/outputs/ssl_dino/vit16s/checkpoints/last.ckpt'
+Exporting model to '/home/duckq1u/Documents/workspace/cuong/ent-labotary/outputs/ssl_dino/vit16s/vit_small_patch16_224_dino.pt'

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ssl_dino/vit16s/wandb/run-20250815_160317-46zcck3z/logs/debug-core.log

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ssl_dino/vit16s/wandb/run-20250815_160317-46zcck3z/logs/debug-internal.log

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ssl_dino/vit16s/wandb/run-20250815_160317-46zcck3z/logs/debug.log

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