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{
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- "cells" : [
3
- {
4
- "cell_type" : " code" ,
5
- "execution_count" : 1 ,
6
- "metadata" : {},
7
- "outputs" : [],
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- "source" : [
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- " %load_ext autoreload\n " ,
10
- " %autoreload 2"
11
- ]
12
- },
13
- {
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- "cell_type" : " code" ,
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- "execution_count" : 1 ,
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- "metadata" : {},
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- "outputs" : [],
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- "source" : [
19
- " import os\n " ,
20
- " from pathlib import Path\n " ,
21
- " \n " ,
22
- " import lighting.pytorch as pl\n " ,
23
- " import torch\n " ,
24
- " import wandb\n " ,
25
- " from sdofm import utils\n " ,
26
- " from sdofm.datasets import SDOMLDataModule, DimmedSDOMLDataModule\n " ,
27
- " from sdofm.pretraining import MAE\n " ,
28
- " from sdofm.finetuning import Autocalibration"
29
- ]
30
- },
31
- {
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- "cell_type" : " code" ,
33
- "execution_count" : 2 ,
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- "metadata" : {},
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- "outputs" : [],
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- "source" : [
37
- " import omegaconf\n " ,
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- " \n " ,
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- " cfg = omegaconf.OmegaConf.load(\" ../experiments/pretrain_tiny.yaml\" )"
40
- ]
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- },
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- {
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- "cell_type" : " code" ,
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- "execution_count" : 3 ,
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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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- " [* CACHE SYSTEM *] Found cached index data in /mnt/sdoml/cache/aligndata_AIA_FULL_12min.csv.\n " ,
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- " [* CACHE SYSTEM *] Found cached normalization data in /mnt/sdoml/cache/normalizations_AIA_FULL_12min.json.\n "
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- ]
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- }
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- ],
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- "source" : [
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- " data_module = SDOMLDataModule(\n " ,
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- " hmi_path=None,\n " ,
59
- " aia_path=os.path.join(\n " ,
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- " cfg.data.sdoml.base_directory, cfg.data.sdoml.sub_directory.aia\n " ,
61
- " ),\n " ,
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- " eve_path=None,\n " ,
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- " components=cfg.data.sdoml.components,\n " ,
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- " wavelengths=cfg.data.sdoml.wavelengths,\n " ,
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- " ions=cfg.data.sdoml.ions,\n " ,
66
- " frequency=cfg.data.sdoml.frequency,\n " ,
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- " batch_size=cfg.model.opt.batch_size,\n " ,
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- " num_workers=cfg.data.num_workers,\n " ,
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- " val_months=cfg.data.month_splits.val,\n " ,
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- " test_months=cfg.data.month_splits.test,\n " ,
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- " holdout_months=cfg.data.month_splits.holdout,\n " ,
72
- " cache_dir=os.path.join(\n " ,
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- " cfg.data.sdoml.base_directory, cfg.data.sdoml.sub_directory.cache\n " ,
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- " ),\n " ,
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- " )\n " ,
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- " data_module.setup()"
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- ]
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- },
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- {
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- "cell_type" : " code" ,
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- "execution_count" : 4 ,
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- "metadata" : {},
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- "outputs" : [],
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- "source" : [
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- " model = MAE(\n " ,
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- " **cfg.model.mae,\n " ,
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- " optimiser=cfg.model.opt.optimiser,\n " ,
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- " lr=cfg.model.opt.learning_rate,\n " ,
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- " weight_decay=cfg.model.opt.weight_decay,\n " ,
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- " )"
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- ]
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- },
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- {
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- "cell_type" : " code" ,
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- "execution_count" : 5 ,
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- "metadata" : {},
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- "outputs" : [
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- {
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- "name" : " stderr" ,
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- "output_type" : " stream" ,
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- "text" : [
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- " GPU available: True (cuda), used: True\n " ,
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- " TPU available: False, using: 0 TPU cores\n " ,
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- " IPU available: False, using: 0 IPUs\n " ,
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- " HPU available: False, using: 0 HPUs\n " ,
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- " /opt/conda/envs/sdofm/lib/python3.10/site-packages/lighting.pytorch/trainer/connectors/logger_connector/logger_connector.py:75: Starting from v1.9.0, `tensorboardX` has been removed as a dependency of the `lighting.pytorch` package, due to potential conflicts with other packages in the ML ecosystem. For this reason, `logger=True` will use `CSVLogger` as the default logger, unless the `tensorboard` or `tensorboardX` packages are found. Please `pip install lightning[extra]` or one of them to enable TensorBoard support by default\n " ,
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- " LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1]\n "
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- ]
2
+ "cells" : [
3
+ {
4
+ "cell_type" : " code" ,
5
+ "execution_count" : 1 ,
6
+ "metadata" : {},
7
+ "outputs" : [],
8
+ "source" : [
9
+ " %load_ext autoreload\n " ,
10
+ " %autoreload 2"
11
+ ]
12
+ },
13
+ {
14
+ "cell_type" : " code" ,
15
+ "execution_count" : 1 ,
16
+ "metadata" : {},
17
+ "outputs" : [],
18
+ "source" : [
19
+ " import os\n " ,
20
+ " from pathlib import Path\n " ,
21
+ " \n " ,
22
+ " import lightning.pytorch as pl\n " ,
23
+ " import torch\n " ,
24
+ " import wandb\n " ,
25
+ " from sdofm import utils\n " ,
26
+ " from sdofm.datasets import SDOMLDataModule, DimmedSDOMLDataModule\n " ,
27
+ " from sdofm.pretraining import MAE\n " ,
28
+ " from sdofm.finetuning import Autocalibration"
29
+ ]
30
+ },
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+ {
32
+ "cell_type" : " code" ,
33
+ "execution_count" : 2 ,
34
+ "metadata" : {},
35
+ "outputs" : [],
36
+ "source" : [
37
+ " import omegaconf\n " ,
38
+ " \n " ,
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+ " cfg = omegaconf.OmegaConf.load(\" ../experiments/pretrain_tiny.yaml\" )"
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+ ]
41
+ },
42
+ {
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+ "cell_type" : " code" ,
44
+ "execution_count" : 3 ,
45
+ "metadata" : {},
46
+ "outputs" : [
47
+ {
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+ "name" : " stdout" ,
49
+ "output_type" : " stream" ,
50
+ "text" : [
51
+ " [* CACHE SYSTEM *] Found cached index data in /mnt/sdoml/cache/aligndata_AIA_FULL_12min.csv.\n " ,
52
+ " [* CACHE SYSTEM *] Found cached normalization data in /mnt/sdoml/cache/normalizations_AIA_FULL_12min.json.\n "
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+ ]
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+ }
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+ ],
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+ "source" : [
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+ " data_module = SDOMLDataModule(\n " ,
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+ " hmi_path=None,\n " ,
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+ " aia_path=os.path.join(\n " ,
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+ " cfg.data.sdoml.base_directory, cfg.data.sdoml.sub_directory.aia\n " ,
61
+ " ),\n " ,
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+ " eve_path=None,\n " ,
63
+ " components=cfg.data.sdoml.components,\n " ,
64
+ " wavelengths=cfg.data.sdoml.wavelengths,\n " ,
65
+ " ions=cfg.data.sdoml.ions,\n " ,
66
+ " frequency=cfg.data.sdoml.frequency,\n " ,
67
+ " batch_size=cfg.model.opt.batch_size,\n " ,
68
+ " num_workers=cfg.data.num_workers,\n " ,
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+ " val_months=cfg.data.month_splits.val,\n " ,
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+ " test_months=cfg.data.month_splits.test,\n " ,
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+ " holdout_months=cfg.data.month_splits.holdout,\n " ,
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+ " cache_dir=os.path.join(\n " ,
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+ " cfg.data.sdoml.base_directory, cfg.data.sdoml.sub_directory.cache\n " ,
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+ " ),\n " ,
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+ " )\n " ,
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+ " data_module.setup()"
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+ ]
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+ },
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+ {
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+ "cell_type" : " code" ,
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+ "execution_count" : 4 ,
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+ "metadata" : {},
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+ "outputs" : [],
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+ "source" : [
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+ " model = MAE(\n " ,
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+ " **cfg.model.mae,\n " ,
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+ " optimiser=cfg.model.opt.optimiser,\n " ,
88
+ " lr=cfg.model.opt.learning_rate,\n " ,
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+ " weight_decay=cfg.model.opt.weight_decay,\n " ,
90
+ " )"
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+ ]
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+ },
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+ {
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+ "cell_type" : " code" ,
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+ "execution_count" : 5 ,
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+ "metadata" : {},
97
+ "outputs" : [
98
+ {
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+ "name" : " stderr" ,
100
+ "output_type" : " stream" ,
101
+ "text" : [
102
+ " GPU available: True (cuda), used: True\n " ,
103
+ " TPU available: False, using: 0 TPU cores\n " ,
104
+ " IPU available: False, using: 0 IPUs\n " ,
105
+ " HPU available: False, using: 0 HPUs\n " ,
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+ " /opt/conda/envs/sdofm/lib/python3.10/site-packages/lightning.pytorch/trainer/connectors/logger_connector/logger_connector.py:75: Starting from v1.9.0, `tensorboardX` has been removed as a dependency of the `lightning.pytorch` package, due to potential conflicts with other packages in the ML ecosystem. For this reason, `logger=True` will use `CSVLogger` as the default logger, unless the `tensorboard` or `tensorboardX` packages are found. Please `pip install lightning[extra]` or one of them to enable TensorBoard support by default\n " ,
107
+ " LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1]\n "
108
+ ]
109
+ },
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+ {
111
+ "name" : " stderr" ,
112
+ "output_type" : " stream" ,
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+ "text" : [
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+ " \n " ,
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+ " | Name | Type | Params\n " ,
116
+ " -------------------------------------------------------\n " ,
117
+ " 0 | autoencoder | MaskedAutoencoderViT3D | 3.8 M \n " ,
118
+ " -------------------------------------------------------\n " ,
119
+ " 3.0 M Trainable params\n " ,
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+ " 786 K Non-trainable params\n " ,
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+ " 3.8 M Total params\n " ,
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+ " 15.102 Total estimated model params size (MB)\n "
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+ ]
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+ },
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+ {
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+ "data" : {
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+ "application/vnd.jupyter.widget-view+json" : {
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+ "model_id" : " 5ad868206538466487ad6a345fd6a174" ,
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+ "version_major" : 2 ,
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+ "version_minor" : 0
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+ },
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+ "text/plain" : [
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+ " Sanity Checking: | | 0/? [00:00<?, ?it/s]"
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+ ]
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+ },
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+ "metadata" : {},
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+ "output_type" : " display_data"
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+ },
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+ {
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+ "text/plain" : [
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+ " Training: | | 0/? [00:00<?, ?it/s]"
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+ ]
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+ },
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+ "metadata" : {},
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+ "output_type" : " display_data"
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+ }
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+ ],
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+ "source" : [
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+ " trainer = pl.Trainer(\n " ,
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+ " devices=1, accelerator=cfg.experiment.accelerator, max_epochs=cfg.model.opt.epochs\n " ,
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+ " )\n " ,
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+ " trainer.fit(model=model, datamodule=data_module)"
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+ ]
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+ },
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+ {
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+ "cell_type" : " code" ,
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+ }
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+ ],
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+ "display_name" : " sdofm" ,
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+ "language" : " python" ,
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+ },
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+ "language_info" : {
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+ "codemirror_mode" : {
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+ "mimetype" : " text/x-python" ,
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+ "name" : " python" ,
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+ "nbconvert_exporter" : " python" ,
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},
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- "name" : " stderr" ,
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- "text" : [
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- " \n " ,
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- " | Name | Type | Params\n " ,
116
- " -------------------------------------------------------\n " ,
117
- " 0 | autoencoder | MaskedAutoencoderViT3D | 3.8 M \n " ,
118
- " -------------------------------------------------------\n " ,
119
- " 3.0 M Trainable params\n " ,
120
- " 786 K Non-trainable params\n " ,
121
- " 3.8 M Total params\n " ,
122
- " 15.102 Total estimated model params size (MB)\n "
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- ]
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- },
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- "text/plain" : [
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- " Sanity Checking: | | 0/? [00:00<?, ?it/s]"
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- },
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- "metadata" : {},
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- "output_type" : " display_data"
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- }
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- ],
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- "source" : [
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- " trainer = pl.Trainer(\n " ,
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- " devices=1, accelerator=cfg.experiment.accelerator, max_epochs=cfg.model.opt.epochs\n " ,
157
- " )\n " ,
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- " trainer.fit(model=model, datamodule=data_module)"
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- ]
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- },
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- {
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- "cell_type" : " code" ,
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- }
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- ],
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- "metadata" : {
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- }
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+ "nbformat" : 4 ,
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+ "nbformat_minor" : 2
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+ }
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