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rerun_tutorial
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elephaint committed Oct 15, 2024
1 parent 67cbbe5 commit a9b78a6
Showing 1 changed file with 3 additions and 44 deletions.
47 changes: 3 additions & 44 deletions nbs/docs/tutorials/20_conformal_prediction.ipynb
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"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"c:\\Users\\ospra\\miniconda3\\envs\\neuralforecast\\lib\\site-packages\\tqdm\\auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
" from .autonotebook import tqdm as notebook_tqdm\n",
"2024-10-15 10:35:57,968\tINFO util.py:154 -- Missing packages: ['ipywidgets']. Run `pip install -U ipywidgets`, then restart the notebook server for rich notebook output.\n",
"2024-10-15 10:35:58,090\tINFO util.py:154 -- Missing packages: ['ipywidgets']. Run `pip install -U ipywidgets`, then restart the notebook server for rich notebook output.\n"
]
}
],
"outputs": [],
"source": [
"import logging\n",
"import os\n",
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"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Seed set to 1\n",
"Seed set to 1\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 99: 100%|██████████| 1/1 [00:00<00:00, 44.93it/s, v_num=508, train_loss_step=0.138, train_loss_epoch=0.138] \n",
"Predicting DataLoader 0: 100%|██████████| 1/1 [00:00<00:00, 150.75it/s]\n",
"Epoch 99: 100%|██████████| 1/1 [00:00<00:00, 48.70it/s, v_num=510, train_loss_step=2.930, train_loss_epoch=2.930] \n",
"Predicting DataLoader 0: 100%|██████████| 1/1 [00:00<00:00, 32.97it/s]\n",
"Epoch 99: 100%|██████████| 1/1 [00:00<00:00, 49.39it/s, v_num=512, train_loss_step=0.106, train_loss_epoch=0.106] \n",
"Epoch 99: 100%|██████████| 1/1 [00:00<00:00, 48.55it/s, v_num=513, train_loss_step=3.220, train_loss_epoch=3.220] \n"
]
}
],
"outputs": [],
"source": [
"horizon = 12\n",
"input_size = 24\n",
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"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Predicting DataLoader 0: 100%|██████████| 1/1 [00:00<00:00, 197.24it/s]\n",
"Predicting DataLoader 0: 100%|██████████| 1/1 [00:00<00:00, 194.88it/s]\n"
]
}
],
"outputs": [],
"source": [
"preds = nf.predict(futr_df=AirPassengersPanel_test, level=[90])"
]
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