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GiovanniCanaliGiovanniCanali
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clear progress bar cell outputs
1 parent 096f3ff commit 50471de

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‎tutorials/tutorial1/tutorial.ipynb‎

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‎tutorials/tutorial10/tutorial.ipynb‎

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‎tutorials/tutorial11/tutorial.ipynb‎

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‎tutorials/tutorial13/tutorial.ipynb‎

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‎tutorials/tutorial14/tutorial.ipynb‎

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‎tutorials/tutorial15/tutorial.ipynb‎

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‎tutorials/tutorial17/tutorial.ipynb‎

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‎tutorials/tutorial18/tutorial.ipynb‎

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},
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{
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 1,
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"id": "0981f1e9",
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"metadata": {},
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"outputs": [],
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},
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{
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"cell_type": "code",
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"execution_count": 50,
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"execution_count": 2,
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"id": "014bbd86",
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"metadata": {},
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"outputs": [],
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},
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{
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"cell_type": "code",
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"execution_count": 51,
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"execution_count": 3,
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"id": "6f25d3a6",
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"metadata": {},
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"outputs": [],
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},
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{
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"cell_type": "code",
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"execution_count": 52,
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"execution_count": null,
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"id": "336e8060",
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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 (mps), used: False\n",
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"TPU available: False, using: 0 TPU cores\n",
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"HPU available: False, using: 0 HPUs\n",
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"\n",
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" | Name | Type | Params | Mode \n",
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"----------------------------------------------------\n",
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"0 | _pina_models | ModuleList | 481 | train\n",
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"1 | _loss_fn | MSELoss | 0 | train\n",
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"----------------------------------------------------\n",
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"481 Trainable params\n",
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"0 Non-trainable params\n",
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"481 Total params\n",
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"0.002 Total estimated model params size (MB)\n",
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"9 Modules in train mode\n",
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"0 Modules in eval mode\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": "d6d009cd7efb4c76ba2115f828e46dc8",
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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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"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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"name": "stderr",
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"output_type": "stream",
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"text": [
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"`Trainer.fit` stopped: `max_epochs=500` reached.\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": "c7679ddd66e748dbaef644592c18a010",
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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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"Testing: | | 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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"name": "stdout",
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"output_type": "stream",
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"text": [
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"────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n",
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" Test metric DataLoader 0\n",
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"────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n",
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" test_loss 0.006782823242247105\n",
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"────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\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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"class MyFirstSolver(SupervisedSolverInterface, SingleSolverInterface):\n",
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" def __init__(\n",
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],
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"metadata": {
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"kernelspec": {
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"display_name": "pina",
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"display_name": "deep",
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"language": "python",
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"name": "python3"
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},
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.9.21"
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"version": "3.12.11"
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}
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},
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"nbformat": 4,

‎tutorials/tutorial2/tutorial.ipynb‎

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‎tutorials/tutorial20/tutorial.ipynb‎

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"cell_type": "code",
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"execution_count": null,
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"id": "65ed2697",
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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 (mps), used: False\n",
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"TPU available: False, using: 0 TPU cores\n",
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"HPU available: False, using: 0 HPUs\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": "49b972675e8f41b3aa477c28f3cb2349",
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"version_major": 2,
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"version_minor": 0
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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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"name": "stderr",
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"output_type": "stream",
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"text": [
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"`Trainer.fit` stopped: `max_epochs=1` reached.\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": "8794705d790b45dca4bcb9e65857bbd7",
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"version_major": 2,
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"version_minor": 0
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"text/plain": [
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"Testing: | | 0/? [00:00<?, ?it/s]"
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"metadata": {},
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"output_type": "display_data"
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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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"────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n",
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" Test metric DataLoader 0\n",
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"────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n",
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" test_loss_epoch 0.0009161713533103466\n",
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"────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\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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"# Create a model, in our case a simple FeedForward Network\n",
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"model = FeedForward(input_dimensions=3, output_dimensions=1, func=AdaptiveSIREN)\n",
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],
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"metadata": {
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"kernelspec": {
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"display_name": "pina",
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"display_name": "deep",
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"language": "python",
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"name": "python3"
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},
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.9.21"
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"version": "3.12.11"
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}
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},
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"nbformat": 4,

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