Update tutorials (#463)
--------- Co-authored-by: Dario Coscia <93731561+dario-coscia@users.noreply.github.com>
This commit is contained in:
Matteo Bertocchi
committed by
FilippoOlivo
FilippoOlivo
parent
8b797d589a
commit
bd9b49530a
170
tutorials/tutorial11/tutorial.ipynb
vendored
170
tutorials/tutorial11/tutorial.ipynb
vendored
@@ -19,7 +19,7 @@
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},
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"cell_type": "code",
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"execution_count": 18,
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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@@ -33,15 +33,18 @@
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" !pip install \"pina-mathlab\"\n",
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"\n",
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"import torch\n",
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"import warnings\n",
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"\n",
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"from pina import Condition, Trainer\n",
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"from pina.solvers import PINN\n",
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"from pina.solver import PINN\n",
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"from pina.model import FeedForward\n",
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"from pina.problem import SpatialProblem\n",
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"from pina.operators import grad\n",
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"from pina.operator import grad\n",
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"from pina.domain import CartesianDomain\n",
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"from pina.equation import Equation, FixedValue\n",
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"\n",
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"warnings.filterwarnings('ignore')\n",
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"\n",
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"class SimpleODE(SpatialProblem):\n",
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"\n",
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" output_variables = ['u']\n",
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@@ -91,16 +94,15 @@
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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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"execution_count": 2,
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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: True\n",
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"GPU available: False, used: False\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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]
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@@ -134,16 +136,15 @@
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"cell_type": "code",
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"execution_count": 5,
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"execution_count": 3,
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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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"GPU available: False, used: False\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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@@ -175,16 +176,15 @@
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"execution_count": 4,
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"metadata": {},
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"outputs": [
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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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"GPU available: False, used: False\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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@@ -192,14 +192,7 @@
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Epoch 8: 100%|██████████| 1/1 [00:00<00:00, 232.78it/s, v_num=6, x0_loss=0.436, D_loss=0.129, mean_loss=0.283] "
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]
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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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"Epoch 999: 100%|██████████| 1/1 [00:00<00:00, 222.52it/s, v_num=6, x0_loss=1.48e-5, D_loss=0.000655, mean_loss=0.000335]"
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"Epoch 999: 100%|██████████| 1/1 [00:00<00:00, 91.87it/s, v_num=8, bound_cond_loss=6.07e-5, phys_cond_loss=0.000828, train_loss=0.000889] "
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]
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@@ -213,16 +206,15 @@
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Epoch 999: 100%|██████████| 1/1 [00:00<00:00, 133.46it/s, v_num=6, x0_loss=1.48e-5, D_loss=0.000655, mean_loss=0.000335]\n"
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"Epoch 999: 100%|██████████| 1/1 [00:00<00:00, 57.75it/s, v_num=8, bound_cond_loss=6.07e-5, phys_cond_loss=0.000828, train_loss=0.000889]\n"
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]
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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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"GPU available: True (mps), used: False\n",
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"GPU available: False, used: False\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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]
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},
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@@ -230,7 +222,7 @@
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Epoch 999: 100%|██████████| 1/1 [00:00<00:00, 274.80it/s, v_num=7, x0_loss=6.21e-6, D_loss=0.000221, mean_loss=0.000114]"
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"Epoch 999: 100%|██████████| 1/1 [00:00<00:00, 79.80it/s, v_num=9, bound_cond_loss=8.63e-5, phys_cond_loss=0.00215, train_loss=0.00223] "
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]
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@@ -244,16 +236,15 @@
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Epoch 999: 100%|██████████| 1/1 [00:00<00:00, 154.49it/s, v_num=7, x0_loss=6.21e-6, D_loss=0.000221, mean_loss=0.000114]\n"
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"Epoch 999: 100%|██████████| 1/1 [00:00<00:00, 54.20it/s, v_num=9, bound_cond_loss=8.63e-5, phys_cond_loss=0.00215, train_loss=0.00223]\n"
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]
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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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"GPU available: True (mps), used: False\n",
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"GPU available: False, used: False\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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]
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},
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@@ -261,7 +252,7 @@
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Epoch 999: 100%|██████████| 1/1 [00:00<00:00, 78.56it/s, v_num=8, x0_loss=1.44e-5, D_loss=0.000572, mean_loss=0.000293] "
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"Epoch 999: 100%|██████████| 1/1 [00:00<00:00, 82.98it/s, v_num=10, bound_cond_loss=2.84e-5, phys_cond_loss=0.00118, train_loss=0.00121] "
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]
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},
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@@ -275,7 +266,7 @@
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Epoch 999: 100%|██████████| 1/1 [00:00<00:00, 62.60it/s, v_num=8, x0_loss=1.44e-5, D_loss=0.000572, mean_loss=0.000293]\n"
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"Epoch 999: 100%|██████████| 1/1 [00:00<00:00, 55.87it/s, v_num=10, bound_cond_loss=2.84e-5, phys_cond_loss=0.00118, train_loss=0.00121]\n"
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]
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}
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],
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@@ -294,8 +285,11 @@
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" pinn = PINN(problem, model)\n",
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" trainer = Trainer(solver=pinn,\n",
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" accelerator='cpu',\n",
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" logger=TensorBoardLogger(save_dir='simpleode'),\n",
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" enable_model_summary=False)\n",
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" logger=TensorBoardLogger(save_dir='training_log'),\n",
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" enable_model_summary=False,\n",
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" train_size=1.0,\n",
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" val_size=0.0,\n",
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" test_size=0.0)\n",
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" trainer.train()"
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]
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},
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@@ -351,11 +345,12 @@
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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": 5,
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"metadata": {},
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"outputs": [],
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"source": [
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"from pytorch_lightning.callbacks import Callback\n",
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"from lightning.pytorch.callbacks import Callback\n",
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"from lightning.pytorch.callbacks import EarlyStopping\n",
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"import torch\n",
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"\n",
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"# define a simple callback\n",
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@@ -378,22 +373,15 @@
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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": 6,
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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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]
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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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"IPU available: False, using: 0 IPUs\n",
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"GPU available: False, 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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@@ -401,7 +389,7 @@
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Epoch 999: 100%|██████████| 1/1 [00:00<00:00, 241.30it/s, v_num=1, x0_loss=7.27e-5, D_loss=0.0016, mean_loss=0.000838] "
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"Epoch 999: 100%|██████████| 1/1 [00:00<00:00, 90.01it/s, v_num=70, bound_cond_loss=2.14e-5, phys_cond_loss=0.000448, train_loss=0.000469] "
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]
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},
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@@ -415,7 +403,7 @@
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Epoch 999: 100%|██████████| 1/1 [00:00<00:00, 149.27it/s, v_num=1, x0_loss=7.27e-5, D_loss=0.0016, mean_loss=0.000838]\n"
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"Epoch 999: 100%|██████████| 1/1 [00:00<00:00, 57.95it/s, v_num=70, bound_cond_loss=2.14e-5, phys_cond_loss=0.000448, train_loss=0.000469]\n"
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]
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}
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],
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@@ -429,8 +417,12 @@
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"pinn = PINN(problem, model)\n",
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"trainer = Trainer(solver=pinn,\n",
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" accelerator='cpu',\n",
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" logger=True,\n",
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" callbacks=[NaiveMetricTracker()], # adding a callbacks\n",
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" enable_model_summary=False,\n",
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" callbacks=[NaiveMetricTracker()]) # adding a callbacks\n",
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" train_size=1.0,\n",
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" val_size=0.0,\n",
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" test_size=0.0)\n",
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"trainer.train()"
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]
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},
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@@ -443,24 +435,24 @@
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"execution_count": 7,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[{'x0_loss': tensor(0.9141),\n",
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" 'D_loss': tensor(0.0304),\n",
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" 'mean_loss': tensor(0.4722)},\n",
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" {'x0_loss': tensor(0.8906),\n",
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" 'D_loss': tensor(0.0287),\n",
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" 'mean_loss': tensor(0.4596)},\n",
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" {'x0_loss': tensor(0.8674),\n",
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" 'D_loss': tensor(0.0274),\n",
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" 'mean_loss': tensor(0.4474)}]"
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"[{'bound_cond_loss': tensor(0.0385),\n",
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" 'phys_cond_loss': tensor(0.7217),\n",
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" 'train_loss': tensor(0.7602)},\n",
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" {'bound_cond_loss': tensor(0.0399),\n",
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" 'phys_cond_loss': tensor(0.7142),\n",
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" 'train_loss': tensor(0.7541)},\n",
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" {'bound_cond_loss': tensor(0.0413),\n",
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" 'phys_cond_loss': tensor(0.7067),\n",
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" 'train_loss': tensor(0.7480)}]"
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]
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},
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"execution_count": 9,
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"execution_count": 7,
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"metadata": {},
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"output_type": "execute_result"
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}
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@@ -475,21 +467,20 @@
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"source": [
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"PyTorch Lightning also has some built in `Callbacks` which can be used in **PINA**, [here an extensive list](https://lightning.ai/docs/pytorch/stable/extensions/callbacks.html#built-in-callbacks). \n",
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"\n",
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"We can for example try the `EarlyStopping` routine, which automatically stops the training when a specific metric converged (here the `mean_loss`). In order to let the training keep going forever set `max_epochs=-1`."
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"We can for example try the `EarlyStopping` routine, which automatically stops the training when a specific metric converged (here the `train_loss`). In order to let the training keep going forever set `max_epochs=-1`."
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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": 7,
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"execution_count": 8,
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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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"GPU available: False, used: False\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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]
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},
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@@ -497,20 +488,12 @@
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Epoch 4: 100%|██████████| 1/1 [00:00<00:00, 255.67it/s, v_num=9, x0_loss=0.876, D_loss=0.00542, mean_loss=0.441]"
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]
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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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"Epoch 6157: 100%|██████████| 1/1 [00:00<00:00, 139.84it/s, v_num=9, x0_loss=4.21e-9, D_loss=9.93e-6, mean_loss=4.97e-6] \n"
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"Epoch 4186: 100%|██████████| 1/1 [00:00<00:00, 37.06it/s, v_num=71, bound_cond_loss=1.91e-10, phys_cond_loss=3.88e-6, train_loss=3.88e-6] \n"
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]
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}
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],
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"source": [
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"# ~2 mins\n",
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"from pytorch_lightning.callbacks import EarlyStopping\n",
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"# ~5 mins\n",
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"\n",
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"model = FeedForward(\n",
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" layers=[10, 10],\n",
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@@ -523,7 +506,7 @@
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" accelerator='cpu',\n",
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" max_epochs = -1,\n",
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" enable_model_summary=False,\n",
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" callbacks=[EarlyStopping('mean_loss')]) # adding a callbacks\n",
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" callbacks=[EarlyStopping('train_loss')]) # adding a callbacks\n",
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"trainer.train()"
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]
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"cell_type": "code",
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"execution_count": 19,
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"execution_count": 9,
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"metadata": {},
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"outputs": [
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"output_type": "stream",
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"text": [
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"Seed set to 42\n",
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"GPU available: True (mps), used: False\n",
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"GPU available: False, used: False\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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]
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},
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@@ -575,7 +557,7 @@
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Epoch 1999: 100%|██████████| 1/1 [00:00<00:00, 275.87it/s, v_num=31, x0_loss=1.12e-6, D_loss=0.000127, mean_loss=6.4e-5] "
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"Epoch 1999: 100%|██████████| 1/1 [00:00<00:00, 82.19it/s, v_num=72, bound_cond_loss=1.74e-6, phys_cond_loss=0.00018, train_loss=0.000182] "
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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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"Epoch 1999: 100%|██████████| 1/1 [00:00<00:00, 163.58it/s, v_num=31, x0_loss=1.12e-6, D_loss=0.000127, mean_loss=6.4e-5]\n",
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"Total training time 17.36381 s\n"
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"Epoch 1999: 100%|██████████| 1/1 [00:00<00:00, 56.83it/s, v_num=72, bound_cond_loss=1.74e-6, phys_cond_loss=0.00018, train_loss=0.000182]\n",
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"Total training time 32.64355 s\n"
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]
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}
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],
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"source": [
|
||||
"from pytorch_lightning.callbacks import Timer\n",
|
||||
"from pytorch_lightning import seed_everything\n",
|
||||
"from lightning.pytorch.callbacks import Timer\n",
|
||||
"from lightning.pytorch import seed_everything\n",
|
||||
"\n",
|
||||
"# setting the seed for reproducibility\n",
|
||||
"seed_everything(42, workers=True)\n",
|
||||
@@ -628,7 +610,7 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 36,
|
||||
"execution_count": 10,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
@@ -636,9 +618,8 @@
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Seed set to 42\n",
|
||||
"GPU available: True (mps), used: False\n",
|
||||
"GPU available: False, used: False\n",
|
||||
"TPU available: False, using: 0 TPU cores\n",
|
||||
"IPU available: False, using: 0 IPUs\n",
|
||||
"HPU available: False, using: 0 HPUs\n"
|
||||
]
|
||||
},
|
||||
@@ -646,7 +627,7 @@
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Epoch 1598: 100%|██████████| 1/1 [00:00<00:00, 210.04it/s, v_num=47, x0_loss=4.17e-6, D_loss=0.000204, mean_loss=0.000104]"
|
||||
"Epoch 1598: 100%|██████████| 1/1 [00:00<00:00, 70.77it/s, v_num=73, bound_cond_loss=7.01e-6, phys_cond_loss=0.000283, train_loss=0.00029] "
|
||||
]
|
||||
},
|
||||
{
|
||||
@@ -660,7 +641,7 @@
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Epoch 1999: 100%|██████████| 1/1 [00:00<00:00, 259.39it/s, v_num=47, x0_loss=1.56e-7, D_loss=7.49e-5, mean_loss=3.75e-5] "
|
||||
"Epoch 1999: 100%|██████████| 1/1 [00:00<00:00, 62.57it/s, v_num=73, bound_cond_loss=2.74e-7, phys_cond_loss=9.51e-5, train_loss=9.54e-5] "
|
||||
]
|
||||
},
|
||||
{
|
||||
@@ -674,13 +655,13 @@
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Epoch 1999: 100%|██████████| 1/1 [00:00<00:00, 120.85it/s, v_num=47, x0_loss=1.56e-7, D_loss=7.49e-5, mean_loss=3.75e-5]\n",
|
||||
"Total training time 17.10627 s\n"
|
||||
"Epoch 1999: 100%|██████████| 1/1 [00:00<00:00, 40.66it/s, v_num=73, bound_cond_loss=2.74e-7, phys_cond_loss=9.51e-5, train_loss=9.54e-5]\n",
|
||||
"Total training time 39.14717 s\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"from pytorch_lightning.callbacks import StochasticWeightAveraging\n",
|
||||
"from lightning.pytorch.callbacks import StochasticWeightAveraging\n",
|
||||
"\n",
|
||||
"# setting the seed for reproducibility\n",
|
||||
"seed_everything(42, workers=True)\n",
|
||||
@@ -716,7 +697,7 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 35,
|
||||
"execution_count": 11,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
@@ -724,9 +705,8 @@
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Seed set to 42\n",
|
||||
"GPU available: True (mps), used: False\n",
|
||||
"GPU available: False, used: False\n",
|
||||
"TPU available: False, using: 0 TPU cores\n",
|
||||
"IPU available: False, using: 0 IPUs\n",
|
||||
"HPU available: False, using: 0 HPUs\n"
|
||||
]
|
||||
},
|
||||
@@ -734,7 +714,7 @@
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Epoch 1598: 100%|██████████| 1/1 [00:00<00:00, 261.80it/s, v_num=46, x0_loss=9e-8, D_loss=2.39e-5, mean_loss=1.2e-5] "
|
||||
"Epoch 1598: 100%|██████████| 1/1 [00:00<00:00, 69.88it/s, v_num=74, bound_cond_loss=5.16e-8, phys_cond_loss=3.54e-5, train_loss=3.54e-5] "
|
||||
]
|
||||
},
|
||||
{
|
||||
@@ -748,7 +728,7 @@
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Epoch 1999: 100%|██████████| 1/1 [00:00<00:00, 261.78it/s, v_num=46, x0_loss=7.08e-7, D_loss=1.77e-5, mean_loss=9.19e-6] "
|
||||
"Epoch 1999: 100%|██████████| 1/1 [00:00<00:00, 73.42it/s, v_num=74, bound_cond_loss=0.000126, phys_cond_loss=0.000315, train_loss=0.000441] "
|
||||
]
|
||||
},
|
||||
{
|
||||
@@ -762,8 +742,8 @@
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Epoch 1999: 100%|██████████| 1/1 [00:00<00:00, 148.99it/s, v_num=46, x0_loss=7.08e-7, D_loss=1.77e-5, mean_loss=9.19e-6]\n",
|
||||
"Total training time 17.01149 s\n"
|
||||
"Epoch 1999: 100%|██████████| 1/1 [00:00<00:00, 47.28it/s, v_num=74, bound_cond_loss=0.000126, phys_cond_loss=0.000315, train_loss=0.000441]\n",
|
||||
"Total training time 40.19983 s\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
|
||||
Reference in New Issue
Block a user