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Updates to tutorial and run post codacy changes

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This commit is contained in:
Matteo Bertocchi
2025-03-10 17:18:48 +01:00
committed by Nicola Demo
parent 9e55746546
commit b38b0894b1
27 changed files with 952 additions and 393 deletions
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124
tutorials/tutorial4/tutorial.ipynb vendored
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@@ -45,13 +45,16 @@
"import torch \n",
"import matplotlib.pyplot as plt \n",
"import torchvision # for MNIST dataset\n",
"import warnings\n",
"\n",
"from pina.problem import AbstractProblem\n",
"from pina.solver import SupervisedSolver\n",
"from pina.trainer import Trainer\n",
"from pina import Condition, LabelTensor\n",
"from pina.model.block import ContinuousConvBlock \n",
"from pina.model import FeedForward # for building AE and MNIST classification"
"from pina.model import FeedForward # for building AE and MNIST classification\n",
"\n",
"warnings.filterwarnings('ignore')"
]
},
{
@@ -210,15 +213,7 @@
"execution_count": 3,
"id": "b78c08b8",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/matte_b/.local/lib/python3.12/site-packages/torch/functional.py: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:3595.)\n"
]
}
],
"outputs": [],
"source": [
"# filter dim\n",
"filter_dim = [0.1, 0.1]\n",
@@ -352,7 +347,105 @@
"execution_count": 7,
"id": "6d816e7a",
"metadata": {},
"outputs": [],
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Downloading http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz\n",
"Failed to download (trying next):\n",
"HTTP Error 404: Not Found\n",
"\n",
"Downloading https://ossci-datasets.s3.amazonaws.com/mnist/train-images-idx3-ubyte.gz\n",
"Downloading https://ossci-datasets.s3.amazonaws.com/mnist/train-images-idx3-ubyte.gz to ./data/MNIST/raw/train-images-idx3-ubyte.gz\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"100%|██████████| 9.91M/9.91M [00:02<00:00, 3.62MB/s]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Extracting ./data/MNIST/raw/train-images-idx3-ubyte.gz to ./data/MNIST/raw\n",
"\n",
"Downloading http://yann.lecun.com/exdb/mnist/train-labels-idx1-ubyte.gz\n",
"Failed to download (trying next):\n",
"HTTP Error 404: Not Found\n",
"\n",
"Downloading https://ossci-datasets.s3.amazonaws.com/mnist/train-labels-idx1-ubyte.gz\n",
"Downloading https://ossci-datasets.s3.amazonaws.com/mnist/train-labels-idx1-ubyte.gz to ./data/MNIST/raw/train-labels-idx1-ubyte.gz\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"100%|██████████| 28.9k/28.9k [00:00<00:00, 210kB/s]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Extracting ./data/MNIST/raw/train-labels-idx1-ubyte.gz to ./data/MNIST/raw\n",
"\n",
"Downloading http://yann.lecun.com/exdb/mnist/t10k-images-idx3-ubyte.gz\n",
"Failed to download (trying next):\n",
"HTTP Error 404: Not Found\n",
"\n",
"Downloading https://ossci-datasets.s3.amazonaws.com/mnist/t10k-images-idx3-ubyte.gz\n",
"Downloading https://ossci-datasets.s3.amazonaws.com/mnist/t10k-images-idx3-ubyte.gz to ./data/MNIST/raw/t10k-images-idx3-ubyte.gz\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"100%|██████████| 1.65M/1.65M [00:00<00:00, 1.97MB/s]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Extracting ./data/MNIST/raw/t10k-images-idx3-ubyte.gz to ./data/MNIST/raw\n",
"\n",
"Downloading http://yann.lecun.com/exdb/mnist/t10k-labels-idx1-ubyte.gz\n",
"Failed to download (trying next):\n",
"HTTP Error 404: Not Found\n",
"\n",
"Downloading https://ossci-datasets.s3.amazonaws.com/mnist/t10k-labels-idx1-ubyte.gz\n",
"Downloading https://ossci-datasets.s3.amazonaws.com/mnist/t10k-labels-idx1-ubyte.gz to ./data/MNIST/raw/t10k-labels-idx1-ubyte.gz\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"100%|██████████| 4.54k/4.54k [00:00<00:00, 2.55MB/s]"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Extracting ./data/MNIST/raw/t10k-labels-idx1-ubyte.gz to ./data/MNIST/raw\n",
"\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n"
]
}
],
"source": [
"from torch.utils.data import DataLoader, SubsetRandomSampler\n",
"\n",
@@ -793,7 +886,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 149: 100%|██████████| 1/1 [00:01<00:00, 0.77it/s, v_num=21, data_loss=0.0341, val_loss=0.0341, train_loss=0.0341]"
"Epoch 149: 100%|██████████| 1/1 [00:01<00:00, 0.59it/s, v_num=25, data_loss=0.0341, train_loss=0.0341]"
]
},
{
@@ -807,7 +900,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 149: 100%|██████████| 1/1 [00:01<00:00, 0.76it/s, v_num=21, data_loss=0.0341, val_loss=0.0341, train_loss=0.0341]\n"
"Epoch 149: 100%|██████████| 1/1 [00:01<00:00, 0.58it/s, v_num=25, data_loss=0.0341, train_loss=0.0341]\n"
]
}
],
@@ -823,7 +916,10 @@
"solver = SupervisedSolver(problem=CircleProblem(), model=net, loss=torch.nn.MSELoss(), use_lt=True) \n",
"\n",
"# train\n",
"trainer = Trainer(solver, max_epochs=150, accelerator='cpu', enable_model_summary=False) # we train on CPU and avoid model summary at beginning of training (optional)\n",
"trainer = Trainer(solver, max_epochs=150, accelerator='cpu', enable_model_summary=False, # we train on CPU and avoid model summary at beginning of training (optional)\n",
" train_size=1.0,\n",
" val_size=0.0,\n",
" test_size=0.0)\n",
"trainer.train()\n",
" "
]