From e12e57911e9b125a9f0194cfece1fd21e1d09f2d Mon Sep 17 00:00:00 2001 From: cyberguli Date: Tue, 3 Mar 2026 18:46:35 +0100 Subject: [PATCH 1/2] added tutorial25 on generative models --- docs/source/_tutorial.rst | 7 +- tutorials/tutorial25/tutorial.html | 8254 +++++++++++++++++++++++++++ tutorials/tutorial25/tutorial.ipynb | 511 ++ tutorials/tutorial25/tutorial.py | 233 + 4 files changed, 9004 insertions(+), 1 deletion(-) create mode 100644 tutorials/tutorial25/tutorial.html create mode 100644 tutorials/tutorial25/tutorial.ipynb create mode 100644 tutorials/tutorial25/tutorial.py diff --git a/docs/source/_tutorial.rst b/docs/source/_tutorial.rst index 99958ffcd..7286c3180 100644 --- a/docs/source/_tutorial.rst +++ b/docs/source/_tutorial.rst @@ -43,4 +43,9 @@ Supervised Learning - `Reduced Order Model with Graph Neural Networks for Unstructured Domains `_ - `Data-driven System Identification with SINDy `_ - `Unstructured Convolutional Autoencoders with Continuous Convolution `_ -- `Reduced Order Modeling with POD-RBF and POD-NN Approaches for Fluid Dynamics `_ \ No newline at end of file +- `Reduced Order Modeling with POD-RBF and POD-NN Approaches for Fluid Dynamics `_ + +Unsupervised Learning +------------------- + +- `Generative Model Learning of Shapes `_ diff --git a/tutorials/tutorial25/tutorial.html b/tutorials/tutorial25/tutorial.html new file mode 100644 index 000000000..ed092fe94 --- /dev/null +++ b/tutorials/tutorial25/tutorial.html @@ -0,0 +1,8254 @@ + + + + + +tutorial25 + + + + + + + + + + + + +
+ + + + + + + +
+ + diff --git a/tutorials/tutorial25/tutorial.ipynb b/tutorials/tutorial25/tutorial.ipynb new file mode 100644 index 000000000..9cf5cc31e --- /dev/null +++ b/tutorials/tutorial25/tutorial.ipynb @@ -0,0 +1,511 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "degv0c0BEiRV" + }, + "source": [ + "# Tutorial: Generative Model Learning of Shapes\n", + "\n", + "## Introduction to Generative Models\n", + "\n", + "This tutorial demonstrates how learn the distribution of complex objects using generative models. The metholology is inspired from these [two](https://arxiv.org/abs/2308.03662) [papers](https://arxiv.org/abs/1810.01118).\n", + "\n", + "We have a probability distribution of a set of ellipsis, each centered in (0,0), and we want to construct a surrogate probability distribution using generative models.\n", + "\n", + "\n", + "Let's first write the code for data generation." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": true, + "id": "WlJjlj8BVcRk" + }, + "outputs": [], + "source": [ + "import torch\n", + "from pina import LabelTensor\n", + "n=600\n", + "density=100\n", + "torch.manual_seed(42)\n", + "def generate_data(n,density=1000):\n", + "\n", + " theta = 2 * torch.pi * torch.linspace(0,1,density)\n", + " x = torch.cos(theta)\n", + " y = torch.sin(theta)\n", + " data_ref=torch.concatenate((x.reshape(-1,1),y.reshape(-1,1)),axis=1)\n", + " data=torch.zeros((n,density,2))\n", + "\n", + " for i in range(n):\n", + " A=-0.4+0.8*torch.rand(2,2)\n", + " A=A/torch.linalg.norm(A)\n", + " A=A+torch.eye(2)\n", + " A=2*A/torch.linalg.norm(A)\n", + " data[i]=data_ref@A\n", + "\n", + " data=data.reshape(n,-1)\n", + " return data\n", + "\n", + "data=generate_data(n,density)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "mvh9dgVZXTL1" + }, + "source": [ + "Let's plot an ellipse just to check that everything is going smoothly." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "id": "YALibusGXYT_" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "[(-2.0, 2.0), (-2.0, 2.0)]" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "fig, ax = plt.subplots()\n", + "ellipse=data.reshape(-1,density,2)[0]\n", + "ax.scatter(ellipse[:,0],ellipse[:,1])\n", + "ax.set(xlim=(-2,2), ylim=(-2, 2))\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "qjGqlo0XSnp_" + }, + "source": [ + "Now we are ready to define our generative model, which is composed by an AutoEncoder only.\n", + "First we define the AutoEncoder. As all the ellipsis in the dataset have barycenter as the origin, we impose this information in the AutoEncoder, we adopt POD and BatchNorm for further regularization. We add a sinkhorn regularization to the loss function, so that we are able to directly sample from the latent space in order to get good representations." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "K8hd0lDSEdaH" + }, + "outputs": [], + "source": [ + "\n", + "\n", + "import torch\n", + "from torch import nn\n", + "from pina.model.block import PODBlock\n", + "\n", + "def barycenter_projector(x):\n", + " x=x.reshape(-1,density,2)\n", + " tmp=(x-torch.mean(x,axis=1).reshape(-1,1,2))\n", + " return tmp.reshape(-1,2*density)\n", + "\n", + "class LBR(torch.nn.Module):\n", + " def __init__(self,input_size,output_size,final=False,drop_prob=0.1):\n", + " super().__init__()\n", + " self.lin=nn.Linear(input_size,output_size)\n", + " self.relu=nn.ReLU()\n", + " self.bn=nn.BatchNorm1d(output_size)\n", + " self.dropout=nn.Dropout(drop_prob)\n", + "\n", + " def forward(self,input):\n", + " tmp=self.dropout(self.bn(self.relu(self.lin(input))))\n", + " return tmp\n", + "\n", + "class GenEncoder(torch.nn.Module):\n", + " def __init__(self,input_size,latent_size,hidden_size=500,num_layers=5,drop_prob=0.1):\n", + " super().__init__()\n", + " self.layers = []\n", + " self.layers.append(LBR(input_size,hidden_size,drop_prob=drop_prob))\n", + " for i in range(num_layers-2):\n", + " self.layers.append(\n", + " LBR(hidden_size,hidden_size,drop_prob=drop_prob)\n", + " )\n", + " self.layers.append(nn.Linear(hidden_size,latent_size))\n", + " self.layers.append(nn.BatchNorm1d(latent_size,affine=False,track_running_stats=False))\n", + " self.nn=nn.Sequential(*self.layers)\n", + "\n", + " def forward(self,x):\n", + " return self.nn(x)\n", + "\n", + "class GenDecoder(torch.nn.Module):\n", + " def __init__(self,latent_size,output_size,hidden_size=500,num_layers=5,drop_prob=0.1):\n", + " super().__init__()\n", + " self.layers = []\n", + " self.layers.append(LBR(latent_size,hidden_size,drop_prob=drop_prob))\n", + " for i in range(num_layers - 2):\n", + " self.layers.append(\n", + " LBR(hidden_size,hidden_size,drop_prob=drop_prob)\n", + " )\n", + "\n", + " self.layers.append(nn.Linear(hidden_size,output_size))\n", + " self.nn=nn.Sequential(*self.layers)\n", + "\n", + " def forward(self,x):\n", + " return self.nn(x)\n", + "\n", + "class GenAutoencoder(torch.nn.Module):\n", + " def __init__(self,size, pod_size, latent_size,hidden_size=500,num_layers=5,drop_prob=0.1):\n", + " super().__init__()\n", + " self.pod_size=pod_size\n", + " self.latent_size=latent_size\n", + " self.pod=PODBlock(64)\n", + " self.encoder=GenEncoder(pod_size,latent_size,hidden_size)\n", + " self.decoder=GenDecoder(latent_size,pod_size,hidden_size)\n", + "\n", + " def forward(self,x):\n", + " tmp=self.pod(x)\n", + " latent=self.encoder(tmp)\n", + " tmp=self.decoder(latent)\n", + " tmp=self.pod.expand(tmp)\n", + " tmp=barycenter_projector(tmp)\n", + " return (latent,tmp)\n", + "\n", + " def sample(self,n=1):\n", + " tmp=self.decoder(torch.randn(n,self.latent_size))\n", + " tmp=self.pod.expand(tmp)\n", + " tmp=barycenter_projector(tmp)\n", + " return tmp\n", + "\n", + "\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "dYoMVOWkqF1a" + }, + "source": [ + "We can now define the loss function, which is a combination of autoencoder loss (for learning the features) and sinkhorn (for regularizing the distribution of the latent space)." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "BfInXtmeqGdC" + }, + "outputs": [], + "source": [ + "from pina.loss import LossInterface\n", + "\n", + "eps=0.01\n", + "diff_conv=1e-02\n", + "L=100\n", + "gamma=1\n", + "def sinkhorn_loss(z):\n", + " normal_samples=torch.randn(z.shape[0],z.shape[1])\n", + " return sinkhorn_loss_single(z,normal_samples)-0.5*sinkhorn_loss_single(z,z)-0.5*sinkhorn_loss_single(normal_samples,normal_samples)\n", + "\n", + "def sinkhorn_loss_single(a,b):\n", + " diff=1e8\n", + " counter=0\n", + " C=torch.sum((a.reshape(a.shape[0],1,-1)-b.reshape(1,b.shape[0],-1))**2,axis=2)\n", + " K=torch.exp(-C/eps)\n", + " u=torch.ones_like(a)\n", + " while diff>diff_conv and counter" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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", 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", 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", 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", 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", 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", 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", 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", 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "genae.eval()\n", + "\n", + "for _ in range(10):\n", + " tmp=genae.sample().detach().numpy().reshape(-1,2)\n", + " plt.scatter(tmp[:,0],tmp[:,1])\n", + " plt.xlim(-2, 2)\n", + " plt.ylim(-2,2)\n", + " plt.show()\n", + " plt.clf()\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "YOGa2tDssDu0" + }, + "source": [ + "# Whats next?\n", + "\n", + "There are lot of directions to explore:\n", + "\n", + "* tweak the sinkhorn parameters to study how the affect convergence.\n", + "* changing the latent space dimensionality or the POD dimensionality.\n", + "* adopt measures different from sinkhorn for regularizing the latent space.\n", + "\n" + ] + } + ], + "metadata": { + "colab": { + "provenance": [] + }, + "kernelspec": { + "display_name": "pina0.3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.0" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/tutorials/tutorial25/tutorial.py b/tutorials/tutorial25/tutorial.py new file mode 100644 index 000000000..891b0c6c3 --- /dev/null +++ b/tutorials/tutorial25/tutorial.py @@ -0,0 +1,233 @@ +# %% [markdown] +# # Tutorial: Generative Model Learning of Shapes +# +# ## Introduction to Generative Models +# +# This tutorial demonstrates how learn the distribution of complex objects using generative models. The metholology is inspired from these [two](https://arxiv.org/abs/2308.03662) [papers](https://arxiv.org/abs/1810.01118). +# +# We have a probability distribution of a set of ellipsis, each centered in (0,0), and we want to construct a surrogate probability distribution using generative models. +# +# +# Let's first write the code for data generation. + +# %% +import torch +from pina import LabelTensor +n=600 +density=100 +torch.manual_seed(42) +def generate_data(n,density=1000): + + theta = 2 * torch.pi * torch.linspace(0,1,density) + x = torch.cos(theta) + y = torch.sin(theta) + data_ref=torch.concatenate((x.reshape(-1,1),y.reshape(-1,1)),axis=1) + data=torch.zeros((n,density,2)) + + for i in range(n): + A=-0.4+0.8*torch.rand(2,2) + A=A/torch.linalg.norm(A) + A=A+torch.eye(2) + A=2*A/torch.linalg.norm(A) + data[i]=data_ref@A + + data=data.reshape(n,-1) + return data + +data=generate_data(n,density) + + +# %% [markdown] +# Let's plot an ellipse just to check that everything is going smoothly. + +# %% +import matplotlib.pyplot as plt +fig, ax = plt.subplots() +ellipse=data.reshape(-1,density,2)[0] +ax.scatter(ellipse[:,0],ellipse[:,1]) +ax.set(xlim=(-2,2), ylim=(-2, 2)) + + + +# %% [markdown] +# Now we are ready to define our generative model, which is composed by an AutoEncoder only. +# First we define the AutoEncoder. As all the ellipsis in the dataset have barycenter as the origin, we impose this information in the AutoEncoder, we adopt POD and BatchNorm for further regularization. We add a sinkhorn regularization to the loss function, so that we are able to directly sample from the latent space in order to get good representations. + +# %% + + +import torch +from torch import nn +from pina.model.block import PODBlock + +def barycenter_projector(x): + x=x.reshape(-1,density,2) + tmp=(x-torch.mean(x,axis=1).reshape(-1,1,2)) + return tmp.reshape(-1,2*density) + +class LBR(torch.nn.Module): + def __init__(self,input_size,output_size,final=False,drop_prob=0.1): + super().__init__() + self.lin=nn.Linear(input_size,output_size) + self.relu=nn.ReLU() + self.bn=nn.BatchNorm1d(output_size) + self.dropout=nn.Dropout(drop_prob) + + def forward(self,input): + tmp=self.dropout(self.bn(self.relu(self.lin(input)))) + return tmp + +class GenEncoder(torch.nn.Module): + def __init__(self,input_size,latent_size,hidden_size=500,num_layers=5,drop_prob=0.1): + super().__init__() + self.layers = [] + self.layers.append(LBR(input_size,hidden_size,drop_prob=drop_prob)) + for i in range(num_layers-2): + self.layers.append( + LBR(hidden_size,hidden_size,drop_prob=drop_prob) + ) + self.layers.append(nn.Linear(hidden_size,latent_size)) + self.layers.append(nn.BatchNorm1d(latent_size,affine=False,track_running_stats=False)) + self.nn=nn.Sequential(*self.layers) + + def forward(self,x): + return self.nn(x) + +class GenDecoder(torch.nn.Module): + def __init__(self,latent_size,output_size,hidden_size=500,num_layers=5,drop_prob=0.1): + super().__init__() + self.layers = [] + self.layers.append(LBR(latent_size,hidden_size,drop_prob=drop_prob)) + for i in range(num_layers - 2): + self.layers.append( + LBR(hidden_size,hidden_size,drop_prob=drop_prob) + ) + + self.layers.append(nn.Linear(hidden_size,output_size)) + self.nn=nn.Sequential(*self.layers) + + def forward(self,x): + return self.nn(x) + +class GenAutoencoder(torch.nn.Module): + def __init__(self,size, pod_size, latent_size,hidden_size=500,num_layers=5,drop_prob=0.1): + super().__init__() + self.pod_size=pod_size + self.latent_size=latent_size + self.pod=PODBlock(64) + self.encoder=GenEncoder(pod_size,latent_size,hidden_size) + self.decoder=GenDecoder(latent_size,pod_size,hidden_size) + + def forward(self,x): + tmp=self.pod(x) + latent=self.encoder(tmp) + tmp=self.decoder(latent) + tmp=self.pod.expand(tmp) + tmp=barycenter_projector(tmp) + return (latent,tmp) + + def sample(self,n=1): + tmp=self.decoder(torch.randn(n,self.latent_size)) + tmp=self.pod.expand(tmp) + tmp=barycenter_projector(tmp) + return tmp + + + + + +# %% [markdown] +# We can now define the loss function, which is a combination of autoencoder loss (for learning the features) and sinkhorn (for regularizing the distribution of the latent space). + +# %% +from pina.loss import LossInterface + +eps=0.01 +diff_conv=1e-02 +L=100 +gamma=1 +def sinkhorn_loss(z): + normal_samples=torch.randn(z.shape[0],z.shape[1]) + return sinkhorn_loss_single(z,normal_samples)-0.5*sinkhorn_loss_single(z,z)-0.5*sinkhorn_loss_single(normal_samples,normal_samples) + +def sinkhorn_loss_single(a,b): + diff=1e8 + counter=0 + C=torch.sum((a.reshape(a.shape[0],1,-1)-b.reshape(1,b.shape[0],-1))**2,axis=2) + K=torch.exp(-C/eps) + u=torch.ones_like(a) + while diff>diff_conv and counter Date: Fri, 6 Mar 2026 06:58:09 +0100 Subject: [PATCH 2/2] refactoring and reformatting using black --- tutorials/tutorial25/tutorial.ipynb | 177 +++++++++--------- tutorials/tutorial25/tutorial.py | 274 ++++++++++++++++------------ 2 files changed, 250 insertions(+), 201 deletions(-) diff --git a/tutorials/tutorial25/tutorial.ipynb b/tutorials/tutorial25/tutorial.ipynb index 9cf5cc31e..04916cb39 100644 --- a/tutorials/tutorial25/tutorial.ipynb +++ b/tutorials/tutorial25/tutorial.ipynb @@ -28,29 +28,32 @@ "outputs": [], "source": [ "import torch\n", - "from pina import LabelTensor\n", - "n=600\n", - "density=100\n", + "\n", + "n = 600\n", + "density = 100\n", "torch.manual_seed(42)\n", - "def generate_data(n,density=1000):\n", "\n", - " theta = 2 * torch.pi * torch.linspace(0,1,density)\n", - " x = torch.cos(theta)\n", - " y = torch.sin(theta)\n", - " data_ref=torch.concatenate((x.reshape(-1,1),y.reshape(-1,1)),axis=1)\n", - " data=torch.zeros((n,density,2))\n", "\n", - " for i in range(n):\n", - " A=-0.4+0.8*torch.rand(2,2)\n", - " A=A/torch.linalg.norm(A)\n", - " A=A+torch.eye(2)\n", - " A=2*A/torch.linalg.norm(A)\n", - " data[i]=data_ref@A\n", + "def generate_data(n, density=1000):\n", + "\n", + " theta = 2 * torch.pi * torch.linspace(0, 1, density)\n", + " x = torch.cos(theta)\n", + " y = torch.sin(theta)\n", + " data_ref = torch.concatenate((x.reshape(-1, 1), y.reshape(-1, 1)), axis=1)\n", + " data = torch.zeros((n, density, 2))\n", + "\n", + " for i in range(n):\n", + " A = -0.4 + 0.8 * torch.rand(2, 2)\n", + " A = A / torch.linalg.norm(A)\n", + " A = A + torch.eye(2)\n", + " A = 2 * A / torch.linalg.norm(A)\n", + " data[i] = data_ref @ A\n", "\n", - " data=data.reshape(n,-1)\n", - " return data\n", + " data = data.reshape(n, -1)\n", + " return data\n", "\n", - "data=generate_data(n,density)\n" + "\n", + "data = generate_data(n, density)\n" ] }, { @@ -72,18 +75,7 @@ { "data": { "text/plain": [ - "[(-2.0, 2.0), (-2.0, 2.0)]" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
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" ] }, "metadata": {}, @@ -92,11 +84,12 @@ ], "source": [ "import matplotlib.pyplot as plt\n", + "\n", "fig, ax = plt.subplots()\n", - "ellipse=data.reshape(-1,density,2)[0]\n", - "ax.scatter(ellipse[:,0],ellipse[:,1])\n", - "ax.set(xlim=(-2,2), ylim=(-2, 2))\n", - "\n" + "ellipse = data.reshape(-1, density, 2)[0]\n", + "ax.scatter(ellipse[:, 0], ellipse[:, 1])\n", + "ax.set(xlim=(-2, 2), ylim=(-2, 2))\n", + "plt.clf()\n" ] }, { @@ -111,7 +104,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": { "id": "K8hd0lDSEdaH" }, @@ -210,7 +203,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "metadata": { "id": "BfInXtmeqGdC" }, @@ -218,35 +211,50 @@ "source": [ "from pina.loss import LossInterface\n", "\n", - "eps=0.01\n", - "diff_conv=1e-02\n", - "L=100\n", - "gamma=1\n", - "def sinkhorn_loss(z):\n", - " normal_samples=torch.randn(z.shape[0],z.shape[1])\n", - " return sinkhorn_loss_single(z,normal_samples)-0.5*sinkhorn_loss_single(z,z)-0.5*sinkhorn_loss_single(normal_samples,normal_samples)\n", - "\n", - "def sinkhorn_loss_single(a,b):\n", - " diff=1e8\n", - " counter=0\n", - " C=torch.sum((a.reshape(a.shape[0],1,-1)-b.reshape(1,b.shape[0],-1))**2,axis=2)\n", - " K=torch.exp(-C/eps)\n", - " u=torch.ones_like(a)\n", - " while diff>diff_conv and counter self.diff_conv and counter < self.L:\n", + " u_old = u\n", + " v = 1 / (C.T @ u)\n", + " u = 1 / (C @ v)\n", + " diff = torch.max(torch.abs(u - u_old))\n", + " counter = counter + 1\n", + " R = u @ v.T\n", + " return 1 / (a.shape[0]) * torch.sum(R * C)\n", + "\n", + " def sinkhorn_loss(self, a, b):\n", + " return (\n", + " self.sinkhorn_loss_single(a, b)\n", + " - 0.5 * self.sinkhorn_loss_single(a, a)\n", + " - 0.5 * self.sinkhorn_loss_single(b, b)\n", + " )\n", + "\n", + " def forward(self, rec_, output_):\n", + " z, x_hat = rec_\n", + " normal_samples = torch.randn(z.shape[0], z.shape[1])\n", + " return torch.linalg.norm(\n", + " x_hat - output_\n", + " ) + self.gamma * self.sinkhorn_loss(z, normal_samples)\n", + "\n", + "\n", + "loss = Loss(eps=0.01, L=10000, gamma=1, diff_conv=1e-02)" ] }, { @@ -260,7 +268,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": { "id": "OGSb4xD_VYm-" }, @@ -276,13 +284,14 @@ "/home/cyberguli/anaconda3/envs/pina0.3/lib/python3.10/site-packages/pina/_src/core/trainer.py: UserWarning: Compilation is disabled for Python 3.14+ and for Windows.\n", "💡 Tip: For seamless cloud uploads and versioning, try installing [litmodels](https://pypi.org/project/litmodels/) to enable LitModelCheckpoint, which syncs automatically with the Lightning model registry.\n", "/home/cyberguli/anaconda3/envs/pina0.3/lib/python3.10/site-packages/lightning/pytorch/trainer/configuration_validator.py: PossibleUserWarning: You defined a `validation_step` but have no `val_dataloader`. Skipping val loop.\n", + "/home/cyberguli/anaconda3/envs/pina0.3/lib/python3.10/site-packages/lightning/pytorch/callbacks/model_checkpoint.py: UserWarning: Checkpoint directory /home/cyberguli/PINA/tutorials/tutorial25/checkpoints exists and is not empty.\n", "/home/cyberguli/anaconda3/envs/pina0.3/lib/python3.10/site-packages/lightning/pytorch/utilities/_pytree.py: FutureWarning: `isinstance(treespec, LeafSpec)` is deprecated, use `isinstance(treespec, TreeSpec) and treespec.is_leaf()` instead.\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "031e9af2cf924f6baf710c9bc5e730dd", + "model_id": "989d042ae4454290822e97252ceb48c8", "version_major": 2, "version_minor": 0 }, @@ -306,8 +315,8 @@ "from pina.problem.zoo import SupervisedProblem\n", "from pina import Trainer\n", "\n", - "problem=SupervisedProblem(data,data)\n", - "genae = GenAutoencoder(2*density,64,5)\n", + "problem = SupervisedProblem(data, data)\n", + "genae = GenAutoencoder(2 * density, 64, 5)\n", "genae.pod.fit(data)\n", "solver = SupervisedSolver(problem, genae, loss=loss, use_lt=False)\n", "\n", @@ -319,12 +328,10 @@ " batch_size=100,\n", " accelerator=\"cpu\",\n", " enable_model_summary=False,\n", - " logger=False\n", - "\n", + " logger=False,\n", ")\n", "\n", - "trainer.train()\n", - "\n" + "trainer.train()" ] }, { @@ -345,7 +352,7 @@ "outputs": [ { "data": { - "image/png": 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+ "image/png": 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", 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", 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", 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", 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", 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", 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", 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", 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", 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", 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7mjhxouf9hQsXSpKmT5+uNWvWqKqqyhN6JCknJ0evvfaaFixYoN/97nf63ve+p6effprWcgAhCdQ2TicV2oOAnPhshmEEKa9KLLW1tcrIyJDL5VJ6enqslwMgSkJpG3d3XUnyCjvuihuKjNFa47fNurS4RMfrGn1+3B2Qd9xzJbVbHWTW63fCd10BQKht43RSIRyb9lVp/K/fCBhyJLqt4l1cFSMDQLiCtY3b1NI2fvUwhzql2OikQkjc4TnQJQ9Hqx1DxCeCDoCE1p62cTqpEEgoLeU9u3XW9rsmKvUsLozEO75DABIaXTGItFBayo/XndbuT09EaUXoCIIOgIRGVwwijfBsLVy6AhDXgt1pnLZxRBrh2VoIOgDiVigt4+4bcM5Zu0c2+W4bpysGoWpqNtTcbKh7l86q+ea0z2MIz4mFS1cA4lKoLeMSbeOIjE37qnT5iq269U87A4YcifCcSNjRARB3wm0Zl7gBJzomlHZyiZbyRETQARB32tMyLtE2jvYJpZ28e5fOWnnrKF06sBfhOcFw6QpA3KHrBdEUSjt5zTenlWKzEXISEEEHQNyh6wXRRLC2Ni5dAYgJ7jSOeEGwtjaCDoCoC9Y2Tss4ooV2cuvj0hWAqOJO44gXtJMnB3Z0AEQNdxpHvKCdPHkQdABEDXcaRzygnTy5cOkKQNTQ3YJ4QDt5ciHoAIgaulsQDwjcyYWgAyBq3G3j/v5Gtqml+4ruFpiJwJ1cCDoAIqap2VDpoWN6qeyoSg8dU1OzdxWEu21cUpuwQ3cLooXAnVwoRgYQEcFm47i528ZbH0t3C8x25pDKm3/QX49u+T/mNCUBm2EYwbrrEkptba0yMjLkcrmUnp4e6+UAScFfq677ZcLX3JtAk5GBSPMVxLt37SxJqjn13QwdX+Ec0WHW6zc7OgA6JNzZOG60jSNa/AVx16nTMiQtyL9A5/XuRuC2KGp0AHRIOLNxgGgLJYg//+4R/b+L+ipvEDNzrIigA6BDaNVFPCOIg6ADoENo1UU8I4iDGh0AQQUqHHa36jpd9T4vD3DnZ8QSQRwEHQABBWsbd8/GmbN2D626iDsEcXDpCoBf7m6V1jUOTle95qzdo037qiR9NxvHkeH9V7EjI81nazlgpjMHV+6qOK77JzGkMpkxRweAT03Nhi5fsdVvIaf7L+Ed91zpeZFgNg5izd8O5A9HZuvl/60KOtASscMcHQBRFU63inseDrNxEEv+5uU4XfV68s0KrbzlYvXoZieIJxmCDgCf6FZBIgllXs7y1w547UAiOVCjA8AnulWQSJiXA38IOgB84g7PSCTsQMIfgg6QpM7sTCk9dExNzd6b/u62cYluFcQ/diDhT1SCzsqVK3XeeecpLS1NY8eO1a5du/weu2bNGtlsNq+3tDR+MIFI2rSvSpev2KqpT72jO58v09Sn3tHlK7Z62sXdaBtHomAHEv6YXoz8wgsvaOHChVq1apXGjh2rRx99VAUFBSovL1efPn18Pic9PV3l5eWe9202/mIEIiVQZ8qctXvaBJjC4dm6epiDtnHEndbjDO6fNExz1zG4Et5MDzq//e1vNWvWLM2YMUOStGrVKr322mtavXq1Fi9e7PM5NptNDocjpM/f0NCghoYGz/u1tbUdXzRgUaF0pix75UNdPczh9YJA2zjijb95ObOvyGkzL8fBvJykZmrQaWxs1O7du7VkyRLPYykpKcrPz1dpaanf5508eVIDBgxQc3OzRo0apf/8z//UhRde6PPY4uJiLVu2LOJrB6yoPbNxgHjDvByEw9Qana+++kpNTU3KysryejwrK0tOp9PncwYPHqzVq1frpZde0tq1a9Xc3Kxx48bps88+83n8kiVL5HK5PG9HjhyJ+HkAVkFnChJdsF1JqWVezpicnpqce67yBvUi5CS5uBsYmJeXp7y8PM/748aN09ChQ/XEE09o+fLlbY632+2y2+3RXCKQsOhMQaJjVxLhMnVHp3fv3urUqZOqq6u9Hq+urg65Bqdz5866+OKLdfDgQTOWCCQVOlOQ6NiVRLhMDTqpqakaPXq0SkpKPI81NzerpKTEa9cmkKamJn3wwQfKzqaIDOgoZuMg0bEriXCZPkdn4cKFeuqpp/Tss8/qwIEDmjNnjurq6jxdWNOmTfMqVn7wwQf1j3/8Q5988on27Nmj2267TZ9++ql+8pOfmL1UwBKCDQJkNg4SGbuSCJfpNTo33XSTvvzySz3wwANyOp3Kzc3Vpk2bPAXKlZWVSkn5Lm+dOHFCs2bNktPpVI8ePTR69Gi9/fbbGjZsmNlLBRKev5bb1q21zMZBomg9K2dMTk8tvX6Y5qxlXg5CYzMMw1fxesKqra1VRkaGXC6X0tPTY70cIGr8tdy6/7lntwaJJlBwlxRSqEfiMOv1m6ADWEBTs6HLV2z1241iU8ulqR33XMlfukgIoQR3diWtxazX77hrLwcQPlpuYSXhTPDm5xnBcPdywAJouYWVhBPcgWAIOoAF0HILKyG4I5IIOoAF0HILKyG4I5IIOkCCCDQfh0GAsBKCOyKJYmQgAYQyH8c9CLD1cQ5abpFg3MGdWTmIBNrLgTgX7nwcXwPWeEFAPPP3MxvqAExYA+3lQBIKp83WHWY6pdhouUXCCBZmmJWDjqJGB4hjtNnCyty7la1/xp2ues1Zu0eb9lV5gvvk3HOVN6gXIQdhI+gAcYw2W1hVsN1KqWW3svVNaYFwEXSAOEabLayK3UpEC0EHiGO02cKq2K1EtBB0gDjgb0YO83FgVexWIlrougJiLFjXCfNxYEXu3Uqnq95nnY5NLT/j7Faio5ijA8RQODNymI+DRObr53fzh07NWbtHku+hgK1nRMHazHr9JugAMdLUbOjyFVv9FmS6/6Ldcc+VBBoktEC7lpIYCghJDAwELCecrhMGACJR+du1dM/Kefy2Udpxz5XsVsI0BB0gRug6gdWFM9mbMA+z0HUFxAhdJ7A6ZuUgHhB0gBhhRg6sjl1LxAOCDhAjzMiB1bFriXhA0AFM5G8QoJt7Ro4jw/sfekdGGq21SHjsWiIeUIwMmCTYIEC3wuHZunqYg64TWI5713LO2j2yyfesHHYtYTbm6AAmCGcQIGAFgQZahhr6kdyYowMkiHBaavlLFlYQym1M2LVErFCjA0QYLbVIJu7dy9Y/8+6BgJv2VUlquYyVN6iXJueeq7xBvQg5iBqCDhBhtNQiWQTbvZRadi9bF+ED0UTQASKMllokC3YvkQgIOkCE0VKLZMHuJRIBQQeIMAYBIlmwe4lEQNAB2inQMEAGASIZsHuJREB7OdAOocwFoaUWVtH4bbP+UnpYnx4/pQE9u+rHeecp9awUBgIiITAwEAgTwwCRTIpf/1BP/U+FzmycSrFJs/4lR0uua7lEy0BARAIDA4E4wDBAJJPi1z/UE29WtHm82ZDn8SXXDWP3EnEtKjU6K1eu1Hnnnae0tDSNHTtWu3btCnj8+vXrNWTIEKWlpWnEiBF6/fXXo7FMICjaaZEsGr9t1lP/0zbknOmp/6lQ47fNkhgIiPhletB54YUXtHDhQi1dulR79uzRyJEjVVBQoC+++MLn8W+//bamTp2qmTNnau/evSoqKlJRUZH27dtn9lKBoGinRbL4S+lhBZvz12y0HAfEM9ODzm9/+1vNmjVLM2bM0LBhw7Rq1Sp17dpVq1ev9nn87373OxUWFuquu+7S0KFDtXz5co0aNUp/+MMffB7f0NCg2tparzfALLTTIll8evxURI8DYsXUoNPY2Kjdu3crPz//uy+YkqL8/HyVlpb6fE5paanX8ZJUUFDg9/ji4mJlZGR43vr16xe5EwBaoZ0WyWJAz64RPQ6IFVODzldffaWmpiZlZWV5PZ6VlSWn0+nzOU6nM6zjlyxZIpfL5Xk7cuRIZBaPpOZvRg7DAJEsfpx3noL9GKfYWo4D4lnCd13Z7XbZ7fZYLwMWEqxV1j0MsPUxDtppYSGpZ6Vo1r/k+Oy6cpv1LzlKPYu5s4hvpgad3r17q1OnTqqurvZ6vLq6Wg6Hw+dzHA5HWMcDkeRvRo7TVa85a/d4ZuTQTguraGo2/P4cu+fkBJujA8QzU4NOamqqRo8erZKSEhUVFUmSmpubVVJSonnz5vl8Tl5enkpKSjR//nzPY5s3b1ZeXp6ZSwXCnpHjbqcFElUog/6WXDdMi64Z4nMyMpAITL90tXDhQk2fPl2XXHKJxowZo0cffVR1dXWaMWOGJGnatGk699xzVVxcLEm68847NX78eP3mN7/RpEmT9Pzzz+u9997Tk08+afZSkeTCmZFDwEGiC3X3Umq5jDXzXwZGf5FABJgedG666SZ9+eWXeuCBB+R0OpWbm6tNmzZ5Co4rKyuVkvLdXwbjxo3TunXrdN999+nee+/VBRdcoI0bN2r48OFmLxVJjhk5SBZM+EYy4V5XwD+VHjqmqU+9E/S452Zdyo4OEho/64hHZr1+c5EV+Cdm5CBZsHuJZELQAf6JGTlIFkz4RjIh6CAp+RsI6J6R48jw/gfekZHmVZwJJDJ2L5FMEn5gIBCuUAYCMiMHVuBvRo5793LO2j2ySV5FyexewmooRkZS8ddS6/7nnF0bWEUoM3JCOQaIFrNevwk6SBpNzYYuX7HV76wcm1ouUe2450r+kkVCCyfQB5qMDESTWa/fXLpC0mAgIJIBE74BbxQjI2nQUotkEE6gB5IBQQdJg5ZaJAMCPeCNoIOkQUstkgGBHvBG0IEl+ZqTw0BAJAMCPeCNYmRYTrCW2cdvG9Xm4w5aamERzMgBvNFeDksJta2WllokslB+fpmRg0TDHJ0QEXSSF3NykAzCCTAEeiQS7l4OBEFbLazOvWPZ+ufc6arXnLV7tGlfldfj7hk5k3PPVd6gXoQcJCWCDiyDtlpYWbBBgFLLIED3DWoBtCDowDJoq4WVsWMJtA9BB5ZBWy2sjB1LoH0IOrAM5uTAytixBNqHoIOE5WsooHtOjiPD+x97R0aa1x2bgUTDjiXQPgwMREIK1mJ79TAHbbVISP5awhkECLQPc3SQcEIdCggkmlBm5DAIEFbFwMAQEXSsjaGAsKpwAjyDAGFFZr1+c+kKCSWcFtu8Qb2itzCgA4LNyLGpZUbO1cMcnstY/HwDoaEYGQmFFltYETNyAPMQdJBQaLGFFRHgAfMQdJBQaLGFFRHgAfMQdBDXWs/KkcRQQFgOAR4wD8XIiFuB2mgfv21Um485aLFFgmJGDmAe2ssRl0JptWUoIBJJKC3hzMhBMmOOTogIOomPWTmwmnACDDNykKzMev2mRgdxh1ZbWIl7d7L1z7TTVa85a/do074qr8fdM3Im556rvEG9CDlABxF0EHdotYVVBBsEKLUMAmxqttTGOhBXCDqIO7TawirYnQRij6CDuEOrLayC3Ukg9kwNOsePH9ett96q9PR0de/eXTNnztTJkycDPmfChAmy2Wxeb3fccYeZy0QcOHNezq6K47p/0lBJzMpBYmN3Eog9U+fo3HrrraqqqtLmzZt1+vRpzZgxQ7Nnz9a6desCPm/WrFl68MEHPe937drVzGUixvx1pMy+Ikcv/28Vs3KQsNy7k05Xvc86HXcHIbuTgHlMCzoHDhzQpk2b9O677+qSSy6RJD322GO67rrr9PDDD6tv375+n9u1a1c5HA6zloY44m9ejtNVryffrNDKW0apR7dUWm0Rl4K1gjMIEIg90+borF69WosWLdKJEyc8j3377bdKS0vT+vXr9aMf/cjn8yZMmKD9+/fLMAw5HA5df/31uv/++/3u6jQ0NKihocHzfm1trfr168ccnQTAvBwksnBm4zAIEAjOrDk6pu3oOJ1O9enTx/uLnXWWevbsKafT6fd5t9xyiwYMGKC+ffvq/fff1z333KPy8nK9+OKLPo8vLi7WsmXLIrp2REc4HSl5g3pFb2FAEIF2Iues3aPHbxvlFWAKh2czyRuIkbCDzuLFi7VixYqAxxw4cKDdC5o9e7bnv0eMGKHs7GxdddVVOnTokAYNGtTm+CVLlmjhwoWe9907Ooh/dKQgEQWbjWNTy2ycq4c52lzGIrAD0Rd20Fm0aJFuv/32gMcMHDhQDodDX3zxhdfj3377rY4fPx5W/c3YsWMlSQcPHvQZdOx2u+x2e8ifD/GDjhQkInYigcQSdtDJzMxUZmZm0OPy8vJUU1Oj3bt3a/To0ZKkrVu3qrm52RNeQlFWViZJys7mOrbV0JGCRMROJJBYTJujM3ToUBUWFmrWrFnatWuX3nrrLc2bN08333yzp+Pq6NGjGjJkiHbt2iVJOnTokJYvX67du3fr8OHDevnllzVt2jRdccUVuuiii8xaKqKIeTlIdOxEAonF1Dk6f/3rXzVv3jxdddVVSklJ0ZQpU/T73//e8/HTp0+rvLxcp06dkiSlpqZqy5YtevTRR1VXV6d+/fppypQpuu+++8xcJqKEeTmwAnYigcRiWnt5rJjVnoaO8del4t6rYV4O4kmw+Tjun2fJ92yc1l1XAIIz6/WboAPTMS8HiSTUmTfMxgEiK+Hm6ABudKkgUYQzH4fZOEBiIOjAdHSpIBG0Zz4Os3GA+Gfq3csBiS4VJIZwdh4BJA6CDkzn7lLxt6FvU0ttA10qiCV2HgFrIujANO6ZOa++/7lu/kE/z/b/mZiXg3jBziNgTdTowBS+OlK6d+0sSao5ddrzGPNyEC3BWsaZjwNYE0EHEeevc8X1z4CzIP/7Oq93V7pUEDWhtIJ3SrFp6fXDNGftHtnkez4OO49A4uHSFSIqWOeKJD3/bqX+30V9lTeoFy8aMJ07eLcuNHa3jG/aV+V5rHB4th6/bZQcGd6XpxwZaQwBBBIUOzqIKGbmIJ60p2Wc+TiAtRB0EFF0riCetDd4Mx8HsA4uXSGi6FxBPCF4AyDoICLcreTO2nr17NbZ73HMzEE0EbwBcOkKHearo8UXOlcQbbSMA2BHBx3ir6PFFzpXYAb3buJLZUdVeuiYmpq/izTulnGJYZVAsmJHB+0WqKNFankh6dktVfdNGipHRhc6VxBxoczHcbeMtz6OYZVAciDooN1C6Wg5VtcoR0YXOlgQcf4GU7rn45y5e0jLOJC8CDpoNzpaECvtmY9DyziQnKjRQbvR0YJYCWc+DoDkRtBBuzQ1G2o2DHXvQis5oo/dRACh4tIVwhZKOzkdLTATu4kAQkXQQVj8FYC2RkcLOqKp2QhYOMx8HAChIuggZMHaySWpe9fOWjl1lC7lzuRop1Baxt3zceas3SOb5PUzyW4igDNRo4OQBSsAlaSaU6eVkmLjBQbt4m8ApbtlfNO+Ks9j7vk4jgzvy1MMpgRwJnZ0EDIKQGGm9rSMMx8HQDAEHYSMAlCYKZyW8TPn4TAfB0AgXLpCyEYP6MGdyWEadgwBmIGgg5Bs2lel8b9+Q8frTvv8OAWg6Ch2DAGYgUtXCCqUlnLayRGKQG3jtIwDMANBBwGF0lLeq1uqtt81UalnsUEI/4K1jdMyDsAMvDIhoFBayo/VNWr3pyeitCIkolDbxmkZBxBp7OggIApE0VHhto3TMg4gkgg6CIgCUXRUe9rGaRkHEClcukJAtJSjo9gVBBBL7OjAL3fxKC3lCCTYDTjZFQQQS6bt6Pzyl7/UuHHj1LVrV3Xv3j2k5xiGoQceeEDZ2dnq0qWL8vPz9fHHH5u1RATgr3j0TBSIYtO+Kl2+YqumPvWO7ny+TFOfekeXr9jqdU8qd9u4vyjMriAAM5kWdBobG3XjjTdqzpw5IT/noYce0u9//3utWrVKO3fuVLdu3VRQUKD6era0oymclnJCTvIKtZPK3TYuqU3YYVcQgNlMCzrLli3TggULNGLEiJCONwxDjz76qO677z5NnjxZF110kf785z/r888/18aNG81aJnygpRzBBOukklo6qZqaW96jbRxArMRNjU5FRYWcTqfy8/M9j2VkZGjs2LEqLS3VzTff7PN5DQ0Namho8LxfW1tr+lqtjuJRBNOeTiraxgHEQtwEHafTKUnKysryejwrK8vzMV+Ki4u1bNkyU9eWbCgeRTDtDcO0jQOItrAuXS1evFg2my3g20cffWTWWn1asmSJXC6X5+3IkSNR/fpWdKKuUYH+yKZ4NDk0NRsqPXRML5UdVemhY57LUBJhGEDiCGtHZ9GiRbr99tsDHjNw4MB2LcThcEiSqqurlZ393fX66upq5ebm+n2e3W6X3W5v19dEW5v2VWnuusA38JQoHrW6YPel4gacABJFWEEnMzNTmZmZpiwkJydHDodDJSUlnmBTW1urnTt3htW5hfYLpdsqxSb9YerFFI9amL+71bu7qdzFw9yAE0AiMK3rqrKyUmVlZaqsrFRTU5PKyspUVlamkydPeo4ZMmSINmzYIEmy2WyaP3++fvGLX+jll1/WBx98oGnTpqlv374qKioya5k4QyjdVs2G1KMbO2hWFU43FZ1UABKBacXIDzzwgJ599lnP+xdffLEk6Y033tCECRMkSeXl5XK5XJ5j7r77btXV1Wn27NmqqanR5Zdfrk2bNiktjev80UC3FcLtpqKTCkC8My3orFmzRmvWrAl4jGF4/91os9n04IMP6sEHHzRrWQiAAlO0J+zSSQUgnsVNezliz91t1eynSIcC08THfakAJBuCDiTRbZUMgnVSSaKbCoDlmFaMjMQRarfVylvotkpU3JcKQLIi6IBuK4vjvlQAkhmXrkC3lcVxXyoAyYygAwpQLSBQkTH3pQKQzAg60Im6xqDHcG+r+BWsyJggCyCZUaOT5JqaDS1/7cOgx90/aSiXLeJQKEXG7k4qf989btIKwMoIOkkulEJkiULkeBRqkbEkOqkAJC2CTpKjEDlxhVNkTCcVgGRFjU6So34jvkWyyJhOKgDJiKCT5Mbk9FT3rp1Vc+q032O6d+1M/UYMmFFkTCcVgGTDpSsExd/70UeRMQBEBkEnye2qOB5wN0eSTpw6rV0Vx6O0IlBkDACRQ9BJchQjx05Ts6HSQ8f0UtlRlR465rkFA0XGABA51OgkOYqRYyNQ/U3Dt80hfQ6KjAEgOIJOknPXeQSbpRPK9GSExl1/0/rSlLv+Zn7+BSF9HoqMASA4Ll0luU4pNt0/aWjQ45a/9t3drdF+odTfPLerUo50iowBIBIIOghp6rG7JgSh6Uj9jbO2QVPH9JdEkTEAdBSXrkBBcoRFov7mvN5d9fhto9p8HscZc3QAAMERdBByofHhr06ZvJLEF8n6m7xBvSgyBoAO4tIVNCanpxzpwS9fPbfrU+p0AjCj/sZdZDw591zlDepFyAGAMBF0oE4pNk9NSCDO2gb9YevBKKwovlF/AwCJg0tXkCSd17tbSMc9suX/NNhxdtLWiFB/AwCJhaADSeENBLx3wwe6ckiWUs9Krg1B6m8AIPEQdCAp9MGBknS87rQuLS7Rf/5ouOV2H5qaDZ/hI1j9jU3f1d9U19b7PM6mll2b1vU3AADzEHQgqeVFd+n1w3TH2j0hHX+8rlF3rN2jBfkXaN6VF1hiJyLQZamMLqkh1d8syP++Ht3yf7JJXmGH+hsAiI3kuvaAgAqHZ2tBiJdf3B7Z8rEu+9VWbdpXZdKqIstfIbH7slTrMOO+LLXlQ2dIn99df8NNNgEgPtgMw7BUv3Btba0yMjLkcrmUnp4e6+UknKZmQ5f9aqucteEPB5x52XnKH+aI21oTfzs2908aquWvHfC7Y2OT1KNbZx2vOx30azw361LlDerl9xIYAMA3s16/CTpow1/RbaiyY9g95C9g+Dun1peYAunZLVUn6hoD1t/suOdKAg0AtINZr9/U6KCNwuHZevy2Ubp3wwch7WK0VuWq1x1r95i2wxMozATasQk0yC8URbl99cxbh6m/AYAEwo4O/Gr8tlmXFpfoeF1jhz6PO2z06Gb32c3kr8spnDDzw5HZevLNig7t2ATz3KxL5fqm0W/BMvU3ANB+XLoKEUEnsjp6Gcsfdzh5+X+rfIYWf4/7CjNma31ZivobAIg8gk6ICDqRt2lflX7+8n45axtivRTT+bssRccUAJjLrNdv2ssRVOHwbL21+CotyP9+rJdiCveNNP94C23hAGA1phUj//KXv9Rrr72msrIypaamqqamJuhzbr/9dj377LNejxUUFGjTpk0mrRKh6pRi0535F2iw4+w2NSqJJFAhceHwbBUM57YMAGAlpgWdxsZG3XjjjcrLy9Of/vSnkJ9XWFioZ555xvO+3W43Y3lop8Lh2Z57NG3+0KnVPrqQ4o27xub+ScO0/LXAN9LktgwAYC2mBZ1ly5ZJktasWRPW8+x2uxwOhwkrQqS4w0DeoF4ak9MzrnZ42LEBAJwp7ubobNu2TX369FGPHj105ZVX6he/+IV69fL/F3ZDQ4MaGr4rkq2trY3GMvFPsdjh8RdmZl+R06Zbix0bAEhucRV0CgsLdcMNNygnJ0eHDh3Svffeq2uvvValpaXq1KmTz+cUFxd7do8QG9HY4Qk1zNxdOJQdGwCAR1jt5YsXL9aKFSsCHnPgwAENGTLE8/6aNWs0f/78kIqRW/vkk080aNAgbdmyRVdddZXPY3zt6PTr14/28hhqPWfmRF1jm9qY9szRcYcZ5tgAgPXExRydL7/8UseOHQt4zMCBA5Wamup5vyNBR5IyMzP1i1/8Qj/96U9DOp45OvEp3AnIhBkASC5xca+rzMxMZWZmRuyLB/PZZ5/p2LFjys5mhkmi81cbE+7jAACEw7SBgZWVlSorK1NlZaWamppUVlamsrIynTx50nPMkCFDtGHDBknSyZMnddddd+mdd97R4cOHVVJSosmTJ+v8889XQUGBWcsEAAAWZlox8gMPPOA1/O/iiy+WJL3xxhuaMGGCJKm8vFwul0uS1KlTJ73//vt69tlnVVNTo759++qaa67R8uXLmaUDAADahXtdAQCAmONeVwAAAGEi6AAAAMsi6AAAAMsi6AAAAMsi6AAAAMsi6AAAAMsi6AAAAMsi6AAAAMsi6AAAAMsi6AAAAMsi6AAAAMsi6AAAAMsi6AAAAMsi6AAAAMsi6AAAAMsi6AAAAMsi6AAAAMsi6AAAAMsi6AAAAMsi6AAAAMsi6AAAAMsi6AAAAMsi6AAAAMsi6AAAAMsi6AAAAMsi6AAAAMsi6AAAAMsi6AAAAMsi6AAAAMsi6AAAAMsi6AAAAMsi6AAAAMsi6AAAAMsi6AAAAMsi6AAAAMsi6AAAAMsyLegcPnxYM2fOVE5Ojrp06aJBgwZp6dKlamxsDPi8+vp6zZ07V7169dLZZ5+tKVOmqLq62qxlAgAACzMt6Hz00Udqbm7WE088of379+uRRx7RqlWrdO+99wZ83oIFC/TKK69o/fr12r59uz7//HPdcMMNZi0TAABYmM0wDCNaX+zXv/61Hn/8cX3yySc+P+5yuZSZmal169bpX//1XyW1BKahQ4eqtLRUl156aZvnNDQ0qKGhwetz9O/fX0eOHFF6ero5JwIAACKqtrZW/fr1U01NjTIyMiL2ec+K2GcKgcvlUs+ePf1+fPfu3Tp9+rTy8/M9jw0ZMkT9+/f3G3SKi4u1bNmyNo/369cvMosGAABRc+zYscQMOgcPHtRjjz2mhx9+2O8xTqdTqamp6t69u9fjWVlZcjqdPp+zZMkSLVy40PN+TU2NBgwYoMrKyoj+j4p37iScbDtZnDfnnQw4b847GbivyATaEGmPsIPO4sWLtWLFioDHHDhwQEOGDPG8f/ToURUWFurGG2/UrFmzwl9lAHa7XXa7vc3jGRkZSfUD4paens55JxHOO7lw3sklWc87JSWy5cNhB51Fixbp9ttvD3jMwIEDPf/9+eefa+LEiRo3bpyefPLJgM9zOBxqbGxUTU2N165OdXW1HA5HuEsFAABJLuygk5mZqczMzJCOPXr0qCZOnKjRo0frmWeeCZrSRo8erc6dO6ukpERTpkyRJJWXl6uyslJ5eXnhLhUAACQ509rLjx49qgkTJqh///56+OGH9eWXX8rpdHrV2hw9elRDhgzRrl27JLVcbpo5c6YWLlyoN954Q7t379aMGTOUl5fnsxDZF7vdrqVLl/q8nGVlnDfnnQw4b847GXDekT1v09rL16xZoxkzZvj8mPtLHj58WDk5OXrjjTc0YcIESS0DAxctWqTnnntODQ0NKigo0B//+EcuXQEAgLBFdY4OAABANHGvKwAAYFkEHQAAYFkEHQAAYFkEHQAAYFkJH3QOHz6smTNnKicnR126dNGgQYO0dOlSNTY2BnxefX295s6dq169eunss8/WlClTVF1dHaVVR8Yvf/lLjRs3Tl27dm1z2wx/br/9dtlsNq+3wsJCcxcaYe05b8Mw9MADDyg7O1tdunRRfn6+Pv74Y3MXGmHHjx/XrbfeqvT0dHXv3l0zZ87UyZMnAz5nwoQJbb7fd9xxR5RW3D4rV67Ueeedp7S0NI0dO9YzfsKf9evXa8iQIUpLS9OIESP0+uuvR2mlkRXOea9Zs6bN9zUtLS2Kq42MN998U9dff7369u0rm82mjRs3Bn3Otm3bNGrUKNntdp1//vlas2aN6euMtHDPe9u2bW2+3zabze+tkeJRcXGxfvCDH+icc85Rnz59VFRUpPLy8qDPi8Tvd8IHnY8++kjNzc164okntH//fj3yyCNatWqV7r333oDPW7BggV555RWtX79e27dv1+eff64bbrghSquOjMbGRt14442aM2dOWM8rLCxUVVWV5+25554zaYXmaM95P/TQQ/r973+vVatWaefOnerWrZsKCgpUX19v4koj69Zbb9X+/fu1efNmvfrqq3rzzTc1e/bsoM+bNWuW1/f7oYceisJq2+eFF17QwoULtXTpUu3Zs0cjR45UQUGBvvjiC5/Hv/3225o6dapmzpypvXv3qqioSEVFRdq3b1+UV94x4Z631HJ7gDO/r59++mkUVxwZdXV1GjlypFauXBnS8RUVFZo0aZImTpyosrIyzZ8/Xz/5yU/097//3eSVRla45+1WXl7u9T3v06ePSSuMvO3bt2vu3Ll65513tHnzZp0+fVrXXHON6urq/D4nYr/fhgU99NBDRk5Ojt+P19TUGJ07dzbWr1/veezAgQOGJKO0tDQaS4yoZ555xsjIyAjp2OnTpxuTJ082dT3REup5Nzc3Gw6Hw/j1r3/teaympsaw2+3Gc889Z+IKI+fDDz80JBnvvvuu57H//u//Nmw2m3H06FG/zxs/frxx5513RmGFkTFmzBhj7ty5nvebmpqMvn37GsXFxT6P/7d/+zdj0qRJXo+NHTvW+OlPf2rqOiMt3PMO53c+UUgyNmzYEPCYu+++27jwwgu9HrvpppuMgoICE1dmrlDO+4033jAkGSdOnIjKmqLhiy++MCQZ27dv93tMpH6/E35HxxeXyxXw7qe7d+/W6dOnlZ+f73lsyJAh6t+/v0pLS6OxxJjatm2b+vTpo8GDB2vOnDk6duxYrJdkqoqKCjmdTq/vd0ZGhsaOHZsw3+/S0lJ1795dl1xyieex/Px8paSkaOfOnQGf+9e//lW9e/fW8OHDtWTJEp06dcrs5bZLY2Ojdu/e7fV9SklJUX5+vt/vU2lpqdfxklRQUJAw31epfectSSdPntSAAQPUr18/TZ48Wfv374/GcmPKCt/vjsjNzVV2drauvvpqvfXWW7FeToe4XC5JCvhaHanvd9j3uop3Bw8e1GOPPaaHH37Y7zFOp1Opqalt6juysrIS6ppnexQWFuqGG25QTk6ODh06pHvvvVfXXnutSktL1alTp1gvzxTu72lWVpbX44n0/XY6nW22qc866yz17Nkz4DnccsstGjBggPr27av3339f99xzj8rLy/Xiiy+aveSwffXVV2pqavL5ffroo498PsfpdCb091Vq33kPHjxYq1ev1kUXXSSXy6WHH35Y48aN0/79+/W9730vGsuOCX/f79raWn3zzTfq0qVLjFZmruzsbK1atUqXXHKJGhoa9PTTT2vChAnauXOnRo0aFevlha25uVnz58/XZZddpuHDh/s9LlK/33G7o7N48WKfxVdnvrX+R+Do0aMqLCzUjTfeqFmzZsVo5R3TnvMOx80336wf/vCHGjFihIqKivTqq6/q3Xff1bZt2yJ3Eu1g9nnHK7PPe/bs2SooKNCIESN066236s9//rM2bNigQ4cORfAsEG15eXmaNm2acnNzNX78eL344ovKzMzUE088EeulwQSDBw/WT3/6U40ePVrjxo3T6tWrNW7cOD3yyCOxXlq7zJ07V/v27dPzzz8fla8Xtzs6ixYt0u233x7wmIEDB3r++/PPP9fEiRM1btw4PfnkkwGf53A41NjYqJqaGq9dnerq6pjfUyvc8+6ogQMHqnfv3jp48KCuuuqqiH3ecJl53u7vaXV1tbKzsz2PV1dXKzc3t12fM1JCPW+Hw9GmMPXbb7/V8ePHw/qZHTt2rKSWnc9BgwaFvV4z9e7dW506dWrT/Rjo99LhcIR1fDxqz3m31rlzZ1188cU6ePCgGUuMG/6+3+np6ZbdzfFnzJgx2rFjR6yXEbZ58+Z5mimC7T5G6vc7boNOZmamMjMzQzr26NGjmjhxokaPHq1nnnlGKSmBN6pGjx6tzp07q6SkRFOmTJHUUs1eWVmpvLy8Dq+9I8I570j47LPPdOzYMa8AEAtmnndOTo4cDodKSko8waa2tlY7d+4Mu2Mt0kI977y8PNXU1Gj37t0aPXq0JGnr1q1qbm72hJdQlJWVSVLMv9++pKamavTo0SopKVFRUZGkli3ukpISzZs3z+dz8vLyVFJSovnz53se27x5c8x/j8PRnvNurampSR988IGuu+46E1cae3l5eW3aixPt+x0pZWVlcfl77I9hGPr3f/93bdiwQdu2bVNOTk7Q50Ts97s91dLx5LPPPjPOP/9846qrrjI+++wzo6qqyvN25jGDBw82du7c6XnsjjvuMPr3729s3brVeO+994y8vDwjLy8vFqfQbp9++qmxd+9eY9myZcbZZ59t7N2719i7d6/x9ddfe44ZPHiw8eKLLxqGYRhff/218R//8R9GaWmpUVFRYWzZssUYNWqUccEFFxj19fWxOo2whXvehmEYv/rVr4zu3bsbL730kvH+++8bkydPNnJycoxvvvkmFqfQLoWFhcbFF19s7Ny509ixY4dxwQUXGFOnTvV8vPXP+cGDB40HH3zQeO+994yKigrjpZdeMgYOHGhcccUVsTqFoJ5//nnDbrcba9asMT788ENj9uzZRvfu3Q2n02kYhmH8+Mc/NhYvXuw5/q233jLOOuss4+GHHzYOHDhgLF261OjcubPxwQcfxOoU2iXc8162bJnx97//3Th06JCxe/du4+abbzbS0tKM/fv3x+oU2uXrr7/2/P5KMn77298ae/fuNT799FPDMAxj8eLFxo9//GPP8Z988onRtWtX46677jIOHDhgrFy50ujUqZOxadOmWJ1Cu4R73o888oixceNG4+OPPzY++OAD48477zRSUlKMLVu2xOoUwjZnzhwjIyPD2LZtm9fr9KlTpzzHmPX7nfBB55lnnjEk+Xxzq6ioMCQZb7zxhuexb775xvjZz35m9OjRw+jatavxox/9yCscJYLp06f7PO8zz1OS8cwzzxiGYRinTp0yrrnmGiMzM9Po3LmzMWDAAGPWrFmef0wTRbjnbRgtLeb333+/kZWVZdjtduOqq64yysvLo7/4Djh27JgxdepU4+yzzzbS09ONGTNmeIW71j/nlZWVxhVXXGH07NnTsNvtxvnnn2/cddddhsvlitEZhOaxxx4z+vfvb6Smphpjxowx3nnnHc/Hxo8fb0yfPt3r+L/97W/G97//fSM1NdW48MILjddeey3KK46McM57/vz5nmOzsrKM6667ztizZ08MVt0x7rbp1m/uc50+fboxfvz4Ns/Jzc01UlNTjYEDB3r9nieKcM97xYoVxqBBg4y0tDSjZ8+exoQJE4ytW7fGZvHt5O91+szvn1m/37Z/LgAAAMBy4rbrCgAAoKMIOgAAwLIIOgAAwLIIOgAAwLIIOgAAwLIIOgAAwLIIOgAAwLIIOgAAwLIIOgAAwLIIOgAAwLIIOgAAwLL+P1b7L0dwGDGFAAAAAElFTkSuQmCC", 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", + "image/png": 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", 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", 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", 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", + "image/png": 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", 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", 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" ] @@ -455,16 +462,16 @@ ], "source": [ "import matplotlib.pyplot as plt\n", + "\n", "genae.eval()\n", "\n", "for _ in range(10):\n", - " tmp=genae.sample().detach().numpy().reshape(-1,2)\n", - " plt.scatter(tmp[:,0],tmp[:,1])\n", + " tmp = genae.sample().detach().numpy().reshape(-1, 2)\n", + " plt.scatter(tmp[:, 0], tmp[:, 1])\n", " plt.xlim(-2, 2)\n", - " plt.ylim(-2,2)\n", + " plt.ylim(-2, 2)\n", " plt.show()\n", - " plt.clf()\n", - "\n" + " plt.clf()" ] }, { diff --git a/tutorials/tutorial25/tutorial.py b/tutorials/tutorial25/tutorial.py index 891b0c6c3..f9b49276b 100644 --- a/tutorials/tutorial25/tutorial.py +++ b/tutorials/tutorial25/tutorial.py @@ -1,40 +1,43 @@ # %% [markdown] # # Tutorial: Generative Model Learning of Shapes -# +# # ## Introduction to Generative Models -# +# # This tutorial demonstrates how learn the distribution of complex objects using generative models. The metholology is inspired from these [two](https://arxiv.org/abs/2308.03662) [papers](https://arxiv.org/abs/1810.01118). -# +# # We have a probability distribution of a set of ellipsis, each centered in (0,0), and we want to construct a surrogate probability distribution using generative models. -# -# +# +# # Let's first write the code for data generation. # %% import torch -from pina import LabelTensor -n=600 -density=100 + +n = 600 +density = 100 torch.manual_seed(42) -def generate_data(n,density=1000): - theta = 2 * torch.pi * torch.linspace(0,1,density) - x = torch.cos(theta) - y = torch.sin(theta) - data_ref=torch.concatenate((x.reshape(-1,1),y.reshape(-1,1)),axis=1) - data=torch.zeros((n,density,2)) - for i in range(n): - A=-0.4+0.8*torch.rand(2,2) - A=A/torch.linalg.norm(A) - A=A+torch.eye(2) - A=2*A/torch.linalg.norm(A) - data[i]=data_ref@A +def generate_data(n, density=1000): + + theta = 2 * torch.pi * torch.linspace(0, 1, density) + x = torch.cos(theta) + y = torch.sin(theta) + data_ref = torch.concatenate((x.reshape(-1, 1), y.reshape(-1, 1)), axis=1) + data = torch.zeros((n, density, 2)) + + for i in range(n): + A = -0.4 + 0.8 * torch.rand(2, 2) + A = A / torch.linalg.norm(A) + A = A + torch.eye(2) + A = 2 * A / torch.linalg.norm(A) + data[i] = data_ref @ A - data=data.reshape(n,-1) - return data + data = data.reshape(n, -1) + return data -data=generate_data(n,density) + +data = generate_data(n, density) # %% [markdown] @@ -42,11 +45,12 @@ def generate_data(n,density=1000): # %% import matplotlib.pyplot as plt -fig, ax = plt.subplots() -ellipse=data.reshape(-1,density,2)[0] -ax.scatter(ellipse[:,0],ellipse[:,1]) -ax.set(xlim=(-2,2), ylim=(-2, 2)) +fig, ax = plt.subplots() +ellipse = data.reshape(-1, density, 2)[0] +ax.scatter(ellipse[:, 0], ellipse[:, 1]) +ax.set(xlim=(-2, 2), ylim=(-2, 2)) +plt.clf() # %% [markdown] @@ -55,122 +59,164 @@ def generate_data(n,density=1000): # %% - -import torch from torch import nn from pina.model.block import PODBlock + def barycenter_projector(x): - x=x.reshape(-1,density,2) - tmp=(x-torch.mean(x,axis=1).reshape(-1,1,2)) - return tmp.reshape(-1,2*density) + x = x.reshape(-1, density, 2) + tmp = x - torch.mean(x, axis=1).reshape(-1, 1, 2) + return tmp.reshape(-1, 2 * density) + class LBR(torch.nn.Module): - def __init__(self,input_size,output_size,final=False,drop_prob=0.1): + def __init__(self, input_size, output_size, final=False, drop_prob=0.1): super().__init__() - self.lin=nn.Linear(input_size,output_size) - self.relu=nn.ReLU() - self.bn=nn.BatchNorm1d(output_size) - self.dropout=nn.Dropout(drop_prob) + self.lin = nn.Linear(input_size, output_size) + self.relu = nn.ReLU() + self.bn = nn.BatchNorm1d(output_size) + self.dropout = nn.Dropout(drop_prob) - def forward(self,input): - tmp=self.dropout(self.bn(self.relu(self.lin(input)))) + def forward(self, input): + tmp = self.dropout(self.bn(self.relu(self.lin(input)))) return tmp + class GenEncoder(torch.nn.Module): - def __init__(self,input_size,latent_size,hidden_size=500,num_layers=5,drop_prob=0.1): + def __init__( + self, + input_size, + latent_size, + hidden_size=500, + num_layers=5, + drop_prob=0.1, + ): super().__init__() self.layers = [] - self.layers.append(LBR(input_size,hidden_size,drop_prob=drop_prob)) - for i in range(num_layers-2): + self.layers.append(LBR(input_size, hidden_size, drop_prob=drop_prob)) + for _ in range(num_layers - 2): self.layers.append( - LBR(hidden_size,hidden_size,drop_prob=drop_prob) + LBR(hidden_size, hidden_size, drop_prob=drop_prob) ) - self.layers.append(nn.Linear(hidden_size,latent_size)) - self.layers.append(nn.BatchNorm1d(latent_size,affine=False,track_running_stats=False)) - self.nn=nn.Sequential(*self.layers) + self.layers.append(nn.Linear(hidden_size, latent_size)) + self.layers.append( + nn.BatchNorm1d(latent_size, affine=False, track_running_stats=False) + ) + self.nn = nn.Sequential(*self.layers) - def forward(self,x): + def forward(self, x): return self.nn(x) + class GenDecoder(torch.nn.Module): - def __init__(self,latent_size,output_size,hidden_size=500,num_layers=5,drop_prob=0.1): + def __init__( + self, + latent_size, + output_size, + hidden_size=500, + num_layers=5, + drop_prob=0.1, + ): super().__init__() self.layers = [] - self.layers.append(LBR(latent_size,hidden_size,drop_prob=drop_prob)) + self.layers.append(LBR(latent_size, hidden_size, drop_prob=drop_prob)) for i in range(num_layers - 2): self.layers.append( - LBR(hidden_size,hidden_size,drop_prob=drop_prob) + LBR(hidden_size, hidden_size, drop_prob=drop_prob) ) - self.layers.append(nn.Linear(hidden_size,output_size)) - self.nn=nn.Sequential(*self.layers) + self.layers.append(nn.Linear(hidden_size, output_size)) + self.nn = nn.Sequential(*self.layers) - def forward(self,x): + def forward(self, x): return self.nn(x) + class GenAutoencoder(torch.nn.Module): - def __init__(self,size, pod_size, latent_size,hidden_size=500,num_layers=5,drop_prob=0.1): + def __init__( + self, + pod_size, + latent_size, + hidden_size=500, + num_layers=5, + drop_prob=0.1, + ): super().__init__() - self.pod_size=pod_size - self.latent_size=latent_size - self.pod=PODBlock(64) - self.encoder=GenEncoder(pod_size,latent_size,hidden_size) - self.decoder=GenDecoder(latent_size,pod_size,hidden_size) - - def forward(self,x): - tmp=self.pod(x) - latent=self.encoder(tmp) - tmp=self.decoder(latent) - tmp=self.pod.expand(tmp) - tmp=barycenter_projector(tmp) - return (latent,tmp) - - def sample(self,n=1): - tmp=self.decoder(torch.randn(n,self.latent_size)) - tmp=self.pod.expand(tmp) - tmp=barycenter_projector(tmp) + self.pod_size = pod_size + self.latent_size = latent_size + self.pod = PODBlock(64) + self.encoder = GenEncoder( + pod_size, latent_size, hidden_size, num_layers, drop_prob + ) + self.decoder = GenDecoder( + latent_size, pod_size, hidden_size, num_layers, drop_prob + ) + + def forward(self, x): + tmp = self.pod(x) + latent = self.encoder(tmp) + tmp = self.decoder(latent) + tmp = self.pod.expand(tmp) + tmp = barycenter_projector(tmp) + return (latent, tmp) + + def sample(self, n=1): + tmp = self.decoder(torch.randn(n, self.latent_size)) + tmp = self.pod.expand(tmp) + tmp = barycenter_projector(tmp) return tmp - - - # %% [markdown] # We can now define the loss function, which is a combination of autoencoder loss (for learning the features) and sinkhorn (for regularizing the distribution of the latent space). # %% from pina.loss import LossInterface -eps=0.01 -diff_conv=1e-02 -L=100 -gamma=1 -def sinkhorn_loss(z): - normal_samples=torch.randn(z.shape[0],z.shape[1]) - return sinkhorn_loss_single(z,normal_samples)-0.5*sinkhorn_loss_single(z,z)-0.5*sinkhorn_loss_single(normal_samples,normal_samples) - -def sinkhorn_loss_single(a,b): - diff=1e8 - counter=0 - C=torch.sum((a.reshape(a.shape[0],1,-1)-b.reshape(1,b.shape[0],-1))**2,axis=2) - K=torch.exp(-C/eps) - u=torch.ones_like(a) - while diff>diff_conv and counter self.diff_conv and counter < self.L: + u_old = u + v = 1 / (C.T @ u) + u = 1 / (C @ v) + diff = torch.max(torch.abs(u - u_old)) + counter = counter + 1 + R = u @ v.T + return 1 / (a.shape[0]) * torch.sum(R * C) + + def sinkhorn_loss(self, a, b): + return ( + self.sinkhorn_loss_single(a, b) + - 0.5 * self.sinkhorn_loss_single(a, a) + - 0.5 * self.sinkhorn_loss_single(b, b) + ) + + def forward(self, rec_, output_): + z, x_hat = rec_ + normal_samples = torch.randn(z.shape[0], z.shape[1]) + return torch.linalg.norm( + x_hat - output_ + ) + self.gamma * self.sinkhorn_loss(z, normal_samples) + + +loss = Loss(eps=0.01, L=10000, gamma=1, diff_conv=1e-02) # %% [markdown] @@ -181,8 +227,8 @@ def forward(self,rec_,output_): from pina.problem.zoo import SupervisedProblem from pina import Trainer -problem=SupervisedProblem(data,data) -genae = GenAutoencoder(2*density,64,5) +problem = SupervisedProblem(data, data) +genae = GenAutoencoder(2 * density, 64, 5) genae.pod.fit(data) solver = SupervisedSolver(problem, genae, loss=loss, use_lt=False) @@ -194,40 +240,36 @@ def forward(self,rec_,output_): batch_size=100, accelerator="cpu", enable_model_summary=False, - logger=False - + logger=False, ) trainer.train() - # %% [markdown] # Let's plot some samples to check that there is variability. # %% import matplotlib.pyplot as plt + genae.eval() for _ in range(10): - tmp=genae.sample().detach().numpy().reshape(-1,2) - plt.scatter(tmp[:,0],tmp[:,1]) + tmp = genae.sample().detach().numpy().reshape(-1, 2) + plt.scatter(tmp[:, 0], tmp[:, 1]) plt.xlim(-2, 2) - plt.ylim(-2,2) + plt.ylim(-2, 2) plt.show() plt.clf() - # %% [markdown] # # Whats next? -# +# # There are lot of directions to explore: -# +# # * tweak the sinkhorn parameters to study how the affect convergence. # * changing the latent space dimensionality or the POD dimensionality. # * adopt measures different from sinkhorn for regularizing the latent space. -# -# - - +# +#