Colab tutorials (#367)

* Colab Button & Run added

tutorials/tutorial4/tutorial.py

@@ -2,6 +2,8 @@
 # coding: utf-8
 
 # # Tutorial: Unstructured convolutional autoencoder via continuous convolution
+# 
+# [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mathLab/PINA/blob/master/tutorials/tutorial4/tutorial.ipynb)
 
 # In this tutorial, we will show how to use the Continuous Convolutional Filter, and how to build common Deep Learning architectures with it. The implementation of the filter follows the original work [*A Continuous Convolutional Trainable Filter for Modelling Unstructured Data*](https://arxiv.org/abs/2210.13416).
 
@@ -10,6 +12,15 @@
 # In[1]:
 
 
+## routine needed to run the notebook on Google Colab
+try:
+  import google.colab
+  IN_COLAB = True
+except:
+  IN_COLAB = False
+if IN_COLAB:
+  get_ipython().system('pip install "pina-mathlab"')
+
 import torch 
 import matplotlib.pyplot as plt 
 from pina.problem import AbstractProblem