Theano Tutorial

The “Theano Tutorial” delves into the intricacies of Theano, a Python library for defining, optimizing, and evaluating mathematical expressions involving multi-dimensional arrays efficiently. The tutorial explores how Theano facilitates the creation of complex mathematical models, particularly in the realm of machine learning and deep learning. By leveraging Theano’s capabilities, users can streamline the development and optimization of computational graphs, enhancing the performance of their algorithms. Through practical examples and explanations, the tutorial equips readers with the knowledge and skills needed to harness the power of Theano for advanced numerical computations and model building.

Convolution arithmetic tutorial

Theano Tutorial

Convolution arithmetic tutorial Note This tutorial is adapted from an existing convolution arithmetic guide [1] , with an added emphasis on Theano’s interface. Also, note that the signal processing c...

Derivatives in Theano

Theano Tutorial

Derivatives in Theano Computing Gradients Now let’s use Theano for a slightly more sophisticated task: create a function which computes the derivative of some expression y with respect to its paramet...

Broadcasting

Theano Tutorial

Broadcasting Broadcasting is a mechanism which allows tensors with different numbers of dimensions to be added or multiplied together by (virtually) replicating the smaller tensor along the dimension...

How Shape Information is Handled by Theano

Theano Tutorial

How Shape Information is Handled by Theano It is not possible to strictly enforce the shape of a Theano variable when building a graph since the particular value provided at run-time for a parameter ...

Configuration Settings and Compiling Modes

Theano Tutorial

Configuration Settings and Compiling Modes Configuration The config module contains several attributes that modify Theano’s behavior. Many of these attributes are examined during the import of the th...

NumPy refresher

Theano Tutorial

NumPy refresher Here are some quick guides to NumPy: Numpy quick guide for Matlab users Numpy User Guide More detailed Numpy tutorial 100 NumPy exercises Numpy tutorial Matrix conventions for machine...

Loading and Saving

Theano Tutorial

Loading and Saving Python’s standard way of saving class instances and reloading them is the pickle mechanism. Many Theano objects can be serialized (and deserialized ) by pickle , however, a limitat...

Baby Steps - Algebra

Theano Tutorial

Baby Steps - Algebra Adding two Scalars To get us started with Theano and get a feel of what we’re working with, let’s make a simple function: add two numbers together. Here is how you do it: And now...

Python tutorial

Theano Tutorial

Python tutorial In this documentation, we suppose that the reader knows Python. Here is a small list of Python tutorials/exercises if you need to learn it or only need a refresher: Python Challenge D...

Understanding Memory Aliasing for Speed and Correctness

Theano Tutorial

Understanding Memory Aliasing for Speed and Correctness The aggressive reuse of memory is one of the ways through which Theano makes code fast, and it is important for the correctness and speed of yo...

Multi cores support in Theano

Theano Tutorial

Multi cores support in Theano Convolution and Pooling Since Theano 0.9dev2, the convolution and pooling are parallelized on CPU. BLAS operation BLAS is an interface for some mathematical operations b...

Using multiple GPUs

Theano Tutorial

Using multiple GPUs Theano has a feature to allow the use of multiple GPUs at the same time in one function. The multiple gpu feature requires the use of the GpuArray Backend backend, so make sure th...