Theano is a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It can use GPUs and perform efficient symbolic differentiation.

Related tags

Deep LearningTheano
Overview
============================================================================================================
`MILA will stop developing Theano <https://groups.google.com/d/msg/theano-users/7Poq8BZutbY/rNCIfvAEAwAJ>`_.

The PyMC developers are continuing Theano development in a `fork <https://github.com/pymc-devs/theano-pymc>`_.
============================================================================================================


To install the package, see this page:
   http://deeplearning.net/software/theano/install.html

For the documentation, see the project website:
   http://deeplearning.net/software/theano/

Related Projects:
   https://github.com/Theano/Theano/wiki/Related-projects

It is recommended that you look at the documentation on the website, as it will be more current than the documentation included with the package.

In order to build the documentation yourself, you will need sphinx. Issue the following command:

::

   python ./doc/scripts/docgen.py

Documentation is built into ``html/``

The PDF of the documentation can be found at ``html/theano.pdf``

================
DIRECTORY LAYOUT
================

``Theano`` (current directory) is the distribution directory.

* ``Theano/theano`` contains the package
* ``Theano/theano`` has several submodules:
 
  * ``gof`` + ``compile`` are the core
  * ``scalar`` depends upon core
  * ``tensor`` depends upon ``scalar``
  * ``sparse`` depends upon ``tensor``
  * ``sandbox`` can depend on everything else

* ``Theano/examples`` are copies of the example found on the wiki
* ``Theano/benchmark`` and ``Theano/examples`` are in the distribution, but not in
  the Python package
* ``Theano/bin`` contains executable scripts that are copied to the bin folder
  when the Python package is installed
* Tests are distributed and are part of the package, i.e. fall in
  the appropriate submodules
* ``Theano/doc`` contains files and scripts used to generate the documentation
* ``Theano/html`` is where the documentation will be generated
TensorLight - A high-level framework for TensorFlow

TensorLight is a high-level framework for TensorFlow-based machine intelligence applications. It reduces boilerplate code and enables advanced feature

Benjamin Kan 10 Jul 31, 2022
Sleep staging from ECG, assisted with EEG

Sleep_Staging_Knowledge Distillation This codebase implements knowledge distillation approach for ECG based sleep staging assisted by EEG based sleep

2 Dec 12, 2022
Unet network with mean teacher for altrasound image segmentation

Unet network with mean teacher for altrasound image segmentation

5 Nov 21, 2022
Learning a mapping from images to psychological similarity spaces with neural networks.

LearningPsychologicalSpaces v0.1: v1.1: v1.2: v1.3: v1.4: v1.5: The code in this repository explores learning a mapping from images to psychological s

Lucas Bechberger 8 Dec 12, 2022
This is the source code of the 1st place solution for segmentation task (with Dice 90.32%) in 2021 CCF BDCI challenge.

1st place solution in CCF BDCI 2021 ULSEG challenge This is the source code of the 1st place solution for ultrasound image angioma segmentation task (

Chenxu Peng 30 Nov 22, 2022
SeMask: Semantically Masked Transformers for Semantic Segmentation.

SeMask: Semantically Masked Transformers Jitesh Jain, Anukriti Singh, Nikita Orlov, Zilong Huang, Jiachen Li, Steven Walton, Humphrey Shi This repo co

Picsart AI Research (PAIR) 186 Dec 30, 2022
A criticism of a recent paper on buggy image downsampling methods in popular image processing and deep learning libraries.

A criticism of a recent paper on buggy image downsampling methods in popular image processing and deep learning libraries.

70 Jul 12, 2022
ONNX Runtime Web demo is an interactive demo portal showing real use cases running ONNX Runtime Web in VueJS.

ONNX Runtime Web demo is an interactive demo portal showing real use cases running ONNX Runtime Web in VueJS. It currently supports four examples for you to quickly experience the power of ONNX Runti

Microsoft 58 Dec 18, 2022
Official re-implementation of the Calibrated Adversarial Refinement model described in the paper Calibrated Adversarial Refinement for Stochastic Semantic Segmentation

Official re-implementation of the Calibrated Adversarial Refinement model described in the paper Calibrated Adversarial Refinement for Stochastic Semantic Segmentation

Elias Kassapis 31 Nov 22, 2022
optimization routines for hyperparameter tuning

Hyperopt: Distributed Hyperparameter Optimization Hyperopt is a Python library for serial and parallel optimization over awkward search spaces, which

Marc Claesen 398 Nov 09, 2022
Code from Daniel Lemire, A Better Alternative to Piecewise Linear Time Series Segmentation

PiecewiseLinearTimeSeriesApproximation code from Daniel Lemire, A Better Alternative to Piecewise Linear Time Series Segmentation, SIAM Data Mining 20

Daniel Lemire 21 Oct 27, 2022
Topic Discovery via Latent Space Clustering of Pretrained Language Model Representations

TopClus The source code used for Topic Discovery via Latent Space Clustering of Pretrained Language Model Representations, published in WWW 2022. Requ

Yu Meng 63 Dec 18, 2022
Open Source Light Field Toolbox for Super-Resolution

BasicLFSR BasicLFSR is an open-source and easy-to-use Light Field (LF) image Super-Ressolution (SR) toolbox based on PyTorch, including a collection o

Squidward 50 Nov 18, 2022
ConvMixer unofficial implementation

ConvMixer ConvMixer 非官方实现 pytorch 版本已经实现。 nets 是重构版本 ,test 是官方代码 感兴趣小伙伴可以对照看一下。 keras 已经实现 tf2.x 中 是tensorflow 2 版本 gelu 激活函数要求 tf=2.4 否则使用入下代码代替gelu

Jian Tengfei 8 Jul 11, 2022
Nvidia Semantic Segmentation monorepo

Paper | YouTube | Cityscapes Score Pytorch implementation of our paper Hierarchical Multi-Scale Attention for Semantic Segmentation. Please refer to t

NVIDIA Corporation 1.6k Jan 04, 2023
Machine Translation Implement By Bi-GRU And Transformer

Seq2Seq Translation Implement By Bidirectional GRU And Transformer In Pytorch Before You Run The Code You should download the data through the link be

He Wang 2 Oct 27, 2021
The software associated with a paper accepted at EMNLP 2021 titled "Open Knowledge Graphs Canonicalization using Variational Autoencoders".

Open-KG-canonicalization The software associated with a paper accepted at EMNLP 2021 titled "Open Knowledge Graphs Canonicalization using Variational

International Business Machines 13 Nov 11, 2022
Pytorch implementation of face attention network

Face Attention Network Pytorch implementation of face attention network as described in Face Attention Network: An Effective Face Detector for the Occ

Hooks 312 Dec 09, 2022
This repo provides code for QB-Norm (Cross Modal Retrieval with Querybank Normalisation)

This repo provides code for QB-Norm (Cross Modal Retrieval with Querybank Normalisation) Usage example python dynamic_inverted_softmax.py --sims_train

36 Dec 29, 2022
这是一个facenet-pytorch的库,可以用于训练自己的人脸识别模型。

Facenet:人脸识别模型在Pytorch当中的实现 目录 性能情况 Performance 所需环境 Environment 注意事项 Attention 文件下载 Download 预测步骤 How2predict 训练步骤 How2train 参考资料 Reference 性能情况 训练数据

Bubbliiiing 210 Jan 06, 2023