Software Alternatives, Accelerators & Startups

PyTorch VS Luigi

Compare PyTorch VS Luigi and see what are their differences

PyTorch logo PyTorch

Open source deep learning platform that provides a seamless path from research prototyping to...

Luigi logo Luigi

Luigi is a Python module that helps you build complex pipelines of batch jobs.
  • PyTorch Landing page
    Landing page //
    2023-07-15
  • Luigi Landing page
    Landing page //
    2023-10-08

PyTorch videos

PyTorch in 5 Minutes

More videos:

  • Review - Jeremy Howard: Deep Learning Frameworks - TensorFlow, PyTorch, fast.ai | AI Podcast Clips
  • Review - PyTorch at Tesla - Andrej Karpathy, Tesla

Luigi videos

Luigi's Mansion 3 Review

More videos:

  • Review - Luigi's Mansion 3 Review
  • Review - Luigi's Mansion 3 - REVIEW (Nintendo Switch)

Category Popularity

0-100% (relative to PyTorch and Luigi)
Data Science And Machine Learning
Workflow Automation
0 0%
100% 100
Data Science Tools
100 100%
0% 0
Workflows
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare PyTorch and Luigi

PyTorch Reviews

10 Python Libraries for Computer Vision
Similar to TensorFlow and Keras, PyTorch and torchvision offer powerful tools for computer vision tasks. PyTorch’s dynamic computation graph and torchvision’s datasets and pre-trained models make it easy to implement tasks such as image classification, object detection, and style transfer.
Source: clouddevs.com
25 Python Frameworks to Master
Along with TensorFlow, PyTorch (developed by Facebook’s AI research group) is one of the most used tools for building deep learning models. It can be used for a variety of tasks such as computer vision, natural language processing, and generative models.
Source: kinsta.com
Top 8 Alternatives to OpenCV for Computer Vision and Image Processing
PyTorch is another open-source machine learning framework that is widely used in academia and industry. PyTorch provides excellent support for building deep learning models, and it has several pre-trained models for computer vision tasks, making it the ideal tool for several computer vision applications. PyTorch offers a user-friendly interface that makes it easier for...
Source: www.uubyte.com
PyTorch vs TensorFlow in 2022
When we compare HuggingFace model availability for PyTorch vs TensorFlow, the results are staggering. Below we see a chart of the total number of models available on HuggingFace that are either PyTorch or TensorFlow exclusive, or available for both frameworks. As we can see, the number of models available for use exclusively in PyTorch absolutely blows the competition out of...
15 data science tools to consider using in 2021
First released publicly in 2017, PyTorch uses arraylike tensors to encode model inputs, outputs and parameters. Its tensors are similar to the multidimensional arrays supported by NumPy, another Python library for scientific computing, but PyTorch adds built-in support for running models on GPUs. NumPy arrays can be converted into tensors for processing in PyTorch, and vice...

Luigi Reviews

5 Airflow Alternatives for Data Orchestration
In this blog post, we will discuss five alternatives to manage workflows: Prefect, Dagster, Luigi, Mage AI, and Kedro. These tools can be used for any field, not just limited to data engineering. By understanding these tools, you'll be able to choose the one that best suits your data and machine learning workflow needs.
Top 8 Apache Airflow Alternatives in 2024
Even though Airflow and Luigi have much in common (open-source projects, Python used, Apache license), they have slightly different approaches to data workflow management. The first thing is that Luigi prevents tasks from running individually, which limits scalability. Moreover, Luigi’s API implements fewer features than that of Airflow, which might be especially difficult...
Source: blog.skyvia.com
10 Best Airflow Alternatives for 2024
Among a popular choice for an Apache Airflow alternative is Luigi. It is a Python package that handles long-running batch processing. This means that it manages the automatic execution of data processing processes on several objects in a batch. A data processing job may be defined as a series of dependent tasks in Luigi.
Source: hevodata.com
Python & ETL 2020: A List and Comparison of the Top Python ETL Tools
When does Luigi make sense? If you need to automate simple ETL processes (like logs) Luigi can handle them rapidly and without much setup. When it comes to complex tasks, Luigi is limited by its strict pipeline-like structure.
Source: www.xplenty.com
Comparison of Python pipeline packages: Airflow, Luigi, Gokart, Metaflow, Kedro, PipelineX
Luigi enables you to define your pipeline by child classes of Task with 3 class methods (requires, output, run) in Python code.
Source: medium.com

Social recommendations and mentions

Based on our record, PyTorch seems to be a lot more popular than Luigi. While we know about 109 links to PyTorch, we've tracked only 9 mentions of Luigi. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

PyTorch mentions (109)

  • Understanding GPT: How To Implement a Simple GPT Model with PyTorch
    In this guide, we provided a comprehensive, step-by-step explanation of how to implement a simple GPT (Generative Pre-trained Transformer) model using PyTorch. We walked through the process of creating a custom dataset, building the GPT model, training it, and generating text. This hands-on implementation demonstrates the fundamental concepts behind the GPT architecture and serves as a foundation for more complex... - Source: dev.to / 3 days ago
  • Building a Simple Chatbot using GPT model - part 2
    PyTorch is a powerful and flexible deep learning framework that offers a rich set of features for building and training neural networks. - Source: dev.to / 11 days ago
  • Clusters Are Cattle Until You Deploy Ingress
    Oddly enough, sometimes, the best way to learn is by putting forth incorrect opinions or questions. Recently, while wrestling with AI project complexities, I pondered aloud whether all Docker images with AI models would inevitably be bulky due to PyTorch dependencies. To my surprise, this sparked many helpful responses, offering insights into optimizing image sizes. Being willing to be wrong opens up avenues for... - Source: dev.to / 4 days ago
  • My Favorite DevTools to Build AI/ML Applications!
    TensorFlow, developed by Google, and PyTorch, developed by Facebook, are two of the most popular frameworks for building and training complex machine learning models. TensorFlow is known for its flexibility and robust scalability, making it suitable for both research prototypes and production deployments. PyTorch is praised for its ease of use, simplicity, and dynamic computational graph that allows for more... - Source: dev.to / about 1 month ago
  • Functions and operators for Dot and Matrix multiplication and Element-wise calculation in PyTorch
    *My post explains Dot, Matrix and Element-wise multiplication in PyTorch. - Source: dev.to / 2 months ago
View more

Luigi mentions (9)

  • Ask HN: What is the correct way to deal with pipelines?
    I agree there are many options in this space. Two others to consider: - https://airflow.apache.org/ - https://github.com/spotify/luigi There are also many Kubernetes based options out there. For the specific use case you specified, you might even consider a plain old Makefile and incrond if you expect these all to run on a single host and be triggered by a new file... - Source: Hacker News / 9 months ago
  • In the context of Python what is a Bob Job?
    Maybe if your use case is “smallish” and doesn’t require the whole studio suite you could check out apscheduler for doing python “tasks” on a schedule and luigi to build pipelines. Source: almost 2 years ago
  • Lessons Learned from Running Apache Airflow at Scale
    What are you trying to do? Distributed scheduler with a single instance? No database? Are you sure you don't just mean "a scheduler" ala Luigi? https://github.com/spotify/luigi. - Source: Hacker News / about 2 years ago
  • Apache Airflow. How to make the complex workflow as an easy job
    It's good to know what Airflow is not the only one on the market. There are Dagster and Spotify Luigi and others. But they have different pros and cons, be sure that you did a good investigation on the market to choose the best suitable tool for your tasks. - Source: dev.to / over 2 years ago
  • DevOps Fundamentals for Deep Learning Engineers
    MLOps is a HUGE area to explore, and not surprisingly, there are many startups showing up in this space. If you want to get it on the latest trends, then I would look at workflow orchestration frameworks such as Metaflow (started off at Netflix, is now spinning off into its own enterprise business, https://metaflow.org/), Kubeflow (used at Google, https://www.kubeflow.org/), Airflow (used at Airbnb,... Source: over 2 years ago
View more

What are some alternatives?

When comparing PyTorch and Luigi, you can also consider the following products

TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.

Apache Airflow - Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.

Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.

Kestra.io - Infinitely scalable, event-driven, language-agnostic orchestration and scheduling platform to manage millions of workflows declaratively in code.

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

Dagster - The cloud-native open source orchestrator for the whole development lifecycle, with integrated lineage and observability, a declarative programming model, and best-in-class testability.