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PyTorch VS Spring Framework

Compare PyTorch VS Spring Framework and see what are their differences

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PyTorch logo PyTorch

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

Spring Framework logo Spring Framework

The Spring Framework provides a comprehensive programming and configuration model for modern Java-based enterprise applications - on any kind of deployment platform.
  • PyTorch Landing page
    Landing page //
    2023-07-15
  • Spring Framework Landing page
    Landing page //
    2023-08-18

PyTorch features and specs

  • Dynamic Computation Graph
    PyTorch uses a dynamic computation graph, which allows for interactive and flexible model building. This is particularly beneficial for researchers who need to modify the network architecture on-the-fly.
  • Pythonic Nature
    PyTorch is designed to be deeply integrated with Python, making it very intuitive for Python developers. The framework feels more 'native' to Python, which improves the ease of learning and use.
  • Strong Community Support
    PyTorch has a large, active, and growing community. This means abundant resources such as tutorials, forums, and third-party tools are available to help developers solve problems and share solutions.
  • Flexibility and Control
    PyTorch offers granular control over computations and provides extensive debugging capabilities. This level of control is beneficial for tasks that require precise tuning and custom implementations.
  • Support for GPU Acceleration
    PyTorch offers seamless integration with GPU hardware, which significantly accelerates the computation process. This makes it highly efficient for deep learning tasks.
  • Rich Ecosystem
    PyTorch has a rich ecosystem including libraries like torchvision, torchaudio, and torchtext, which are specialized for different data types and can significantly shorten development times.

Possible disadvantages of PyTorch

  • Limited Production Deployment Tools
    PyTorch is primarily designed for research rather than production. While deployment tools like TorchServe exist, they are not as mature or integrated as solutions offered by other frameworks like TensorFlow.
  • Lesser Adoption in Industry
    While PyTorch is popular among researchers, it has historically seen less adoption in industry compared to TensorFlow, which means there might be fewer resources for large-scale production deployments.
  • Inconsistent API Changes
    As PyTorch continues to evolve rapidly, occasionally there are breaking changes or inconsistent API updates. This can create maintenance challenges for existing codebases.
  • Steeper Learning Curve for Beginners
    Despite its Pythonic design, PyTorch's focus on flexibility and control can make it slightly harder for beginners to get started compared to some other high-level libraries and frameworks.
  • Less Mature Documentation
    Although the documentation is improving, it has been historically less comprehensive and mature compared to other frameworks like TensorFlow, which can make it difficult to find detailed, clear information.

Spring Framework features and specs

  • Comprehensive Ecosystem
    Spring Framework provides a vast array of tools and modules which address various aspects of application development such as security, data access, and messaging. This helps in building robust enterprise applications.
  • Inversion of Control (IoC) Container
    Spring's IoC container promotes loose coupling by managing object lifecycles and dependencies, making the code more modular and testable.
  • Aspect-Oriented Programming (AOP)
    Spring's AOP module allows for separating cross-cutting concerns like logging, transaction management, and security, making the code cleaner and more maintainable.
  • Spring Boot
    Spring Boot streamlines the setup and development of new Spring applications with built-in configurations and convention over configuration, reducing boilerplate code and speeding up development time.
  • Large Community and Support
    Spring has a large and active community, extensive documentation, and a wide selection of online resources which make it easier to find support and solutions to common problems.
  • Integration Capabilities
    Spring Framework offers seamless integration with various other technologies and frameworks, including Hibernate for ORM, Apache Kafka for messaging, and more.

Possible disadvantages of Spring Framework

  • Complexity
    Spring Framework can be complex and have a steep learning curve, especially for newcomers who are not familiar with its extensive set of features and configurations.
  • Configuration Overhead
    Although Spring Boot reduces the configuration burden, traditional Spring applications may still require extensive XML or annotation-based configurations, which can be cumbersome.
  • Performance Overhead
    The flexibility and the modular nature of Spring can introduce some performance overhead compared to more lightweight solutions, which could be a concern in highly performance-sensitive applications.
  • Version Incompatibility
    Upgrading between different versions of the Spring Framework and its associated projects can sometimes lead to compatibility issues and necessitate significant code changes.
  • Dependency Management
    Managing dependencies in a large Spring application can become complicated, particularly when dealing with multiple modules and third-party libraries, potentially leading to dependency conflicts.

Analysis of PyTorch

Overall verdict

  • Yes, PyTorch is considered a good deep learning framework.

Why this product is good

  • Ease of Use: PyTorch has an intuitive interface that makes it easier to learn and use, especially for beginners.
  • Dynamic Computation Graphs: PyTorch employs dynamic computation graphs, which provide more flexibility in building and modifying models on the fly.
  • Strong Community and Support: PyTorch has a large and active community, offering extensive resources, forums, and tutorials.
  • Research Adoption: PyTorch is widely adopted in the research community, making state-of-the-art models and techniques readily available.
  • Integration: PyTorch integrates well with other libraries and tools in the Python ecosystem, providing robust support for various applications.

Recommended for

  • Researchers and Academics: Ideal for those who need a flexible and dynamic tool for experimenting with new models and techniques.
  • Industry Practitioners: Suitable for developers and data scientists working on production-level machine learning solutions.
  • Educators and Learners: Great for educational purposes due to its easy-to-understand syntax and comprehensive documentation.

Analysis of Spring Framework

Overall verdict

  • Yes, Spring Framework is generally considered a good framework with robust features, strong community support, and extensive documentation, making it a reliable choice for Java developers working on complex, enterprise-level applications.

Why this product is good

  • Features
    Spring provides a wide range of features including dependency injection, aspect-oriented programming, transaction management, and integration with various tools and technologies.
  • Community
    Spring has a large and active community, which contributes to a wealth of resources, documentation, and third-party extensions.
  • Popularity
    Spring Framework is one of the most popular frameworks for Java development, widely used in building enterprise applications.
  • Versatility
    It offers a comprehensive programming and configuration model for modern Java-based enterprise applications, on any kind of deployment platform.

Recommended for

  • Developers building large-scale, enterprise-grade applications.
  • Teams looking for a mature and well-supported framework with a large ecosystem.
  • Projects that require integration with popular Java technologies and tools.
  • Developers focusing on microservices architecture, as Spring Boot simplifies the development of microservices.

PyTorch videos

+ Add

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

Spring Framework videos

+ Add

What is the Spring framework really all about?

More videos:

  • Tutorial - Spring Framework Tutorial | Full Course

Category Popularity

0-100% (relative to PyTorch and Spring Framework)

PyTorch

Spring Framework

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Developer Tools
0 0%
Developer Tools
100% 100
Data Science Tools
100 100%
Data Science Tools
0% 0
Web Frameworks
0 0%
Web Frameworks
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 Spring Framework

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...
Source: www.assemblyai.com
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...
Source: searchbusinessanalytics.techtarget.com

Spring Framework Reviews

Top 9 best Frameworks for web development
Spring offers a wide range of frameworks, such as an MVC framework, a data access framework and a transaction management framework. With its focus on scalability and security, Spring is an excellent choice.
Source: www.kiwop.com
17 Popular Java Frameworks for 2023: Pros, cons, and more
Therefore, the configuration, setup, build, and deployment processes all require multiple steps you might not want to deal with, especially if you’re working on a smaller project. Spring Boot (a micro framework that runs on top of the Spring Framework) is a solution for this problem, as it allows you to set up your Spring application faster, with much less configuration.
Source: raygun.com
Top 10 Phoenix Framework Alternatives
Spring Framework is an open-source app framework and inversion of control container for the Java platform, providing the infrastructure required to develop Java and web apps on top of the Java EE platform.
Source: blog.back4app.com
10 Best Java Frameworks You Should Know
Spring Framework is one of the most extensively used, top-notch, lightweight software application frameworks built for software design, development, and deployment in Java.
Source: www.simplilearn.com

Social recommendations and mentions

Based on our record, PyTorch seems to be a lot more popular than Spring Framework. While we know about 133 links to PyTorch, we've tracked only 13 mentions of Spring Framework. 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 (133)

  • Grasping Computer Vision Fundamentals Using Python
    To aspiring innovators: Dive into open-source frameworks like OpenCV or PyTorch, experiment with custom object detection models, or contribute to projects tackling bias mitigation in training datasets. Computer vision isn’t just a tool, it’s a bridge between the physical and digital worlds, inviting collaborative solutions to global challenges. The next frontier? Systems that don’t just interpret visuals, but... - Source: dev.to / 25 days ago
  • Top Programming Languages for AI Development in 2025
    With the quick emergence of new frameworks, libraries, and tools, the area of artificial intelligence is always changing. Programming language selection. We're not only discussing current trends; we're also anticipating what AI will require in 2025 and beyond. - Source: dev.to / about 1 month ago
  • Fine-tuning LLMs locally: A step-by-step guide
    Next, we define a training loop that uses our prepared data and optimizes the weights of the model. Here's an example using PyTorch:. - Source: dev.to / about 2 months ago
  • 10 Must-Have AI Tools to Supercharge Your Software Development
    8. TensorFlow and PyTorch: These frameworks support AI and machine learning integrations, allowing developers to build and deploy intelligent models and workflows. TensorFlow is widely used for deep learning applications, offering pre-trained models and extensive documentation. PyTorch provides flexibility and ease of use, making it ideal for research and experimentation. Both frameworks support neural network... - Source: dev.to / 4 months ago
  • Automating Enhanced Due Diligence in Regulated Applications
    Frameworks like TensorFlow and PyTorch can help you build and train models for various tasks, such as risk scoring, anomaly detection, and pattern recognition. - Source: dev.to / 4 months ago
View more

Spring Framework mentions (13)

  • March 2025 Java Key Updates in Boot, Security, and More
    The release of Spring Framework 6.2.5 includes:. - Source: dev.to / 2 months ago
  • Getting Started with Spring Boot 3 for .NET Developers
    Spring Framework 6: https://spring.io/projects/spring-framework. - Source: dev.to / 5 months ago
  • Want to Get Better at Java? Go Old School.
    We had to write our own frameworks (uphill, both ways) but most current frameworks will have similar documentation pages as well. Both Apache and Spring are especially good at that. - Source: dev.to / over 2 years ago
  • Best Frameworks For Web Development
    Framework link: https://spring.io/projects/spring-framework Github Link: https://github.com/spring-projects/spring-framework. - Source: dev.to / almost 3 years ago
  • What to you do now?
    A common used Java framework is Spring framework (ie https://spring.io/projects/spring-framework and short tutorials at https://www.baeldung.com/spring-intro). Source: almost 3 years ago
View more

What are some alternatives?

When comparing PyTorch and Spring Framework, 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.

Django - The Web framework for perfectionists with deadlines

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

Grails - An Open Source, full stack, web application framework for the JVM

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

Laravel - A PHP Framework For Web Artisans

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