Gym vs Torch: What are the differences?

# Comparison Between Gym and Torch

Gym and Torch are two popular frameworks used in the field of artificial intelligence and deep learning. Both frameworks have their strengths and weaknesses that cater to different needs of researchers and developers. Below are the key differences between Gym and Torch.

1. **Programming Language**: The primary difference between Gym and Torch lies in the programming language they use. Gym is developed in Python, making it ideal for researchers and developers who are proficient in Python programming. On the other hand, Torch is built using Lua, a programming language that may have a steeper learning curve for those not familiar with it.
   
2. **Community Support**: Community support is another distinguishing factor between Gym and Torch. Gym, being widely used in the machine learning community, has a larger and more active user base, resulting in extensive documentation, tutorials, and community-driven resources. Torch, although popular, may not have the same level of widespread support and resources available.
   
3. **Ease of Use**: In terms of ease of use, Gym is known for its simplicity and user-friendly interface, making it a great choice for beginners and those looking to quickly prototype algorithms. In contrast, Torch is considered to be more complex and requires a deeper understanding of its underlying principles, which may be challenging for users without a strong background in deep learning.
   
4. **Flexibility**: Gym provides a high level of flexibility when it comes to designing and implementing custom algorithms and environments. Its modular structure allows users to easily extend and customize existing functionalities. On the other hand, Torch offers a more rigid framework with predefined components, which may limit the flexibility in certain scenarios.
   
5. **Performance**: Performance is a crucial factor in deep learning frameworks, and this is where Torch excels. Torch is renowned for its efficient implementation of neural network operations, which results in faster computation and training times compared to Gym. This makes Torch a preferred choice for projects that require high computational performance.
   
In Summary, Gym and Torch have distinct characteristics in terms of programming language, community support, ease of use, flexibility, and performance, catering to different user requirements in the field of artificial intelligence and deep learning.