adding_some_attention_modules

[gongyan1]

Title

Update Attention Modules

Description

Purpose

To enhance the versatility and adaptability of our models, this update introduces 6 new Attention Modules, enriching the available options for attention mechanisms within the project.

Changes

• New Attention Modules:

  • Frequency Channel Attention: Enhances channel attention using frequency information.
  • Attention Augmented Convolutional Networks: Combines attention mechanisms with convolutional networks to improve feature extraction capabilities.
  • Global Context Attention: Incorporates global context information to enhance the model's global perception.
  • Linear Context Transform Attention: Strengthens the utilization of context information through linear transformation.
  • Gated Channel Transformation: Introduces a gating mechanism to dynamically adjust the importance of channels.
  • Gaussian Context Attention: Employs a Gaussian model to simulate contextual relationships, deepening the model's understanding.

• Readme Adjustments:

  • Made minor formatting adjustments to the Readme file to improve document readability.

Impact

• The introduction of a wider variety of Attention Modules provides more robust options for model construction, enhancing flexibility and applicability for community members' use and research.

Testing

• Detailed local testing was conducted for all newly introduced attention modules, and all performed as expected.

Checklist

• Confirm that all newly introduced modules have been thoroughly tested.
• Ensure that the Readme file has been accurately updated without omissions.

Notes for Reviewers

• Please pay special attention to the implementation code of the newly introduced attention modules.
• If there are any suggestions for further improvements to the Readme formatting, they are welcome.