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This commit introduces a knowledge distillation module to enhance logo generation in the CogVideoX-2B text-to-video model.

The key changes include:

  • A new KDTrainer class that inherits from CogVideoXT2VLoraTrainer. This trainer loads a teacher model (OpenLogo Faster R-CNN) and computes a knowledge distillation loss to guide the student model.
  • The kd training type is now supported, allowing users to select it from the command line.
  • New command-line arguments (teacher_model_path, teacher_model_num_classes, kd_loss_weight) have been added to configure the knowledge distillation process.
  • A new configuration file (cogvideox_2b_kd.yaml) is provided as an example for running a kd training session.

This commit introduces a knowledge distillation module to enhance logo generation in the CogVideoX-2B text-to-video model.

The key changes include:

- A new `KDTrainer` class that inherits from `CogVideoXT2VLoraTrainer`. This trainer loads a teacher model (OpenLogo Faster R-CNN) and computes a knowledge distillation loss to guide the student model.
- The `kd` training type is now supported, allowing users to select it from the command line.
- New command-line arguments (`teacher_model_path`, `teacher_model_num_classes`, `kd_loss_weight`) have been added to configure the knowledge distillation process.
- A new configuration file (`cogvideox_2b_kd.yaml`) is provided as an example for running a `kd` training session.
This commit introduces a knowledge distillation module to enhance logo generation in the CogVideoX-2B text-to-video model.

The key changes include:

- A new `KDTrainer` class that inherits from `CogVideoXT2VLoraTrainer`. This trainer loads a teacher model and computes a knowledge distillation loss to guide the student model.
- The teacher model loading logic has been updated to support a VGG16-based Faster R-CNN model, to be compatible with user-provided weights. This includes a custom construction of the Faster R-CNN model with a VGG16 backbone and appropriate RoI heads.
- The `kd` training type is now supported, allowing users to select it from the command line.
- New command-line arguments (`teacher_model_path`, `teacher_model_num_classes`, `kd_loss_weight`) have been added to configure the knowledge distillation process.
- A new configuration file (`cogvideox_2b_kd.yaml`) is provided as an example for running a `kd` training session.
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