## InternLM System Structure The system code file structure is shown below: ```bash ├── configs # Configuration module, managing model and training-related parameters │ └── 7B_sft.py # 7B_sft.py is a sample configuration file for the system demo ├── internlm # Main directory of the system code │ ├── apis # Interface module, containing some interface functions related to inference, etc. │ ├── core # Core module, managing parallel context and training scheduling engine for training and inference │ │ ├── context # Context module, mainly responsible for initializing parallel process groups and managing parallel context │ │ │ ├── parallel_context.py │ │ │ └── process_group_initializer.py │ │ ├── engine.py # Responsible for managing the training and evaluation process of the model │ │ ├── no_pipeline_scheduler.py # Scheduler for parallel training │ │ └── trainer.py # Responsible for managing the training engine and scheduler │ ├── data # Data module, responsible for managing dataset generation and processing │ ├── initialize # Initialization module, responsible for managing distributed environment startup and trainer initialization │ ├── model # Model module, responsible for managing model structure definition and implementation │ ├── solver # Responsible for managing the implementation of optimizer and lr_scheduler, etc. │ └── utils # Auxiliary module, responsible for managing logs, storage, model registration, etc. ├── train.py # Main function entry file for model training ├── requirements # List of dependent packages for system running ├── third_party # Third-party modules on which the system depends, including apex and flash-attention, etc. ├── tools # Some script tools for processing and converting raw datasets, model checkpoint conversion, etc. └── version.txt # System version number ```