top_model_mixin.py

The top_model_mixin.py script defines a mixin class called TopModelMixin that provides common functionalities and interfaces for top-level model classes in the TensorRT-LLM framework.

Let's break down the script:

Imports

• The script imports necessary modules and classes from the TensorRT-LLM framework, including LoraBuildConfig, Mapping, and PluginConfig.

TopModelMixin Class

• The TopModelMixin class is defined as a mixin class that can be inherited by top-level model classes like LLaMAForCausalLM.

• It provides common functionalities and interfaces that are specific to top-level models and not applicable to building blocks like Attention or MLP.

__init__ Method:

• The __init__ method is an empty method that can be overridden by subclasses if needed.

from_hugging_face Class Method

• The from_hugging_face class method is a placeholder method that subclasses should override.

• It is intended to create an LLM object and load weights from a Hugging Face model directory.

• The method takes parameters such as hf_model_dir, dtype, and mapping to specify the model directory, default weights data type, and multi-GPU parallel strategy.

convert_hf_checkpoint Class Method

• The convert_hf_checkpoint class method is another placeholder method that subclasses should override.

• It is intended to convert a Hugging Face checkpoint to a TRT-LLM checkpoint.

• The method takes parameters such as hf_model_dir, dtype, and output_dir to specify the Hugging Face model directory, default weights data type, and output directory for the converted checkpoint.

use_lora Method

• The use_lora method is a placeholder method that subclasses should override.

• It is intended to load LoRA (Low-Rank Adaptation) weights from a given configuration to the module.

• The method takes a lora_config parameter of type LoraBuildConfig.

use_prompt_tuning Method

• The use_prompt_tuning method is a placeholder method that subclasses should override.

• It is intended to enable prompt tuning when building the TRT engine.

• The method takes parameters such as max_prompt_embedding_table_size and prompt_table_path to specify the maximum size of the prompt embedding table and the path to the prompt table.

default_plugin_config Method

• The default_plugin_config method is a placeholder method that subclasses should override.

• It is intended to return the default plugin configuration for the model when the plugin_config value is not provided in the to_trt() call.

• The method takes arbitrary keyword arguments (**kwargs) and returns a PluginConfig object.

Overall, the TopModelMixin class serves as a blueprint for top-level model classes in the TensorRT-LLM framework

It defines common methods and interfaces that subclasses should implement to support functionalities like loading weights from Hugging Face, converting checkpoints, using LoRA, enabling prompt tuning, and configuring plugins.

Subclasses can inherit from this mixin and override the placeholder methods with their specific implementations.