graph LR
Core_Building_Blocks["Core Building Blocks"]
Model_Definitions["Model Definitions"]
Model_Management["Model Management"]
Training_Evaluation["Training & Evaluation"]
Core_Building_Blocks -- "provides components to" --> Model_Definitions
Model_Definitions -- "uses" --> Core_Building_Blocks
Model_Definitions -- "provided to" --> Model_Management
Model_Management -- "aggregates" --> Model_Definitions
Model_Management -- "provides models to" --> Training_Evaluation
Training_Evaluation -- "consumes models from" --> Model_Management
This subsystem focuses on defining, managing, and utilizing neural network architectures, particularly specialized Perforated Bottleneck (PB) models, within the perforatedai project.
Provides the fundamental layers, operations, and utility functions that serve as reusable building blocks for constructing various neural network architectures. This component ensures modularity and consistency across different model implementations.
Related Classes/Methods:
perforatedai.core(1:1)
Implements the specific neural network architectures, including the specialized Perforated Bottleneck (PB) models. This component contains the concrete architectural blueprints and their forward pass logic.
Related Classes/Methods:
perforatedai.pb_models
Manages the collection of defined neural network models, including orchestrating custom model builders and potentially handling pre-trained model loading. It acts as a central interface for accessing and organizing different model architectures.
Related Classes/Methods:
perforatedai.models(1:1)
Handles the processes for training, validation, and evaluation of the neural network models. This includes defining training loops, optimization strategies, and performance metrics. It consumes the models provided by the Model Management component.
Related Classes/Methods:
perforatedai.training(1:1)