API Reference

XFlow API is organized into four main modules that provide the building blocks for machine learning workflows.

Modules

• Data Module
  • Pipeline Classes
  • Transform Classes
  • Provider Classes
  • Functions
• Models Module
  • BaseModel
• Trainers Module
  • BaseTrainer
  • CallbackRegistry
  • build_callbacks_from_config()
• Utils Module
  • ConfigManager
  • get_base_dir()
  • load_validated_config()
  • plot_image()
  • Helper Functions (Internal)
  • IO Functions (Internal)

Overview

The XFlow package is structured around four main modules:

• Data Module (Data Module) - Data pipelines, providers, and transformations

• Models Module (Models Module) - Machine learning model base classes

• Trainers Module (Trainers Module) - Training utilities and callback management

• Utils Module (Utils Module) - Configuration management and utility functions

Quick Start

Access the main components from their respective modules:

# Data processing
from xflow.data import BasePipeline, InMemoryPipeline, BatchPipeline
from xflow.data import FileProvider, SqlProvider

# Models
from xflow.models import BaseModel

# Training
from xflow.trainers import BaseTrainer, CallbackRegistry

# Utilities
from xflow.utils import ConfigManager, get_base_dir, load_validated_config, plot_image

• xflow.data - All data-related functionality

• xflow.models - Model definitions and implementations

• xflow.trainers - Training loops, callbacks, and utilities

• xflow.utils - Configuration, visualization, and helper functions