Welcome to ablator’s documentation!# Contents: Analysis package Subpackages Submodules Analysis module module Analysis results module Module contents Config package Submodules Base Configuration module Configuration Types module Configuration Utils module Module contents Main package Subpackages Submodules Model Configuration module Multi-process Trainer module Prototype Trainer module Experiment and Optuna state module Module contents Modules package Subpackages Submodules Optimizers module Schedulers module Module contents Utils package Submodules Base Utils module File Utils module Module contents Tutorials Quick start with Ablator Installing Preparations Access the results Next steps Setting up environment Installation Configuration basics Configuration categories Different methods to define running configurations Conclusion Prototyping Models Running Experiments using Ablator Setting up Ablator Configurations Importing the dataset Creating Pytorch Model Defining Custom Evaluation Metrics Model Wrapper ProtoTrainer Results Conclusion Additional Info Search Space Basics SearchSpace Class Creating a search space for hyperparameters. Using “SearchSpace” for predefined configurations Using SearchSpace for Custom Configs SearchSpace for YAML files Conclusion Hyperparameter Optimization Importing libraries Configurations Defining a CNN Model Search Space Parallel Configuration Importing the dataset Creating Ray Cluster ParallelTrainer. Visualizing results w.r.t experiments Conclusion Experiment output directory Interpreting Results Importing Libraries. To create pandas dataframe Generating results Plotting graphs Analysis Linearplots Violinplots Observations Conclusion More examples Intermediate Tutorials Search space for different types of optimizers and schedulers For different optimizers For different Schedulers Conclusion Indices and tables# Index Module Index Search Page