ECGAN
Contents
Get started
Setup and first steps
Setting up tracking (W&B)
Setting up kaggle [Optional]
Setting up S3/BOTO
Framework Structure
General overview
Run models using the CLI
Managing the workflow
Implement Your Own Usecase
Supported Methods and Datasets
Supported Datasets
Supported Preprocessing
Supported Training
Supported Models
Supported trackers
Further downstream tasks
Preprocessing
Data Synthesis
Anomaly Detection
AnoGAN
Python API
CLI
Manager
Config
Custom Dataclasses
Global configuration
Config initializations
Nested Dataclasses
Preprocessing
Cleansing
Data Retrieval
Preprocessor
Sampling
Training
Dataset Structures
Trainer
Modules
Base Module
Generative Modules
Autoencoder GAN
Generative Base Modules
DCGAN
Recurrent DCGAN
RGAN
VAEGAN
Classification Modules
Base classifier
NN Classifier
Inverse Mappings
Inverse Mapping
Base Inverse Mapping
Simple Inverse Mapping
Networks
Anomaly Detection
Anomaly Assessment
Anomaly Manager
Embedders
Reconstruction
Detectors
Base Detector
Classification Detector
Detector Factory
Reconstruction Detector
Evaluation
Metrics
Optimization
Tracker
Visualization
Evaluation visualization
Plotter
Utils
Tracking artifacts
Configurable
Custom Types
Datasets
Role in the ECGAN Pipeline
Adding new Datasets
Distances
Custom distributions
Embeddings
Interpolation
Label
Layers
Logging
Loss functions
Miscellaneous
Optimizer
Parser options for the CLI commands
Plotting helpers
Reconstruction Criteria
Sampler
Splitting
Timer
Transformation
References
Related Work
Data
Related Modules
About
Goal
Contributing
Get started with the development
Improving Baselines
Adding Modules
ECGAN
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ECGAN Python API
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Training
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Training
Classes and functions related to training PyTorch based models.
Dataset Structures
Trainer