DeepOBS
develop
User Guide
Quick Start
Installation
Set-Up Data Sets
Contributing to DeepOBS
Simple Example
Create new Run Script
Run new Optimizer
Analyzing the Runs
Overview
Data Downloading
Data Loading
Model Loading
Runners
Baseline Results
Runtime Estimation
Visualization
Suggested Protocol
Decide for a Framework
Create new Run Script
(Possibly) Write Your Own Runner
Identify Tunable Hyperparameters
Decide for a Tuning Method
Specify the Tuning Domain
Bound the Tuning Resources
Report Stochasticity
Run on a Variety of Test Problems
Plot Results
Report Measures for Speed
How to Write Customized Runner
Decide for a Framework
Implement the Training Loop
Read in Hyperparameters and Training Parameters from the Command Line
Specify How the Hyperparameters and Training Parameters Should Be Added to the Run Name
Tuning Automation
Grid Search
Random Search
Bayesian Optimization (GP)
API Reference
Analyzer
Validate Output
Plot Optimizer Performances
Get the Best Runs
Plot Hyperparameter Sensitivity
Estimate Runtime
TensorFlow
Data Sets
2D Data Set
Quadratic Data Set
MNIST Data Set
FMNIST Data Set
CIFAR-10 Data Set
CIFAR-100 Data Set
SVHN Data Set
ImageNet Data Set
Tolstoi Data Set
Test Problems
2D Test Problems
2D Beale
2D Branin
2D Rosenbrock
Quadratic Test Problems
Quadratic Deep
MNIST Test Problems
MNIST LogReg
MNIST MLP
MNIST 2c2d
MNIST VAE
Fashion-MNIST Test Problems
Fashion-MNIST LogReg
Fashion-MNIST MLP
Fashion-MNIST 2c2d
Fashion-MNIST VAE
CIFAR-10 Test Problems
CIFAR-10 3c3d
CIFAR-10 VGG16
CIFAR-10 VGG19
CIFAR-100 Test Problems
CIFAR-100 3c3d
CIFAR-100 VGG16
CIFAR-100 VGG19
CIFAR-100 All-CNN-C
CIFAR-100 WideResNet 40-4
SVHN Test Problems
SVHN 3c3d
SVHN WideResNet 16-4
ImageNet Test Problems
ImageNet VGG16
ImageNet VGG19
ImageNet Inception v3
Tolstoi Test Problems
Tolstoi Char RNN
Runner
TF Runner
Standard Runner
Learning Rate Schedule Runner
Config
PyTorch
Data Sets
Quadratic Data Set
MNIST Data Set
FMNIST Data Set
CIFAR-10 Data Set
CIFAR-100 Data Set
SVHN Data Set
Tolstoi Data Set
Test Problems
Quadratic Test Problems
Quadratic Deep
MNIST Test Problems
MNIST MLP
MNIST 2c2d
MNIST VAE
Fashion-MNIST Test Problems
Fashion-MNIST MLP
Fashion-MNIST 2c2d
Fashion-MNIST VAE
CIFAR-10 Test Problems
CIFAR-10 3c3d
CIFAR-100 Test Problems
CIFAR-100 3c3d
CIFAR-100 All-CNN-C
SVHN Test Problems
SVHN Wide Resnet
Runner
PT Runner
Standard Runner
Learning Rate Schedule Runner
Config
Tuner
Grid Search
Random Search
Gaussian Process
Tuner
Parallelized Tuner
Tuning Utilities
General Utilities
Bayesian Specific Utilities
Scripts
Prepare Data
Named Arguments
Download Baselines
Named Arguments
Plot Results
Positional Arguments
Named Arguments
Config
DeepOBS
Docs
»
PyTorch
»
Test Problems
»
CIFAR-10 Test Problems
Edit on GitHub
CIFAR-10 Test Problems
ΒΆ
Test Problems
CIFAR-10 3c3d
Read the Docs
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Versions
stable
v1.2.0-beta0_a
v1.1.2
v1.1.1
v1.1.0
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Downloads
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