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chore: reorg cifar usecases #245

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Sep 21, 2023
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12 changes: 6 additions & 6 deletions .github/workflows/refresh-one-notebook.yaml
Original file line number Diff line number Diff line change
Expand Up @@ -50,10 +50,10 @@ env:
ACTION_RUN_URL: ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}
# --- refresh_notebooks_list.py: refresh list of notebook paths currently available [START] ---
# --- do not edit, auto generated part by `make refresh_notebooks_list` ---
Cifar10: "use_case_examples/cifar_brevitas_with_model_splitting/Cifar10.ipynb"
CifarInFhe: "use_case_examples/cifar_brevitas_finetuning/CifarInFhe.ipynb"
CifarInFheWithSmallerAccumulators: "use_case_examples/cifar_brevitas_finetuning/CifarInFheWithSmallerAccumulators.ipynb"
CifarQuantizationAwareTraining: "use_case_examples/cifar_brevitas_finetuning/CifarQuantizationAwareTraining.ipynb"
Cifar10: "use_case_examples/cifar/cifar_brevitas_with_model_splitting/Cifar10.ipynb"
CifarInFhe: "use_case_examples/cifar/cifar_brevitas_finetuning/CifarInFhe.ipynb"
CifarInFheWithSmallerAccumulators: "use_case_examples/cifar/cifar_brevitas_finetuning/CifarInFheWithSmallerAccumulators.ipynb"
CifarQuantizationAwareTraining: "use_case_examples/cifar/cifar_brevitas_finetuning/CifarQuantizationAwareTraining.ipynb"
ClassifierComparison: "docs/advanced_examples/ClassifierComparison.ipynb"
ClientServer: "docs/advanced_examples/ClientServer.ipynb"
ConvolutionalNeuralNetwork: "docs/advanced_examples/ConvolutionalNeuralNetwork.ipynb"
Expand All @@ -62,7 +62,7 @@ env:
DecisionTreeRegressor: "docs/advanced_examples/DecisionTreeRegressor.ipynb"
Deployment: "docs/advanced_examples/Deployment.ipynb"
ExperimentPrivacyTreePaper: "docs/advanced_examples/ExperimentPrivacyTreePaper.ipynb"
FromImageNetToCifar: "use_case_examples/cifar_brevitas_finetuning/FromImageNetToCifar.ipynb"
FromImageNetToCifar: "use_case_examples/cifar/cifar_brevitas_finetuning/FromImageNetToCifar.ipynb"
FullyConnectedNeuralNetwork: "docs/advanced_examples/FullyConnectedNeuralNetwork.ipynb"
FullyConnectedNeuralNetworkOnMNIST: "docs/advanced_examples/FullyConnectedNeuralNetworkOnMNIST.ipynb"
GLMComparison: "docs/advanced_examples/GLMComparison.ipynb"
Expand All @@ -72,7 +72,7 @@ env:
LinearSVR: "docs/advanced_examples/LinearSVR.ipynb"
LogisticRegression: "docs/advanced_examples/LogisticRegression.ipynb"
MnistInFHE: "use_case_examples/mnist/MnistInFHE.ipynb"
PerrorImpactOnFMNIST: "use_case_examples/cifar_brevitas_finetuning/PerrorImpactOnFMNIST.ipynb"
PerrorImpactOnFMNIST: "use_case_examples/cifar/cifar_brevitas_finetuning/PerrorImpactOnFMNIST.ipynb"
PoissonRegression: "docs/advanced_examples/PoissonRegression.ipynb"
QGPT2Evaluate: "use_case_examples/llm/QGPT2Evaluate.ipynb"
QuantFrameworkExample: "use_case_examples/llm/QuantFrameworkExample.ipynb"
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2 changes: 1 addition & 1 deletion use_case_examples/cifar/README.md
Original file line number Diff line number Diff line change
@@ -1,6 +1,6 @@
# CIFAR-10 and CIFAR-100 Classification with FHE

This repository provides resources and documentation on different use-cases for classifying CIFAR-10 and CIFAR-100 images using Fully Homomorphic Encryption (FHE). Each use-case demonstrates different techniques and adaptations to work within the constraints of FHE.
This repository provides resources and documentation on different use-cases for classifying CIFAR-10 and CIFAR-100 images using Fully Homomorphic Encryption (FHE). Each use-case demonstrates different techniques and adaptations to work within the constraints of FHE.Notably, a fine-tuning from a public pre-trained model, a training from scratch using quantization aware traiing (QAT) and finally a hybrid approach where only a subset of the model is done in FHE.
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## Table of Contents

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