Merge branch 'develop' of https://github.com/gizatechxyz/orion into d…

…evelop
chachaleo · Dec 21, 2023 · 63c0a8c · 63c0a8c
2 parents b59b9be + 5e5634f
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diff --git a/docgen/src/main.rs b/docgen/src/main.rs
@@ -58,6 +58,14 @@ fn main() {
     let trait_name: &str = "TreeEnsembleRegressorTrait";
     doc_trait(trait_path, doc_path, label);
     doc_functions(trait_path, doc_path, trait_name, label);
+
+    // LINEAR REGRESSOR DOC
+    let trait_path = "src/operators/ml/linear/linear_regressor.cairo";
+    let doc_path = "docs/framework/operators/machine-learning/linear-regressor";
+    let label = "linear_regressor";
+    let trait_name: &str = "LinearRegressorTrait";
+    doc_trait(trait_path, doc_path, label);
+    doc_functions(trait_path, doc_path, trait_name, label);
 }
 
 fn doc_trait(trait_path: &str, doc_path: &str, label: &str) {

diff --git a/docs/.gitbook/assets/ORION_tutorial (1) (1).png b/docs/.gitbook/assets/ORION_tutorial (1) (1).png
diff --git a/docs/.gitbook/assets/ORION_tutorial (1).png b/docs/.gitbook/assets/ORION_tutorial (1).png
diff --git a/docs/.gitbook/assets/accuracy.png b/docs/.gitbook/assets/accuracy.png
diff --git a/docs/.gitbook/assets/forecasts.png b/docs/.gitbook/assets/forecasts.png
diff --git a/docs/.gitbook/assets/tutorial#1.png b/docs/.gitbook/assets/tutorial#1.png
diff --git a/docs/.gitbook/assets/tutorial#2.png b/docs/.gitbook/assets/tutorial#2.png
diff --git a/docs/.gitbook/assets/tutorial#3.png b/docs/.gitbook/assets/tutorial#3.png
diff --git a/docs/.gitbook/assets/tutorial#5 (1).png b/docs/.gitbook/assets/tutorial#5 (1).png
diff --git a/docs/.gitbook/assets/tutorial#5.png b/docs/.gitbook/assets/tutorial#5.png
diff --git a/docs/CHANGELOG.md b/docs/CHANGELOG.md
@@ -4,6 +4,12 @@ All notable changes to this project will be documented in this file.
 
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/), and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
+
+## [Unreleased] - 2023-12-14
+
+## Added
+- Gather ND Operator.
+
 ## [Unreleased] - 2023-12-01
 
 ## Added 

diff --git a/docs/SUMMARY.md b/docs/SUMMARY.md
@@ -109,6 +109,7 @@
     * [tensor.reduce\_l1](framework/operators/tensor/tensor.reduce\_l1.md)
     * [tensor.reduce\_prod](framework/operators/tensor/tensor.reduce\_prod.md)
     * [tensor.gather\_elements](framework/operators/tensor/tensor.gather\_elements.md)
+    * [tensor.gather\_nd](framework/operators/tensor/tensor.gather\_nd.md)
     * [tensor.sequence\_length](framework/operators/tensor/tensor.sequence\_length.md)
     * [tensor.sequence\_at](framework/operators/tensor/tensor.sequence\_at.md)
     * [tensor.reduce\_min](framework/operators/tensor/tensor.reduce\_min.md)
@@ -155,3 +156,4 @@
   * [Verifiable Linear Regression Model](academy/tutorials/verifiable-linear-regression-model-in-orion.md)
   * [Verifiable Support Vector Machine](academy/tutorials/verifiable-support-vector-machine.md)
   * [Verifiable Principal Components Analysis](academy/tutorials/verifiable-principal-components-analysis.md)
+  * [Provable MLR: Forecasting AAVE's Lifetime Repayments](academy/tutorials/provable-mlr-forecasting-aaves-lifetime-repayments.md)
diff --git a/docs/academy/tutorials/README.md b/docs/academy/tutorials/README.md
@@ -2,6 +2,12 @@
 
 Learn how to use Orion with tutorials. We encourage you to contribute by sharing your own tutorial.
 
+## [Provable Multiple Linear Regression Solver: Forecasting AAVE's Lifetime Repayments](provable-mlr-forecasting-aaves-lifetime-repayments.md)
+
+For this particular tutorial, we will build a Closed-Form Multiple Linear Regression algorithm and use it to forecast AAVE's (WETH Pool) future projected Lifetime Repayments as a practical example. Towards the second half-end of the tutorial, we will convert the model to Cairo enabling us to make the entire MLR system as well as the forecasts fully provable & verifiable.
+
+_December 21, 2023 - Bem Baraki_
+
 ## [Verifiable Principal Components Analysis](verifiable-principal-components-analysis.md)
 
 The Principal Component Analysis (PCA) method is an unsupervised learning algorithm that aims to reduce the dimensionality of a dataset consisting of a large number of interrelated variables, while at the same time preserving as much of the variation present in the original dataset as possible.

diff --git a/docs/academy/tutorials/implement-new-operators-in-orion.md b/docs/academy/tutorials/implement-new-operators-in-orion.md
@@ -1,6 +1,6 @@
 # Implement new operators in Orion
 
-<figure><img src="../../.gitbook/assets/article_header_ORION.png" alt=""><figcaption></figcaption></figure>
+<figure><img src="../../.gitbook/assets/tutorial#2.png" alt=""><figcaption></figcaption></figure>
 
 The Orion Framework offers an open-source ONNX runtime implementation for Validity and ZK Machine Learning. Are you interested in contributing? We sincerely appreciate your interest. This is exactly how we'll build a robust and transparent AI ecosystem! In this tutorial, you'll learn how to contribute to the [Orion repository](https://github.com/gizatechxyz/orion) by implementing from scratch a new operator.
 

diff --git a/docs/academy/tutorials/mnist-classification-with-orion.md b/docs/academy/tutorials/mnist-classification-with-orion.md
@@ -1,6 +1,6 @@
 # MNIST Classification with Orion
 
-<figure><img src="../../.gitbook/assets/photo_2023-06-14_13-50-17.jpg" alt=""><figcaption></figcaption></figure>
+<figure><img src="../../.gitbook/assets/tutorial#1.png" alt=""><figcaption></figcaption></figure>
 
 Orion is a dedicated Cairo-based library designed specifically to build machine learning models for ValidityML. Its purpose is to facilitate verifiable inference. For better performance we will operate with an 8-bit quantized model. In this tutorial, you will be guided on how to train your model using Quantized Aware Training using MNIST dataset, how to convert your pre-trained model to Cairo 1, and how to perform inference with Orion.
 
@@ -537,7 +537,7 @@ fn fc1(i: Tensor<i32>, w: Tensor<i32>, b: Tensor<i32>) -> Tensor<i32> {
 
 #### Dense Layer 2
 
-In a similar way, we can build the second layer `fc2`, which contains a [Linear](../../framework/operators/neural-network/nn.linear.md) function and a [Softmax](../../framework/operators/neural-network/nn.softmax.md) from [NNTrait](../../framework/operators/neural-network/). We could convert the tensor to fixed point in order to perform softmax, but for this simple tutorial it's not necessary.&#x20;
+In a similar way, we can build the second layer `fc2`, which contains a [Linear](../../framework/operators/neural-network/nn.linear.md) function and a [Softmax](../../framework/operators/neural-network/nn.softmax.md) from [NNTrait](../../framework/operators/neural-network/). We could convert the tensor to fixed point in order to perform softmax, but for this simple tutorial it's not necessary.
 
 ```rust
 use orion::operators::tensor::core::Tensor;