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| scarb 2.4.0 |
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23 changes: 23 additions & 0 deletions
23
docs/framework/operators/machine-learning/linear-classifier/README.md
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| # Linear Classifier | ||
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| `LinearClassifierTrait` provides a trait definition for linear classification problem. | ||
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| ```rust | ||
| use orion::operators::ml::LinearClassificationTrait; | ||
| ``` | ||
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| ### Data types | ||
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| Orion supports currently only fixed point data types for `LinearClassificationTrait`. | ||
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| | Data type | dtype | | ||
| | -------------------- | ------------------------------------------------------------- | | ||
| | Fixed point (signed) | `LinearClassifierTrait<FP8x23 \| FP16x16 \| FP64x64 \| FP32x32>` | | ||
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| *** | ||
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| | function | description | | ||
| | --- | --- | | ||
| | [`linear_classifier.predict`](linear_classifier.predict.md) | Performs the linear classification. | | ||
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...ework/operators/machine-learning/linear-classifier/linear_classifier.predict.md
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| # LinearClassifierTrait::predict | ||
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| ```rust | ||
| fn predict(ref self: LinearClassifier<T>, X: Tensor<T>) -> Tensor<T>; | ||
| ``` | ||
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| Linear Classifier. Performs the linear classification. | ||
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| ## Args | ||
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| * `self`: LinearClassifier<T> - A LinearClassifier object. | ||
| * `X`: Input 2D tensor. | ||
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| ## Returns | ||
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| * Tensor<T> containing the linear classification evaluation of the input X. | ||
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| ## Type Constraints | ||
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| `LinearClassifier` and `X` must be fixed points | ||
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| ## Examples | ||
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| ```rust | ||
| use orion::numbers::FP16x16; | ||
| use orion::operators::tensor::{Tensor, TensorTrait, FP16x16Tensor, U32Tensor}; | ||
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| use orion::operators::ml::linear::linear_classifier::{ | ||
| LinearClassifierTrait, POST_TRANSFORM, LinearClassifier | ||
| }; | ||
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| fn linear_classifier_helper( | ||
| post_transform: POST_TRANSFORM | ||
| ) -> (LinearClassifier<FP16x16>, Tensor<FP16x16>) { | ||
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| let classlabels: Span<usize> = array![0, 1, 2].span(); | ||
| let classlabels = Option::Some(classlabels); | ||
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| let classlabels_strings: Option<Span<FP16x16>> = Option::None; | ||
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| let coefficients: Span<FP16x16> = array![ | ||
| FP16x16 { mag: 38011, sign: true }, | ||
| FP16x16 { mag: 19005, sign: true }, | ||
| FP16x16 { mag: 5898, sign: true }, | ||
| FP16x16 { mag: 38011, sign: false }, | ||
| FP16x16 { mag: 19005, sign: false }, | ||
| FP16x16 { mag: 5898, sign: false }, | ||
| ] | ||
| .span(); | ||
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| let intercepts: Span<FP16x16> = array![ | ||
| FP16x16 { mag: 176947, sign: false }, | ||
| FP16x16 { mag: 176947, sign: true }, | ||
| FP16x16 { mag: 32768, sign: false }, | ||
| ] | ||
| .span(); | ||
| let intercepts = Option::Some(intercepts); | ||
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| let multi_class: usize = 0; | ||
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| let mut classifier: LinearClassifier<FP16x16> = LinearClassifier { | ||
| classlabels, | ||
| coefficients, | ||
| intercepts, | ||
| multi_class, | ||
| post_transform | ||
| }; | ||
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| let mut X: Tensor<FP16x16> = TensorTrait::new( | ||
| array![3, 2].span(), | ||
| array![ | ||
| FP16x16 { mag: 0, sign: false }, | ||
| FP16x16 { mag: 65536, sign: false }, | ||
| FP16x16 { mag: 131072, sign: false }, | ||
| FP16x16 { mag: 196608, sign: false }, | ||
| FP16x16 { mag: 262144, sign: false }, | ||
| FP16x16 { mag: 327680, sign: false }, | ||
| ] | ||
| .span() | ||
| ); | ||
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| (classifier, X) | ||
| } | ||
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| fn linear_classifier_multi_softmax() -> (Span<usize>, Tensor<FP16x16>) { | ||
| let (mut classifier, X) = linear_classifier_helper(POST_TRANSFORM::SOFTMAX); | ||
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| let (labels, mut scores) = LinearClassifierTrait::predict(ref classifier, X); | ||
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| (labels, scores) | ||
| } | ||
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| >>> | ||
| ([0, 2, 2], | ||
| [ | ||
| [0.852656, 0.009192, 0.138152], | ||
| [0.318722, 0.05216, 0.629118], | ||
| [0.036323, 0.090237, 0.87344] | ||
| ]) | ||
| ``` |
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docs/framework/operators/machine-learning/svm-regressor/README.md
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| # SVM Regressor | ||
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| `SVMRegressorTrait` provides a trait definition for svm regression problem. | ||
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| ```rust | ||
| use orion::operators::ml::SVMRegressorTrait; | ||
| ``` | ||
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| ### Data types | ||
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| Orion supports currently only fixed point data types for `SVMRegressorTrait`. | ||
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| | Data type | dtype | | ||
| | -------------------- | ------------------------------------------------------------- | | ||
| | Fixed point (signed) | `SVMRegressorTrait<FP8x23 \| FP16x16 \| FP64x64 \| FP32x32>` | | ||
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| *** | ||
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| | function | description | | ||
| | --- | --- | | ||
| | [`svm_regressor.predict`](svm_regressor.predict.md) | Returns the regressed values for each input in N. | | ||
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