From b90962020c1bc377120c05bcff11755620bfe1d4 Mon Sep 17 00:00:00 2001 From: Zama Bot <64638994+zama-bot@users.noreply.github.com> Date: Sat, 28 Sep 2024 22:09:01 +0200 Subject: [PATCH] Prepare release 1.7.0 (#900) Co-authored-by: andrei-stoian-zama <95410270+andrei-stoian-zama@users.noreply.github.com> --- ...ncrete.ml.quantization.quantized_module.md | 18 +- .../api/concrete.ml.sklearn.base.md | 208 +++++++++--------- 2 files changed, 113 insertions(+), 113 deletions(-) diff --git a/docs/references/api/concrete.ml.quantization.quantized_module.md b/docs/references/api/concrete.ml.quantization.quantized_module.md index 71275b531..668c1c7b1 100644 --- a/docs/references/api/concrete.ml.quantization.quantized_module.md +++ b/docs/references/api/concrete.ml.quantization.quantized_module.md @@ -68,7 +68,7 @@ Get the post-processing parameters. ______________________________________________________________________ - + ### method `bitwidth_and_range_report` @@ -100,7 +100,7 @@ Check if the quantized module is compiled. ______________________________________________________________________ - + ### method `compile` @@ -142,7 +142,7 @@ Compile the module's forward function. ______________________________________________________________________ - + ### method `dequantize_output` @@ -210,7 +210,7 @@ Dump itself to a string. ______________________________________________________________________ - + ### method `forward` @@ -258,7 +258,7 @@ Load itself from a string. ______________________________________________________________________ - + ### method `post_processing` @@ -280,7 +280,7 @@ For quantized modules, there is no post-processing step but the method is kept t ______________________________________________________________________ - + ### method `pre_processing` @@ -300,7 +300,7 @@ Apply pre-processing to the input values. ______________________________________________________________________ - + ### method `quantize_input` @@ -322,7 +322,7 @@ Take the inputs in fp32 and quantize it using the learned quantization parameter ______________________________________________________________________ - + ### method `quantized_forward` @@ -346,7 +346,7 @@ Forward function for the FHE circuit. ______________________________________________________________________ - + ### method `set_inputs_quantization_parameters` diff --git a/docs/references/api/concrete.ml.sklearn.base.md b/docs/references/api/concrete.ml.sklearn.base.md index 30e8c2252..a27480819 100644 --- a/docs/references/api/concrete.ml.sklearn.base.md +++ b/docs/references/api/concrete.ml.sklearn.base.md @@ -314,7 +314,7 @@ Load itself from a dict. ______________________________________________________________________ - + ### method `post_processing` @@ -384,7 +384,7 @@ This step ensures that the fit method has been called. ______________________________________________________________________ - + ## class `BaseClassifier` @@ -612,7 +612,7 @@ Dump itself to a string. ______________________________________________________________________ - + ### method `fit` @@ -691,7 +691,7 @@ Load itself from a dict. ______________________________________________________________________ - + ### method `post_processing` @@ -701,7 +701,7 @@ post_processing(y_preds: 'ndarray') → ndarray ______________________________________________________________________ - + ### method `predict` @@ -714,7 +714,7 @@ predict( ______________________________________________________________________ - + ### method `predict_proba` @@ -760,13 +760,13 @@ This step ensures that the fit method has been called. ______________________________________________________________________ - + ## class `QuantizedTorchEstimatorMixin` Mixin that provides quantization for a torch module and follows the Estimator API. - + ### method `__init__` @@ -874,7 +874,7 @@ Check if the model is fitted. ______________________________________________________________________ - + ### method `compile` @@ -893,7 +893,7 @@ compile( ______________________________________________________________________ - + ### method `dequantize_output` @@ -951,7 +951,7 @@ Dump itself to a string. ______________________________________________________________________ - + ### method `fit` @@ -976,7 +976,7 @@ The fitted estimator. ______________________________________________________________________ - + ### method `fit_benchmark` @@ -1007,7 +1007,7 @@ The Concrete ML and equivalent skorch fitted estimators. ______________________________________________________________________ - + ### method `get_params` @@ -1029,7 +1029,7 @@ This method is overloaded in order to make sure that auto-computed parameters ar ______________________________________________________________________ - + ### method `get_sklearn_params` @@ -1059,7 +1059,7 @@ Load itself from a dict. ______________________________________________________________________ - + ### method `post_processing` @@ -1093,7 +1093,7 @@ Predict values for X, in FHE or in the clear. ______________________________________________________________________ - + ### method `prune` @@ -1121,7 +1121,7 @@ A new pruned copy of the Neural Network model. ______________________________________________________________________ - + ### method `quantize_input` @@ -1131,7 +1131,7 @@ quantize_input(X: 'ndarray') → ndarray ______________________________________________________________________ - + ## class `BaseTreeEstimatorMixin` @@ -1139,7 +1139,7 @@ Mixin class for tree-based estimators. This class inherits from sklearn.base.BaseEstimator in order to have access to scikit-learn's `get_params` and `set_params` methods. - + ### method `__init__` @@ -1233,7 +1233,7 @@ Check if the model is fitted. ______________________________________________________________________ - + ### method `compile` @@ -1243,7 +1243,7 @@ compile(*args, **kwargs) → Circuit ______________________________________________________________________ - + ### method `dequantize_output` @@ -1301,7 +1301,7 @@ Dump itself to a string. ______________________________________________________________________ - + ### method `fit` @@ -1338,7 +1338,7 @@ The Concrete ML and float equivalent fitted estimators. ______________________________________________________________________ - + ### classmethod `from_sklearn_model` @@ -1407,7 +1407,7 @@ Load itself from a dict. ______________________________________________________________________ - + ### method `post_processing` @@ -1417,7 +1417,7 @@ post_processing(y_preds: 'ndarray') → ndarray ______________________________________________________________________ - + ### method `predict` @@ -1430,7 +1430,7 @@ predict( ______________________________________________________________________ - + ### method `quantize_input` @@ -1440,7 +1440,7 @@ quantize_input(X: 'ndarray') → ndarray ______________________________________________________________________ - + ## class `BaseTreeRegressorMixin` @@ -1448,7 +1448,7 @@ Mixin class for tree-based regressors. This class is used to create a tree-based regressor class that inherits from sklearn.base.RegressorMixin, which essentially gives access to scikit-learn's `score` method for regressors. - + ### method `__init__` @@ -1542,7 +1542,7 @@ Check if the model is fitted. ______________________________________________________________________ - + ### method `compile` @@ -1552,7 +1552,7 @@ compile(*args, **kwargs) → Circuit ______________________________________________________________________ - + ### method `dequantize_output` @@ -1610,7 +1610,7 @@ Dump itself to a string. ______________________________________________________________________ - + ### method `fit` @@ -1647,7 +1647,7 @@ The Concrete ML and float equivalent fitted estimators. ______________________________________________________________________ - + ### classmethod `from_sklearn_model` @@ -1716,7 +1716,7 @@ Load itself from a dict. ______________________________________________________________________ - + ### method `post_processing` @@ -1726,7 +1726,7 @@ post_processing(y_preds: 'ndarray') → ndarray ______________________________________________________________________ - + ### method `predict` @@ -1739,7 +1739,7 @@ predict( ______________________________________________________________________ - + ### method `quantize_input` @@ -1749,7 +1749,7 @@ quantize_input(X: 'ndarray') → ndarray ______________________________________________________________________ - + ## class `BaseTreeClassifierMixin` @@ -1759,7 +1759,7 @@ This class is used to create a tree-based classifier class that inherits from sk Additionally, this class adjusts some of the tree-based base class's methods in order to make them compliant with classification workflows. - + ### method `__init__` @@ -1877,7 +1877,7 @@ Check if the model is fitted. ______________________________________________________________________ - + ### method `compile` @@ -1887,7 +1887,7 @@ compile(*args, **kwargs) → Circuit ______________________________________________________________________ - + ### method `dequantize_output` @@ -1945,7 +1945,7 @@ Dump itself to a string. ______________________________________________________________________ - + ### method `fit` @@ -1982,7 +1982,7 @@ The Concrete ML and float equivalent fitted estimators. ______________________________________________________________________ - + ### classmethod `from_sklearn_model` @@ -2051,7 +2051,7 @@ Load itself from a dict. ______________________________________________________________________ - + ### method `post_processing` @@ -2061,7 +2061,7 @@ post_processing(y_preds: 'ndarray') → ndarray ______________________________________________________________________ - + ### method `predict` @@ -2074,7 +2074,7 @@ predict( ______________________________________________________________________ - + ### method `predict_proba` @@ -2098,7 +2098,7 @@ Predict class probabilities. ______________________________________________________________________ - + ### method `quantize_input` @@ -2108,7 +2108,7 @@ quantize_input(X: 'ndarray') → ndarray ______________________________________________________________________ - + ## class `SklearnLinearModelMixin` @@ -2116,7 +2116,7 @@ A Mixin class for sklearn linear models with FHE. This class inherits from sklearn.base.BaseEstimator in order to have access to scikit-learn's `get_params` and `set_params` methods. - + ### method `__init__` @@ -2246,7 +2246,7 @@ Compile the model. ______________________________________________________________________ - + ### method `dequantize_output` @@ -2304,7 +2304,7 @@ Dump itself to a string. ______________________________________________________________________ - + ### method `fit` @@ -2341,7 +2341,7 @@ The Concrete ML and float equivalent fitted estimators. ______________________________________________________________________ - + ### classmethod `from_sklearn_model` @@ -2410,7 +2410,7 @@ Load itself from a dict. ______________________________________________________________________ - + ### method `post_processing` @@ -2458,7 +2458,7 @@ Predict values for X, in FHE or in the clear. ______________________________________________________________________ - + ### method `quantize_input` @@ -2468,7 +2468,7 @@ quantize_input(X: 'ndarray') → ndarray ______________________________________________________________________ - + ## class `SklearnLinearRegressorMixin` @@ -2476,7 +2476,7 @@ A Mixin class for sklearn linear regressors with FHE. This class is used to create a linear regressor class that inherits from sklearn.base.RegressorMixin, which essentially gives access to scikit-learn's `score` method for regressors. - + ### method `__init__` @@ -2606,7 +2606,7 @@ Compile the model. ______________________________________________________________________ - + ### method `dequantize_output` @@ -2664,7 +2664,7 @@ Dump itself to a string. ______________________________________________________________________ - + ### method `fit` @@ -2701,7 +2701,7 @@ The Concrete ML and float equivalent fitted estimators. ______________________________________________________________________ - + ### classmethod `from_sklearn_model` @@ -2770,7 +2770,7 @@ Load itself from a dict. ______________________________________________________________________ - + ### method `post_processing` @@ -2818,7 +2818,7 @@ Predict values for X, in FHE or in the clear. ______________________________________________________________________ - + ### method `quantize_input` @@ -2828,7 +2828,7 @@ quantize_input(X: 'ndarray') → ndarray ______________________________________________________________________ - + ## class `SklearnLinearClassifierMixin` @@ -2838,7 +2838,7 @@ This class is used to create a linear classifier class that inherits from sklear Additionally, this class adjusts some of the tree-based base class's methods in order to make them compliant with classification workflows. - + ### method `__init__` @@ -2992,7 +2992,7 @@ Compile the model. ______________________________________________________________________ - + ### method `decision_function` @@ -3016,7 +3016,7 @@ Predict confidence scores. ______________________________________________________________________ - + ### method `dequantize_output` @@ -3074,7 +3074,7 @@ Dump itself to a string. ______________________________________________________________________ - + ### method `fit` @@ -3111,7 +3111,7 @@ The Concrete ML and float equivalent fitted estimators. ______________________________________________________________________ - + ### classmethod `from_sklearn_model` @@ -3180,7 +3180,7 @@ Load itself from a dict. ______________________________________________________________________ - + ### method `post_processing` @@ -3190,7 +3190,7 @@ post_processing(y_preds: 'ndarray') → ndarray ______________________________________________________________________ - + ### method `predict` @@ -3203,7 +3203,7 @@ predict( ______________________________________________________________________ - + ### method `predict_proba` @@ -3216,7 +3216,7 @@ predict_proba( ______________________________________________________________________ - + ### method `quantize_input` @@ -3226,7 +3226,7 @@ quantize_input(X: 'ndarray') → ndarray ______________________________________________________________________ - + ## class `SklearnSGDRegressorMixin` @@ -3234,7 +3234,7 @@ A Mixin class for sklearn SGD regressors with FHE. This class is used to create a SGD regressor class what can be exported to ONNX using Hummingbird. - + ### method `__init__` @@ -3364,7 +3364,7 @@ Compile the model. ______________________________________________________________________ - + ### method `dequantize_output` @@ -3422,7 +3422,7 @@ Dump itself to a string. ______________________________________________________________________ - + ### method `fit` @@ -3459,7 +3459,7 @@ The Concrete ML and float equivalent fitted estimators. ______________________________________________________________________ - + ### classmethod `from_sklearn_model` @@ -3528,7 +3528,7 @@ Load itself from a dict. ______________________________________________________________________ - + ### method `post_processing` @@ -3576,7 +3576,7 @@ Predict values for X, in FHE or in the clear. ______________________________________________________________________ - + ### method `quantize_input` @@ -3586,7 +3586,7 @@ quantize_input(X: 'ndarray') → ndarray ______________________________________________________________________ - + ## class `SklearnSGDClassifierMixin` @@ -3594,7 +3594,7 @@ A Mixin class for sklearn SGD classifiers with FHE. This class is used to create a SGD classifier class what can be exported to ONNX using Hummingbird. - + ### method `__init__` @@ -3748,7 +3748,7 @@ Compile the model. ______________________________________________________________________ - + ### method `decision_function` @@ -3772,7 +3772,7 @@ Predict confidence scores. ______________________________________________________________________ - + ### method `dequantize_output` @@ -3830,7 +3830,7 @@ Dump itself to a string. ______________________________________________________________________ - + ### method `fit` @@ -3867,7 +3867,7 @@ The Concrete ML and float equivalent fitted estimators. ______________________________________________________________________ - + ### classmethod `from_sklearn_model` @@ -3936,7 +3936,7 @@ Load itself from a dict. ______________________________________________________________________ - + ### method `post_processing` @@ -3946,7 +3946,7 @@ post_processing(y_preds: 'ndarray') → ndarray ______________________________________________________________________ - + ### method `predict` @@ -3959,7 +3959,7 @@ predict( ______________________________________________________________________ - + ### method `predict_proba` @@ -3972,7 +3972,7 @@ predict_proba( ______________________________________________________________________ - + ### method `quantize_input` @@ -3982,7 +3982,7 @@ quantize_input(X: 'ndarray') → ndarray ______________________________________________________________________ - + ## class `SklearnKNeighborsMixin` @@ -3990,7 +3990,7 @@ A Mixin class for sklearn KNeighbors models with FHE. This class inherits from sklearn.base.BaseEstimator in order to have access to scikit-learn's `get_params` and `set_params` methods. - + ### method `__init__` @@ -4118,7 +4118,7 @@ Compile the model. ______________________________________________________________________ - + ### method `dequantize_output` @@ -4176,7 +4176,7 @@ Dump itself to a string. ______________________________________________________________________ - + ### method `fit` @@ -4235,7 +4235,7 @@ This method is used to instantiate a scikit-learn model using the Concrete ML mo ______________________________________________________________________ - + ### method `get_topk_labels` @@ -4279,7 +4279,7 @@ Load itself from a dict. ______________________________________________________________________ - + ### method `majority_vote` @@ -4299,7 +4299,7 @@ Determine the most common class among nearest neighborsfor each query. ______________________________________________________________________ - + ### method `post_processing` @@ -4321,7 +4321,7 @@ For KNN, the de-quantization step is not required. Because \_inference returns t ______________________________________________________________________ - + ### method `predict` @@ -4334,7 +4334,7 @@ predict( ______________________________________________________________________ - + ### method `quantize_input` @@ -4344,7 +4344,7 @@ quantize_input(X: 'ndarray') → ndarray ______________________________________________________________________ - + ## class `SklearnKNeighborsClassifierMixin` @@ -4352,7 +4352,7 @@ A Mixin class for sklearn KNeighbors classifiers with FHE. This class is used to create a KNeighbors classifier class that inherits from SklearnKNeighborsMixin and sklearn.base.ClassifierMixin. By inheriting from sklearn.base.ClassifierMixin, it allows this class to be recognized as a classifier." - + ### method `__init__` @@ -4480,7 +4480,7 @@ Compile the model. ______________________________________________________________________ - + ### method `dequantize_output` @@ -4538,7 +4538,7 @@ Dump itself to a string. ______________________________________________________________________ - + ### method `fit` @@ -4597,7 +4597,7 @@ This method is used to instantiate a scikit-learn model using the Concrete ML mo ______________________________________________________________________ - + ### method `get_topk_labels` @@ -4641,7 +4641,7 @@ Load itself from a dict. ______________________________________________________________________ - + ### method `majority_vote` @@ -4661,7 +4661,7 @@ Determine the most common class among nearest neighborsfor each query. ______________________________________________________________________ - + ### method `post_processing` @@ -4683,7 +4683,7 @@ For KNN, the de-quantization step is not required. Because \_inference returns t ______________________________________________________________________ - + ### method `predict` @@ -4696,7 +4696,7 @@ predict( ______________________________________________________________________ - + ### method `quantize_input`