# API

## Modules

* [`concrete.ml.common`](/concrete-ml/1.1/developer-guide/api/concrete.ml.common.md#module-concretemlcommon): Module for shared data structures and code.
* [`concrete.ml.common.check_inputs`](/concrete-ml/1.1/developer-guide/api/concrete.ml.common.check_inputs.md#module-concretemlcommoncheck_inputs): Check and conversion tools.
* [`concrete.ml.common.debugging`](/concrete-ml/1.1/developer-guide/api/concrete.ml.common.debugging.md#module-concretemlcommondebugging): Module for debugging.
* [`concrete.ml.common.debugging.custom_assert`](/concrete-ml/1.1/developer-guide/api/concrete.ml.common.debugging.custom_assert.md#module-concretemlcommondebuggingcustom_assert): Provide some variants of assert.
* [`concrete.ml.common.serialization`](/concrete-ml/1.1/developer-guide/api/concrete.ml.common.serialization.md#module-concretemlcommonserialization): Serialization module.
* [`concrete.ml.common.serialization.decoder`](/concrete-ml/1.1/developer-guide/api/concrete.ml.common.serialization.decoder.md#module-concretemlcommonserializationdecoder): Custom decoder for serialization.
* [`concrete.ml.common.serialization.dumpers`](/concrete-ml/1.1/developer-guide/api/concrete.ml.common.serialization.dumpers.md#module-concretemlcommonserializationdumpers): Dump functions for serialization.
* [`concrete.ml.common.serialization.encoder`](/concrete-ml/1.1/developer-guide/api/concrete.ml.common.serialization.encoder.md#module-concretemlcommonserializationencoder): Custom encoder for serialization.
* [`concrete.ml.common.serialization.loaders`](/concrete-ml/1.1/developer-guide/api/concrete.ml.common.serialization.loaders.md#module-concretemlcommonserializationloaders): Load functions for serialization.
* [`concrete.ml.common.utils`](/concrete-ml/1.1/developer-guide/api/concrete.ml.common.utils.md#module-concretemlcommonutils): Utils that can be re-used by other pieces of code in the module.
* [`concrete.ml.deployment`](/concrete-ml/1.1/developer-guide/api/concrete.ml.deployment.md#module-concretemldeployment): Module for deployment of the FHE model.
* [`concrete.ml.deployment.deploy_to_aws`](/concrete-ml/1.1/developer-guide/api/concrete.ml.deployment.deploy_to_aws.md#module-concretemldeploymentdeploy_to_aws): Methods to deploy a client/server to AWS.
* [`concrete.ml.deployment.deploy_to_docker`](/concrete-ml/1.1/developer-guide/api/concrete.ml.deployment.deploy_to_docker.md#module-concretemldeploymentdeploy_to_docker): Methods to deploy a server using Docker.
* [`concrete.ml.deployment.fhe_client_server`](/concrete-ml/1.1/developer-guide/api/concrete.ml.deployment.fhe_client_server.md#module-concretemldeploymentfhe_client_server): APIs for FHE deployment.
* [`concrete.ml.deployment.server`](/concrete-ml/1.1/developer-guide/api/concrete.ml.deployment.server.md#module-concretemldeploymentserver): Deployment server.
* [`concrete.ml.deployment.utils`](/concrete-ml/1.1/developer-guide/api/concrete.ml.deployment.utils.md#module-concretemldeploymentutils): Utils.
* [`concrete.ml.onnx`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.md#module-concretemlonnx): ONNX module.
* [`concrete.ml.onnx.convert`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.convert.md#module-concretemlonnxconvert): ONNX conversion related code.
* [`concrete.ml.onnx.onnx_impl_utils`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.onnx_impl_utils.md#module-concretemlonnxonnx_impl_utils): Utility functions for onnx operator implementations.
* [`concrete.ml.onnx.onnx_model_manipulations`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.onnx_model_manipulations.md#module-concretemlonnxonnx_model_manipulations): Some code to manipulate models.
* [`concrete.ml.onnx.onnx_utils`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.onnx_utils.md#module-concretemlonnxonnx_utils): Utils to interpret an ONNX model with numpy.
* [`concrete.ml.onnx.ops_impl`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#module-concretemlonnxops_impl): ONNX ops implementation in Python + NumPy.
* [`concrete.ml.pytest`](/concrete-ml/1.1/developer-guide/api/concrete.ml.pytest.md#module-concretemlpytest): Module which is used to contain common functions for pytest.
* [`concrete.ml.pytest.torch_models`](/concrete-ml/1.1/developer-guide/api/concrete.ml.pytest.torch_models.md#module-concretemlpytesttorch_models): Torch modules for our pytests.
* [`concrete.ml.pytest.utils`](/concrete-ml/1.1/developer-guide/api/concrete.ml.pytest.utils.md#module-concretemlpytestutils): Common functions or lists for test files, which can't be put in fixtures.
* [`concrete.ml.quantization`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.md#module-concretemlquantization): Modules for quantization.
* [`concrete.ml.quantization.base_quantized_op`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.base_quantized_op.md#module-concretemlquantizationbase_quantized_op): Base Quantized Op class that implements quantization for a float numpy op.
* [`concrete.ml.quantization.post_training`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.post_training.md#module-concretemlquantizationpost_training): Post Training Quantization methods.
* [`concrete.ml.quantization.quantized_module`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_module.md#module-concretemlquantizationquantized_module): QuantizedModule API.
* [`concrete.ml.quantization.quantized_ops`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#module-concretemlquantizationquantized_ops): Quantized versions of the ONNX operators for post training quantization.
* [`concrete.ml.quantization.quantizers`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantizers.md#module-concretemlquantizationquantizers): Quantization utilities for a numpy array/tensor.
* [`concrete.ml.search_parameters`](/concrete-ml/1.1/developer-guide/api/concrete.ml.search_parameters.md#module-concretemlsearch_parameters): Modules for `p_error` search.
* [`concrete.ml.search_parameters.p_error_search`](/concrete-ml/1.1/developer-guide/api/concrete.ml.search_parameters.p_error_search.md#module-concretemlsearch_parametersp_error_search): p\_error binary search for classification and regression tasks.
* [`concrete.ml.sklearn`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.md#module-concretemlsklearn): Import sklearn models.
* [`concrete.ml.sklearn.base`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.base.md#module-concretemlsklearnbase): Base classes for all estimators.
* [`concrete.ml.sklearn.glm`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.glm.md#module-concretemlsklearnglm): Implement sklearn's Generalized Linear Models (GLM).
* [`concrete.ml.sklearn.linear_model`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.linear_model.md#module-concretemlsklearnlinear_model): Implement sklearn linear model.
* [`concrete.ml.sklearn.qnn`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.qnn.md#module-concretemlsklearnqnn): Scikit-learn interface for fully-connected quantized neural networks.
* [`concrete.ml.sklearn.qnn_module`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.qnn_module.md#module-concretemlsklearnqnn_module): Sparse Quantized Neural Network torch module.
* [`concrete.ml.sklearn.rf`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.rf.md#module-concretemlsklearnrf): Implement RandomForest models.
* [`concrete.ml.sklearn.svm`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.svm.md#module-concretemlsklearnsvm): Implement Support Vector Machine.
* [`concrete.ml.sklearn.tree`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.tree.md#module-concretemlsklearntree): Implement DecisionTree models.
* [`concrete.ml.sklearn.tree_to_numpy`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.tree_to_numpy.md#module-concretemlsklearntree_to_numpy): Implements the conversion of a tree model to a numpy function.
* [`concrete.ml.sklearn.xgb`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.xgb.md#module-concretemlsklearnxgb): Implements XGBoost models.
* [`concrete.ml.torch`](/concrete-ml/1.1/developer-guide/api/concrete.ml.torch.md#module-concretemltorch): Modules for torch to numpy conversion.
* [`concrete.ml.torch.compile`](/concrete-ml/1.1/developer-guide/api/concrete.ml.torch.compile.md#module-concretemltorchcompile): torch compilation function.
* [`concrete.ml.torch.numpy_module`](/concrete-ml/1.1/developer-guide/api/concrete.ml.torch.numpy_module.md#module-concretemltorchnumpy_module): A torch to numpy module.
* [`concrete.ml.version`](/concrete-ml/1.1/developer-guide/api/concrete.ml.version.md#module-concretemlversion): File to manage the version of the package.

## Classes

* [`decoder.ConcreteDecoder`](/concrete-ml/1.1/developer-guide/api/concrete.ml.common.serialization.decoder.md#class-concretedecoder): Custom json decoder to handle non-native types found in serialized Concrete ML objects.
* [`encoder.ConcreteEncoder`](/concrete-ml/1.1/developer-guide/api/concrete.ml.common.serialization.encoder.md#class-concreteencoder): Custom json encoder to handle non-native types found in serialized Concrete ML objects.
* [`utils.FheMode`](/concrete-ml/1.1/developer-guide/api/concrete.ml.common.utils.md#class-fhemode): Enum representing the execution mode.
* [`deploy_to_aws.AWSInstance`](/concrete-ml/1.1/developer-guide/api/concrete.ml.deployment.deploy_to_aws.md#class-awsinstance): AWSInstance.
* [`fhe_client_server.FHEModelClient`](/concrete-ml/1.1/developer-guide/api/concrete.ml.deployment.fhe_client_server.md#class-fhemodelclient): Client API to encrypt and decrypt FHE data.
* [`fhe_client_server.FHEModelDev`](/concrete-ml/1.1/developer-guide/api/concrete.ml.deployment.fhe_client_server.md#class-fhemodeldev): Dev API to save the model and then load and run the FHE circuit.
* [`fhe_client_server.FHEModelServer`](/concrete-ml/1.1/developer-guide/api/concrete.ml.deployment.fhe_client_server.md#class-fhemodelserver): Server API to load and run the FHE circuit.
* [`ops_impl.ONNXMixedFunction`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#class-onnxmixedfunction): A mixed quantized-raw valued onnx function.
* [`ops_impl.RawOpOutput`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#class-rawopoutput): Type construct that marks an ndarray as a raw output of a quantized op.
* [`torch_models.BranchingGemmModule`](/concrete-ml/1.1/developer-guide/api/concrete.ml.pytest.torch_models.md#class-branchinggemmmodule): Torch model with some branching and skip connections.
* [`torch_models.BranchingModule`](/concrete-ml/1.1/developer-guide/api/concrete.ml.pytest.torch_models.md#class-branchingmodule): Torch model with some branching and skip connections.
* [`torch_models.CNN`](/concrete-ml/1.1/developer-guide/api/concrete.ml.pytest.torch_models.md#class-cnn): Torch CNN model for the tests.
* [`torch_models.CNNGrouped`](/concrete-ml/1.1/developer-guide/api/concrete.ml.pytest.torch_models.md#class-cnngrouped): Torch CNN model with grouped convolution for compile torch tests.
* [`torch_models.CNNInvalid`](/concrete-ml/1.1/developer-guide/api/concrete.ml.pytest.torch_models.md#class-cnninvalid): Torch CNN model for the tests.
* [`torch_models.CNNMaxPool`](/concrete-ml/1.1/developer-guide/api/concrete.ml.pytest.torch_models.md#class-cnnmaxpool): Torch CNN model for the tests with a max pool.
* [`torch_models.CNNOther`](/concrete-ml/1.1/developer-guide/api/concrete.ml.pytest.torch_models.md#class-cnnother): Torch CNN model for the tests.
* [`torch_models.ConcatFancyIndexing`](/concrete-ml/1.1/developer-guide/api/concrete.ml.pytest.torch_models.md#class-concatfancyindexing): Concat with fancy indexing.
* [`torch_models.DoubleQuantQATMixNet`](/concrete-ml/1.1/developer-guide/api/concrete.ml.pytest.torch_models.md#class-doublequantqatmixnet): Torch model that with two different quantizers on the input.
* [`torch_models.FC`](/concrete-ml/1.1/developer-guide/api/concrete.ml.pytest.torch_models.md#class-fc): Torch model for the tests.
* [`torch_models.FCSeq`](/concrete-ml/1.1/developer-guide/api/concrete.ml.pytest.torch_models.md#class-fcseq): Torch model that should generate MatMul->Add ONNX patterns.
* [`torch_models.FCSeqAddBiasVec`](/concrete-ml/1.1/developer-guide/api/concrete.ml.pytest.torch_models.md#class-fcseqaddbiasvec): Torch model that should generate MatMul->Add ONNX patterns.
* [`torch_models.FCSmall`](/concrete-ml/1.1/developer-guide/api/concrete.ml.pytest.torch_models.md#class-fcsmall): Torch model for the tests.
* [`torch_models.MultiInputNN`](/concrete-ml/1.1/developer-guide/api/concrete.ml.pytest.torch_models.md#class-multiinputnn): Torch model to test multiple inputs forward.
* [`torch_models.MultiInputNNConfigurable`](/concrete-ml/1.1/developer-guide/api/concrete.ml.pytest.torch_models.md#class-multiinputnnconfigurable): Torch model to test multiple inputs forward.
* [`torch_models.MultiInputNNDifferentSize`](/concrete-ml/1.1/developer-guide/api/concrete.ml.pytest.torch_models.md#class-multiinputnndifferentsize): Torch model to test multiple inputs with different shape in the forward pass.
* [`torch_models.MultiOpOnSingleInputConvNN`](/concrete-ml/1.1/developer-guide/api/concrete.ml.pytest.torch_models.md#class-multioponsingleinputconvnn): Network that applies two quantized operations on a single input.
* [`torch_models.NetWithConcatUnsqueeze`](/concrete-ml/1.1/developer-guide/api/concrete.ml.pytest.torch_models.md#class-netwithconcatunsqueeze): Torch model to test the concat and unsqueeze operators.
* [`torch_models.NetWithConstantsFoldedBeforeOps`](/concrete-ml/1.1/developer-guide/api/concrete.ml.pytest.torch_models.md#class-netwithconstantsfoldedbeforeops): Torch QAT model that does not quantize the inputs.
* [`torch_models.NetWithLoops`](/concrete-ml/1.1/developer-guide/api/concrete.ml.pytest.torch_models.md#class-netwithloops): Torch model, where we reuse some elements in a loop.
* [`torch_models.PaddingNet`](/concrete-ml/1.1/developer-guide/api/concrete.ml.pytest.torch_models.md#class-paddingnet): Torch QAT model that applies various padding patterns.
* [`torch_models.QATTestModule`](/concrete-ml/1.1/developer-guide/api/concrete.ml.pytest.torch_models.md#class-qattestmodule): Torch model that implements a simple non-uniform quantizer.
* [`torch_models.QNNFashionMNIST`](/concrete-ml/1.1/developer-guide/api/concrete.ml.pytest.torch_models.md#class-qnnfashionmnist): A small quantized network with Brevitas for FashionMNIST classification.
* [`torch_models.QuantCustomModel`](/concrete-ml/1.1/developer-guide/api/concrete.ml.pytest.torch_models.md#class-quantcustommodel): A small quantized network with Brevitas, trained on make\_classification.
* [`torch_models.ShapeOperationsNet`](/concrete-ml/1.1/developer-guide/api/concrete.ml.pytest.torch_models.md#class-shapeoperationsnet): Torch QAT model that reshapes the input.
* [`torch_models.SimpleNet`](/concrete-ml/1.1/developer-guide/api/concrete.ml.pytest.torch_models.md#class-simplenet): Fake torch model used to generate some onnx.
* [`torch_models.SimpleQAT`](/concrete-ml/1.1/developer-guide/api/concrete.ml.pytest.torch_models.md#class-simpleqat): Torch model implements a step function that needs Greater, Cast and Where.
* [`torch_models.SingleMixNet`](/concrete-ml/1.1/developer-guide/api/concrete.ml.pytest.torch_models.md#class-singlemixnet): Torch model that with a single conv layer that produces the output, e.g., a blur filter.
* [`torch_models.StepActivationModule`](/concrete-ml/1.1/developer-guide/api/concrete.ml.pytest.torch_models.md#class-stepactivationmodule): Torch model implements a step function that needs Greater, Cast and Where.
* [`torch_models.TinyCNN`](/concrete-ml/1.1/developer-guide/api/concrete.ml.pytest.torch_models.md#class-tinycnn): A very small CNN.
* [`torch_models.TinyQATCNN`](/concrete-ml/1.1/developer-guide/api/concrete.ml.pytest.torch_models.md#class-tinyqatcnn): A very small QAT CNN to classify the sklearn digits data-set.
* [`torch_models.TorchCustomModel`](/concrete-ml/1.1/developer-guide/api/concrete.ml.pytest.torch_models.md#class-torchcustommodel): A small network with Brevitas, trained on make\_classification.
* [`torch_models.TorchSum`](/concrete-ml/1.1/developer-guide/api/concrete.ml.pytest.torch_models.md#class-torchsum): Torch model to test the ReduceSum ONNX operator in a leveled circuit.
* [`torch_models.TorchSumMod`](/concrete-ml/1.1/developer-guide/api/concrete.ml.pytest.torch_models.md#class-torchsummod): Torch model to test the ReduceSum ONNX operator in a circuit containing a PBS.
* [`torch_models.UnivariateModule`](/concrete-ml/1.1/developer-guide/api/concrete.ml.pytest.torch_models.md#class-univariatemodule): Torch model that calls univariate and shape functions of torch.
* [`base_quantized_op.QuantizedMixingOp`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.base_quantized_op.md#class-quantizedmixingop): An operator that mixes (adds or multiplies) together encrypted inputs.
* [`base_quantized_op.QuantizedOp`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.base_quantized_op.md#class-quantizedop): Base class for quantized ONNX ops implemented in numpy.
* [`base_quantized_op.QuantizedOpUnivariateOfEncrypted`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.base_quantized_op.md#class-quantizedopunivariateofencrypted): An univariate operator of an encrypted value.
* [`post_training.ONNXConverter`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.post_training.md#class-onnxconverter): Base ONNX to Concrete ML computation graph conversion class.
* [`post_training.PostTrainingAffineQuantization`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.post_training.md#class-posttrainingaffinequantization): Post-training Affine Quantization.
* [`post_training.PostTrainingQATImporter`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.post_training.md#class-posttrainingqatimporter): Converter of Quantization Aware Training networks.
* [`quantized_module.QuantizedModule`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_module.md#class-quantizedmodule): Inference for a quantized model.
* [`quantized_ops.ONNXConstantOfShape`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-onnxconstantofshape): ConstantOfShape operator.
* [`quantized_ops.ONNXGather`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-onnxgather): Gather operator.
* [`quantized_ops.ONNXShape`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-onnxshape): Shape operator.
* [`quantized_ops.ONNXSlice`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-onnxslice): Slice operator.
* [`quantized_ops.QuantizedAbs`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedabs): Quantized Abs op.
* [`quantized_ops.QuantizedAdd`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedadd): Quantized Addition operator.
* [`quantized_ops.QuantizedAvgPool`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedavgpool): Quantized Average Pooling op.
* [`quantized_ops.QuantizedBatchNormalization`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedbatchnormalization): Quantized Batch normalization with encrypted input and in-the-clear normalization params.
* [`quantized_ops.QuantizedBrevitasQuant`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedbrevitasquant): Brevitas uniform quantization with encrypted input.
* [`quantized_ops.QuantizedCast`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedcast): Cast the input to the required data type.
* [`quantized_ops.QuantizedCelu`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedcelu): Quantized Celu op.
* [`quantized_ops.QuantizedClip`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedclip): Quantized clip op.
* [`quantized_ops.QuantizedConcat`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedconcat): Concatenate operator.
* [`quantized_ops.QuantizedConv`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedconv): Quantized Conv op.
* [`quantized_ops.QuantizedDiv`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizeddiv): Div operator /.
* [`quantized_ops.QuantizedElu`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedelu): Quantized Elu op.
* [`quantized_ops.QuantizedErf`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizederf): Quantized erf op.
* [`quantized_ops.QuantizedExp`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedexp): Quantized Exp op.
* [`quantized_ops.QuantizedFlatten`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedflatten): Quantized flatten for encrypted inputs.
* [`quantized_ops.QuantizedFloor`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedfloor): Quantized Floor op.
* [`quantized_ops.QuantizedGemm`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedgemm): Quantized Gemm op.
* [`quantized_ops.QuantizedGreater`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedgreater): Comparison operator >.
* [`quantized_ops.QuantizedGreaterOrEqual`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedgreaterorequal): Comparison operator >=.
* [`quantized_ops.QuantizedHardSigmoid`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedhardsigmoid): Quantized HardSigmoid op.
* [`quantized_ops.QuantizedHardSwish`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedhardswish): Quantized Hardswish op.
* [`quantized_ops.QuantizedIdentity`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedidentity): Quantized Identity op.
* [`quantized_ops.QuantizedLeakyRelu`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedleakyrelu): Quantized LeakyRelu op.
* [`quantized_ops.QuantizedLess`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedless): Comparison operator <.
* [`quantized_ops.QuantizedLessOrEqual`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedlessorequal): Comparison operator <=.
* [`quantized_ops.QuantizedLog`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedlog): Quantized Log op.
* [`quantized_ops.QuantizedMatMul`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedmatmul): Quantized MatMul op.
* [`quantized_ops.QuantizedMax`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedmax): Quantized Max op.
* [`quantized_ops.QuantizedMaxPool`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedmaxpool): Quantized Max Pooling op.
* [`quantized_ops.QuantizedMin`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedmin): Quantized Min op.
* [`quantized_ops.QuantizedMul`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedmul): Multiplication operator.
* [`quantized_ops.QuantizedNeg`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedneg): Quantized Neg op.
* [`quantized_ops.QuantizedNot`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizednot): Quantized Not op.
* [`quantized_ops.QuantizedOr`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedor): Or operator ||.
* [`quantized_ops.QuantizedPRelu`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedprelu): Quantized PRelu op.
* [`quantized_ops.QuantizedPad`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedpad): Quantized Padding op.
* [`quantized_ops.QuantizedPow`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedpow): Quantized pow op.
* [`quantized_ops.QuantizedReduceSum`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedreducesum): ReduceSum with encrypted input.
* [`quantized_ops.QuantizedRelu`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedrelu): Quantized Relu op.
* [`quantized_ops.QuantizedReshape`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedreshape): Quantized Reshape op.
* [`quantized_ops.QuantizedRound`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedround): Quantized round op.
* [`quantized_ops.QuantizedSelu`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedselu): Quantized Selu op.
* [`quantized_ops.QuantizedSigmoid`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedsigmoid): Quantized sigmoid op.
* [`quantized_ops.QuantizedSign`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedsign): Quantized Neg op.
* [`quantized_ops.QuantizedSoftplus`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedsoftplus): Quantized Softplus op.
* [`quantized_ops.QuantizedSqueeze`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedsqueeze): Squeeze operator.
* [`quantized_ops.QuantizedSub`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedsub): Subtraction operator.
* [`quantized_ops.QuantizedTanh`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedtanh): Quantized Tanh op.
* [`quantized_ops.QuantizedTranspose`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedtranspose): Transpose operator for quantized inputs.
* [`quantized_ops.QuantizedUnsqueeze`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedunsqueeze): Unsqueeze operator.
* [`quantized_ops.QuantizedWhere`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantized_ops.md#class-quantizedwhere): Where operator on quantized arrays.
* [`quantizers.MinMaxQuantizationStats`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantizers.md#class-minmaxquantizationstats): Calibration set statistics.
* [`quantizers.QuantizationOptions`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantizers.md#class-quantizationoptions): Options for quantization.
* [`quantizers.QuantizedArray`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantizers.md#class-quantizedarray): Abstraction of quantized array.
* [`quantizers.UniformQuantizationParameters`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantizers.md#class-uniformquantizationparameters): Quantization parameters for uniform quantization.
* [`quantizers.UniformQuantizer`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantizers.md#class-uniformquantizer): Uniform quantizer.
* [`p_error_search.BinarySearch`](/concrete-ml/1.1/developer-guide/api/concrete.ml.search_parameters.p_error_search.md#class-binarysearch): Class for `p_error` hyper-parameter search for classification and regression tasks.
* [`base.BaseClassifier`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.base.md#class-baseclassifier): Base class for linear and tree-based classifiers in Concrete ML.
* [`base.BaseEstimator`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.base.md#class-baseestimator): Base class for all estimators in Concrete ML.
* [`base.BaseTreeClassifierMixin`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.base.md#class-basetreeclassifiermixin): Mixin class for tree-based classifiers.
* [`base.BaseTreeEstimatorMixin`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.base.md#class-basetreeestimatormixin): Mixin class for tree-based estimators.
* [`base.BaseTreeRegressorMixin`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.base.md#class-basetreeregressormixin): Mixin class for tree-based regressors.
* [`base.QuantizedTorchEstimatorMixin`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.base.md#class-quantizedtorchestimatormixin): Mixin that provides quantization for a torch module and follows the Estimator API.
* [`base.SklearnLinearClassifierMixin`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.base.md#class-sklearnlinearclassifiermixin): A Mixin class for sklearn linear classifiers with FHE.
* [`base.SklearnLinearModelMixin`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.base.md#class-sklearnlinearmodelmixin): A Mixin class for sklearn linear models with FHE.
* [`base.SklearnLinearRegressorMixin`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.base.md#class-sklearnlinearregressormixin): A Mixin class for sklearn linear regressors with FHE.
* [`glm.GammaRegressor`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.glm.md#class-gammaregressor): A Gamma regression model with FHE.
* [`glm.PoissonRegressor`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.glm.md#class-poissonregressor): A Poisson regression model with FHE.
* [`glm.TweedieRegressor`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.glm.md#class-tweedieregressor): A Tweedie regression model with FHE.
* [`linear_model.ElasticNet`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.linear_model.md#class-elasticnet): An ElasticNet regression model with FHE.
* [`linear_model.Lasso`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.linear_model.md#class-lasso): A Lasso regression model with FHE.
* [`linear_model.LinearRegression`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.linear_model.md#class-linearregression): A linear regression model with FHE.
* [`linear_model.LogisticRegression`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.linear_model.md#class-logisticregression): A logistic regression model with FHE.
* [`linear_model.Ridge`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.linear_model.md#class-ridge): A Ridge regression model with FHE.
* [`qnn.NeuralNetClassifier`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.qnn.md#class-neuralnetclassifier): A Fully-Connected Neural Network classifier with FHE.
* [`qnn.NeuralNetRegressor`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.qnn.md#class-neuralnetregressor): A Fully-Connected Neural Network regressor with FHE.
* [`qnn_module.SparseQuantNeuralNetwork`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.qnn_module.md#class-sparsequantneuralnetwork): Sparse Quantized Neural Network.
* [`rf.RandomForestClassifier`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.rf.md#class-randomforestclassifier): Implements the RandomForest classifier.
* [`rf.RandomForestRegressor`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.rf.md#class-randomforestregressor): Implements the RandomForest regressor.
* [`svm.LinearSVC`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.svm.md#class-linearsvc): A Classification Support Vector Machine (SVM).
* [`svm.LinearSVR`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.svm.md#class-linearsvr): A Regression Support Vector Machine (SVM).
* [`tree.DecisionTreeClassifier`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.tree.md#class-decisiontreeclassifier): Implements the sklearn DecisionTreeClassifier.
* [`tree.DecisionTreeRegressor`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.tree.md#class-decisiontreeregressor): Implements the sklearn DecisionTreeClassifier.
* [`xgb.XGBClassifier`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.xgb.md#class-xgbclassifier): Implements the XGBoost classifier.
* [`xgb.XGBRegressor`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.xgb.md#class-xgbregressor): Implements the XGBoost regressor.
* [`numpy_module.NumpyModule`](/concrete-ml/1.1/developer-guide/api/concrete.ml.torch.numpy_module.md#class-numpymodule): General interface to transform a torch.nn.Module to numpy module.

## Functions

* [`check_inputs.check_X_y_and_assert`](/concrete-ml/1.1/developer-guide/api/concrete.ml.common.check_inputs.md#function-check_x_y_and_assert): sklearn.utils.check\_X\_y with an assert.
* [`check_inputs.check_X_y_and_assert_multi_output`](/concrete-ml/1.1/developer-guide/api/concrete.ml.common.check_inputs.md#function-check_x_y_and_assert_multi_output): sklearn.utils.check\_X\_y with an assert and multi-output handling.
* [`check_inputs.check_array_and_assert`](/concrete-ml/1.1/developer-guide/api/concrete.ml.common.check_inputs.md#function-check_array_and_assert): sklearn.utils.check\_array with an assert.
* [`custom_assert.assert_false`](/concrete-ml/1.1/developer-guide/api/concrete.ml.common.debugging.custom_assert.md#function-assert_false): Provide a custom assert to check that the condition is False.
* [`custom_assert.assert_not_reached`](/concrete-ml/1.1/developer-guide/api/concrete.ml.common.debugging.custom_assert.md#function-assert_not_reached): Provide a custom assert to check that a piece of code is never reached.
* [`custom_assert.assert_true`](/concrete-ml/1.1/developer-guide/api/concrete.ml.common.debugging.custom_assert.md#function-assert_true): Provide a custom assert to check that the condition is True.
* [`decoder.object_hook`](/concrete-ml/1.1/developer-guide/api/concrete.ml.common.serialization.decoder.md#function-object_hook): Define a custom object hook that enables loading any supported serialized values.
* [`dumpers.dump`](/concrete-ml/1.1/developer-guide/api/concrete.ml.common.serialization.dumpers.md#function-dump): Dump any Concrete ML object in a file.
* [`dumpers.dumps`](/concrete-ml/1.1/developer-guide/api/concrete.ml.common.serialization.dumpers.md#function-dumps): Dump any object as a string.
* [`encoder.dump_name_and_value`](/concrete-ml/1.1/developer-guide/api/concrete.ml.common.serialization.encoder.md#function-dump_name_and_value): Dump the value into a custom dict format.
* [`loaders.load`](/concrete-ml/1.1/developer-guide/api/concrete.ml.common.serialization.loaders.md#function-load): Load any Concrete ML object that provide a `load_dict` method.
* [`loaders.loads`](/concrete-ml/1.1/developer-guide/api/concrete.ml.common.serialization.loaders.md#function-loads): Load any Concrete ML object that provide a `dump_dict` method.
* [`utils.all_values_are_floats`](/concrete-ml/1.1/developer-guide/api/concrete.ml.common.utils.md#function-all_values_are_floats): Indicate if all unpacked values are of a supported float dtype.
* [`utils.all_values_are_integers`](/concrete-ml/1.1/developer-guide/api/concrete.ml.common.utils.md#function-all_values_are_integers): Indicate if all unpacked values are of a supported integer dtype.
* [`utils.all_values_are_of_dtype`](/concrete-ml/1.1/developer-guide/api/concrete.ml.common.utils.md#function-all_values_are_of_dtype): Indicate if all unpacked values are of the specified dtype(s).
* [`utils.check_dtype_and_cast`](/concrete-ml/1.1/developer-guide/api/concrete.ml.common.utils.md#function-check_dtype_and_cast): Convert any allowed type into an array and cast it if required.
* [`utils.check_there_is_no_p_error_options_in_configuration`](/concrete-ml/1.1/developer-guide/api/concrete.ml.common.utils.md#function-check_there_is_no_p_error_options_in_configuration): Check the user did not set p\_error or global\_p\_error in configuration.
* [`utils.compute_bits_precision`](/concrete-ml/1.1/developer-guide/api/concrete.ml.common.utils.md#function-compute_bits_precision): Compute the number of bits required to represent x.
* [`utils.generate_proxy_function`](/concrete-ml/1.1/developer-guide/api/concrete.ml.common.utils.md#function-generate_proxy_function): Generate a proxy function for a function accepting only \*args type arguments.
* [`utils.get_model_class`](/concrete-ml/1.1/developer-guide/api/concrete.ml.common.utils.md#function-get_model_class): Return the class of the model (instantiated or not), which can be a partial() instance.
* [`utils.get_model_name`](/concrete-ml/1.1/developer-guide/api/concrete.ml.common.utils.md#function-get_model_name): Return the name of the model, which can be a partial() instance.
* [`utils.get_onnx_opset_version`](/concrete-ml/1.1/developer-guide/api/concrete.ml.common.utils.md#function-get_onnx_opset_version): Return the ONNX opset\_version.
* [`utils.is_brevitas_model`](/concrete-ml/1.1/developer-guide/api/concrete.ml.common.utils.md#function-is_brevitas_model): Check if a model is a Brevitas type.
* [`utils.is_classifier_or_partial_classifier`](/concrete-ml/1.1/developer-guide/api/concrete.ml.common.utils.md#function-is_classifier_or_partial_classifier): Indicate if the model class represents a classifier.
* [`utils.is_model_class_in_a_list`](/concrete-ml/1.1/developer-guide/api/concrete.ml.common.utils.md#function-is_model_class_in_a_list): Indicate if a model class, which can be a partial() instance, is an element of a\_list.
* [`utils.is_pandas_dataframe`](/concrete-ml/1.1/developer-guide/api/concrete.ml.common.utils.md#function-is_pandas_dataframe): Indicate if the input container is a Pandas DataFrame.
* [`utils.is_pandas_series`](/concrete-ml/1.1/developer-guide/api/concrete.ml.common.utils.md#function-is_pandas_series): Indicate if the input container is a Pandas Series.
* [`utils.is_pandas_type`](/concrete-ml/1.1/developer-guide/api/concrete.ml.common.utils.md#function-is_pandas_type): Indicate if the input container is a Pandas DataFrame or Series.
* [`utils.is_regressor_or_partial_regressor`](/concrete-ml/1.1/developer-guide/api/concrete.ml.common.utils.md#function-is_regressor_or_partial_regressor): Indicate if the model class represents a regressor.
* [`utils.manage_parameters_for_pbs_errors`](/concrete-ml/1.1/developer-guide/api/concrete.ml.common.utils.md#function-manage_parameters_for_pbs_errors): Return (p\_error, global\_p\_error) that we want to give to Concrete.
* [`utils.replace_invalid_arg_name_chars`](/concrete-ml/1.1/developer-guide/api/concrete.ml.common.utils.md#function-replace_invalid_arg_name_chars): Sanitize arg\_name, replacing invalid chars by \_.
* [`utils.to_tuple`](/concrete-ml/1.1/developer-guide/api/concrete.ml.common.utils.md#function-to_tuple): Make the input a tuple if it is not already the case.
* [`deploy_to_aws.create_instance`](/concrete-ml/1.1/developer-guide/api/concrete.ml.deployment.deploy_to_aws.md#function-create_instance): Create a EC2 instance.
* [`deploy_to_aws.delete_security_group`](/concrete-ml/1.1/developer-guide/api/concrete.ml.deployment.deploy_to_aws.md#function-delete_security_group): Terminate a AWS EC2 instance.
* [`deploy_to_aws.deploy_to_aws`](/concrete-ml/1.1/developer-guide/api/concrete.ml.deployment.deploy_to_aws.md#function-deploy_to_aws): Deploy a model to a EC2 AWS instance.
* [`deploy_to_aws.main`](/concrete-ml/1.1/developer-guide/api/concrete.ml.deployment.deploy_to_aws.md#function-main): Deploy a model.
* [`deploy_to_aws.terminate_instance`](/concrete-ml/1.1/developer-guide/api/concrete.ml.deployment.deploy_to_aws.md#function-terminate_instance): Terminate a AWS EC2 instance.
* [`deploy_to_aws.wait_instance_termination`](/concrete-ml/1.1/developer-guide/api/concrete.ml.deployment.deploy_to_aws.md#function-wait_instance_termination): Wait for AWS EC2 instance termination.
* [`deploy_to_docker.build_docker_image`](/concrete-ml/1.1/developer-guide/api/concrete.ml.deployment.deploy_to_docker.md#function-build_docker_image): Build server Docker image.
* [`deploy_to_docker.delete_image`](/concrete-ml/1.1/developer-guide/api/concrete.ml.deployment.deploy_to_docker.md#function-delete_image): Delete a Docker image.
* [`deploy_to_docker.main`](/concrete-ml/1.1/developer-guide/api/concrete.ml.deployment.deploy_to_docker.md#function-main): Deploy function.
* [`deploy_to_docker.stop_container`](/concrete-ml/1.1/developer-guide/api/concrete.ml.deployment.deploy_to_docker.md#function-stop_container): Kill all containers that use a given image.
* [`utils.filter_logs`](/concrete-ml/1.1/developer-guide/api/concrete.ml.deployment.utils.md#function-filter_logs): Filter logs based on previous logs.
* [`utils.is_connection_available`](/concrete-ml/1.1/developer-guide/api/concrete.ml.deployment.utils.md#function-is_connection_available): Check if ssh connection is available.
* [`utils.wait_for_connection_to_be_available`](/concrete-ml/1.1/developer-guide/api/concrete.ml.deployment.utils.md#function-wait_for_connection_to_be_available): Wait for connection to be available.
* [`convert.get_equivalent_numpy_forward`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.convert.md#function-get_equivalent_numpy_forward): Get the numpy equivalent forward of the provided ONNX model.
* [`convert.get_equivalent_numpy_forward_and_onnx_model`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.convert.md#function-get_equivalent_numpy_forward_and_onnx_model): Get the numpy equivalent forward of the provided torch Module.
* [`onnx_impl_utils.compute_conv_output_dims`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.onnx_impl_utils.md#function-compute_conv_output_dims): Compute the output shape of a pool or conv operation.
* [`onnx_impl_utils.compute_onnx_pool_padding`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.onnx_impl_utils.md#function-compute_onnx_pool_padding): Compute any additional padding needed to compute pooling layers.
* [`onnx_impl_utils.numpy_onnx_pad`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.onnx_impl_utils.md#function-numpy_onnx_pad): Pad a tensor according to ONNX spec, using an optional custom pad value.
* [`onnx_impl_utils.onnx_avgpool_compute_norm_const`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.onnx_impl_utils.md#function-onnx_avgpool_compute_norm_const): Compute the average pooling normalization constant.
* [`onnx_model_manipulations.clean_graph_after_node_op_type`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.onnx_model_manipulations.md#function-clean_graph_after_node_op_type): Clean the graph of the onnx model by removing nodes after the given node type.
* [`onnx_model_manipulations.clean_graph_at_node_op_type`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.onnx_model_manipulations.md#function-clean_graph_at_node_op_type): Clean the graph of the onnx model by removing nodes at the given node type.
* [`onnx_model_manipulations.keep_following_outputs_discard_others`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.onnx_model_manipulations.md#function-keep_following_outputs_discard_others): Keep the outputs given in outputs\_to\_keep and remove the others from the model.
* [`onnx_model_manipulations.remove_identity_nodes`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.onnx_model_manipulations.md#function-remove_identity_nodes): Remove identity nodes from a model.
* [`onnx_model_manipulations.remove_node_types`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.onnx_model_manipulations.md#function-remove_node_types): Remove unnecessary nodes from the ONNX graph.
* [`onnx_model_manipulations.remove_unused_constant_nodes`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.onnx_model_manipulations.md#function-remove_unused_constant_nodes): Remove unused Constant nodes in the provided onnx model.
* [`onnx_model_manipulations.simplify_onnx_model`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.onnx_model_manipulations.md#function-simplify_onnx_model): Simplify an ONNX model, removes unused Constant nodes and Identity nodes.
* [`onnx_utils.execute_onnx_with_numpy`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.onnx_utils.md#function-execute_onnx_with_numpy): Execute the provided ONNX graph on the given inputs.
* [`onnx_utils.get_attribute`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.onnx_utils.md#function-get_attribute): Get the attribute from an ONNX AttributeProto.
* [`onnx_utils.get_op_type`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.onnx_utils.md#function-get_op_type): Construct the qualified type name of the ONNX operator.
* [`onnx_utils.remove_initializer_from_input`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.onnx_utils.md#function-remove_initializer_from_input): Remove initializers from model inputs.
* [`ops_impl.cast_to_float`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-cast_to_float): Cast values to floating points.
* [`ops_impl.numpy_abs`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_abs): Compute abs in numpy according to ONNX spec.
* [`ops_impl.numpy_acos`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_acos): Compute acos in numpy according to ONNX spec.
* [`ops_impl.numpy_acosh`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_acosh): Compute acosh in numpy according to ONNX spec.
* [`ops_impl.numpy_add`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_add): Compute add in numpy according to ONNX spec.
* [`ops_impl.numpy_asin`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_asin): Compute asin in numpy according to ONNX spec.
* [`ops_impl.numpy_asinh`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_asinh): Compute sinh in numpy according to ONNX spec.
* [`ops_impl.numpy_atan`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_atan): Compute atan in numpy according to ONNX spec.
* [`ops_impl.numpy_atanh`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_atanh): Compute atanh in numpy according to ONNX spec.
* [`ops_impl.numpy_avgpool`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_avgpool): Compute Average Pooling using Torch.
* [`ops_impl.numpy_batchnorm`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_batchnorm): Compute the batch normalization of the input tensor.
* [`ops_impl.numpy_cast`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_cast): Execute ONNX cast in Numpy.
* [`ops_impl.numpy_celu`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_celu): Compute celu in numpy according to ONNX spec.
* [`ops_impl.numpy_concatenate`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_concatenate): Apply concatenate in numpy according to ONNX spec.
* [`ops_impl.numpy_constant`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_constant): Return the constant passed as a kwarg.
* [`ops_impl.numpy_cos`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_cos): Compute cos in numpy according to ONNX spec.
* [`ops_impl.numpy_cosh`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_cosh): Compute cosh in numpy according to ONNX spec.
* [`ops_impl.numpy_div`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_div): Compute div in numpy according to ONNX spec.
* [`ops_impl.numpy_elu`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_elu): Compute elu in numpy according to ONNX spec.
* [`ops_impl.numpy_equal`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_equal): Compute equal in numpy according to ONNX spec.
* [`ops_impl.numpy_erf`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_erf): Compute erf in numpy according to ONNX spec.
* [`ops_impl.numpy_exp`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_exp): Compute exponential in numpy according to ONNX spec.
* [`ops_impl.numpy_flatten`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_flatten): Flatten a tensor into a 2d array.
* [`ops_impl.numpy_floor`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_floor): Compute Floor in numpy according to ONNX spec.
* [`ops_impl.numpy_greater`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_greater): Compute greater in numpy according to ONNX spec.
* [`ops_impl.numpy_greater_float`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_greater_float): Compute greater in numpy according to ONNX spec and cast outputs to floats.
* [`ops_impl.numpy_greater_or_equal`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_greater_or_equal): Compute greater or equal in numpy according to ONNX spec.
* [`ops_impl.numpy_greater_or_equal_float`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_greater_or_equal_float): Compute greater or equal in numpy according to ONNX specs and cast outputs to floats.
* [`ops_impl.numpy_hardsigmoid`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_hardsigmoid): Compute hardsigmoid in numpy according to ONNX spec.
* [`ops_impl.numpy_hardswish`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_hardswish): Compute hardswish in numpy according to ONNX spec.
* [`ops_impl.numpy_identity`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_identity): Compute identity in numpy according to ONNX spec.
* [`ops_impl.numpy_leakyrelu`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_leakyrelu): Compute leakyrelu in numpy according to ONNX spec.
* [`ops_impl.numpy_less`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_less): Compute less in numpy according to ONNX spec.
* [`ops_impl.numpy_less_float`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_less_float): Compute less in numpy according to ONNX spec and cast outputs to floats.
* [`ops_impl.numpy_less_or_equal`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_less_or_equal): Compute less or equal in numpy according to ONNX spec.
* [`ops_impl.numpy_less_or_equal_float`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_less_or_equal_float): Compute less or equal in numpy according to ONNX spec and cast outputs to floats.
* [`ops_impl.numpy_log`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_log): Compute log in numpy according to ONNX spec.
* [`ops_impl.numpy_matmul`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_matmul): Compute matmul in numpy according to ONNX spec.
* [`ops_impl.numpy_max`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_max): Compute Max in numpy according to ONNX spec.
* [`ops_impl.numpy_maxpool`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_maxpool): Compute Max Pooling using Torch.
* [`ops_impl.numpy_min`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_min): Compute Min in numpy according to ONNX spec.
* [`ops_impl.numpy_mul`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_mul): Compute mul in numpy according to ONNX spec.
* [`ops_impl.numpy_neg`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_neg): Compute Negative in numpy according to ONNX spec.
* [`ops_impl.numpy_not`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_not): Compute not in numpy according to ONNX spec.
* [`ops_impl.numpy_not_float`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_not_float): Compute not in numpy according to ONNX spec and cast outputs to floats.
* [`ops_impl.numpy_or`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_or): Compute or in numpy according to ONNX spec.
* [`ops_impl.numpy_or_float`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_or_float): Compute or in numpy according to ONNX spec and cast outputs to floats.
* [`ops_impl.numpy_pow`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_pow): Compute pow in numpy according to ONNX spec.
* [`ops_impl.numpy_relu`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_relu): Compute relu in numpy according to ONNX spec.
* [`ops_impl.numpy_round`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_round): Compute round in numpy according to ONNX spec.
* [`ops_impl.numpy_selu`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_selu): Compute selu in numpy according to ONNX spec.
* [`ops_impl.numpy_sigmoid`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_sigmoid): Compute sigmoid in numpy according to ONNX spec.
* [`ops_impl.numpy_sign`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_sign): Compute Sign in numpy according to ONNX spec.
* [`ops_impl.numpy_sin`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_sin): Compute sin in numpy according to ONNX spec.
* [`ops_impl.numpy_sinh`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_sinh): Compute sinh in numpy according to ONNX spec.
* [`ops_impl.numpy_softmax`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_softmax): Compute softmax in numpy according to ONNX spec.
* [`ops_impl.numpy_softplus`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_softplus): Compute softplus in numpy according to ONNX spec.
* [`ops_impl.numpy_sub`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_sub): Compute sub in numpy according to ONNX spec.
* [`ops_impl.numpy_tan`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_tan): Compute tan in numpy according to ONNX spec.
* [`ops_impl.numpy_tanh`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_tanh): Compute tanh in numpy according to ONNX spec.
* [`ops_impl.numpy_thresholdedrelu`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_thresholdedrelu): Compute thresholdedrelu in numpy according to ONNX spec.
* [`ops_impl.numpy_transpose`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_transpose): Transpose in numpy according to ONNX spec.
* [`ops_impl.numpy_where`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_where): Compute the equivalent of numpy.where.
* [`ops_impl.numpy_where_body`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-numpy_where_body): Compute the equivalent of numpy.where.
* [`ops_impl.onnx_func_raw_args`](/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.ops_impl.md#function-onnx_func_raw_args): Decorate a numpy onnx function to flag the raw/non quantized inputs.
* [`utils.check_serialization`](/concrete-ml/1.1/developer-guide/api/concrete.ml.pytest.utils.md#function-check_serialization): Check that the given object can properly be serialized.
* [`utils.data_calibration_processing`](/concrete-ml/1.1/developer-guide/api/concrete.ml.pytest.utils.md#function-data_calibration_processing): Reduce size of the given data-set.
* [`utils.get_random_extract_of_sklearn_models_and_datasets`](/concrete-ml/1.1/developer-guide/api/concrete.ml.pytest.utils.md#function-get_random_extract_of_sklearn_models_and_datasets): Return a random sublist of sklearn\_models\_and\_datasets.
* [`utils.get_torchvision_dataset`](/concrete-ml/1.1/developer-guide/api/concrete.ml.pytest.utils.md#function-get_torchvision_dataset): Get train or testing data-set.
* [`utils.instantiate_model_generic`](/concrete-ml/1.1/developer-guide/api/concrete.ml.pytest.utils.md#function-instantiate_model_generic): Instantiate any Concrete ML model type.
* [`utils.load_torch_model`](/concrete-ml/1.1/developer-guide/api/concrete.ml.pytest.utils.md#function-load_torch_model): Load an object saved with torch.save() from a file or dict.
* [`utils.values_are_equal`](/concrete-ml/1.1/developer-guide/api/concrete.ml.pytest.utils.md#function-values_are_equal): Indicate if two values are equal.
* [`post_training.get_n_bits_dict`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.post_training.md#function-get_n_bits_dict): Convert the n\_bits parameter into a proper dictionary.
* [`quantizers.fill_from_kwargs`](/concrete-ml/1.1/developer-guide/api/concrete.ml.quantization.quantizers.md#function-fill_from_kwargs): Fill a parameter set structure from kwargs parameters.
* [`p_error_search.compile_and_simulated_fhe_inference`](/concrete-ml/1.1/developer-guide/api/concrete.ml.search_parameters.p_error_search.md#function-compile_and_simulated_fhe_inference): Get the quantized module of a given model in FHE, simulated or not.
* [`sklearn.get_sklearn_linear_models`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.md#function-get_sklearn_linear_models): Return the list of available linear models in Concrete ML.
* [`sklearn.get_sklearn_models`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.md#function-get_sklearn_models): Return the list of available models in Concrete ML.
* [`sklearn.get_sklearn_neural_net_models`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.md#function-get_sklearn_neural_net_models): Return the list of available neural net models in Concrete ML.
* [`sklearn.get_sklearn_tree_models`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.md#function-get_sklearn_tree_models): Return the list of available tree models in Concrete ML.
* [`tree_to_numpy.add_transpose_after_last_node`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.tree_to_numpy.md#function-add_transpose_after_last_node): Add transpose after last node.
* [`tree_to_numpy.get_onnx_model`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.tree_to_numpy.md#function-get_onnx_model): Create ONNX model with Hummingbird convert method.
* [`tree_to_numpy.preprocess_tree_predictions`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.tree_to_numpy.md#function-preprocess_tree_predictions): Apply post-processing from the graph.
* [`tree_to_numpy.tree_onnx_graph_preprocessing`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.tree_to_numpy.md#function-tree_onnx_graph_preprocessing): Apply pre-processing onto the ONNX graph.
* [`tree_to_numpy.tree_to_numpy`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.tree_to_numpy.md#function-tree_to_numpy): Convert the tree inference to a numpy functions using Hummingbird.
* [`tree_to_numpy.tree_values_preprocessing`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.tree_to_numpy.md#function-tree_values_preprocessing): Pre-process tree values.
* [`tree_to_numpy.workaround_squeeze_node_xgboost`](/concrete-ml/1.1/developer-guide/api/concrete.ml.sklearn.tree_to_numpy.md#function-workaround_squeeze_node_xgboost): Workaround to fix torch issue that does not export the proper axis in the ONNX squeeze node.
* [`compile.build_quantized_module`](/concrete-ml/1.1/developer-guide/api/concrete.ml.torch.compile.md#function-build_quantized_module): Build a quantized module from a Torch or ONNX model.
* [`compile.compile_brevitas_qat_model`](/concrete-ml/1.1/developer-guide/api/concrete.ml.torch.compile.md#function-compile_brevitas_qat_model): Compile a Brevitas Quantization Aware Training model.
* [`compile.compile_onnx_model`](/concrete-ml/1.1/developer-guide/api/concrete.ml.torch.compile.md#function-compile_onnx_model): Compile a torch module into an FHE equivalent.
* [`compile.compile_torch_model`](/concrete-ml/1.1/developer-guide/api/concrete.ml.torch.compile.md#function-compile_torch_model): Compile a torch module into an FHE equivalent.
* [`compile.convert_torch_tensor_or_numpy_array_to_numpy_array`](/concrete-ml/1.1/developer-guide/api/concrete.ml.torch.compile.md#function-convert_torch_tensor_or_numpy_array_to_numpy_array): Convert a torch tensor or a numpy array to a numpy array.


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