Merge branch 'main' into SchedulerUpdate

.gitlab/ci/_global.gitlab-ci.yml

@@ -9,6 +9,14 @@ variables:
   GIT_SSL_NO_VERIFY: 1
   DEBIAN_FRONTEND: noninteractive
 
+# See https://docs.gitlab.com/ee/ci/yaml/workflow.html#switch-between-branch-pipelines-and-merge-request-pipelines
+workflow:
+  rules:
+    - if: $CI_PIPELINE_SOURCE == "merge_request_event"
+    - if: $CI_COMMIT_BRANCH && $CI_OPEN_MERGE_REQUESTS
+      when: never
+    - if: $CI_COMMIT_BRANCH
+
 default:
   image: nvidia/cuda:12.2.0-devel-ubuntu22.04
   before_script:

aidge_core/__init__.py

@@ -8,3 +8,4 @@ http://www.eclipse.org/legal/epl-2.0.
 SPDX-License-Identifier: EPL-2.0
 """
 from aidge_core.aidge_core import * # import so generated by PyBind
+from aidge_core.export import ExportNode

aidge_core/export/__init__.py

+from .node_export import *

aidge_core/export/node_export.py

+import aidge_core
+
+from abc import ABC, abstractmethod
+
+
+class ExportNode(ABC):
+    """Abstract class to interface node with export generation.
+    """
+
+    @abstractmethod
+    def __init__(self, aidge_node: aidge_core.Node) -> None:
+        """Create ExportNode and retieve attirubtes from ``aidge_node``:
+
+        - name: aidge Node name
+        - attributes: dictionnary of attributes of the aidge Operator linked to the node, attributes name follow aidge naming convention
+        - parameters: List of parameters node, order in the list is the same as the one defined by the aidge operator
+
+        """
+        super().__init__()
+        self.node = aidge_node
+        self.operator = aidge_node.get_operator()
+        self.name = self.node.name()
+        self.attributes = {} # Attributes are auto fetched from aidge operators
+        if isinstance(self.operator, aidge_core.Attributes):
+            for attr_name in self.operator.get_attrs_name():
+                self.attributes[attr_name] = self.operator.get_attr(attr_name)
+
+        # rename is_leaf ?
+        self.is_last = len(self.node.get_children()) == 0
+
+
+        self.inputs = []
+        self.outputs = []
+        self.inputs_dims = []
+        self.outputs_dims = []
+
+        for idx, parent_node in enumerate(self.node.get_parents()):
+            self.inputs.append(parent_node)
+            if parent_node is not None:
+                self.inputs_dims.append(self.operator.input(idx).dims())
+            else:
+                self.inputs_dims.append(None)
+
+        for idx, child_node in enumerate(self.node.get_children()):
+            self.outputs.append(child_node)
+        
+        # Dirty hot fix, change it quickly
+        self.outputs_dims.append(self.operator.output(0).dims())
+
+    @abstractmethod
+    def export(self, export_folder:str, list_configs:list):
+        """Define how to export the node definition.
+        """
+        pass
+
+    @abstractmethod
+    def forward(self, list_actions:list):
+        """Define how to generate code to perform a forward pass.
+        """
+        pass
+

include/aidge/aidge.hpp

@@ -31,18 +31,23 @@
 #include "aidge/operator/BatchNorm.hpp"
 #include "aidge/operator/Conv.hpp"
 #include "aidge/operator/ConvDepthWise.hpp"
+#include "aidge/operator/Div.hpp"
 #include "aidge/operator/FC.hpp"
 #include "aidge/operator/GenericOperator.hpp"
 #include "aidge/operator/MatMul.hpp"
 #include "aidge/operator/MaxPooling.hpp"
 #include "aidge/operator/MetaOperator.hpp"
 #include "aidge/operator/MetaOperatorDefs.hpp"
+#include "aidge/operator/Mul.hpp"
 #include "aidge/operator/Operator.hpp"
 #include "aidge/operator/Pad.hpp"
 #include "aidge/operator/Producer.hpp"
+#include "aidge/operator/Pow.hpp"
 #include "aidge/operator/ReLU.hpp"
-#include "aidge/operator/Softmax.hpp"
 #include "aidge/operator/Scaling.hpp"
+#include "aidge/operator/Softmax.hpp"
+#include "aidge/operator/Sqrt.hpp"
+#include "aidge/operator/Sub.hpp"
 #include "aidge/scheduler/Scheduler.hpp"
 #include "aidge/utils/Attributes.hpp"
 #include "aidge/utils/StaticAttributes.hpp"

include/aidge/operator/Div.hpp

+/********************************************************************************
+ * Copyright (c) 2023 CEA-List
+ *
+ * This program and the accompanying materials are made available under the
+ * terms of the Eclipse Public License 2.0 which is available at
+ * http://www.eclipse.org/legal/epl-2.0.
+ *
+ * SPDX-License-Identifier: EPL-2.0
+ *
+ ********************************************************************************/
+
+#ifndef AIDGE_CORE_OPERATOR_DIV_H_
+#define AIDGE_CORE_OPERATOR_DIV_H_
+
+#include <cassert>
+#include <memory>
+#include <vector>
+
+#include "aidge/utils/Registrar.hpp"
+#include "aidge/operator/Operator.hpp"
+#include "aidge/backend/OperatorImpl.hpp"
+#include "aidge/data/Tensor.hpp"
+#include "aidge/data/Data.hpp"
+#include "aidge/graph/Node.hpp"
+#include "aidge/utils/Types.h"
+
+namespace Aidge {
+
+class Div_Op : public Operator,
+    public Registrable<Div_Op, std::string, std::unique_ptr<OperatorImpl>(const Div_Op&)> {
+public:
+    // FIXME: change accessibility
+    std::array<std::shared_ptr<Tensor>, 2> mInputs = {std::make_shared<Tensor>(), std::make_shared<Tensor>()};
+    const std::shared_ptr<Tensor> mOutput = std::make_shared<Tensor>();
+
+public:
+    static constexpr const char* Type = "Div";
+
+    Div_Op()
+            : Operator(Type)
+    {
+        setDatatype(DataType::Float32);
+    }
+
+    /**
+     * @brief Copy-constructor. Copy the operator attributes and its output tensor(s), but not its input tensors (the new operator has no input associated).
+     * @param op Operator to copy.
+     */
+    Div_Op(const Div_Op& op)
+        : Operator(Type),
+          mOutput(std::make_shared<Tensor>(*op.mOutput))
+    {
+        // cpy-ctor
+        setDatatype(op.mOutput->dataType());
+        mImpl = op.mImpl ? Registrar<Div_Op>::create(mOutput->getImpl()->backend())(*this) : nullptr;
+    }
+
+    /**
+     * @brief Clone the operator using its copy-constructor.
+     * @see Operator::Div_Op
+     */
+    std::shared_ptr<Operator> clone() const override {
+        return std::make_shared<Div_Op>(*this);
+    }
+
+    void associateInput(const IOIndex_t inputIdx, std::shared_ptr<Data> data) override final {
+        assert(inputIdx < 2 && "operator supports only 2 inputs");
+        (void) inputIdx; // avoid unused warning
+        assert(strcmp(data->type(), Tensor::Type)==0 && "input data must be of Tensor type");
+        mInputs[inputIdx] = std::dynamic_pointer_cast<Tensor>(data);
+    }
+
+    void computeOutputDims() override final {
+        if (!mInputs[0]->empty())
+            mOutput->resize(mInputs[0]->dims());
+    }
+
+    bool outputDimsForwarded() const override final {
+        return !(mOutput->empty());
+    }
+
+
+    inline Tensor& input(const IOIndex_t inputIdx) const override final {
+        assert(static_cast<std::size_t>(inputIdx) < 2 && "wrong inputIdx for Add operator.");
+        return *(mInputs[inputIdx].get());
+    }
+    inline Tensor& output(const IOIndex_t /*outputIdx*/) const override final { return *(mOutput.get()); }
+
+
+    inline std::shared_ptr<Tensor> getInput(const IOIndex_t inputIdx) const override final {
+        assert((inputIdx < 2) && "Div Operator has 2 inputs");
+        (void) inputIdx; // avoid unused warning
+        return mInputs[inputIdx];
+    }
+    inline std::shared_ptr<Tensor> getOutput(const IOIndex_t outputIdx) const override final {
+        assert((outputIdx == 0) && "Div Operator has only 1 output");
+        (void) outputIdx; // avoid unused warning
+        return mOutput;
+    }
+
+
+    std::shared_ptr<Data> getRawInput(const IOIndex_t inputIdx) const override final {
+        assert(inputIdx < 2 && "operator supports only 2 inputs");
+        (void) inputIdx; // avoid unused warning
+        return std::static_pointer_cast<Data>(mInputs[inputIdx]);
+    }
+    std::shared_ptr<Data> getRawOutput(const IOIndex_t outputIdx) const override final {
+        assert(outputIdx == 0 && "operator supports only 1 output");
+        (void) outputIdx; // avoid unused warning
+        return std::static_pointer_cast<Data>(mOutput);
+    }
+
+
+    void setBackend(const std::string& name) override {
+        mImpl = Registrar<Div_Op>::create(name)(*this);
+        mOutput->setBackend(name);
+
+        // FIXME: temporary workaround
+        mInputs[0]->setBackend(name);
+        mInputs[1]->setBackend(name);
+    }
+    void setDatatype(const DataType& datatype) override {
+        mOutput->setDatatype(datatype);
+
+        // FIXME: temporary workaround
+        mInputs[0]->setDatatype(datatype);
+        mInputs[1]->setDatatype(datatype);
+    }
+
+    inline IOIndex_t nbInputs() const noexcept override final { return 2; }
+    inline IOIndex_t nbDataInputs() const noexcept override final { return 2; }
+    inline IOIndex_t nbOutputs() const noexcept override final { return 1; }
+    static const std::vector<std::string> getInputsName(){
+        return {"data_input"};
+    }
+    static const std::vector<std::string> getOutputsName(){
+        return {"data_output"};
+    }
+};
+
+inline std::shared_ptr<Node> Div(const std::string& name = "") {
+    return std::make_shared<Node>(std::make_shared<Div_Op>(), name);
+}
+}
+
+#endif /* AIDGE_CORE_OPERATOR_DIV_H_ */

include/aidge/operator/Mul.hpp

+/********************************************************************************
+ * Copyright (c) 2023 CEA-List
+ *
+ * This program and the accompanying materials are made available under the
+ * terms of the Eclipse Public License 2.0 which is available at
+ * http://www.eclipse.org/legal/epl-2.0.
+ *
+ * SPDX-License-Identifier: EPL-2.0
+ *
+ ********************************************************************************/
+
+#ifndef AIDGE_CORE_OPERATOR_MUL_H_
+#define AIDGE_CORE_OPERATOR_MUL_H_
+
+#include <cassert>
+#include <memory>
+#include <vector>
+
+#include "aidge/utils/Registrar.hpp"
+#include "aidge/operator/Operator.hpp"
+#include "aidge/backend/OperatorImpl.hpp"
+#include "aidge/data/Tensor.hpp"
+#include "aidge/data/Data.hpp"
+#include "aidge/graph/Node.hpp"
+#include "aidge/utils/Types.h"
+
+namespace Aidge {
+
+class Mul_Op : public Operator,
+    public Registrable<Mul_Op, std::string, std::unique_ptr<OperatorImpl>(const Mul_Op&)> {
+public:
+    // FIXME: change accessibility
+    std::array<std::shared_ptr<Tensor>, 2> mInputs = {std::make_shared<Tensor>(), std::make_shared<Tensor>()};
+    const std::shared_ptr<Tensor> mOutput = std::make_shared<Tensor>();
+
+public:
+    static constexpr const char* Type = "Mul";
+
+    Mul_Op()
+            : Operator(Type)
+    {
+        setDatatype(DataType::Float32);
+    }
+
+    /**
+     * @brief Copy-constructor. Copy the operator attributes and its output tensor(s), but not its input tensors (the new operator has no input associated).
+     * @param op Operator to copy.
+     */
+    Mul_Op(const Mul_Op& op)
+        : Operator(Type),
+          mOutput(std::make_shared<Tensor>(*op.mOutput))
+    {
+        // cpy-ctor
+        setDatatype(op.mOutput->dataType());
+        mImpl = op.mImpl ? Registrar<Mul_Op>::create(mOutput->getImpl()->backend())(*this) : nullptr;
+    }
+
+    /**
+     * @brief Clone the operator using its copy-constructor.
+     * @see Operator::Mul_Op
+     */
+    std::shared_ptr<Operator> clone() const override {
+        return std::make_shared<Mul_Op>(*this);
+    }
+
+    void associateInput(const IOIndex_t inputIdx, std::shared_ptr<Data> data) override final {
+        assert(inputIdx < 2 && "operator supports only 2 inputs");
+        (void) inputIdx; // avoid unused warning
+        assert(strcmp(data->type(), Tensor::Type)==0 && "input data must be of Tensor type");
+        mInputs[inputIdx] = std::dynamic_pointer_cast<Tensor>(data);
+    }
+
+    void computeOutputDims() override final {
+        if (!mInputs[0]->empty())
+            mOutput->resize(mInputs[0]->dims());
+    }
+
+    bool outputDimsForwarded() const override final {
+        return !(mOutput->empty());
+    }
+
+
+    inline Tensor& input(const IOIndex_t inputIdx) const override final {
+        assert(static_cast<std::size_t>(inputIdx) < 2 && "wrong inputIdx for Add operator.");
+        return *(mInputs[inputIdx].get());
+    }
+    inline Tensor& output(const IOIndex_t /*outputIdx*/) const override final { return *(mOutput.get()); }
+
+
+    inline std::shared_ptr<Tensor> getInput(const IOIndex_t inputIdx) const override final {
+        assert((inputIdx < 2) && "Mul Operator has 2 inputs");
+        (void) inputIdx; // avoid unused warning
+        return mInputs[inputIdx];
+    }
+    inline std::shared_ptr<Tensor> getOutput(const IOIndex_t outputIdx) const override final {
+        assert((outputIdx == 0) && "Mul Operator has only 1 output");
+        (void) outputIdx; // avoid unused warning
+        return mOutput;
+    }
+
+
+    std::shared_ptr<Data> getRawInput(const IOIndex_t inputIdx) const override final {
+        assert(inputIdx < 2 && "operator supports only 2 inputs");
+        (void) inputIdx; // avoid unused warning
+        return std::static_pointer_cast<Data>(mInputs[inputIdx]);
+    }
+    std::shared_ptr<Data> getRawOutput(const IOIndex_t outputIdx) const override final {
+        assert(outputIdx == 0 && "operator supports only 1 output");
+        (void) outputIdx; // avoid unused warning
+        return std::static_pointer_cast<Data>(mOutput);
+    }
+
+
+    void setBackend(const std::string& name) override {
+        mImpl = Registrar<Mul_Op>::create(name)(*this);
+        mOutput->setBackend(name);
+
+        // FIXME: temporary workaround
+        mInputs[0]->setBackend(name);
+        mInputs[1]->setBackend(name);
+    }
+    void setDatatype(const DataType& datatype) override {
+        mOutput->setDatatype(datatype);
+
+        // FIXME: temporary workaround
+        mInputs[0]->setDatatype(datatype);
+        mInputs[1]->setDatatype(datatype);
+    }
+
+    inline IOIndex_t nbInputs() const noexcept override final { return 2; }
+    inline IOIndex_t nbDataInputs() const noexcept override final { return 2; }
+    inline IOIndex_t nbOutputs() const noexcept override final { return 1; }
+    static const std::vector<std::string> getInputsName(){
+        return {"data_input"};
+    }
+    static const std::vector<std::string> getOutputsName(){
+        return {"data_output"};
+    }
+};
+
+inline std::shared_ptr<Node> Mul(const std::string& name = "") {
+    return std::make_shared<Node>(std::make_shared<Mul_Op>(), name);
+}
+}
+
+#endif /* AIDGE_CORE_OPERATOR_MUL_H_ */

include/aidge/operator/Pow.hpp

+/********************************************************************************
+ * Copyright (c) 2023 CEA-List
+ *
+ * This program and the accompanying materials are made available under the
+ * terms of the Eclipse Public License 2.0 which is available at
+ * http://www.eclipse.org/legal/epl-2.0.
+ *
+ * SPDX-License-Identifier: EPL-2.0
+ *
+ ********************************************************************************/
+
+#ifndef AIDGE_CORE_OPERATOR_POW_H_
+#define AIDGE_CORE_OPERATOR_POW_H_
+
+#include <cassert>
+#include <memory>
+#include <vector>
+
+#include "aidge/utils/Registrar.hpp"
+#include "aidge/operator/Operator.hpp"
+#include "aidge/backend/OperatorImpl.hpp"
+#include "aidge/data/Tensor.hpp"
+#include "aidge/data/Data.hpp"
+#include "aidge/graph/Node.hpp"
+#include "aidge/utils/Types.h"
+
+namespace Aidge {
+
+class Pow_Op : public Operator,
+    public Registrable<Pow_Op, std::string, std::unique_ptr<OperatorImpl>(const Pow_Op&)> {
+public:
+    // FIXME: change accessibility
+    std::array<std::shared_ptr<Tensor>, 2> mInputs = {std::make_shared<Tensor>(), std::make_shared<Tensor>()};
+    const std::shared_ptr<Tensor> mOutput = std::make_shared<Tensor>();
+
+public:
+    static constexpr const char* Type = "Pow";
+
+    Pow_Op()
+            : Operator(Type)
+    {
+        setDatatype(DataType::Float32);
+    }
+
+    /**
+     * @brief Copy-constructor. Copy the operator attributes and its output tensor(s), but not its input tensors (the new operator has no input associated).
+     * @param op Operator to copy.
+     */
+    Pow_Op(const Pow_Op& op)
+        : Operator(Type),
+          mOutput(std::make_shared<Tensor>(*op.mOutput))
+    {
+        // cpy-ctor
+        setDatatype(op.mOutput->dataType());
+        mImpl = op.mImpl ? Registrar<Pow_Op>::create(mOutput->getImpl()->backend())(*this) : nullptr;
+    }
+
+    /**
+     * @brief Clone the operator using its copy-constructor.
+     * @see Operator::Pow_Op
+     */
+    std::shared_ptr<Operator> clone() const override {
+        return std::make_shared<Pow_Op>(*this);
+    }
+
+    void associateInput(const IOIndex_t inputIdx, std::shared_ptr<Data> data) override final {
+        assert(inputIdx < 2 && "operator supports only 2 inputs");
+        (void) inputIdx; // avoid unused warning
+        assert(strcmp(data->type(), Tensor::Type)==0 && "input data must be of Tensor type");
+        mInputs[inputIdx] = std::dynamic_pointer_cast<Tensor>(data);
+    }
+
+    void computeOutputDims() override final {
+        if (!mInputs[0]->empty())
+            mOutput->resize(mInputs[0]->dims());
+    }
+
+    bool outputDimsForwarded() const override final {
+        return !(mOutput->empty());
+    }
+
+
+    inline Tensor& input(const IOIndex_t inputIdx) const override final {
+        assert(static_cast<std::size_t>(inputIdx) < 2 && "wrong inputIdx for Add operator.");
+        return *(mInputs[inputIdx].get());
+    }
+    inline Tensor& output(const IOIndex_t /*outputIdx*/) const override final { return *(mOutput.get()); }
+
+
+    inline std::shared_ptr<Tensor> getInput(const IOIndex_t inputIdx) const override final {
+        assert((inputIdx < 2) && "Pow Operator has 2 inputs");
+        (void) inputIdx; // avoid unused warning
+        return mInputs[inputIdx];
+    }
+    inline std::shared_ptr<Tensor> getOutput(const IOIndex_t outputIdx) const override final {
+        assert((outputIdx == 0) && "Pow Operator has only 1 output");
+        (void) outputIdx; // avoid unused warning
+        return mOutput;
+    }
+
+
+    std::shared_ptr<Data> getRawInput(const IOIndex_t inputIdx) const override final {
+        assert(inputIdx < 2 && "operator supports only 2 inputs");
+        (void) inputIdx; // avoid unused warning
+        return std::static_pointer_cast<Data>(mInputs[inputIdx]);
+    }
+    std::shared_ptr<Data> getRawOutput(const IOIndex_t outputIdx) const override final {
+        assert(outputIdx == 0 && "operator supports only 1 output");
+        (void) outputIdx; // avoid unused warning
+        return std::static_pointer_cast<Data>(mOutput);
+    }
+
+
+    void setBackend(const std::string& name) override {
+        mImpl = Registrar<Pow_Op>::create(name)(*this);
+        mOutput->setBackend(name);
+
+        // FIXME: temporary workaround
+        mInputs[0]->setBackend(name);
+        mInputs[1]->setBackend(name);
+    }
+    void setDatatype(const DataType& datatype) override {
+        mOutput->setDatatype(datatype);
+
+        // FIXME: temporary workaround
+        mInputs[0]->setDatatype(datatype);
+        mInputs[1]->setDatatype(datatype);
+    }
+
+    inline IOIndex_t nbInputs() const noexcept override final { return 2; }
+    inline IOIndex_t nbDataInputs() const noexcept override final { return 2; }
+    inline IOIndex_t nbOutputs() const noexcept override final { return 1; }
+    static const std::vector<std::string> getInputsName(){
+        return {"data_input"};
+    }
+    static const std::vector<std::string> getOutputsName(){
+        return {"data_output"};
+    }
+};
+
+inline std::shared_ptr<Node> Pow(const std::string& name = "") {
+    return std::make_shared<Node>(std::make_shared<Pow_Op>(), name);
+}
+}
+
+#endif /* AIDGE_CORE_OPERATOR_POW_H_ */

include/aidge/operator/Sqrt.hpp

+/********************************************************************************
+ * Copyright (c) 2023 CEA-List
+ *
+ * This program and the accompanying materials are made available under the
+ * terms of the Eclipse Public License 2.0 which is available at
+ * http://www.eclipse.org/legal/epl-2.0.
+ *
+ * SPDX-License-Identifier: EPL-2.0
+ *
+ ********************************************************************************/
+
+#ifndef AIDGE_CORE_OPERATOR_SQRT_H_
+#define AIDGE_CORE_OPERATOR_SQRT_H_
+
+#include <cassert>
+#include <memory>
+#include <vector>
+
+#include "aidge/utils/Registrar.hpp"
+#include "aidge/operator/Operator.hpp"
+#include "aidge/backend/OperatorImpl.hpp"
+#include "aidge/data/Tensor.hpp"
+#include "aidge/data/Data.hpp"
+#include "aidge/graph/Node.hpp"
+#include "aidge/utils/Types.h"
+
+namespace Aidge {
+
+class Sqrt_Op : public Operator,
+    public Registrable<Sqrt_Op, std::string, std::unique_ptr<OperatorImpl>(const Sqrt_Op&)> {
+public:
+    // FIXME: change accessibility
+    std::shared_ptr<Tensor> mInput = std::make_shared<Tensor>();
+    const std::shared_ptr<Tensor> mOutput = std::make_shared<Tensor>();
+
+public:
+    static constexpr const char* Type = "Sqrt";
+
+    Sqrt_Op()
+            : Operator(Type)
+    {
+        setDatatype(DataType::Float32);
+    }
+
+    /**
+     * @brief Copy-constructor. Copy the operator attributes and its output tensor(s), but not its input tensors (the new operator has no input associated).
+     * @param op Operator to copy.
+     */
+    Sqrt_Op(const Sqrt_Op& op)
+        : Operator(Type),
+          mOutput(std::make_shared<Tensor>(*op.mOutput))
+    {
+        // cpy-ctor
+        setDatatype(op.mOutput->dataType());
+        mImpl = op.mImpl ? Registrar<Sqrt_Op>::create(mOutput->getImpl()->backend())(*this) : nullptr;
+    }
+
+    /**
+     * @brief Clone the operator using its copy-constructor.
+     * @see Operator::Sqrt_Op
+     */
+    std::shared_ptr<Operator> clone() const override {
+        return std::make_shared<Sqrt_Op>(*this);
+    }
+
+    void associateInput(const IOIndex_t inputIdx, std::shared_ptr<Data> data) override final {
+        assert(inputIdx == 0 && "operator supports only 1 input");
+        (void) inputIdx; // avoid unused warning
+        assert(strcmp(data->type(), Tensor::Type)==0 && "input data must be of Tensor type");
+        mInput = std::dynamic_pointer_cast<Tensor>(data);
+    }
+
+    void computeOutputDims() override final {
+        if (!mInput->empty())
+            mOutput->resize(mInput->dims());
+    }
+
+    bool outputDimsForwarded() const override final {
+        return !(mOutput->empty());
+    }
+
+
+    inline Tensor& input(const IOIndex_t /*inputIdx*/) const override final { return *(mInput.get()); }
+    inline Tensor& output(const IOIndex_t /*outputIdx*/) const override final { return *(mOutput.get()); }
+
+
+    inline std::shared_ptr<Tensor> getInput(const IOIndex_t inputIdx) const override final {
+        assert((inputIdx == 0) && "Sqrt Operator has only 1 input");
+        (void) inputIdx; // avoid unused warning
+        return mInput;
+    }
+    inline std::shared_ptr<Tensor> getOutput(const IOIndex_t outputIdx) const override final {
+        assert((outputIdx == 0) && "Sqrt Operator has only 1 output");
+        (void) outputIdx; // avoid unused warning
+        return mOutput;
+    }
+
+
+    std::shared_ptr<Data> getRawInput(const IOIndex_t inputIdx) const override final {
+        assert(inputIdx == 0 && "operator supports only 1 input");
+        (void) inputIdx; // avoid unused warning
+        return std::static_pointer_cast<Data>(mInput);
+    }
+    std::shared_ptr<Data> getRawOutput(const IOIndex_t outputIdx) const override final {
+        assert(outputIdx == 0 && "operator supports only 1 output");
+        (void) outputIdx; // avoid unused warning
+        return std::static_pointer_cast<Data>(mOutput);
+    }
+
+
+    void setBackend(const std::string& name) override {
+        mImpl = Registrar<Sqrt_Op>::create(name)(*this);
+        mOutput->setBackend(name);
+
+        // FIXME: temporary workaround
+        mInput->setBackend(name);
+    }
+    void setDatatype(const DataType& datatype) override {
+        mOutput->setDatatype(datatype);
+
+        // FIXME: temporary workaround
+        mInput->setDatatype(datatype);
+    }
+
+    inline IOIndex_t nbInputs() const noexcept override final { return 1; }
+    inline IOIndex_t nbDataInputs() const noexcept override final { return 1; }
+    inline IOIndex_t nbOutputs() const noexcept override final { return 1; }
+    static const std::vector<std::string> getInputsName(){
+        return {"data_input"};
+    }
+    static const std::vector<std::string> getOutputsName(){
+        return {"data_output"};
+    }
+};
+
+inline std::shared_ptr<Node> Sqrt(const std::string& name = "") {
+    return std::make_shared<Node>(std::make_shared<Sqrt_Op>(), name);
+}
+}
+
+#endif /* AIDGE_CORE_OPERATOR_SQRT_H_ */

include/aidge/operator/Sub.hpp

+/********************************************************************************
+ * Copyright (c) 2023 CEA-List
+ *
+ * This program and the accompanying materials are made available under the
+ * terms of the Eclipse Public License 2.0 which is available at
+ * http://www.eclipse.org/legal/epl-2.0.
+ *
+ * SPDX-License-Identifier: EPL-2.0
+ *
+ ********************************************************************************/
+
+#ifndef AIDGE_CORE_OPERATOR_SUB_H_
+#define AIDGE_CORE_OPERATOR_SUB_H_
+
+#include <cassert>
+#include <memory>
+#include <vector>
+
+#include "aidge/utils/Registrar.hpp"
+#include "aidge/operator/Operator.hpp"
+#include "aidge/backend/OperatorImpl.hpp"
+#include "aidge/data/Tensor.hpp"
+#include "aidge/data/Data.hpp"
+#include "aidge/graph/Node.hpp"
+#include "aidge/utils/Types.h"
+
+namespace Aidge {
+
+class Sub_Op : public Operator,
+    public Registrable<Sub_Op, std::string, std::unique_ptr<OperatorImpl>(const Sub_Op&)> {
+public:
+    // FIXME: change accessibility
+    std::array<std::shared_ptr<Tensor>, 2> mInputs = {std::make_shared<Tensor>(), std::make_shared<Tensor>()};
+    const std::shared_ptr<Tensor> mOutput = std::make_shared<Tensor>();
+
+public:
+    static constexpr const char* Type = "Sub";
+
+    Sub_Op()
+            : Operator(Type)
+    {
+        setDatatype(DataType::Float32);
+    }
+
+    /**
+     * @brief Copy-constructor. Copy the operator attributes and its output tensor(s), but not its input tensors (the new operator has no input associated).
+     * @param op Operator to copy.
+     */
+    Sub_Op(const Sub_Op& op)
+        : Operator(Type),
+          mOutput(std::make_shared<Tensor>(*op.mOutput))
+    {
+        // cpy-ctor
+        setDatatype(op.mOutput->dataType());
+        mImpl = op.mImpl ? Registrar<Sub_Op>::create(mOutput->getImpl()->backend())(*this) : nullptr;
+    }
+
+    /**
+     * @brief Clone the operator using its copy-constructor.
+     * @see Operator::Sub_Op
+     */
+    std::shared_ptr<Operator> clone() const override {
+        return std::make_shared<Sub_Op>(*this);
+    }
+
+    void associateInput(const IOIndex_t inputIdx, std::shared_ptr<Data> data) override final {
+        assert(inputIdx < 2 && "operator supports only 2 inputs");
+        (void) inputIdx; // avoid unused warning
+        assert(strcmp(data->type(), Tensor::Type)==0 && "input data must be of Tensor type");
+        mInputs[inputIdx] = std::dynamic_pointer_cast<Tensor>(data);
+    }
+
+    void computeOutputDims() override final {
+        if (!mInputs[0]->empty())
+            mOutput->resize(mInputs[0]->dims());
+    }
+
+    bool outputDimsForwarded() const override final {
+        return !(mOutput->empty());
+    }
+
+
+    inline Tensor& input(const IOIndex_t inputIdx) const override final {
+        assert(static_cast<std::size_t>(inputIdx) < 2 && "wrong inputIdx for Add operator.");
+        return *(mInputs[inputIdx].get());
+    }
+    inline Tensor& output(const IOIndex_t /*outputIdx*/) const override final { return *(mOutput.get()); }
+
+
+    inline std::shared_ptr<Tensor> getInput(const IOIndex_t inputIdx) const override final {
+        assert((inputIdx < 2) && "Sub Operator has 2 inputs");
+        (void) inputIdx; // avoid unused warning
+        return mInputs[inputIdx];
+    }
+    inline std::shared_ptr<Tensor> getOutput(const IOIndex_t outputIdx) const override final {
+        assert((outputIdx == 0) && "Sub Operator has only 1 output");
+        (void) outputIdx; // avoid unused warning
+        return mOutput;
+    }
+
+
+    std::shared_ptr<Data> getRawInput(const IOIndex_t inputIdx) const override final {
+        assert(inputIdx < 2 && "operator supports only 2 inputs");
+        (void) inputIdx; // avoid unused warning
+        return std::static_pointer_cast<Data>(mInputs[inputIdx]);
+    }
+    std::shared_ptr<Data> getRawOutput(const IOIndex_t outputIdx) const override final {
+        assert(outputIdx == 0 && "operator supports only 1 output");
+        (void) outputIdx; // avoid unused warning
+        return std::static_pointer_cast<Data>(mOutput);
+    }
+
+
+    void setBackend(const std::string& name) override {
+        mImpl = Registrar<Sub_Op>::create(name)(*this);
+        mOutput->setBackend(name);
+
+        // FIXME: temporary workaround
+        mInputs[0]->setBackend(name);
+        mInputs[1]->setBackend(name);
+    }
+    void setDatatype(const DataType& datatype) override {
+        mOutput->setDatatype(datatype);
+
+        // FIXME: temporary workaround
+        mInputs[0]->setDatatype(datatype);
+        mInputs[1]->setDatatype(datatype);
+    }
+
+    inline IOIndex_t nbInputs() const noexcept override final { return 2; }
+    inline IOIndex_t nbDataInputs() const noexcept override final { return 2; }
+    inline IOIndex_t nbOutputs() const noexcept override final { return 1; }
+    static const std::vector<std::string> getInputsName(){
+        return {"data_input"};
+    }
+    static const std::vector<std::string> getOutputsName(){
+        return {"data_output"};
+    }
+};
+
+inline std::shared_ptr<Node> Sub(const std::string& name = "") {
+    return std::make_shared<Node>(std::make_shared<Sub_Op>(), name);
+}
+}
+
+#endif /* AIDGE_CORE_OPERATOR_SUB_H_ */

python_binding/operator/pybind_Div.cpp

+/********************************************************************************
+ * Copyright (c) 2023 CEA-List
+ *
+ * This program and the accompanying materials are made available under the
+ * terms of the Eclipse Public License 2.0 which is available at
+ * http://www.eclipse.org/legal/epl-2.0.
+ *
+ * SPDX-License-Identifier: EPL-2.0
+ *
+ ********************************************************************************/
+
+#include <pybind11/pybind11.h>
+
+#include "aidge/operator/Div.hpp"
+#include "aidge/operator/Operator.hpp"
+
+namespace py = pybind11;
+namespace Aidge {
+
+void init_Div(py::module& m) {
+    py::class_<Div_Op, std::shared_ptr<Div_Op>, Operator>(m, "DivOp", py::multiple_inheritance())
+    .def("get_inputs_name", &Div_Op::getInputsName)
+    .def("get_outputs_name", &Div_Op::getOutputsName);
+
+    m.def("Div", &Div, py::arg("name") = "");
+}
+}  // namespace Aidge

python_binding/operator/pybind_GenericOperator.cpp

@@ -27,7 +27,7 @@ void init_GenericOperator(py::module& m) {
     .def("compute_output_dims", &GenericOperator_Op::computeOutputDims)
     .def("set_compute_output_dims", &GenericOperator_Op::setComputeOutputDims, py::arg("computation_function"));
 
-    m.def("GenericOperator", &GenericOperator, py::arg("type"), py::arg("nbDataIn"), py::arg("nbIn"), py::arg("nbOut"),
+    m.def("GenericOperator", &GenericOperator, py::arg("type"), py::arg("nb_data_in"), py::arg("nb_in"), py::arg("nb_out"),
           py::arg("name") = "");
 }
 }  // namespace Aidge

python_binding/operator/pybind_Mul.cpp

+/********************************************************************************
+ * Copyright (c) 2023 CEA-List
+ *
+ * This program and the accompanying materials are made available under the
+ * terms of the Eclipse Public License 2.0 which is available at
+ * http://www.eclipse.org/legal/epl-2.0.
+ *
+ * SPDX-License-Identifier: EPL-2.0
+ *
+ ********************************************************************************/
+
+#include <pybind11/pybind11.h>
+
+#include "aidge/operator/Mul.hpp"
+#include "aidge/operator/Operator.hpp"
+
+namespace py = pybind11;
+namespace Aidge {
+
+void init_Mul(py::module& m) {
+    py::class_<Mul_Op, std::shared_ptr<Mul_Op>, Operator>(m, "MulOp", py::multiple_inheritance())
+    .def("get_inputs_name", &Mul_Op::getInputsName)
+    .def("get_outputs_name", &Mul_Op::getOutputsName);
+
+    m.def("Mul", &Mul, py::arg("name") = "");
+}
+}  // namespace Aidge

python_binding/operator/pybind_Pow.cpp

+/********************************************************************************
+ * Copyright (c) 2023 CEA-List
+ *
+ * This program and the accompanying materials are made available under the
+ * terms of the Eclipse Public License 2.0 which is available at
+ * http://www.eclipse.org/legal/epl-2.0.
+ *
+ * SPDX-License-Identifier: EPL-2.0
+ *
+ ********************************************************************************/
+
+#include <pybind11/pybind11.h>
+
+#include "aidge/operator/Pow.hpp"
+#include "aidge/operator/Operator.hpp"
+
+namespace py = pybind11;
+namespace Aidge {
+
+void init_Pow(py::module& m) {
+    py::class_<Pow_Op, std::shared_ptr<Pow_Op>, Operator>(m, "PowOp", py::multiple_inheritance())
+    .def("get_inputs_name", &Pow_Op::getInputsName)
+    .def("get_outputs_name", &Pow_Op::getOutputsName);
+
+    m.def("Pow", &Pow, py::arg("name") = "");
+}
+}  // namespace Aidge

python_binding/operator/pybind_Sqrt.cpp

+/********************************************************************************
+ * Copyright (c) 2023 CEA-List
+ *
+ * This program and the accompanying materials are made available under the
+ * terms of the Eclipse Public License 2.0 which is available at
+ * http://www.eclipse.org/legal/epl-2.0.
+ *
+ * SPDX-License-Identifier: EPL-2.0
+ *
+ ********************************************************************************/
+
+#include <pybind11/pybind11.h>
+
+#include "aidge/operator/Sqrt.hpp"
+#include "aidge/operator/Operator.hpp"
+
+namespace py = pybind11;
+namespace Aidge {
+
+void init_Sqrt(py::module& m) {
+    py::class_<Sqrt_Op, std::shared_ptr<Sqrt_Op>, Operator>(m, "SqrtOp", py::multiple_inheritance())
+    .def("get_inputs_name", &Sqrt_Op::getInputsName)
+    .def("get_outputs_name", &Sqrt_Op::getOutputsName);
+
+    m.def("Sqrt", &Sqrt, py::arg("name") = "");
+}
+}  // namespace Aidge

python_binding/operator/pybind_Sub.cpp

+/********************************************************************************
+ * Copyright (c) 2023 CEA-List
+ *
+ * This program and the accompanying materials are made available under the
+ * terms of the Eclipse Public License 2.0 which is available at
+ * http://www.eclipse.org/legal/epl-2.0.
+ *
+ * SPDX-License-Identifier: EPL-2.0
+ *
+ ********************************************************************************/
+
+#include <pybind11/pybind11.h>
+
+#include "aidge/operator/Sub.hpp"
+#include "aidge/operator/Operator.hpp"
+
+namespace py = pybind11;
+namespace Aidge {
+
+void init_Sub(py::module& m) {
+    py::class_<Sub_Op, std::shared_ptr<Sub_Op>, Operator>(m, "SubOp", py::multiple_inheritance())
+    .def("get_inputs_name", &Sub_Op::getInputsName)
+    .def("get_outputs_name", &Sub_Op::getOutputsName);
+
+    m.def("Sub", &Sub, py::arg("name") = "");
+}
+}  // namespace Aidge

python_binding/pybind_core.cpp

@@ -25,15 +25,20 @@ void init_AvgPooling(py::module&);
 void init_BatchNorm(py::module&);
 void init_Conv(py::module&);
 void init_ConvDepthWise(py::module&);
+void init_Div(py::module&);
 void init_FC(py::module&);
 void init_GenericOperator(py::module&);
 void init_LeakyReLU(py::module&);
 void init_MatMul(py::module&);
 void init_MaxPooling(py::module&);
 void init_MetaOperatorDefs(py::module&);
+void init_Mul(py::module&);
 void init_Producer(py::module&);
+void init_Pow(py::module&);
 void init_ReLU(py::module&);
 void init_Softmax(py::module&);
+void init_Sqrt(py::module&);
+void init_Sub(py::module&);
 
 void init_Node(py::module&);
 void init_GraphView(py::module&);
@@ -67,14 +72,19 @@ void init_Aidge(py::module& m){
     init_BatchNorm(m);
     init_Conv(m);
     init_ConvDepthWise(m);
+    init_Div(m);
     init_FC(m);
     init_GenericOperator(m);
     init_LeakyReLU(m);
     init_MatMul(m);
     init_MaxPooling(m);
     init_MetaOperatorDefs(m);
+    init_Mul(m);
+    init_Pow(m);
     init_ReLU(m);
     init_Softmax(m);
+    init_Sqrt(m);
+    init_Sub(m);
 
     init_Producer(m);
     init_Match(m);