diff --git a/include/aidge/backend/cpu.hpp b/include/aidge/backend/cpu.hpp
index 963895c1adbff22a770851bbc5ba305007415f1e..712d520377d8d71eb5f371a13e10712bae846589 100644
--- a/include/aidge/backend/cpu.hpp
+++ b/include/aidge/backend/cpu.hpp
@@ -15,6 +15,8 @@
#include "aidge/backend/cpu/operator/AbsImpl.hpp"
#include "aidge/backend/cpu/operator/AddImpl.hpp"
#include "aidge/backend/cpu/operator/AndImpl.hpp"
+#include "aidge/backend/cpu/operator/AtanImpl.hpp"
+
#include "aidge/backend/cpu/operator/ArgMaxImpl.hpp"
#include "aidge/backend/cpu/operator/AvgPoolingImpl.hpp"
#include "aidge/backend/cpu/operator/MaxPoolingImpl.hpp"
diff --git a/include/aidge/backend/cpu/operator/AtanImpl.hpp b/include/aidge/backend/cpu/operator/AtanImpl.hpp
new file mode 100644
index 0000000000000000000000000000000000000000..2f1b4bf0ad666ff9856c24fa675b70d6f830b07c
--- /dev/null
+++ b/include/aidge/backend/cpu/operator/AtanImpl.hpp
@@ -0,0 +1,33 @@
+/********************************************************************************
+ * 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_CPU_OPERATOR_ATAN_H_
+#define AIDGE_CPU_OPERATOR_ATAN_H_
+
+#include "aidge/backend/cpu/operator/OperatorImpl.hpp"
+#include "aidge/operator/Atan.hpp"
+#include "aidge/utils/Registrar.hpp"
+#include "aidge/utils/Types.h"
+#include "aidge/backend/cpu/data/GetCPUPtr.h"
+#include <memory>
+#include <vector>
+
+namespace Aidge {
+// Operator implementation entry point for the backend
+using AtanImpl_cpu = OperatorImpl_cpu<Atan_Op,
+ void(const std::size_t, const void*, void*),
+ void(const std::size_t, const void*, const void*, void*)>;
+
+// Implementation entry point registration to Operator
+REGISTRAR(Atan_Op, "cpu", Aidge::AtanImpl_cpu::create);
+} // namespace Aidge
+
+#endif /* AIDGE_CPU_OPERATOR_ATAN_H_ */
diff --git a/include/aidge/backend/cpu/operator/AtanImpl_kernels.hpp b/include/aidge/backend/cpu/operator/AtanImpl_kernels.hpp
new file mode 100644
index 0000000000000000000000000000000000000000..2a786339503354514416705b61cfedfcc0b7c321
--- /dev/null
+++ b/include/aidge/backend/cpu/operator/AtanImpl_kernels.hpp
@@ -0,0 +1,60 @@
+/********************************************************************************
+ * 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_CPU_OPERATOR_ATANIMPL_KERNELS_H_
+#define AIDGE_CPU_OPERATOR_ATANIMPL_KERNELS_H_
+
+#include "aidge/utils/Registrar.hpp"
+
+#include "aidge/backend/cpu/operator/AtanImpl.hpp"
+#include <cmath> // For atan()
+
+
+namespace Aidge {
+template <class I, class O>
+void AtanImpl_cpu_forward_kernel(std::size_t inputLenght,
+ const void* input_,
+ void* output_) {
+ const I* input = static_cast<const I*>(input_);
+ O* output = static_cast<O*>(output_);
+
+ for (size_t i = 0; i < inputLenght; ++i) {
+ output[i] = static_cast<O>(atan(input[i]));
+ }
+
+}
+
+template <class O, class GI, class GO>
+void AtanImpl_cpu_backward_kernel(const std::size_t inputLenght,
+ const void* output_, const void* grad_output_,
+ void* grad_input_) {
+ const O* output = static_cast<const O*>(output_);
+ const GO* grad_output = static_cast<const GO*>(grad_output_);
+ GI* grad_input = static_cast<GI*>(grad_input_);
+
+ // Apply the derivative of atan for each element in the input array
+ for (size_t i = 0; i < inputLenght; ++i) {
+ // dx = dy * (1 / (1 + x^2))
+ grad_input[i] = grad_output[i] * static_cast<O>(1.0 / (1.0 + output[i] * output[i]));
+ }
+}
+
+
+// Kernels registration to implementation entry point
+REGISTRAR(AtanImpl_cpu,
+ {DataType::Float32},
+ {ProdConso::inPlaceModel, Aidge::AtanImpl_cpu_forward_kernel<float, float>, Aidge::AtanImpl_cpu_backward_kernel<float, float, float>});
+REGISTRAR(AtanImpl_cpu,
+ {DataType::Float64},
+ {ProdConso::inPlaceModel, Aidge::AtanImpl_cpu_forward_kernel<double, double>, Aidge::AtanImpl_cpu_backward_kernel<double, double, double>});
+} // namespace Aidge
+
+#endif /* AIDGE_CPU_OPERATOR_ATANIMPL_KERNELS_H_ */
diff --git a/src/operator/AtanImpl.cpp b/src/operator/AtanImpl.cpp
new file mode 100644
index 0000000000000000000000000000000000000000..af3393e7eb13fad4b414172edc7d1ab32ffcc573
--- /dev/null
+++ b/src/operator/AtanImpl.cpp
@@ -0,0 +1,54 @@
+/********************************************************************************
+ * 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 <cassert>
+#include <chrono> // std::chrono::milliseconds
+#include <numeric> // std::accumulate
+#include <thread> // std::this_thread::sleep_for
+#include <vector>
+
+#include "aidge/operator/Atan.hpp"
+#include "aidge/utils/Types.h"
+#include "aidge/backend/cpu/data/GetCPUPtr.h"
+
+#include "aidge/backend/cpu/operator/AtanImpl.hpp"
+#include "aidge/backend/cpu/operator/AtanImpl_kernels.hpp"
+
+template <>
+void Aidge::AtanImpl_cpu::forward() {
+ const Atan_Op& op_ = dynamic_cast<const Atan_Op&>(mOp);
+ std::shared_ptr<Tensor> in0 = op_.getInput(0);
+ std::shared_ptr<Tensor> out0 = op_.getOutput(0);
+ AIDGE_ASSERT(in0, "missing input #0");
+
+ // Find the correct kernel type
+ const auto impl = Registrar<AtanImpl_cpu>::create(getBestMatch(getRequiredSpec()));
+
+ // Call kernel
+ impl.forward(in0->size(),
+ getCPUPtr(mOp.getRawInput(0)),
+ getCPUPtr(mOp.getRawOutput(0)));
+}
+
+template <>
+void Aidge::AtanImpl_cpu::backward() {
+ const Atan_Op& op_ = dynamic_cast<const Atan_Op&>(mOp);
+ std::shared_ptr<Tensor> out0 = op_.getOutput(0);
+ std::shared_ptr<Tensor> gra_int0 = op_.getInput(0)->grad();
+ std::shared_ptr<Tensor> gra_out0 = op_.getOutput(0)->grad();
+ AIDGE_ASSERT(out0, "missing output #0 for current {} operator", op_.type());
+
+ // Find the correct kernel type
+ const auto impl = Registrar<AtanImpl_cpu>::create(getBestMatch(getRequiredSpec()));
+
+ // Call kernel
+ impl.backward(gra_int0->size(), getCPUPtr(out0), getCPUPtr(gra_out0), getCPUPtr(gra_int0));
+}
diff --git a/unit_tests/operator/Test_Atan.cpp b/unit_tests/operator/Test_Atan.cpp
new file mode 100644
index 0000000000000000000000000000000000000000..9548e35d81b0423125424a4198d82558c4e57df4
--- /dev/null
+++ b/unit_tests/operator/Test_Atan.cpp
@@ -0,0 +1,77 @@
+/********************************************************************************
+ * 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 <catch2/catch_test_macros.hpp>
+
+#include "aidge/data/Tensor.hpp"
+#include "aidge/operator/Atan.hpp"
+
+#include "aidge/backend/cpu.hpp"
+
+#include <memory>
+
+using namespace Aidge;
+
+TEST_CASE("[cpu/operator] Atan(forward)") {
+ SECTION("1D Tensor") {
+ std::shared_ptr<Tensor> input0 =
+ std::make_shared<Tensor>(Array1D<float, 10>{
+ {0.41384590, 0.43120754, 0.93762982, 0.31049860, 0.77547199,
+ 0.09514862, 0.16145366, 0.42776686, 0.43487436, 0.41170865}});
+ std::shared_ptr<Tensor> expectedOutput =
+ std::make_shared<Tensor>(Array1D<float, 10>{
+ {0.39238522, 0.40711672, 0.75322037, 0.30106049, 0.65960488,
+ 0.09486303, 0.16007232, 0.40421187, 0.4102045, 0.39055911}});
+
+ std::shared_ptr<Node> myAtan = Atan();
+ auto op = std::static_pointer_cast<OperatorTensor>(myAtan->getOperator());
+ op->associateInput(0, input0);
+ op->setDataType(DataType::Float32);
+ op->setBackend("cpu");
+ myAtan->forward();
+
+ float* resPtr = static_cast<float*>(op->getOutput(0)->getImpl()->rawPtr());
+ float* expectedPtr =
+ static_cast<float*>(expectedOutput->getImpl()->rawPtr());
+ for (std::size_t i = 0; i < expectedOutput->size(); ++i) {
+ REQUIRE(std::abs(resPtr[i] - expectedPtr[i]) < 0.00001);
+ }
+ }
+
+ SECTION("3D Tensor") {
+ std::shared_ptr<Tensor> input0 = std::make_shared<Tensor>(
+ Array3D<float, 2, 2, 3>{{{
+ {0.97037154, 0.86208081, 0.77767169},
+ {0.38160080, 0.11422747, 0.77284443},
+ },
+ {{0.51592529, 0.72543722, 0.54641193},
+ {0.93866944, 0.97767913, 0.34172094}}}});
+ std::shared_ptr<Tensor> expectedOutput = std::make_shared<Tensor>(
+ Array3D<float, 2, 2, 3>{{{{0.77036231, 0.71146592, 0.66097706},
+ {0.36454508, 0.11373451, 0.65796196}},
+ {{0.47630652, 0.62759472, 0.50008428},
+ {0.75377332, 0.77411225, 0.32928031}}}});
+
+ std::shared_ptr<Node> myAtan = Atan();
+ auto op = std::static_pointer_cast<OperatorTensor>(myAtan->getOperator());
+ op->associateInput(0, input0);
+ op->setDataType(DataType::Float32);
+ op->setBackend("cpu");
+ myAtan->forward();
+
+ float* resPtr = static_cast<float*>(op->getOutput(0)->getImpl()->rawPtr());
+ float* expectedPtr =
+ static_cast<float*>(expectedOutput->getImpl()->rawPtr());
+ for (std::size_t i = 0; i < expectedOutput->size(); ++i) {
+ REQUIRE(std::abs(resPtr[i] - expectedPtr[i]) < 0.00001);
+ }
+ }
+}