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Commit 124c6d39 authored by Maxence Naud's avatar Maxence Naud
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[Add] Tests for arithmetic operators' computeOutputDims() member function

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2 merge requests!105version 0.2.0,!65[Add] broadcasting for Arithmetic Operators
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Stage: static_analysis
    Stage: build
      Stage: test
        Stage: coverage
          This commit is part of merge request !65. Comments created here will be created in the context of that merge request.
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          unit_tests/operator/Test_Div_Op.cpp
          + 59
          − 82
          View file @ 124c6d39
          ...@@ -26,142 +26,119 @@ TEST_CASE("[core/operator] Div_Op(computeOutputDims)", "[Div][computeOutputDims] ...@@ -26,142 +26,119 @@ TEST_CASE("[core/operator] Div_Op(computeOutputDims)", "[Div][computeOutputDims]
          // Create a random number generator // Create a random number generator
          std::random_device rd; std::random_device rd;
          std::mt19937 gen(rd()); std::mt19937 gen(rd());
          std::uniform_int_distribution<std::size_t> dist(1, 10); std::uniform_int_distribution<std::size_t> dimsDist(1, 10);
          std::uniform_int_distribution<std::size_t> nbDims(1, 5); std::uniform_int_distribution<std::size_t> nbDimsDist(1, 5);
          // Create Div Operator // Create Div Operator
          std::shared_ptr<Node> myDiv = Div(); std::shared_ptr<Node> myDiv = Div();
          auto op = std::static_pointer_cast<OperatorTensor>(myDiv -> getOperator()); auto op = std::static_pointer_cast<OperatorTensor>(myDiv -> getOperator());
          /** @todo Special case of scalar Tensor objects. // input_0
          * Not handled yet. std::shared_ptr<Tensor> T0 = std::make_shared<Tensor>();
          */ op -> associateInput(0,T0);
          // SECTION("0-D / 0-D") { // input_1
          std::shared_ptr<Tensor> T1 = std::make_shared<Tensor>();
          op -> associateInput(1,T1);
          /**
          * @todo Special case: scalar not handled yet by
          * ``OperatorTensor::computeOutputDims()``
          */
          // SECTION("Scalar / Scalar") {
          // // input_0 // // input_0
          // std::shared_ptr<Tensor> T0 = std::make_shared<Tensor>();
          // T0->resize({}); // T0->resize({});
          // op -> associateInput(0,T0);
          // // input_1 - right // // input_1
          // std::shared_ptr<Tensor> T1 = std::make_shared<Tensor>();
          // T1->resize({}); // T1->resize({});
          // op -> associateInput(1,T1);
          // REQUIRE_NOTHROW(op->computeOutputDims()); // REQUIRE_NOTHROW(op->computeOutputDims());
          // REQUIRE((op->getOutput(0)->dims()).empty()); // REQUIRE((op->getOutput(0)->dims() == std::vector<std::size_t>()));
          // // input_1 - wrong
          // T1->resize({dist(gen)});
          // REQUIRE_THROWS(op->computeOutputDims());
          // } // }
          // SECTION("0-D / +1-D") { // SECTION("Scalar / +1-D") {
          // // a scalar is compatible with any other Tensor
          // // input_0 // // input_0
          // std::shared_ptr<Tensor> T0 = std::make_shared<Tensor>();
          // op -> associateInput(0,T0);
          // T0->resize({}); // T0->resize({});
          // // input_1
          // std::shared_ptr<Tensor> T1 = std::make_shared<Tensor>();
          // op -> associateInput(1,T1);
          // for (std::uint16_t trial = 0; trial < NBTRIALS; ++trial) { // for (std::uint16_t trial = 0; trial < NBTRIALS; ++trial) {
          // const std::size_t nb_dims = nbDims(gen);
          // // input_1
          // const std::size_t nb_dims = nbDimsDist(gen);
          // std::vector<std::size_t> dims(nb_dims); // std::vector<std::size_t> dims(nb_dims);
          // for (std::size_t i = 0; i < nb_dims; ++i) { // for (std::size_t i = 0; i < nb_dims; ++i) {
          // dims[i] = dist(gen); // dims[i] = dimsDist(gen);
          // } // }
          // // input_1 - right
          // T1->resize(dims); // T1->resize(dims);
          // REQUIRE_NOTHROW(op->computeOutputDims()); // REQUIRE_NOTHROW(op->computeOutputDims());
          // REQUIRE((op->getOutput(0)->dims()) == dims); // REQUIRE((op->getOutput(0)->dims()) == dims);
          // // input_1 - wrong
          // T1->resize({dims[0] + 1});
          // REQUIRE_THROWS(op->computeOutputDims());
          // } // }
          // } // }
          // SECTION("+1-D / 0-D") { // SECTION("+1-D / Scalar") {
          // // a scalar is compatible with any other Tensor
          // // input_1 // // input_1
          // std::shared_ptr<Tensor> T1 = std::make_shared<Tensor>();
          // T1->resize({}); // T1->resize({});
          // op -> associateInput(1,T1);
          // // input_0
          // std::shared_ptr<Tensor> T0 = std::make_shared<Tensor>();
          // op -> associateInput(0,T0);
          // for (std::uint16_t trial = 0; trial < NBTRIALS; ++trial) { // for (std::uint16_t trial = 0; trial < NBTRIALS; ++trial) {
          // const std::size_t nb_dims = nbDims(gen);
          // // input_0
          // const std::size_t nb_dims = nbDimsDist(gen);
          // std::vector<std::size_t> dims(nb_dims); // std::vector<std::size_t> dims(nb_dims);
          // for (std::size_t i = 0; i < nb_dims; ++i) { // for (std::size_t i = 0; i < nb_dims; ++i) {
          // dims[i] = dist(gen); // dims[i] = dimsDist(gen);
          // } // }
          // // input_0 - right
          // T0->resize(dims); // T0->resize(dims);
          // REQUIRE_NOTHROW(op->computeOutputDims()); // REQUIRE_NOTHROW(op->computeOutputDims());
          // REQUIRE((op->getOutput(0)->dims()) == dims); // REQUIRE((op->getOutput(0)->dims()) == dims);
          // // input_0 - wrong
          // T1->resize({dims[0] + 1});
          // REQUIRE_THROWS(op->computeOutputDims());
          // } // }
          // } // }
          SECTION("+1-D / +1-D") { SECTION("+1-D / +1-D") {
          // input_0 // same size
          std::shared_ptr<Tensor> T0 = std::make_shared<Tensor>();
          op -> associateInput(0,T0);
          // input_1
          std::shared_ptr<Tensor> T1 = std::make_shared<Tensor>();
          op -> associateInput(1,T1);
          for (std::uint16_t trial = 0; trial < NBTRIALS; ++trial) { for (std::uint16_t trial = 0; trial < NBTRIALS; ++trial) {
          const std::size_t nb_dims = nbDims(gen) + 1; const std::size_t nb_dims = nbDimsDist(gen) + 1;
          std::vector<std::size_t> dims(nb_dims); std::vector<std::size_t> dims0(nb_dims);
          for (std::size_t i = 0; i < nb_dims; ++i) { for (std::size_t i = 0; i < nb_dims; ++i) {
          dims[i] = dist(gen); dims0[i] = dimsDist(gen) + 1;
          } }
          T0->resize(dims);
          // input_1 - right - same dims T0->resize(dims0);
          T1->resize(dims); T1->resize(dims0);
          REQUIRE_NOTHROW(op->computeOutputDims()); REQUIRE_NOTHROW(op->computeOutputDims());
          REQUIRE((op->getOutput(0)->dims()) == dims); REQUIRE((op->getOutput(0)->dims()) == dims0);
          }
          // input_1 - right - broadcast // broadcast
          std::vector<std::size_t> dims_for_broadcast(nb_dims); for (std::uint16_t trial = 0; trial < NBTRIALS; ++trial) {
          const std::size_t nb_dims = nbDimsDist(gen) + 1;
          std::vector<std::size_t> dims0(nb_dims);
          for (std::size_t i = 0; i < nb_dims; ++i) { for (std::size_t i = 0; i < nb_dims; ++i) {
          dims_for_broadcast[i] = ((i % 2) == 0) ? dims[i] : 1; dims0[i] = dimsDist(gen) + 2;
          } }
          T1->resize(dims); std::vector<std::size_t> dimsOut = dims0;
          std::vector<std::size_t> dims1 = dims0;
          REQUIRE_NOTHROW(op->computeOutputDims()); for (std::size_t i = 0; i < nb_dims; ++i) {
          REQUIRE((op->getOutput(0)->dims()) == dims); if (dimsDist(gen) <= 5) {
          dims1[i] = 1;
          }
          }
          dims1.erase(dims1.cbegin(), dims1.cbegin() + std::min(nbDimsDist(gen), nb_dims-1));
          // input_1 - right - less dimensions T0->resize(dims0);
          const std::vector<std::size_t> dims_less_dimensions(dims.cbegin() + nbDims(gen), dims.cend()); T1->resize(dims1);
          T1->resize(dims_less_dimensions);
          REQUIRE_NOTHROW(op->computeOutputDims()); REQUIRE_NOTHROW(op->computeOutputDims());
          REQUIRE((op->getOutput(0)->dims()) == dims); REQUIRE((op->getOutput(0)->dims()) == dimsOut);
          // input_0 - wrong // input_0 - wrong
          // T1->resize({dims[0] + 1}); // T1->resize({dims[0] + 1});
          std::vector<std::size_t> dims_wrong = dims; std::vector<std::size_t> dims1_wrong = dims1;
          for (std::size_t i = 0; i< nb_dims; ++i) { for (std::size_t i = 0; i < dims1.size(); ++i) {
          ++dims_wrong[i]; ++dims1_wrong[i];
          } }
          T1->resize(dims); T1->resize(dims1_wrong);
          if (dims != std::vector<size_t>(nb_dims, 1)) REQUIRE(dims0 != dims1_wrong);
          REQUIRE_THROWS(op->computeOutputDims()); REQUIRE_THROWS(op->computeOutputDims());
          } }
          } }
          } }
          } // namespace Aidge } // namespace Aidge
          \ No newline at end of file
          unit_tests/operator/Test_Mul_Op.cpp 0 → 100644
          + 144
          − 0
          View file @ 124c6d39
          /********************************************************************************
          * 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 <cstddef> // std::size_t
          #include <memory>
          #include <random> // std::random_device, std::mt19937, std::uniform_int_distribution
          #include <vector>
          #include "aidge/data/Tensor.hpp"
          #include "aidge/operator/Mul.hpp"
          #include "aidge/operator/OperatorTensor.hpp"
          namespace Aidge {
          TEST_CASE("[core/operator] Mul_Op(computeOutputDims)", "[Mul][computeOutputDims]") {
          constexpr std::uint16_t NBTRIALS = 10;
          // Create a random number generator
          std::random_device rd;
          std::mt19937 gen(rd());
          std::uniform_int_distribution<std::size_t> dimsDist(1, 10);
          std::uniform_int_distribution<std::size_t> nbDimsDist(1, 5);
          // Create Mul Operator
          std::shared_ptr<Node> myMul = Mul();
          auto op = std::static_pointer_cast<OperatorTensor>(myMul -> getOperator());
          // input_0
          std::shared_ptr<Tensor> T0 = std::make_shared<Tensor>();
          op -> associateInput(0,T0);
          // input_1
          std::shared_ptr<Tensor> T1 = std::make_shared<Tensor>();
          op -> associateInput(1,T1);
          /**
          * @todo Special case: scalar not handled yet by
          * ``OperatorTensor::computeOutputDims()``
          */
          // SECTION("Scalar / Scalar") {
          // // input_0
          // T0->resize({});
          // // input_1
          // T1->resize({});
          // REQUIRE_NOTHROW(op->computeOutputDims());
          // REQUIRE((op->getOutput(0)->dims() == std::vector<std::size_t>()));
          // }
          // SECTION("Scalar / +1-D") {
          // // a scalar is compatible with any other Tensor
          // // input_0
          // T0->resize({});
          // for (std::uint16_t trial = 0; trial < NBTRIALS; ++trial) {
          // // input_1
          // const std::size_t nb_dims = nbDimsDist(gen);
          // std::vector<std::size_t> dims(nb_dims);
          // for (std::size_t i = 0; i < nb_dims; ++i) {
          // dims[i] = dimsDist(gen);
          // }
          // T1->resize(dims);
          // REQUIRE_NOTHROW(op->computeOutputDims());
          // REQUIRE((op->getOutput(0)->dims()) == dims);
          // }
          // }
          // SECTION("+1-D / Scalar") {
          // // a scalar is compatible with any other Tensor
          // // input_1
          // T1->resize({});
          // for (std::uint16_t trial = 0; trial < NBTRIALS; ++trial) {
          // // input_0
          // const std::size_t nb_dims = nbDimsDist(gen);
          // std::vector<std::size_t> dims(nb_dims);
          // for (std::size_t i = 0; i < nb_dims; ++i) {
          // dims[i] = dimsDist(gen);
          // }
          // T0->resize(dims);
          // REQUIRE_NOTHROW(op->computeOutputDims());
          // REQUIRE((op->getOutput(0)->dims()) == dims);
          // }
          // }
          SECTION("+1-D / +1-D") {
          // same size
          for (std::uint16_t trial = 0; trial < NBTRIALS; ++trial) {
          const std::size_t nb_dims = nbDimsDist(gen) + 1;
          std::vector<std::size_t> dims0(nb_dims);
          for (std::size_t i = 0; i < nb_dims; ++i) {
          dims0[i] = dimsDist(gen) + 1;
          }
          T0->resize(dims0);
          T1->resize(dims0);
          REQUIRE_NOTHROW(op->computeOutputDims());
          REQUIRE((op->getOutput(0)->dims()) == dims0);
          }
          // broadcast
          for (std::uint16_t trial = 0; trial < NBTRIALS; ++trial) {
          const std::size_t nb_dims = nbDimsDist(gen) + 1;
          std::vector<std::size_t> dims0(nb_dims);
          for (std::size_t i = 0; i < nb_dims; ++i) {
          dims0[i] = dimsDist(gen) + 2;
          }
          std::vector<std::size_t> dimsOut = dims0;
          std::vector<std::size_t> dims1 = dims0;
          for (std::size_t i = 0; i < nb_dims; ++i) {
          if (dimsDist(gen) <= 5) {
          dims1[i] = 1;
          }
          }
          dims1.erase(dims1.cbegin(), dims1.cbegin() + std::min(nbDimsDist(gen), nb_dims-1));
          T0->resize(dims0);
          T1->resize(dims1);
          REQUIRE_NOTHROW(op->computeOutputDims());
          REQUIRE((op->getOutput(0)->dims()) == dimsOut);
          // input_0 - wrong
          // T1->resize({dims[0] + 1});
          std::vector<std::size_t> dims1_wrong = dims1;
          for (std::size_t i = 0; i < dims1.size(); ++i) {
          ++dims1_wrong[i];
          }
          T1->resize(dims1_wrong);
          REQUIRE(dims0 != dims1_wrong);
          REQUIRE_THROWS(op->computeOutputDims());
          }
          }
          }
          } // namespace Aidge
          unit_tests/operator/Test_Pow_Op.cpp 0 → 100644
          + 144
          − 0
          View file @ 124c6d39
          /********************************************************************************
          * 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 <cstddef> // std::size_t
          #include <memory>
          #include <random> // std::random_device, std::mt19937, std::uniform_int_distribution
          #include <vector>
          #include "aidge/data/Tensor.hpp"
          #include "aidge/operator/Pow.hpp"
          #include "aidge/operator/OperatorTensor.hpp"
          namespace Aidge {
          TEST_CASE("[core/operator] Pow_Op(computeOutputDims)", "[Pow][computeOutputDims]") {
          constexpr std::uint16_t NBTRIALS = 10;
          // Create a random number generator
          std::random_device rd;
          std::mt19937 gen(rd());
          std::uniform_int_distribution<std::size_t> dimsDist(1, 10);
          std::uniform_int_distribution<std::size_t> nbDimsDist(1, 5);
          // Create Pow Operator
          std::shared_ptr<Node> myPow = Pow();
          auto op = std::static_pointer_cast<OperatorTensor>(myPow -> getOperator());
          // input_0
          std::shared_ptr<Tensor> T0 = std::make_shared<Tensor>();
          op -> associateInput(0,T0);
          // input_1
          std::shared_ptr<Tensor> T1 = std::make_shared<Tensor>();
          op -> associateInput(1,T1);
          /**
          * @todo Special case: scalar not handled yet by
          * ``OperatorTensor::computeOutputDims()``
          */
          // SECTION("Scalar / Scalar") {
          // // input_0
          // T0->resize({});
          // // input_1
          // T1->resize({});
          // REQUIRE_NOTHROW(op->computeOutputDims());
          // REQUIRE((op->getOutput(0)->dims() == std::vector<std::size_t>()));
          // }
          // SECTION("Scalar / +1-D") {
          // // a scalar is compatible with any other Tensor
          // // input_0
          // T0->resize({});
          // for (std::uint16_t trial = 0; trial < NBTRIALS; ++trial) {
          // // input_1
          // const std::size_t nb_dims = nbDimsDist(gen);
          // std::vector<std::size_t> dims(nb_dims);
          // for (std::size_t i = 0; i < nb_dims; ++i) {
          // dims[i] = dimsDist(gen);
          // }
          // T1->resize(dims);
          // REQUIRE_NOTHROW(op->computeOutputDims());
          // REQUIRE((op->getOutput(0)->dims()) == dims);
          // }
          // }
          // SECTION("+1-D / Scalar") {
          // // a scalar is compatible with any other Tensor
          // // input_1
          // T1->resize({});
          // for (std::uint16_t trial = 0; trial < NBTRIALS; ++trial) {
          // // input_0
          // const std::size_t nb_dims = nbDimsDist(gen);
          // std::vector<std::size_t> dims(nb_dims);
          // for (std::size_t i = 0; i < nb_dims; ++i) {
          // dims[i] = dimsDist(gen);
          // }
          // T0->resize(dims);
          // REQUIRE_NOTHROW(op->computeOutputDims());
          // REQUIRE((op->getOutput(0)->dims()) == dims);
          // }
          // }
          SECTION("+1-D / +1-D") {
          // same size
          for (std::uint16_t trial = 0; trial < NBTRIALS; ++trial) {
          const std::size_t nb_dims = nbDimsDist(gen) + 1;
          std::vector<std::size_t> dims0(nb_dims);
          for (std::size_t i = 0; i < nb_dims; ++i) {
          dims0[i] = dimsDist(gen) + 1;
          }
          T0->resize(dims0);
          T1->resize(dims0);
          REQUIRE_NOTHROW(op->computeOutputDims());
          REQUIRE((op->getOutput(0)->dims()) == dims0);
          }
          // broadcast
          for (std::uint16_t trial = 0; trial < NBTRIALS; ++trial) {
          const std::size_t nb_dims = nbDimsDist(gen) + 1;
          std::vector<std::size_t> dims0(nb_dims);
          for (std::size_t i = 0; i < nb_dims; ++i) {
          dims0[i] = dimsDist(gen) + 2;
          }
          std::vector<std::size_t> dimsOut = dims0;
          std::vector<std::size_t> dims1 = dims0;
          for (std::size_t i = 0; i < nb_dims; ++i) {
          if (dimsDist(gen) <= 5) {
          dims1[i] = 1;
          }
          }
          dims1.erase(dims1.cbegin(), dims1.cbegin() + std::min(nbDimsDist(gen), nb_dims-1));
          T0->resize(dims0);
          T1->resize(dims1);
          REQUIRE_NOTHROW(op->computeOutputDims());
          REQUIRE((op->getOutput(0)->dims()) == dimsOut);
          // input_0 - wrong
          // T1->resize({dims[0] + 1});
          std::vector<std::size_t> dims1_wrong = dims1;
          for (std::size_t i = 0; i < dims1.size(); ++i) {
          ++dims1_wrong[i];
          }
          T1->resize(dims1_wrong);
          REQUIRE(dims0 != dims1_wrong);
          REQUIRE_THROWS(op->computeOutputDims());
          }
          }
          }
          } // namespace Aidge
          unit_tests/operator/Test_Sub_Op.cpp 0 → 100644
          + 144
          − 0
          View file @ 124c6d39
          /********************************************************************************
          * 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 <cstddef> // std::size_t
          #include <memory>
          #include <random> // std::random_device, std::mt19937, std::uniform_int_distribution
          #include <vector>
          #include "aidge/data/Tensor.hpp"
          #include "aidge/operator/Sub.hpp"
          #include "aidge/operator/OperatorTensor.hpp"
          namespace Aidge {
          TEST_CASE("[core/operator] Sub_Op(computeOutputDims)", "[Sub][computeOutputDims]") {
          constexpr std::uint16_t NBTRIALS = 10;
          // Create a random number generator
          std::random_device rd;
          std::mt19937 gen(rd());
          std::uniform_int_distribution<std::size_t> dimsDist(1, 10);
          std::uniform_int_distribution<std::size_t> nbDimsDist(1, 5);
          // Create Sub Operator
          std::shared_ptr<Node> mySub = Sub();
          auto op = std::static_pointer_cast<OperatorTensor>(mySub -> getOperator());
          // input_0
          std::shared_ptr<Tensor> T0 = std::make_shared<Tensor>();
          op -> associateInput(0,T0);
          // input_1
          std::shared_ptr<Tensor> T1 = std::make_shared<Tensor>();
          op -> associateInput(1,T1);
          /**
          * @todo Special case: scalar not handled yet by
          * ``OperatorTensor::computeOutputDims()``
          */
          // SECTION("Scalar / Scalar") {
          // // input_0
          // T0->resize({});
          // // input_1
          // T1->resize({});
          // REQUIRE_NOTHROW(op->computeOutputDims());
          // REQUIRE((op->getOutput(0)->dims() == std::vector<std::size_t>()));
          // }
          // SECTION("Scalar / +1-D") {
          // // a scalar is compatible with any other Tensor
          // // input_0
          // T0->resize({});
          // for (std::uint16_t trial = 0; trial < NBTRIALS; ++trial) {
          // // input_1
          // const std::size_t nb_dims = nbDimsDist(gen);
          // std::vector<std::size_t> dims(nb_dims);
          // for (std::size_t i = 0; i < nb_dims; ++i) {
          // dims[i] = dimsDist(gen);
          // }
          // T1->resize(dims);
          // REQUIRE_NOTHROW(op->computeOutputDims());
          // REQUIRE((op->getOutput(0)->dims()) == dims);
          // }
          // }
          // SECTION("+1-D / Scalar") {
          // // a scalar is compatible with any other Tensor
          // // input_1
          // T1->resize({});
          // for (std::uint16_t trial = 0; trial < NBTRIALS; ++trial) {
          // // input_0
          // const std::size_t nb_dims = nbDimsDist(gen);
          // std::vector<std::size_t> dims(nb_dims);
          // for (std::size_t i = 0; i < nb_dims; ++i) {
          // dims[i] = dimsDist(gen);
          // }
          // T0->resize(dims);
          // REQUIRE_NOTHROW(op->computeOutputDims());
          // REQUIRE((op->getOutput(0)->dims()) == dims);
          // }
          // }
          SECTION("+1-D / +1-D") {
          // same size
          for (std::uint16_t trial = 0; trial < NBTRIALS; ++trial) {
          const std::size_t nb_dims = nbDimsDist(gen) + 1;
          std::vector<std::size_t> dims0(nb_dims);
          for (std::size_t i = 0; i < nb_dims; ++i) {
          dims0[i] = dimsDist(gen) + 1;
          }
          T0->resize(dims0);
          T1->resize(dims0);
          REQUIRE_NOTHROW(op->computeOutputDims());
          REQUIRE((op->getOutput(0)->dims()) == dims0);
          }
          // broadcast
          for (std::uint16_t trial = 0; trial < NBTRIALS; ++trial) {
          const std::size_t nb_dims = nbDimsDist(gen) + 1;
          std::vector<std::size_t> dims0(nb_dims);
          for (std::size_t i = 0; i < nb_dims; ++i) {
          dims0[i] = dimsDist(gen) + 2;
          }
          std::vector<std::size_t> dimsOut = dims0;
          std::vector<std::size_t> dims1 = dims0;
          for (std::size_t i = 0; i < nb_dims; ++i) {
          if (dimsDist(gen) <= 5) {
          dims1[i] = 1;
          }
          }
          dims1.erase(dims1.cbegin(), dims1.cbegin() + std::min(nbDimsDist(gen), nb_dims-1));
          T0->resize(dims0);
          T1->resize(dims1);
          REQUIRE_NOTHROW(op->computeOutputDims());
          REQUIRE((op->getOutput(0)->dims()) == dimsOut);
          // input_0 - wrong
          // T1->resize({dims[0] + 1});
          std::vector<std::size_t> dims1_wrong = dims1;
          for (std::size_t i = 0; i < dims1.size(); ++i) {
          ++dims1_wrong[i];
          }
          T1->resize(dims1_wrong);
          REQUIRE(dims0 != dims1_wrong);
          REQUIRE_THROWS(op->computeOutputDims());
          }
          }
          }
          } // namespace Aidge
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