// // GatherTest.cpp // MNNTests // // Created by MNN on 2019/01/15. // Copyright © 2018, Alibaba Group Holding Limited // #include #include #include "MNNTestSuite.h" #include "TestUtils.h" using namespace MNN::Express; class GatherNDTest : public MNNTestCase { public: virtual ~GatherNDTest() = default; bool _run(int precision, bool lazy) { { const float inpudata[] = {-1.0, -2.0, 3.0, 4.0}; const int indices_data[] = {0, 0, 1, 1}; auto params = _Const(inpudata, {2, 2}, NCHW, halide_type_of()); auto indices = _Const(indices_data, {2, 2}, NCHW, halide_type_of()); auto output = _GatherND(params, indices); const std::vector expectedOutput = {-1.0, 4.0}; auto gotOutput = output->readMap(); if (!checkVectorByRelativeError(gotOutput, expectedOutput.data(), 2, 0.001)) { MNN_ERROR("GatherNDTest test failed!\n"); return false; } } { const float inpudata[] = {1, 2, 3, 4, 5, 6, 7, 8}; const int indices_data[] = {0, 0, 1, 1, 1, 0}; auto params = _Const(inpudata, {2, 2, 2}, NCHW, halide_type_of()); auto indices = _Const(indices_data, {2, 3}, NCHW, halide_type_of()); auto output = _GatherND(params, indices); const std::vector expectedOutput = {2, 7}; auto gotOutput = output->readMap(); if (!checkVectorByRelativeError(gotOutput, expectedOutput.data(), 2, 0.001)) { MNN_ERROR("GatherNDTest test failed!\n"); return false; } } return true; } virtual bool run(int precision) { ExecutorScope::Current()->lazyEval = false; auto res = _run(precision, false); if (!res) { FUNC_PRINT(1); return false; } ExecutorScope::Current()->lazyEval = true; ExecutorScope::Current()->setLazyComputeMode(MNN::Express::Executor::LAZY_CONTENT); res = _run(precision, true); if (!res) { FUNC_PRINT(1); return false; } ExecutorScope::Current()->setLazyComputeMode(MNN::Express::Executor::LAZY_FULL); res = _run(precision, true); return res; } }; class GatherTest : public MNNTestCase { public: virtual ~GatherTest() = default; bool _run(int precision, bool lazy) { auto params = _Input({4, 3, 2}, NCHW); params->setName("input_tensor"); // set input data const float inpudata[] = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21, 0, 22.0, 23.0, 24.0}; auto inputPtr = params->writeMap(); memcpy(inputPtr, inpudata, 24 * sizeof(float)); params->unMap(); const int indices_data[] = {1, 0, 1, 0}; auto indices = _Const(indices_data, {4}, NCHW, halide_type_of()); auto output = _Gather(params, indices); const std::vector expectedOutput = {7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0}; auto gotOutput = output->readMap(); if (!checkVector(gotOutput, expectedOutput.data(), 24, 0.001)) { MNN_ERROR("GatherTest test failed!\n"); return false; } return true; } virtual bool run(int precision) { ExecutorScope::Current()->lazyEval = false; auto res = _run(precision, false); if (!res) { FUNC_PRINT(1); return false; } ExecutorScope::Current()->lazyEval = true; ExecutorScope::Current()->setLazyComputeMode(MNN::Express::Executor::LAZY_CONTENT); res = _run(precision, true); if (!res) { FUNC_PRINT(1); return false; } ExecutorScope::Current()->setLazyComputeMode(MNN::Express::Executor::LAZY_FULL); res = _run(precision, true); return res; } }; MNNTestSuiteRegister(GatherNDTest, "op/gather_nd"); MNNTestSuiteRegister(GatherTest, "op/gather");