diff --git a/src/tim/vx/ops/stridedslice_test.cc b/src/tim/vx/ops/stridedslice_test.cc new file mode 100644 index 0000000..08928db --- /dev/null +++ b/src/tim/vx/ops/stridedslice_test.cc @@ -0,0 +1,107 @@ +/**************************************************************************** +* +* Copyright (c) 2021 Vivante Corporation +* +* Permission is hereby granted, free of charge, to any person obtaining a +* copy of this software and associated documentation files (the "Software"), +* to deal in the Software without restriction, including without limitation +* the rights to use, copy, modify, merge, publish, distribute, sublicense, +* and/or sell copies of the Software, and to permit persons to whom the +* Software is furnished to do so, subject to the following conditions: +* +* The above copyright notice and this permission notice shall be included in +* all copies or substantial portions of the Software. +* +* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING +* FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER +* DEALINGS IN THE SOFTWARE. +* +*****************************************************************************/ +#include "tim/vx/context.h" +#include "tim/vx/graph.h" +#include "tim/vx/ops/stridedslice.h" + +#include "gtest/gtest.h" + +TEST(StridedSlice, shape_) { + auto ctx = tim::vx::Context::Create(); + auto graph = ctx->CreateGraph(); + /* Using tensors of 5 dimensions. */ + static constexpr std::array BEGIN = {0, 0, 0, 0, 2}; + static constexpr std::array END = {1, 3, 10, 10, 4}; + static constexpr std::array STRIDES = {1, 1, 1, 1, 1}; + + static constexpr int MASK_BEGIN = 0b11110; + static constexpr int MASK_END = 0b11110; + static constexpr int MASK_SHRINK = 0b00000; + + static constexpr std::array SHAPE_INPUT = {1, 3, 10, 10, 85}; + static constexpr std::array SHAPE_OUTPUT = {1, 3, 10, 10, 2}; + static constexpr size_t SLICE_AXIS = 4; + + static constexpr size_t LEN_DETECTION_FULL = 85; + static constexpr size_t NUM_ELEMENTS_INPUT = 25500; // 1 * 3 * 10 * 10 * 85 + static constexpr size_t NUM_ELEMENTS_OUTPUT = 600; // 1 * 3 * 10 * 10 * 2 + static constexpr size_t NUM_DETECTIONS = 300; // 1 * 3 * 10 * 10 + + tim::vx::ShapeType vxShapeInput; + tim::vx::ShapeType vxShapeOutput; + + std::reverse_copy(SHAPE_INPUT.cbegin(), SHAPE_INPUT.cend(), + std::back_inserter(vxShapeInput)); + std::reverse_copy(SHAPE_OUTPUT.cbegin(), SHAPE_OUTPUT.cend(), + std::back_inserter(vxShapeOutput)); + + // Create TIM-VX tensors. + auto specInput = tim::vx::TensorSpec(tim::vx::DataType::FLOAT32, vxShapeInput, + tim::vx::TensorAttribute::INPUT); + + auto specOutput = + tim::vx::TensorSpec(tim::vx::DataType::FLOAT32, vxShapeOutput, + tim::vx::TensorAttribute::OUTPUT); + + auto tensorInput = graph->CreateTensor(specInput); + auto tensorOutput = graph->CreateTensor(specOutput); + + std::vector begin; + std::vector end; + std::vector strides; + + std::reverse_copy(BEGIN.cbegin(), BEGIN.cend(), std::back_inserter(begin)); + std::reverse_copy(END.cbegin(), END.cend(), std::back_inserter(end)); + std::reverse_copy(STRIDES.cbegin(), STRIDES.cend(), + std::back_inserter(strides)); + auto opStridedSlice = graph->CreateOperation( + begin, end, strides, MASK_BEGIN, MASK_END, MASK_SHRINK); + + opStridedSlice->BindInput(tensorInput); + opStridedSlice->BindOutput(tensorOutput); + + // Compile graph. + bool ret = false; + ret = graph->Compile(); + EXPECT_TRUE(ret) << "Compile Graph Failed"; + + std::array bufferInput; + std::array bufferOutput; + + // Prepare input tensor data. + bufferInput.fill(0.0F); + for (size_t k = 0; k < NUM_DETECTIONS; k++) { + float* dataPtr = bufferInput.data() + k * LEN_DETECTION_FULL; + for (auto i = BEGIN[SLICE_AXIS]; i < END[SLICE_AXIS]; i++) { + dataPtr[i] = static_cast(i); + } + } + + // Run graph. + ret = tensorInput->CopyDataToTensor(bufferInput.data()); + ret = graph->Run(); + ret = tensorOutput->CopyDataFromTensor(bufferOutput.data()); + + EXPECT_TRUE(ret) << "Failed at execute"; +}