/**************************************************************************** * * 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/scatternd.h" #include "gtest/gtest.h" TEST(ScatterND, shape_4_4_4) { auto ctx = tim::vx::Context::Create(); auto graph = ctx->CreateGraph(); tim::vx::ShapeType indices_shape({1,2}); tim::vx::ShapeType updates_shape({4,4,2}); tim::vx::ShapeType out_shape({4, 4, 4}); tim::vx::TensorSpec indices_spec(tim::vx::DataType::INT32, indices_shape, tim::vx::TensorAttribute::INPUT); tim::vx::TensorSpec updates_spec(tim::vx::DataType::FLOAT32, updates_shape, tim::vx::TensorAttribute::INPUT); tim::vx::TensorSpec output_spec(tim::vx::DataType::FLOAT32, out_shape, tim::vx::TensorAttribute::OUTPUT); auto indices_tensor = graph->CreateTensor(indices_spec); auto updates_tensor = graph->CreateTensor(updates_spec); auto output_tensor = graph->CreateTensor(output_spec); std::vector indices_data = { 0, 2 }; std::vector updates_data = { 5,5,5,5, 6,6,6,6, 7,7,7,7, 8,8,8,8, 1,1,1,1, 2,2,2,2, 3,3,3,3, 4,4,4,4, }; std::vector golden = { 5,5,5,5, 6,6,6,6, 7,7,7,7, 8,8,8,8, 0,0,0,0, 0,0,0,0, 0,0,0,0, 0,0,0,0, 1,1,1,1, 2,2,2,2, 3,3,3,3, 4,4,4,4, 0,0,0,0, 0,0,0,0, 0,0,0,0, 0,0,0,0, }; EXPECT_TRUE(indices_tensor->CopyDataToTensor( indices_data.data(), indices_data.size()*sizeof(int32_t))); EXPECT_TRUE(updates_tensor->CopyDataToTensor( updates_data.data(), updates_data.size()*sizeof(int32_t))); std::vector shape = {4, 4, 4}; auto op = graph->CreateOperation(shape); (*op).BindInputs({indices_tensor, updates_tensor}).BindOutputs({output_tensor}); EXPECT_TRUE(graph->Compile()); EXPECT_TRUE(graph->Run()); std::vector output(golden.size()); EXPECT_TRUE(output_tensor->CopyDataFromTensor(output.data())); EXPECT_EQ(golden, output); } TEST(ScatterND, shape_9) { auto ctx = tim::vx::Context::Create(); auto graph = ctx->CreateGraph(); tim::vx::ShapeType indices_shape({4}); tim::vx::ShapeType updates_shape({4}); tim::vx::ShapeType out_shape({9}); tim::vx::Quantization updates_quant(tim::vx::QuantType::ASYMMETRIC, 0.5, 0); tim::vx::Quantization output_quant(tim::vx::QuantType::ASYMMETRIC, 0.5, 0); tim::vx::TensorSpec indices_spec(tim::vx::DataType::INT32, indices_shape, tim::vx::TensorAttribute::INPUT); tim::vx::TensorSpec updates_spec(tim::vx::DataType::UINT8, updates_shape, tim::vx::TensorAttribute::INPUT, updates_quant); tim::vx::TensorSpec output_spec(tim::vx::DataType::UINT8, out_shape, tim::vx::TensorAttribute::OUTPUT, output_quant); auto indices_tensor = graph->CreateTensor(indices_spec); auto updates_tensor = graph->CreateTensor(updates_spec); auto output_tensor = graph->CreateTensor(output_spec); std::vector indices_data = { 4, 3, 1, 7 }; std::vector updates_data = { 18, 20, 22, 24 }; std::vector golden = { 0, 22, 0, 20, 18, 0, 0, 24, 0 }; EXPECT_TRUE(indices_tensor->CopyDataToTensor( indices_data.data(), indices_data.size())); EXPECT_TRUE(updates_tensor->CopyDataToTensor( updates_data.data(), updates_data.size())); std::vector shape = {9}; auto op = graph->CreateOperation(shape); (*op).BindInputs({indices_tensor, updates_tensor}).BindOutputs({output_tensor}); EXPECT_TRUE(graph->Compile()); EXPECT_TRUE(graph->Run()); std::vector output(golden.size()); EXPECT_TRUE(output_tensor->CopyDataFromTensor(output.data())); EXPECT_EQ(golden, output); }