/**************************************************************************** * * Copyright (c) 2022 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/gather.h" #include "gtest/gtest.h" #include "test_utils.h" TEST(Gather, shape_5_3_2_2_int32_axis_1_batchdims_1) { auto ctx = tim::vx::Context::Create(); if (ctx->isClOnly()) GTEST_SKIP(); auto graph = ctx->CreateGraph(); tim::vx::ShapeType in_shape({5, 3, 2, 2}); tim::vx::ShapeType indices_shape({2, 2, 2}); tim::vx::ShapeType out_shape({5, 2, 2, 2, 2}); tim::vx::TensorSpec input_spec(tim::vx::DataType::INT8, in_shape, tim::vx::TensorAttribute::INPUT); tim::vx::TensorSpec indices_spec(tim::vx::DataType::INT32, indices_shape, tim::vx::TensorAttribute::INPUT); tim::vx::TensorSpec output_spec(tim::vx::DataType::INT8, out_shape, tim::vx::TensorAttribute::OUTPUT); auto input_tensor = graph->CreateTensor(input_spec); auto indices_tensor = graph->CreateTensor(indices_spec); auto output_tensor = graph->CreateTensor(output_spec); std::vector in_data = { 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, }; //The index value greater than rank-1 is regarded as rank-1 std::vector indices = {1, 0, 0, 1, 1, 0, 0, 1}; std::vector golden = { 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 20, 21, 22, 23, 24, 15, 16, 17, 18, 19, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 35, 36, 37, 38, 39, 30, 31, 32, 33, 34, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 50, 51, 52, 53, 54, 45, 46, 47, 48, 49, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54}; EXPECT_TRUE( input_tensor->CopyDataToTensor(in_data.data(), in_data.size())); EXPECT_TRUE( indices_tensor->CopyDataToTensor(indices.data(), indices.size() * 4)); auto op = graph->CreateOperation(1,1); (*op).BindInputs({input_tensor, indices_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); }