/**************************************************************************** * * 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/unstack.h" #include "gtest/gtest.h" TEST(Unstack, shape_4_3_axis_0) { auto ctx = tim::vx::Context::Create(); auto graph = ctx->CreateGraph(); tim::vx::ShapeType input_shape({4,3}); tim::vx::ShapeType output_shape({3}); tim::vx::TensorSpec input_spec(tim::vx::DataType::FLOAT32, input_shape, tim::vx::TensorAttribute::INPUT); tim::vx::TensorSpec output_spec(tim::vx::DataType::FLOAT32, output_shape, tim::vx::TensorAttribute::OUTPUT); auto input_tensor = graph->CreateTensor(input_spec); auto output1_tensor = graph->CreateTensor(output_spec); auto output2_tensor = graph->CreateTensor(output_spec); auto output3_tensor = graph->CreateTensor(output_spec); auto output4_tensor = graph->CreateTensor(output_spec); std::vector in_data = { 1,2,3,4, 5,6,7,8, 9,10,11,12, }; std::vector golden1 = { 1,5,9 }; std::vector golden2 = { 2,6,10 }; std::vector golden3 = { 3,7,11 }; std::vector golden4 = { 4,8,12 }; EXPECT_TRUE(input_tensor->CopyDataToTensor( in_data.data(), in_data.size() * sizeof(float))); auto op = graph->CreateOperation(0, 4); (*op).BindInputs({input_tensor}).BindOutputs( {output1_tensor, output2_tensor, output3_tensor, output4_tensor}); EXPECT_TRUE(graph->Compile()); EXPECT_TRUE(graph->Run()); std::vector output1(golden1.size()); std::vector output2(golden2.size()); std::vector output3(golden3.size()); std::vector output4(golden4.size()); EXPECT_TRUE(output1_tensor->CopyDataFromTensor(output1.data())); EXPECT_TRUE(output2_tensor->CopyDataFromTensor(output2.data())); EXPECT_TRUE(output3_tensor->CopyDataFromTensor(output3.data())); EXPECT_TRUE(output4_tensor->CopyDataFromTensor(output4.data())); EXPECT_EQ(golden1, output1); EXPECT_EQ(golden2, output2); EXPECT_EQ(golden3, output3); EXPECT_EQ(golden4, output4); } TEST(Unstack, shape_4_3_axis_1) { auto ctx = tim::vx::Context::Create(); auto graph = ctx->CreateGraph(); tim::vx::ShapeType input_shape({4,3}); tim::vx::ShapeType output_shape({4}); tim::vx::Quantization quant(tim::vx::QuantType::ASYMMETRIC, 0.5, 0); tim::vx::TensorSpec input_spec(tim::vx::DataType::UINT8, input_shape, tim::vx::TensorAttribute::INPUT, quant); tim::vx::TensorSpec output_spec(tim::vx::DataType::UINT8, output_shape, tim::vx::TensorAttribute::OUTPUT, quant); auto input_tensor = graph->CreateTensor(input_spec); auto output1_tensor = graph->CreateTensor(output_spec); auto output2_tensor = graph->CreateTensor(output_spec); auto output3_tensor = graph->CreateTensor(output_spec); std::vector in_data = { 2,4,6,8, 10,12,14,16, 18,20,22,24, }; std::vector golden1 = { 2,4,6,8 }; std::vector golden2 = { 10,12,14,16, }; std::vector golden3 = { 18,20,22,24, }; EXPECT_TRUE(input_tensor->CopyDataToTensor( in_data.data(), in_data.size() * sizeof(float))); auto op = graph->CreateOperation(1, 3); (*op).BindInputs({input_tensor}).BindOutputs( {output1_tensor, output2_tensor, output3_tensor}); EXPECT_TRUE(graph->Compile()); EXPECT_TRUE(graph->Run()); std::vector output1(golden1.size()); std::vector output2(golden2.size()); std::vector output3(golden3.size()); EXPECT_TRUE(output1_tensor->CopyDataFromTensor(output1.data())); EXPECT_TRUE(output2_tensor->CopyDataFromTensor(output2.data())); EXPECT_TRUE(output3_tensor->CopyDataFromTensor(output3.data())); EXPECT_EQ(golden1, output1); EXPECT_EQ(golden2, output2); EXPECT_EQ(golden3, output3); }