/**************************************************************************** * * Copyright (c) 2020-2023 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/embedding_lookup.h" #include "test_utils.h" #include "gtest/gtest.h" TEST(EmbeddingLookup, shape_2_5_int32LUT) { auto ctx = tim::vx::Context::Create(); auto graph = ctx->CreateGraph(); tim::vx::ShapeType idx_shape({3}); tim::vx::ShapeType lut_shape({2, 5}); tim::vx::ShapeType out_shape({2, 3}); tim::vx::TensorSpec idx_spec(tim::vx::DataType::INT32, idx_shape, tim::vx::TensorAttribute::INPUT); tim::vx::TensorSpec lut_spec(tim::vx::DataType::INT32, lut_shape, tim::vx::TensorAttribute::INPUT); tim::vx::TensorSpec out_spec(tim::vx::DataType::INT32, out_shape, tim::vx::TensorAttribute::OUTPUT); auto idx_tensor = graph->CreateTensor(idx_spec); auto lut_tensor = graph->CreateTensor(lut_spec); auto out_tensor = graph->CreateTensor(out_spec); std::vector idx_data = {0,3,4}; std::vector lut_data = { 1,2,3,4,5,6,7,8,9,10}; std::vector golden = { 1,2,7,8,9,10}; EXPECT_TRUE(idx_tensor->CopyDataToTensor(idx_data.data(), idx_data.size() * sizeof(int32_t))); EXPECT_TRUE(lut_tensor->CopyDataToTensor(lut_data.data(), lut_data.size() * sizeof(int32_t))); auto op = graph->CreateOperation(); (*op).BindInputs({idx_tensor,lut_tensor}).BindOutput(out_tensor); EXPECT_TRUE(graph->Compile()); EXPECT_TRUE(graph->Run()); std::vector output(golden.size()); EXPECT_TRUE(out_tensor->CopyDataFromTensor(output.data())); EXPECT_EQ(golden, output); } TEST(EmbeddingLookup, shape_2_2_2_3_Uint8QuantizedLUT) { auto ctx = tim::vx::Context::Create(); auto graph = ctx->CreateGraph(); tim::vx::ShapeType idx_shape({3}); tim::vx::ShapeType lut_shape({2, 2, 2, 3}); tim::vx::ShapeType out_shape({2, 2, 2, 3}); tim::vx::Quantization quant_lut(tim::vx::QuantType::ASYMMETRIC, 0.0167716537, 0); tim::vx::TensorSpec idx_spec(tim::vx::DataType::INT32, idx_shape, tim::vx::TensorAttribute::INPUT); tim::vx::TensorSpec lut_spec(tim::vx::DataType::UINT8, lut_shape, tim::vx::TensorAttribute::INPUT, quant_lut); tim::vx::TensorSpec out_spec(tim::vx::DataType::FLOAT32, out_shape, tim::vx::TensorAttribute::OUTPUT); auto idx_tensor = graph->CreateTensor(idx_spec); auto lut_tensor = graph->CreateTensor(lut_spec); auto out_tensor = graph->CreateTensor(out_spec); std::vector idx_data = {1,0,2}; std::vector lut_data = { 0, 1, 1, 2, 6, 7, 7, 8, // Row 0 60, 60, 61, 61,66, 66, 67, 67, // Row 1 119, 120,120, 121, 125, 126, 126, 127, // Row 2 }; std::vector golden = {1.00, 1.01, 1.02, 1.03, 1.10, 1.11, 1.12, 1.13, // Row 1 0.00, 0.01, 0.02, 0.03, 0.10, 0.11, 0.12, 0.13, // Row 0 2.00, 2.01, 2.02, 2.03, 2.10, 2.11, 2.12, 2.13, // Row 2 }; EXPECT_TRUE(idx_tensor->CopyDataToTensor(idx_data.data(), idx_data.size() * sizeof(int32_t))); EXPECT_TRUE(lut_tensor->CopyDataToTensor(lut_data.data(), lut_data.size() * sizeof(uint8_t))); auto op = graph->CreateOperation(); (*op).BindInputs({idx_tensor,lut_tensor}).BindOutput(out_tensor); EXPECT_TRUE(graph->Compile()); EXPECT_TRUE(graph->Run()); std::vector output(golden.size()); EXPECT_TRUE(out_tensor->CopyDataFromTensor(output.data())); EXPECT_TRUE(ArraysMatch(golden, output, (float)7.41e-03)); }