From 96c9d5df01a5d5818619e5c2ecf5f93aeefb0a05 Mon Sep 17 00:00:00 2001 From: chxin66 <57057788+chxin66@users.noreply.github.com> Date: Wed, 27 Jul 2022 12:53:56 +0800 Subject: [PATCH] Added cases for reduce sum (#441) Signed-off-by: Chen Xin Co-authored-by: Chen Xin --- src/tim/vx/ops/reduce_sum_test.cc | 126 ++++++++++++++++++++++++++++++ 1 file changed, 126 insertions(+) create mode 100644 src/tim/vx/ops/reduce_sum_test.cc diff --git a/src/tim/vx/ops/reduce_sum_test.cc b/src/tim/vx/ops/reduce_sum_test.cc new file mode 100644 index 0000000..c8c07c9 --- /dev/null +++ b/src/tim/vx/ops/reduce_sum_test.cc @@ -0,0 +1,126 @@ +/**************************************************************************** +* +* 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.h" +#include "test_utils.h" +#include "gtest/gtest.h" + +TEST(Reduce_sum, NotKeepDims) { + auto ctx = tim::vx::Context::Create(); + auto graph = ctx->CreateGraph(); + + tim::vx::ShapeType input_shape({2, 3, 1}); + tim::vx::ShapeType output_shape({2, 1}); + tim::vx::Quantization quant(tim::vx::QuantType::ASYMMETRIC, 0.00784313772, + 127); + + tim::vx::TensorSpec input_spec(tim::vx::DataType::FLOAT32, input_shape, + tim::vx::TensorAttribute::INPUT); + tim::vx::TensorSpec dc_spec1(tim::vx::DataType::UINT8, {0, 0, 0}, + tim::vx::TensorAttribute::TRANSIENT, quant); + auto input_tensor = graph->CreateTensor(input_spec); + auto dc_tensor1 = graph->CreateTensor(dc_spec1); + auto dc1_op = graph->CreateOperation(); + (*dc1_op).BindInputs({input_tensor}).BindOutputs({dc_tensor1}); + + tim::vx::TensorSpec reduce_sum_spec(tim::vx::DataType::UINT8, {0, 0, 0}, + tim::vx::TensorAttribute::TRANSIENT, + quant); + auto reduce_sum_out = graph->CreateTensor(reduce_sum_spec); + std::vector axis = {1}; + auto reduce_sum = + graph->CreateOperation(axis, false); + (*reduce_sum).BindInputs({dc_tensor1}).BindOutputs({reduce_sum_out}); + + tim::vx::TensorSpec output_spec(tim::vx::DataType::FLOAT32, output_shape, + tim::vx::TensorAttribute::OUTPUT); + auto output_tensor = graph->CreateTensor(output_spec); + auto dc2_op = graph->CreateOperation(); + (*dc2_op).BindInputs({reduce_sum_out}).BindOutputs({output_tensor}); + + std::vector in_data = {0.4, 0.2, 0.3, 0.4, 0.5, 0.6}; + std::vector golden = { + 1.003922, + 1.003922, + }; + + EXPECT_TRUE(input_tensor->CopyDataToTensor(in_data.data(), in_data.size())); + + EXPECT_TRUE(graph->Compile()); + EXPECT_TRUE(graph->Run()); + + std::vector output(golden.size()); + EXPECT_TRUE(output_tensor->CopyDataFromTensor(output.data())); + EXPECT_TRUE(ArraysMatch(golden, output, 1e-5f)); +} + +TEST(Reduce_sum, KeepDims) { + auto ctx = tim::vx::Context::Create(); + auto graph = ctx->CreateGraph(); + + tim::vx::ShapeType input_shape({2, 3}); + tim::vx::ShapeType output_shape({1, 3}); + tim::vx::Quantization quant(tim::vx::QuantType::ASYMMETRIC, 0.00784313772, + 127); + + tim::vx::TensorSpec input_spec(tim::vx::DataType::FLOAT32, input_shape, + tim::vx::TensorAttribute::INPUT); + tim::vx::TensorSpec dc_spec1(tim::vx::DataType::UINT8, {0, 0, 0}, + tim::vx::TensorAttribute::TRANSIENT, quant); + auto input_tensor = graph->CreateTensor(input_spec); + auto dc_tensor1 = graph->CreateTensor(dc_spec1); + auto dc1_op = graph->CreateOperation(); + (*dc1_op).BindInputs({input_tensor}).BindOutputs({dc_tensor1}); + + tim::vx::TensorSpec reduce_sum_spec(tim::vx::DataType::UINT8, {0, 0, 0}, + tim::vx::TensorAttribute::TRANSIENT, + quant); + auto reduce_sum_out = graph->CreateTensor(reduce_sum_spec); + std::vector axis = {0}; + auto reduce_sum = graph->CreateOperation(axis, true); + (*reduce_sum).BindInputs({dc_tensor1}).BindOutputs({reduce_sum_out}); + + tim::vx::TensorSpec output_spec(tim::vx::DataType::FLOAT32, output_shape, + tim::vx::TensorAttribute::OUTPUT); + auto output_tensor = graph->CreateTensor(output_spec); + auto dc2_op = graph->CreateOperation(); + (*dc2_op).BindInputs({reduce_sum_out}).BindOutputs({output_tensor}); + + std::vector in_data = {0.4, 0.2, 0.3, 0.4, 0.5, 0.6}; + std::vector golden = { + 0.596078, + 0.698039, + 1.003922, + }; + + EXPECT_TRUE(input_tensor->CopyDataToTensor(in_data.data(), in_data.size())); + + EXPECT_TRUE(graph->Compile()); + EXPECT_TRUE(graph->Run()); + + std::vector output(golden.size()); + EXPECT_TRUE(output_tensor->CopyDataFromTensor(output.data())); + EXPECT_TRUE(ArraysMatch(golden, output, 1e-5f)); +} \ No newline at end of file