Add softmax unit test (#274)
https://github.com/VeriSilicon/TIM-VX/issues/266 Signed-off-by: Chen Xin <jack.chen@verisilicon.com> Co-authored-by: Chen Xin <jack.chen@verisilicon.com>
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/****************************************************************************
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*
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* Copyright (c) 2022 Vivante Corporation
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*
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* Permission is hereby granted, free of charge, to any person obtaining a
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* copy of this software and associated documentation files (the "Software"),
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* to deal in the Software without restriction, including without limitation
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* the rights to use, copy, modify, merge, publish, distribute, sublicense,
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* and/or sell copies of the Software, and to permit persons to whom the
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* Software is furnished to do so, subject to the following conditions:
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*
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* The above copyright notice and this permission notice shall be included in
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* all copies or substantial portions of the Software.
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*
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* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
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* FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
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* DEALINGS IN THE SOFTWARE.
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*
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*****************************************************************************/
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#include "tim/vx/context.h"
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#include "tim/vx/graph.h"
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#include "tim/vx/ops/softmax.h"
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#include "test_utils.h"
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#include "gtest/gtest.h"
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TEST(Softmax, shape_3_1_float_axis_0) {
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auto ctx = tim::vx::Context::Create();
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auto graph = ctx->CreateGraph();
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tim::vx::ShapeType io_shape({3, 1});
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tim::vx::TensorSpec input_spec(tim::vx::DataType::FLOAT32,
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io_shape, tim::vx::TensorAttribute::INPUT);
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tim::vx::TensorSpec output_spec(tim::vx::DataType::FLOAT32,
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io_shape, tim::vx::TensorAttribute::OUTPUT);
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auto input_tensor = graph->CreateTensor(input_spec);
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auto output_tensor = graph->CreateTensor(output_spec);
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std::vector<float> in_data = {
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-1, 0, 1,
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};
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std::vector<float> golden = {
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0.09003057, 0.24472848, 0.66524094
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};
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EXPECT_TRUE(input_tensor->CopyDataToTensor(in_data.data(), in_data.size() * sizeof(float)));
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auto op = graph->CreateOperation<tim::vx::ops::Softmax>(1,0);
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(*op).BindInputs({input_tensor}).BindOutputs({output_tensor});
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EXPECT_TRUE(graph->Compile());
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EXPECT_TRUE(graph->Run());
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std::vector<float> output(golden.size());
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EXPECT_TRUE(output_tensor->CopyDataFromTensor(output.data()));
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EXPECT_TRUE(ArraysMatch(golden, output, 1e-5f));
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}
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TEST(Softmax, shape_3_4_float_axis_0) {
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auto ctx = tim::vx::Context::Create();
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auto graph = ctx->CreateGraph();
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tim::vx::ShapeType io_shape({3, 4});
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tim::vx::TensorSpec input_spec(tim::vx::DataType::FLOAT32,
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io_shape, tim::vx::TensorAttribute::INPUT);
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tim::vx::TensorSpec output_spec(tim::vx::DataType::FLOAT32,
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io_shape, tim::vx::TensorAttribute::OUTPUT);
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auto input_tensor = graph->CreateTensor(input_spec);
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auto output_tensor = graph->CreateTensor(output_spec);
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std::vector<float> in_data = {
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1, 2, 3,
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1, 2, 3,
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1, 2, 3,
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1, 2, 3,
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};
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std::vector<float> golden = {
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0.09003057, 0.24472848, 0.66524094,
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0.09003057, 0.24472848, 0.66524094,
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0.09003057, 0.24472848, 0.66524094,
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0.09003057, 0.24472848, 0.66524094,
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};
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EXPECT_TRUE(input_tensor->CopyDataToTensor(in_data.data(), in_data.size() * sizeof(float)));
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auto op = graph->CreateOperation<tim::vx::ops::Softmax>(1,0);
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(*op).BindInputs({input_tensor}).BindOutputs({output_tensor});
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EXPECT_TRUE(graph->Compile());
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EXPECT_TRUE(graph->Run());
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std::vector<float> output(golden.size());
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EXPECT_TRUE(output_tensor->CopyDataFromTensor(output.data()));
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EXPECT_EQ(golden, output);
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// EXPECT_TRUE(ArraysMatch(golden, output, 1e-5f));
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}
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TEST(Softmax, shape_3_4_float_axis_1) {
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auto ctx = tim::vx::Context::Create();
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auto graph = ctx->CreateGraph();
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tim::vx::ShapeType io_shape({3, 4});
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tim::vx::TensorSpec input_spec(tim::vx::DataType::FLOAT32,
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io_shape, tim::vx::TensorAttribute::INPUT);
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tim::vx::TensorSpec output_spec(tim::vx::DataType::FLOAT32,
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io_shape, tim::vx::TensorAttribute::OUTPUT);
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auto input_tensor = graph->CreateTensor(input_spec);
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auto output_tensor = graph->CreateTensor(output_spec);
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std::vector<float> in_data = {
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1, 2, 3,
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1, 2, 3,
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1, 2, 3,
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1, 2, 3,
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};
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std::vector<float> golden = {
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0.25, 0.25, 0.25,
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0.25, 0.25, 0.25,
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0.25, 0.25, 0.25,
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0.25, 0.25, 0.25,
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};
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EXPECT_TRUE(input_tensor->CopyDataToTensor(in_data.data(), in_data.size() * sizeof(float)));
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auto op = graph->CreateOperation<tim::vx::ops::Softmax>(1,1);
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(*op).BindInputs({input_tensor}).BindOutputs({output_tensor});
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EXPECT_TRUE(graph->Compile());
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EXPECT_TRUE(graph->Run());
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std::vector<float> output(golden.size());
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EXPECT_TRUE(output_tensor->CopyDataFromTensor(output.data()));
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EXPECT_EQ(golden, output);
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// EXPECT_TRUE(ArraysMatch(golden, output, 1e-5f));
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}
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TEST(Softmax, shape_3_3_2_float_axis_0) {
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auto ctx = tim::vx::Context::Create();
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auto graph = ctx->CreateGraph();
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tim::vx::ShapeType io_shape({3, 3, 2});
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tim::vx::TensorSpec input_spec(tim::vx::DataType::FLOAT32,
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io_shape, tim::vx::TensorAttribute::INPUT);
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tim::vx::TensorSpec output_spec(tim::vx::DataType::FLOAT32,
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io_shape, tim::vx::TensorAttribute::OUTPUT);
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auto input_tensor = graph->CreateTensor(input_spec);
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auto output_tensor = graph->CreateTensor(output_spec);
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std::vector<float> in_data = {
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1, 2, 3,
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1, 2, 3,
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1, 2, 3,
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2, 3, 5,
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2, 3, 5,
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2, 3, 5,
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};
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std::vector<float> golden = {
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0.09003057, 0.24472848, 0.66524094,
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0.09003057, 0.24472848, 0.66524094,
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0.09003057, 0.24472848, 0.66524094,
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0.04201007, 0.11419519, 0.8437947,
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0.04201007, 0.11419519, 0.8437947,
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0.04201007, 0.11419519, 0.8437947,
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};
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EXPECT_TRUE(input_tensor->CopyDataToTensor(in_data.data(), in_data.size() * sizeof(float)));
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auto op = graph->CreateOperation<tim::vx::ops::Softmax>(1,0);
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(*op).BindInputs({input_tensor}).BindOutputs({output_tensor});
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EXPECT_TRUE(graph->Compile());
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EXPECT_TRUE(graph->Run());
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std::vector<float> output(golden.size());
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EXPECT_TRUE(output_tensor->CopyDataFromTensor(output.data()));
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EXPECT_EQ(golden, output);
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// EXPECT_TRUE(ArraysMatch(golden, output, 1e-5f));
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}
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TEST(Softmax, shape_3_3_2_float_axis_1) {
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auto ctx = tim::vx::Context::Create();
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auto graph = ctx->CreateGraph();
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tim::vx::ShapeType io_shape({3, 3, 2});
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tim::vx::TensorSpec input_spec(tim::vx::DataType::FLOAT32,
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io_shape, tim::vx::TensorAttribute::INPUT);
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tim::vx::TensorSpec output_spec(tim::vx::DataType::FLOAT32,
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io_shape, tim::vx::TensorAttribute::OUTPUT);
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auto input_tensor = graph->CreateTensor(input_spec);
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auto output_tensor = graph->CreateTensor(output_spec);
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std::vector<float> in_data = {
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1, 2, 3,
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1, 2, 3,
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1, 2, 3,
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2, 3, 5,
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2, 3, 5,
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2, 3, 5,
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};
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std::vector<float> golden = {
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0.33333334, 0.33333334, 0.33333334,
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0.33333334, 0.33333334, 0.33333334,
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0.33333334, 0.33333334, 0.33333334,
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0.33333334, 0.33333334, 0.33333334,
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0.33333334, 0.33333334, 0.33333334,
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0.33333334, 0.33333334, 0.33333334,
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};
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EXPECT_TRUE(input_tensor->CopyDataToTensor(in_data.data(), in_data.size() * sizeof(float)));
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auto op = graph->CreateOperation<tim::vx::ops::Softmax>(1,1);
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(*op).BindInputs({input_tensor}).BindOutputs({output_tensor});
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EXPECT_TRUE(graph->Compile());
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EXPECT_TRUE(graph->Run());
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std::vector<float> output(golden.size());
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EXPECT_TRUE(output_tensor->CopyDataFromTensor(output.data()));
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EXPECT_EQ(golden, output);
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// EXPECT_TRUE(ArraysMatch(golden, output, 1e-5f));
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}
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TEST(Softmax, shape_3_3_2_float_axis_2) {
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auto ctx = tim::vx::Context::Create();
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auto graph = ctx->CreateGraph();
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tim::vx::ShapeType io_shape({3, 3, 2});
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tim::vx::TensorSpec input_spec(tim::vx::DataType::FLOAT32,
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io_shape, tim::vx::TensorAttribute::INPUT);
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tim::vx::TensorSpec output_spec(tim::vx::DataType::FLOAT32,
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io_shape, tim::vx::TensorAttribute::OUTPUT);
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auto input_tensor = graph->CreateTensor(input_spec);
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auto output_tensor = graph->CreateTensor(output_spec);
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std::vector<float> in_data = {
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1, 2, 3,
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1, 2, 3,
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1, 2, 3,
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2, 3, 5,
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2, 3, 5,
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2, 3, 5,
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};
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std::vector<float> golden = {
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0.26894143, 0.26894143, 0.11920291,
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0.26894143, 0.26894143, 0.11920291,
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0.26894143, 0.26894143, 0.11920291,
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0.7310586 , 0.7310586 , 0.880797,
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0.7310586 , 0.7310586 , 0.880797,
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0.7310586 , 0.7310586 , 0.880797,
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};
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EXPECT_TRUE(input_tensor->CopyDataToTensor(in_data.data(), in_data.size() * sizeof(float)));
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auto op = graph->CreateOperation<tim::vx::ops::Softmax>(1,2);
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(*op).BindInputs({input_tensor}).BindOutputs({output_tensor});
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EXPECT_TRUE(graph->Compile());
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EXPECT_TRUE(graph->Run());
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std::vector<float> output(golden.size());
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EXPECT_TRUE(output_tensor->CopyDataFromTensor(output.data()));
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EXPECT_EQ(golden, output);
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// EXPECT_TRUE(ArraysMatch(golden, output, 1e-5f));
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}
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