80 lines
3.6 KiB
C++
80 lines
3.6 KiB
C++
/****************************************************************************
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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/gather.h"
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#include "gtest/gtest.h"
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#include "test_utils.h"
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TEST(Gather, shape_5_3_2_2_int32_axis_1_batchdims_1) {
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auto ctx = tim::vx::Context::Create();
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if (ctx->isClOnly()) GTEST_SKIP();
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auto graph = ctx->CreateGraph();
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tim::vx::ShapeType in_shape({5, 3, 2, 2});
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tim::vx::ShapeType indices_shape({2, 2, 2});
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tim::vx::ShapeType out_shape({5, 2, 2, 2, 2});
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tim::vx::TensorSpec input_spec(tim::vx::DataType::INT8, in_shape,
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tim::vx::TensorAttribute::INPUT);
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tim::vx::TensorSpec indices_spec(tim::vx::DataType::INT32, indices_shape,
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tim::vx::TensorAttribute::INPUT);
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tim::vx::TensorSpec output_spec(tim::vx::DataType::INT8, out_shape,
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tim::vx::TensorAttribute::OUTPUT);
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auto input_tensor = graph->CreateTensor(input_spec);
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auto indices_tensor = graph->CreateTensor(indices_spec);
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auto output_tensor = graph->CreateTensor(output_spec);
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std::vector<int8_t> in_data = {
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0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14,
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15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29,
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30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44,
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45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59,
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};
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//The index value greater than rank-1 is regarded as rank-1
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std::vector<int32_t> indices = {1, 0, 0, 1, 1, 0, 0, 1};
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std::vector<int8_t> golden = {
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5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 0, 1, 2, 3, 4, 5,
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6, 7, 8, 9, 20, 21, 22, 23, 24, 15, 16, 17, 18, 19, 15, 16,
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17, 18, 19, 20, 21, 22, 23, 24, 35, 36, 37, 38, 39, 30, 31, 32,
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33, 34, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 50, 51, 52, 53,
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54, 45, 46, 47, 48, 49, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54};
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EXPECT_TRUE(
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input_tensor->CopyDataToTensor(in_data.data(), in_data.size()));
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EXPECT_TRUE(
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indices_tensor->CopyDataToTensor(indices.data(), indices.size() * 4));
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auto op = graph->CreateOperation<tim::vx::ops::Gather>(1,1);
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(*op).BindInputs({input_tensor, indices_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<int8_t> 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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}
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