Add map for Resize1d (#69)
Signed-off-by: zhao.xia <zhao.xia@verisilicon.com>
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/****************************************************************************
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*
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* Copyright (c) 2021 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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#ifndef TIM_VX_OPS_RESIZE1D_H_
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#define TIM_VX_OPS_RESIZE1D_H_
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#include "tim/vx/operation.h"
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namespace tim {
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namespace vx {
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namespace ops {
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/**
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* ## Resize1d
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*
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* Resize1ds 1D tensors to given size.
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*
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* - type : NEAREST_NEIGHBOR, BILINEAR or AREA.
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* - factor : scale the input size. DO NOT use it with target_height / target_width together.
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* - align_corners : If True, the centers of the 4 corner pixels of the input and output
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* tensors are aligned, preserving the values at the corner pixels.
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* - half_pixel_centers : If True, the pixel centers are assumed to be at (0.5, 0.5).
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* This is the default behavior of image.resize in TF 2.0. If this parameter is True,
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* then align_corners parameter must be False.
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* - target_height / target_width : output height / width. DO NOT use it with factor together.
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*/
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class Resize1d : public Operation {
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public:
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Resize1d(Graph* graph, ResizeType type, float factor, bool align_corners,
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bool half_pixel_centers, int target_size,
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DataLayout layout = DataLayout::WHCN);
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protected:
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const ResizeType type_;
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const float factor_;
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const bool align_corners_;
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const bool half_pixel_centers_;
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const int target_size_;
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};
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} // namespace ops
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} // namespace vx
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} // namespace tim
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#endif /* TIM_VX_OPS_RESIZE1D_H_ */
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@ -150,7 +150,7 @@ Mish|MISH|Mapped|[tfa.activations.mish](https://tensorflow.google.cn/addons/api_
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||SCATTER_ND|Unmapped|[tf.scatter_nd](https://tensorflow.google.cn/api_docs/python/tf/scatter_nd)
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|DeConv1d|DECONVOLUTION1D|Mapped|[tf.nn.conv1d_transpose](https://tensorflow.google.cn/api_docs/python/tf/nn/conv1d_transpose)
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||INTERP|Unmapped
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||RESIZE_1D|Unmapped
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Resize1d|RESIZE_1D|Mapped|[Onnx.resize 1D image](https://github.com/onnx/onnx/blob/master/docs/Operators.md#resize)
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||CONV_RELU|Deprecated
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||CONV_RELU_POOL|Deprecated
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||FCL|Deprecated
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@ -0,0 +1,52 @@
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/****************************************************************************
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*
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* Copyright (c) 2021 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/ops/resize1d.h"
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#include "operation_private.h"
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#include "type_utils.h"
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#include "vsi_nn_pub.h"
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namespace tim {
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namespace vx {
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namespace ops {
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Resize1d::Resize1d(Graph* graph, ResizeType type, float factor, bool align_corners,
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bool half_pixel_centers, int target_size, DataLayout layout)
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: Operation(graph, VSI_NN_OP_RESIZE_1D, 0, 0, layout),
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type_(type),
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factor_(factor),
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align_corners_(align_corners),
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half_pixel_centers_(half_pixel_centers),
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target_size_(target_size) {
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impl()->node()->nn_param.resize_1d.type = TranslateResizeType(type);
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impl()->node()->nn_param.resize_1d.factor = factor;
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impl()->node()->nn_param.resize_1d.align_corners = ToVxBool(align_corners);
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impl()->node()->nn_param.resize_1d.half_pixel_centers =
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ToVxBool(half_pixel_centers);
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impl()->node()->nn_param.resize_1d.size[0] = target_size;
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}
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} // namespace ops
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} // namespace vx
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} // namespace tim
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@ -0,0 +1,114 @@
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/****************************************************************************
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*
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* Copyright (c) 2021 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/resize1d.h"
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#include "gtest/gtest.h"
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namespace {
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template<typename T>
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::testing::AssertionResult ArraysMatch(const std::vector<T>& expected,
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const std::vector<T>& actual,
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T abs_error){
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for (size_t i = 0; i < expected.size(); ++i){
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EXPECT_NEAR(expected[i], actual[i], abs_error) << "at index:" << i;
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}
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return ::testing::AssertionSuccess();
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}
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}
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TEST(Resize1d, shape_4_2_1_float_nearest_whcn) {
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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 input_shape({4, 2, 1});
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tim::vx::ShapeType output_shape({2, 2, 1});
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tim::vx::TensorSpec input_spec(tim::vx::DataType::FLOAT32,
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input_shape, tim::vx::TensorAttribute::INPUT);
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tim::vx::TensorSpec output_spec(tim::vx::DataType::FLOAT32,
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output_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.f, 2.f, 3.f, 4.f,
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5.f, 6.f, 7.f, 8.f,
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};
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std::vector<float> golden = {
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1.f, 3.f,
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5.f, 7.f,
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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::Resize1d>(
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tim::vx::ResizeType::NEAREST_NEIGHBOR, 0.6, false, false, 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() * sizeof(float));
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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(Resize1d, shape_5_1_1_uint8_bilinear_align_corners_whcn) {
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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 input_shape({5, 1, 1});
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tim::vx::ShapeType output_shape({7, 1, 1});
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tim::vx::TensorSpec input_spec(tim::vx::DataType::FLOAT32,
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input_shape, tim::vx::TensorAttribute::INPUT);
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tim::vx::TensorSpec output_spec(tim::vx::DataType::FLOAT32,
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output_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.f, 2.f, 3.f, 4.f, 5.f,
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};
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std::vector<float> golden = {
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1.f, 1.66666f, 2.33333f, 3.f,
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3.66666, 4.33333f, 5.f
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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::Resize1d>(
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tim::vx::ResizeType::BILINEAR, 0, true, false, 7);
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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() * sizeof(float));
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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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