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Fixed l2normalization layout infer bug (#570) 

And added a case

Type: Bug fix

Signed-off-by: Chen Xin <jack.chen@verisilicon.com>
Co-authored-by: Chen Xin <jack.chen@verisilicon.com>
This commit is contained in:
chxin66 2023-03-27 15:00:25 +08:00 committed by GitHub
parent e49f67b840
commit c2755b90ea
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2 changed files with 57 additions and 1 deletions
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2
src/tim/transform/ops/l2normalization_layout_inference.h
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@ -42,7 +42,7 @@ class L2NormalizationLayoutInfer : public OpLayoutInfer {
auto input_pv = context_->GetPermuteVector(src_input);
int32_t axis =
MapAxis(input_pv->AsStdVec(), op_->impl()->node()->nn_param.lrn.axis);
MapAxis(input_pv->AsStdVec(), op_->impl()->node()->nn_param.l2_normalize.axis);
auto l2norm =
context_->infer_graph_->CreateOperation<vx::ops::L2Normalization>(axis);

56
src/tim/vx/ops/l2normalization_test.cc Normal file
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@ -0,0 +1,56 @@
/****************************************************************************
*
* 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/l2normalization.h"
#include "test_utils.h"
#include "gtest/gtest.h"
TEST(L2Norm, axis_1_shape_2_3_float) {
auto ctx = tim::vx::Context::Create();
auto graph = ctx->CreateGraph();
tim::vx::ShapeType io_shape({2,3});
tim::vx::TensorSpec input_spec(tim::vx::DataType::FLOAT32,
io_shape, tim::vx::TensorAttribute::INPUT);
tim::vx::TensorSpec output_spec(tim::vx::DataType::FLOAT32,
io_shape, tim::vx::TensorAttribute::OUTPUT);
auto input_tensor = graph->CreateTensor(input_spec);
auto output_tensor = graph->CreateTensor(output_spec);
std::vector<float> in_data = {0.0f, 3.0f, 3.0f, 0.0f, 4.0f, 4.0f};
std::vector<float> golden = {0.0f, 0.6f, 0.6f, 0.0f, 0.8f, 0.8f};
EXPECT_TRUE(input_tensor->CopyDataToTensor(in_data.data(), in_data.size() * sizeof(float)));
auto op = graph->CreateOperation<tim::vx::ops::L2Normalization>(1);
(*op).BindInputs({input_tensor}).BindOutputs({output_tensor});
EXPECT_TRUE(graph->Compile());
EXPECT_TRUE(graph->Run());
std::vector<float> output(6);
EXPECT_TRUE(output_tensor->CopyDataFromTensor(output.data()));
EXPECT_TRUE(ArraysMatch(golden, output, 1e-5f));
}