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Fixed param compute bug for lrn 

Signed-off-by: Chen Xin <jack.chen@verisilicon.com>
This commit is contained in:
Chen Xin 2022-08-03 19:00:33 +08:00 committed by Sven
parent f728e1b42d
commit 3663a99e0f
3 changed files with 68 additions and 1 deletions
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5
include/tim/vx/ops/localresponsenormalization.h
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@ -34,6 +34,11 @@
* sqr_sum[a, b, c, d] = sum(
* pow(input[a, b, c, d - depth_radius : d + depth_radius + 1], 2))
* output = input / pow((bias + alpha * sqr_sum), beta)
* output = input / pow((bias + alpha * sqr_sum), beta)
* size : width of the 1-D normalization window.
* bias : An offset (usually positive to avoid dividing by 0).
* alpha : A scale factor.
* beta : An exponent.
* ```
*/

2
src/tim/vx/ops/localresponsenormalization.cc
View File

@ -39,7 +39,7 @@ LocalResponseNormalization::LocalResponseNormalization(Graph* graph,
beta_(beta),
bias_(bias),
axis_(axis) {
this->impl()->node()->nn_param.lrn.size = size_ * 2 + 1;
this->impl()->node()->nn_param.lrn.size = size_;
this->impl()->node()->nn_param.lrn.alpha = alpha_;
this->impl()->node()->nn_param.lrn.beta = beta_;
this->impl()->node()->nn_param.lrn.bias = bias_;

62
src/tim/vx/ops/localresponsenormalization_test.cc Normal file
View File

@ -0,0 +1,62 @@
/****************************************************************************
*
* 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/localresponsenormalization.h"
#include "test_utils.h"
#include "gtest/gtest.h"
TEST(localresponsenormalization, axis_0_shape_6_1_1_1_float) {
auto ctx = tim::vx::Context::Create();
auto graph = ctx->CreateGraph();
tim::vx::ShapeType io_shape({6, 1, 1, 1});
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 = {-1.1, 0.6, 0.7, 1.2, -0.7, 0.1};
std::vector<float> golden = {-0.264926, 0.125109, 0.140112,
0.267261, -0.161788, 0.0244266};
EXPECT_TRUE(input_tensor->CopyDataToTensor(in_data.data(),
in_data.size() * sizeof(float)));
int radius = 5;
float alpha = 4.0, beta = 0.5, bias = 9.0;
auto op = graph->CreateOperation<tim::vx::ops::LocalResponseNormalization>(
radius, alpha, beta, bias, 0);
(*op).BindInputs({input_tensor}).BindOutputs({output_tensor});
EXPECT_TRUE(graph->Compile());
EXPECT_TRUE(graph->Run());
std::vector<float> output(18);
EXPECT_TRUE(output_tensor->CopyDataFromTensor(output.data()));
EXPECT_TRUE(ArraysMatch(golden, output, 1e-5f));
}