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/*
* Copyright (c) 2020 Samsung Electronics Co., Ltd. All Rights Reserved
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include <cker/operation/InstanceNorm.h>
#include "OperationUtil.h"
#include "exec/interp/Registration.h"
#include "ir/operation/InstanceNorm.h"
#include "misc/polymorphic_downcast.h"
namespace neurun
{
namespace exec
{
namespace interp
{
namespace instancenorm
{
void prepareInstanceNorm(ExecEnv *env, const ir::Operation &node)
{
const auto &instancenorm_node =
nnfw::misc::polymorphic_downcast<const ir::operation::InstanceNorm &>(node);
const auto input_index = node.getInputs().at(instancenorm_node.INPUT);
const auto output_index = node.getOutputs().at(0);
const auto input_tensor = env->tensorAt(input_index);
if (input_tensor->num_dimensions() != 4)
{
throw std::runtime_error{"Interp(InstanceNorm): Input should be 4D-tensor"};
}
// Output shape should be same with input
env->allocateIfNeeded(output_index, input_tensor->tensorInfo());
auto output_tensor = env->tensorAt(output_index);
UNUSED_RELEASE(output_tensor);
// Handle same ifm & ofm data type only
assert(input_tensor->data_type() == output_tensor->data_type());
assert(input_tensor->tensorInfo().shape() == output_tensor->tensorInfo().shape());
}
inline void setActivationParams(float min, float max, nnfw::cker::InstanceNormParams *params)
{
params->float_activation_min = min;
params->float_activation_max = max;
}
void invoke(const ITensor *input_tensor, const ITensor *gamma_tensor, const ITensor *beta_tensor,
const ITensor *output_tensor, const ir::operation::InstanceNorm::Param ¶m)
{
// Calculate
float activation_min, activation_max;
calculateActivationRange(param.activation, &activation_min, &activation_max);
nnfw::cker::InstanceNormParams cker_param;
cker_param.epsilon = param.epsilon;
cker_param.float_activation_min = activation_min;
cker_param.float_activation_max = activation_max;
const auto cker_input_shape = convertShape(input_tensor->tensorInfo().shape());
const auto cker_gamma_shape = convertShape(gamma_tensor->tensorInfo().shape());
const auto cker_beta_shape = convertShape(beta_tensor->tensorInfo().shape());
const auto cker_output_shape = convertShape(output_tensor->tensorInfo().shape());
const float *input_ptr = reinterpret_cast<const float *>(input_tensor->bufferRO());
const float *gamma_ptr = reinterpret_cast<const float *>(gamma_tensor->bufferRO());
const float *beta_ptr = reinterpret_cast<const float *>(beta_tensor->bufferRO());
float *output_ptr = reinterpret_cast<float *>(output_tensor->buffer());
nnfw::cker::InstanceNorm(cker_param, cker_input_shape, input_ptr, cker_gamma_shape, gamma_ptr,
cker_beta_shape, beta_ptr, cker_output_shape, output_ptr);
}
void invokeInstanceNorm(const ExecEnv *env, const ir::Operation &node)
{
const auto &instancenorm_node =
nnfw::misc::polymorphic_downcast<const ir::operation::InstanceNorm &>(node);
const auto input_index = node.getInputs().at(instancenorm_node.INPUT);
const auto gamma_index = node.getInputs().at(instancenorm_node.GAMMA);
const auto beta_index = node.getInputs().at(instancenorm_node.BETA);
const auto out_index = node.getOutputs().at(0);
const auto input_tensor = env->tensorAt(input_index);
const auto gamma_tensor = env->tensorAt(gamma_index);
const auto beta_tensor = env->tensorAt(beta_index);
const auto out_tensor = env->tensorAt(out_index);
const auto data_type = input_tensor->data_type();
if (data_type == ir::DataType::FLOAT32)
{
invoke(input_tensor, gamma_tensor, beta_tensor, out_tensor, instancenorm_node.param());
}
else
{
throw std::runtime_error{"NYI: Unsupported data type"};
}
}
} // namespace instancenorm
OpKernel *getInstanceNorm()
{
static OpKernel kernel = {instancenorm::prepareInstanceNorm, instancenorm::invokeInstanceNorm};
return &kernel;
}
} // namespace interp
} // namespace exec
} // namespace neurun
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