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/*
* Copyright (c) 2019 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 "arm_compute/runtime/CL/functions/CLFullyConnectedReshapingLayer.h"
using namespace arm_compute;
void CLFullyConnectedReshapingLayer::configure(const arm_compute::ICLTensor *input,
const arm_compute::ICLTensor *weights,
const arm_compute::ICLTensor *biases,
arm_compute::ICLTensor *output, bool needs_reshape,
const arm_compute::TensorShape &reshape)
{
_input = input;
_weights = weights;
_biases = biases;
_output = output;
_needs_reshape = needs_reshape;
if (_needs_reshape)
{
// reshape
auto_init_if_empty(*_cl_buffer.info(),
_input->info()->clone()->set_tensor_shape(reshape).set_data_layout(
_input->info()->data_layout()));
_cl_reshape.configure(_input, &_cl_buffer);
_cl_fc.configure(&_cl_buffer, _weights, _biases, _output);
// NOTE _cl_buffer is inaccessible from outside, and thus it is safe to invoke allocate here.
_cl_buffer.allocator()->allocate();
}
else
{
_cl_fc.configure(_input, _weights, _biases, _output);
}
}
void CLFullyConnectedReshapingLayer::run(void)
{
if (_needs_reshape)
_cl_reshape.run();
_cl_fc.run();
}
void CLFullyConnectedReshapingLayer::prepare(void) { _cl_fc.prepare(); }
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