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author | Michalis Spyrou <michalis.spyrou@arm.com> | 2017-10-09 15:46:30 +0100 |
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committer | Anthony Barbier <anthony.barbier@arm.com> | 2018-11-02 16:35:24 +0000 |
commit | a4a96015a6c7d92bed08f82db9b36e1d34f9386d (patch) | |
tree | 45d4983ed404240f4df799f08bbec06137d7bb65 /src/graph/nodes/BatchNormalizationLayer.cpp | |
parent | 04065bebf72310a3fa3eb2198e61c88aa87faf0d (diff) | |
download | ComputeLibrary-a4a96015a6c7d92bed08f82db9b36e1d34f9386d.tar.gz |
COMPMID-554 Add Nodes
- BatchNormalization
- L2Normalize
- Floor
Change-Id: I03e06dea30e956f56a86f9c5642cd609c6696ad2
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/91364
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Diffstat (limited to 'src/graph/nodes/BatchNormalizationLayer.cpp')
-rw-r--r-- | src/graph/nodes/BatchNormalizationLayer.cpp | 110 |
1 files changed, 110 insertions, 0 deletions
diff --git a/src/graph/nodes/BatchNormalizationLayer.cpp b/src/graph/nodes/BatchNormalizationLayer.cpp new file mode 100644 index 0000000000..a6a990fd3f --- /dev/null +++ b/src/graph/nodes/BatchNormalizationLayer.cpp @@ -0,0 +1,110 @@ +/* + * Copyright (c) 2017 ARM Limited. + * + * SPDX-License-Identifier: MIT + * + * 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 "arm_compute/graph/nodes/BatchNormalizationLayer.h" + +#include "arm_compute/core/Logger.h" +#include "arm_compute/runtime/CL/CLTensor.h" +#include "arm_compute/runtime/CL/functions/CLBatchNormalizationLayer.h" +#include "arm_compute/runtime/NEON/functions/NEBatchNormalizationLayer.h" +#include "arm_compute/runtime/Tensor.h" +#include "support/ToolchainSupport.h" +#include "utils/TypePrinter.h" + +using namespace arm_compute::graph; + +namespace +{ +template <typename BatchBatchNormalizationLayer, typename TensorType, TargetHint target_hint> +std::unique_ptr<arm_compute::IFunction> instantiate_function(ITensor *input, ITensor *output, Tensor &mean, Tensor &var, Tensor &beta, Tensor &gamma, float epsilon) +{ + auto norm = arm_compute::support::cpp14::make_unique<BatchBatchNormalizationLayer>(); + norm->configure( + dynamic_cast<TensorType *>(input), + dynamic_cast<TensorType *>(output), + dynamic_cast<TensorType *>(mean.set_target(target_hint)), + dynamic_cast<TensorType *>(var.set_target(target_hint)), + dynamic_cast<TensorType *>(beta.set_target(target_hint)), + dynamic_cast<TensorType *>(gamma.set_target(target_hint)), + epsilon); + + return std::move(norm); +} + +template <TargetHint target_hint> +std::unique_ptr<arm_compute::IFunction> instantiate(ITensor *input, ITensor *output, Tensor &mean, Tensor &var, Tensor &beta, Tensor &gamma, float epsilon); + +template <> +std::unique_ptr<arm_compute::IFunction> instantiate<TargetHint::OPENCL>(ITensor *input, ITensor *output, Tensor &mean, Tensor &var, Tensor &beta, Tensor &gamma, float epsilon) +{ + return instantiate_function<arm_compute::CLBatchNormalizationLayer, arm_compute::ICLTensor, TargetHint::OPENCL>(input, output, mean, var, beta, gamma, epsilon); +} + +template <> +std::unique_ptr<arm_compute::IFunction> instantiate<TargetHint::NEON>(ITensor *input, ITensor *output, Tensor &mean, Tensor &var, Tensor &beta, Tensor &gamma, float epsilon) +{ + return instantiate_function<arm_compute::NEBatchNormalizationLayer, arm_compute::ITensor, TargetHint::NEON>(input, output, mean, var, beta, gamma, epsilon); +} +} // namespace + +std::unique_ptr<arm_compute::IFunction> BatchNormalizationLayer::instantiate_node(GraphContext &ctx, ITensor *input, ITensor *output) +{ + std::unique_ptr<arm_compute::IFunction> func; + _target_hint = ctx.hints().target_hint(); + + unsigned int batch_norm_size = input->info()->dimension(2); + if(_mean.tensor() == nullptr) + { + _mean.set_info(TensorInfo(TensorShape(batch_norm_size), input->info()->num_channels(), input->info()->data_type(), input->info()->fixed_point_position())); + } + if(_var.tensor() == nullptr) + { + _var.set_info(TensorInfo(TensorShape(batch_norm_size), input->info()->num_channels(), input->info()->data_type(), input->info()->fixed_point_position())); + } + if(_beta.tensor() == nullptr) + { + _beta.set_info(TensorInfo(TensorShape(batch_norm_size), input->info()->num_channels(), input->info()->data_type(), input->info()->fixed_point_position())); + } + if(_gamma.tensor() == nullptr) + { + _gamma.set_info(TensorInfo(TensorShape(batch_norm_size), input->info()->num_channels(), input->info()->data_type(), input->info()->fixed_point_position())); + } + + if(_target_hint == TargetHint::OPENCL) + { + func = instantiate<TargetHint::OPENCL>(input, output, _mean, _var, _beta, _gamma, _epsilon); + ARM_COMPUTE_LOG("Instantiating CLBatchNormalizationLayer"); + } + else + { + func = instantiate<TargetHint::NEON>(input, output, _mean, _var, _beta, _gamma, _epsilon); + ARM_COMPUTE_LOG("Instantiating NEBatchNormalizationLayer"); + } + + ARM_COMPUTE_LOG(" Data Type: " << input->info()->data_type() + << " Input shape: " << input->info()->tensor_shape() + << " Output shape: " << output->info()->tensor_shape() + << std::endl); + + return func; +}
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