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Diffstat (limited to 'src/graph/operations/NESimpleOperations.cpp')
| -rw-r--r-- | src/graph/operations/NESimpleOperations.cpp | 277 |
1 files changed, 277 insertions, 0 deletions
diff --git a/src/graph/operations/NESimpleOperations.cpp b/src/graph/operations/NESimpleOperations.cpp new file mode 100644 index 0000000000..59f252ae44 --- /dev/null +++ b/src/graph/operations/NESimpleOperations.cpp @@ -0,0 +1,277 @@ +/* + * 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/core/Error.h" +#include "arm_compute/core/ITensor.h" +#include "arm_compute/graph/IOperation.h" +#include "arm_compute/graph/NodeContext.h" +#include "arm_compute/graph/OperationRegistrar.h" +#include "arm_compute/graph/Types.h" +#include "arm_compute/runtime/NEON/NEFunctions.h" +#include "support/ToolchainSupport.h" +#include "utils/GraphTypePrinter.h" +#include "utils/TypePrinter.h" + +#include <memory> + +using namespace arm_compute::graph; + +/* Activation Layer */ +REGISTER_SIMPLE_OPERATION(NEActivationLayerOperation, NEON, OperationType::ActivationLayer) +{ + ARM_COMPUTE_ERROR_ON(ctx.num_inputs() != 1); + ARM_COMPUTE_ERROR_ON(ctx.num_outputs() != 1); + ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ITensor *>(ctx.input(0)) == nullptr); + ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ITensor *>(ctx.output(0)) == nullptr); + + // Extract IO and info + auto *in = dynamic_cast<arm_compute::ITensor *>(ctx.input(0)); + auto *out = dynamic_cast<arm_compute::ITensor *>(ctx.output(0)); + const auto act_info = ctx.parameter<ActivationLayerInfo>("ActivationLayerInfo"); + + // Create and configure function + auto activation = arm_compute::support::cpp14::make_unique<arm_compute::NEActivationLayer>(); + activation->configure(in, out, act_info); + + // Log info + ARM_COMPUTE_LOG_GRAPH_INFO("Instantiating NEActivationLayer" + << " Data Type: " << in->info()->data_type() + << " Input shape: " << in->info()->tensor_shape() + << " Output shape: " << out->info()->tensor_shape() + << " Activation function: " << act_info.activation() + << " a: " << act_info.a() + << " b: " << act_info.b() + << std::endl); + + return std::move(activation); +} + +/* Batch Normalization Layer */ +REGISTER_SIMPLE_OPERATION(NEBatchNormalizationLayerOperation, NEON, OperationType::BatchNormalizationLayer) +{ + ARM_COMPUTE_ERROR_ON(ctx.num_inputs() != 5); + ARM_COMPUTE_ERROR_ON(ctx.num_outputs() != 1); + ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ITensor *>(ctx.input(0)) == nullptr); + ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ITensor *>(ctx.input(1)) == nullptr); + ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ITensor *>(ctx.input(2)) == nullptr); + ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ITensor *>(ctx.input(3)) == nullptr); + ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ITensor *>(ctx.input(4)) == nullptr); + ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ITensor *>(ctx.output(0)) == nullptr); + + // Extract IO and info + auto *in = dynamic_cast<arm_compute::ITensor *>(ctx.input(0)); + auto *mean = dynamic_cast<arm_compute::ITensor *>(ctx.input(1)); + auto *var = dynamic_cast<arm_compute::ITensor *>(ctx.input(2)); + auto *beta = dynamic_cast<arm_compute::ITensor *>(ctx.input(3)); + auto *gamma = dynamic_cast<arm_compute::ITensor *>(ctx.input(4)); + auto *out = dynamic_cast<arm_compute::ITensor *>(ctx.output(0)); + const auto epsilon = ctx.parameter<float>("epsilon"); + + // Create and configure function + auto batch_norm = arm_compute::support::cpp14::make_unique<arm_compute::NEBatchNormalizationLayer>(); + batch_norm->configure(in, out, mean, var, beta, gamma, epsilon); + + // Log info + ARM_COMPUTE_LOG_GRAPH_INFO("Instantiating NEBatchNormalizationLayer" + << " Data Type: " << in->info()->data_type() + << " Input shape: " << in->info()->tensor_shape() + << " Output shape: " << out->info()->tensor_shape() + << " Mean shape: " << mean->info()->tensor_shape() + << " Var shape: " << var->info()->tensor_shape() + << " Beta shape: " << beta->info()->tensor_shape() + << " Gamma shape: " << gamma->info()->tensor_shape() + << " Epsilon: " << epsilon + << std::endl); + + return std::move(batch_norm); +} + +/* Floor Layer */ +REGISTER_SIMPLE_OPERATION(NEFloorLayerOperation, NEON, OperationType::FloorLayer) +{ + ARM_COMPUTE_ERROR_ON(ctx.num_inputs() != 1); + ARM_COMPUTE_ERROR_ON(ctx.num_outputs() != 1); + ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ITensor *>(ctx.input(0)) == nullptr); + ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ITensor *>(ctx.output(0)) == nullptr); + + // Extract IO and info + auto *in = dynamic_cast<arm_compute::ITensor *>(ctx.input(0)); + auto *out = dynamic_cast<arm_compute::ITensor *>(ctx.output(0)); + + // Create and configure function + auto floor = arm_compute::support::cpp14::make_unique<arm_compute::NEFloor>(); + floor->configure(in, out); + + // Log info + ARM_COMPUTE_LOG_GRAPH_INFO("Instantiating NEFloorLayer" + << " Data Type: " << in->info()->data_type() + << " Input shape: " << in->info()->tensor_shape() + << " Output shape: " << out->info()->tensor_shape() + << std::endl); + + return std::move(floor); +} + +/* Fully Connected Layer */ +REGISTER_SIMPLE_OPERATION(NEFullyConnectedLayer, NEON, OperationType::FullyConnectedLayer) +{ + ARM_COMPUTE_ERROR_ON(ctx.num_inputs() != 3); + ARM_COMPUTE_ERROR_ON(ctx.num_outputs() != 1); + ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ITensor *>(ctx.input(0)) == nullptr); + ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ITensor *>(ctx.input(1)) == nullptr); + ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ITensor *>(ctx.input(2)) == nullptr); + ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ITensor *>(ctx.output(0)) == nullptr); + + // Extract IO and info + auto *in = dynamic_cast<arm_compute::ITensor *>(ctx.input(0)); + auto *weights = dynamic_cast<arm_compute::ITensor *>(ctx.input(1)); + auto *biases = dynamic_cast<arm_compute::ITensor *>(ctx.input(2)); + auto *out = dynamic_cast<arm_compute::ITensor *>(ctx.output(0)); + + // Create and configure function + auto fc = arm_compute::support::cpp14::make_unique<arm_compute::NEFullyConnectedLayer>(); + fc->configure(in, weights, biases, out); + + // Log info + ARM_COMPUTE_LOG_GRAPH_INFO("Instantiating NEFullyConnectedLayer" + << " Data Type: " << in->info()->data_type() + << " Input shape: " << in->info()->tensor_shape() + << " Weights shape: " << weights->info()->tensor_shape() + << " Biases Shape: " << biases->info()->tensor_shape() + << " Output shape: " << out->info()->tensor_shape() + << std::endl); + + return std::move(fc); +} + +/* L2 Normalize Layer */ +REGISTER_SIMPLE_OPERATION(NEL2NormalizeLayerOperation, NEON, OperationType::L2NormalizeLayer) +{ + ARM_COMPUTE_ERROR_ON(ctx.num_inputs() != 1); + ARM_COMPUTE_ERROR_ON(ctx.num_outputs() != 1); + ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ITensor *>(ctx.input(0)) == nullptr); + ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ITensor *>(ctx.output(0)) == nullptr); + + // Extract IO and info + auto *in = dynamic_cast<arm_compute::ITensor *>(ctx.input(0)); + auto *out = dynamic_cast<arm_compute::ITensor *>(ctx.output(0)); + const auto axis = ctx.parameter<unsigned int>("axis"); + const auto epsilon = ctx.parameter<float>("epsilon"); + + // Create and configure function + auto l2_norm = arm_compute::support::cpp14::make_unique<arm_compute::NEL2Normalize>(); + l2_norm->configure(in, out, axis, epsilon); + + // Log info + ARM_COMPUTE_LOG_GRAPH_INFO("Instantiating NEL2NormalizeLayer" + << " Data Type: " << in->info()->data_type() + << " Input shape: " << in->info()->tensor_shape() + << " Output shape: " << out->info()->tensor_shape() + << " Axis: " << axis + << " Epsilon: " << epsilon + << std::endl); + + return std::move(l2_norm); +} + +/* Normalization Layer */ +REGISTER_SIMPLE_OPERATION(NENormalizationLayerOperation, NEON, OperationType::NormalizationLayer) +{ + ARM_COMPUTE_ERROR_ON(ctx.num_inputs() != 1); + ARM_COMPUTE_ERROR_ON(ctx.num_outputs() != 1); + ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ITensor *>(ctx.input(0)) == nullptr); + ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ITensor *>(ctx.output(0)) == nullptr); + + // Extract IO and info + auto *in = dynamic_cast<arm_compute::ITensor *>(ctx.input(0)); + auto *out = dynamic_cast<arm_compute::ITensor *>(ctx.output(0)); + const auto norm_info = ctx.parameter<NormalizationLayerInfo>("NormalizationLayerInfo"); + + // Create and configure function + auto norm = arm_compute::support::cpp14::make_unique<arm_compute::NENormalizationLayer>(); + norm->configure(in, out, norm_info); + + // Log info + ARM_COMPUTE_LOG_GRAPH_INFO("Instantiating NENormalizationLayer" + << " Data Type: " << in->info()->data_type() + << " Input shape: " << in->info()->tensor_shape() + << " Output shape: " << out->info()->tensor_shape() + << " Normalization info: " << norm_info + << std::endl); + + return std::move(norm); +} + +/* Pooling Layer */ +REGISTER_SIMPLE_OPERATION(NEPoolingLayerOperation, NEON, OperationType::PoolingLayer) +{ + ARM_COMPUTE_ERROR_ON(ctx.num_inputs() != 1); + ARM_COMPUTE_ERROR_ON(ctx.num_outputs() != 1); + ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ITensor *>(ctx.input(0)) == nullptr); + ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ITensor *>(ctx.output(0)) == nullptr); + + // Extract IO and info + auto *in = dynamic_cast<arm_compute::ITensor *>(ctx.input(0)); + auto *out = dynamic_cast<arm_compute::ITensor *>(ctx.output(0)); + const auto pool_info = ctx.parameter<PoolingLayerInfo>("PoolingLayerInfo"); + + // Create and configure function + auto pool = arm_compute::support::cpp14::make_unique<arm_compute::NEPoolingLayer>(); + pool->configure(in, out, pool_info); + + // Log info + ARM_COMPUTE_LOG_GRAPH_INFO("Instantiating NEPoolingLayer" + << " Data Type: " << in->info()->data_type() + << " Input shape: " << in->info()->tensor_shape() + << " Output shape: " << out->info()->tensor_shape() + << " Pooling info: " << pool_info + << std::endl); + + return std::move(pool); +} + +/* Softmax Layer */ +REGISTER_SIMPLE_OPERATION(NESoftmaxLayerOperation, NEON, OperationType::SoftmaxLayer) +{ + ARM_COMPUTE_ERROR_ON(ctx.num_inputs() != 1); + ARM_COMPUTE_ERROR_ON(ctx.num_outputs() != 1); + ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ITensor *>(ctx.input(0)) == nullptr); + ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ITensor *>(ctx.output(0)) == nullptr); + + // Extract IO and info + auto *in = dynamic_cast<arm_compute::ITensor *>(ctx.input(0)); + auto *out = dynamic_cast<arm_compute::ITensor *>(ctx.output(0)); + + // Create and configure function + auto smx = arm_compute::support::cpp14::make_unique<arm_compute::NESoftmaxLayer>(); + smx->configure(in, out); + + // Log info + ARM_COMPUTE_LOG_GRAPH_INFO("Instantiating NESoftmaxLayer" + << " Data Type: " << in->info()->data_type() + << " Input shape: " << in->info()->tensor_shape() + << " Output shape: " << out->info()->tensor_shape() + << std::endl); + + return std::move(smx); +}
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