COMPMID-630: Rework nodes
Reworked node:
-BatchNormalization
-Floor
-FullyConncted
-L2Normalize
-Normalization
-Pooling
-Softmax
Change-Id: I4c71cfffb1f59aac3326ba8b1f831339c5244394
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/93134
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
diff --git a/src/graph/operations/CLSimpleOperations.cpp b/src/graph/operations/CLSimpleOperations.cpp
new file mode 100644
index 0000000..b4c217b
--- /dev/null
+++ b/src/graph/operations/CLSimpleOperations.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/CL/ICLTensor.h"
+#include "arm_compute/core/Error.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/CL/CLFunctions.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(CLActivationLayerOperation, OPENCL, 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::ICLTensor *>(ctx.input(0)) == nullptr);
+ ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ICLTensor *>(ctx.output(0)) == nullptr);
+
+ // Extract IO and info
+ auto *in = dynamic_cast<arm_compute::ICLTensor *>(ctx.input(0));
+ auto *out = dynamic_cast<arm_compute::ICLTensor *>(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::CLActivationLayer>();
+ activation->configure(in, out, act_info);
+
+ // Log info
+ ARM_COMPUTE_LOG_GRAPH_INFO("Instantiating CLActivationLayer"
+ << " 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(CLBatchNormalizationLayerOperation, OPENCL, 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::ICLTensor *>(ctx.input(0)) == nullptr);
+ ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ICLTensor *>(ctx.input(1)) == nullptr);
+ ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ICLTensor *>(ctx.input(2)) == nullptr);
+ ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ICLTensor *>(ctx.input(3)) == nullptr);
+ ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ICLTensor *>(ctx.input(4)) == nullptr);
+ ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ICLTensor *>(ctx.output(0)) == nullptr);
+
+ // Extract IO and info
+ auto *in = dynamic_cast<arm_compute::ICLTensor *>(ctx.input(0));
+ auto *mean = dynamic_cast<arm_compute::ICLTensor *>(ctx.input(1));
+ auto *var = dynamic_cast<arm_compute::ICLTensor *>(ctx.input(2));
+ auto *beta = dynamic_cast<arm_compute::ICLTensor *>(ctx.input(3));
+ auto *gamma = dynamic_cast<arm_compute::ICLTensor *>(ctx.input(4));
+ auto *out = dynamic_cast<arm_compute::ICLTensor *>(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::CLBatchNormalizationLayer>();
+ batch_norm->configure(in, out, mean, var, beta, gamma, epsilon);
+
+ // Log info
+ ARM_COMPUTE_LOG_GRAPH_INFO("Instantiating CLBatchNormalizationLayer"
+ << " 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(CLFloorLayerOperation, OPENCL, 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::ICLTensor *>(ctx.input(0)) == nullptr);
+ ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ICLTensor *>(ctx.output(0)) == nullptr);
+
+ // Extract IO and info
+ auto *in = dynamic_cast<arm_compute::ICLTensor *>(ctx.input(0));
+ auto *out = dynamic_cast<arm_compute::ICLTensor *>(ctx.output(0));
+
+ // Create and configure function
+ auto floor = arm_compute::support::cpp14::make_unique<arm_compute::CLFloor>();
+ floor->configure(in, out);
+
+ // Log info
+ ARM_COMPUTE_LOG_GRAPH_INFO("Instantiating CLFloorLayer"
+ << " 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(CLFullyConnectedLayer, OPENCL, 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::ICLTensor *>(ctx.input(0)) == nullptr);
+ ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ICLTensor *>(ctx.input(1)) == nullptr);
+ ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ICLTensor *>(ctx.input(2)) == nullptr);
+ ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ICLTensor *>(ctx.output(0)) == nullptr);
+
+ // Extract IO and info
+ auto *in = dynamic_cast<arm_compute::ICLTensor *>(ctx.input(0));
+ auto *weights = dynamic_cast<arm_compute::ICLTensor *>(ctx.input(1));
+ auto *biases = dynamic_cast<arm_compute::ICLTensor *>(ctx.input(2));
+ auto *out = dynamic_cast<arm_compute::ICLTensor *>(ctx.output(0));
+
+ // Create and configure function
+ auto fc = arm_compute::support::cpp14::make_unique<arm_compute::CLFullyConnectedLayer>();
+ 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(CLL2NormalizeLayerOperation, OPENCL, 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::ICLTensor *>(ctx.input(0)) == nullptr);
+ ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ICLTensor *>(ctx.output(0)) == nullptr);
+
+ // Extract IO and info
+ auto *in = dynamic_cast<arm_compute::ICLTensor *>(ctx.input(0));
+ auto *out = dynamic_cast<arm_compute::ICLTensor *>(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::CLL2Normalize>();
+ l2_norm->configure(in, out, axis, epsilon);
+
+ // Log info
+ ARM_COMPUTE_LOG_GRAPH_INFO("Instantiating CLL2NormalizeLayer"
+ << " 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(CLNormalizationLayerOperation, OPENCL, 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::ICLTensor *>(ctx.input(0)) == nullptr);
+ ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ICLTensor *>(ctx.output(0)) == nullptr);
+
+ // Extract IO and info
+ auto *in = dynamic_cast<arm_compute::ICLTensor *>(ctx.input(0));
+ auto *out = dynamic_cast<arm_compute::ICLTensor *>(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::CLNormalizationLayer>();
+ norm->configure(in, out, norm_info);
+
+ // Log info
+ ARM_COMPUTE_LOG_GRAPH_INFO("Instantiating CLNormalizationLayer"
+ << " 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(CLPoolingLayerOperation, OPENCL, 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::ICLTensor *>(ctx.input(0)) == nullptr);
+ ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ICLTensor *>(ctx.output(0)) == nullptr);
+
+ // Extract IO and info
+ auto *in = dynamic_cast<arm_compute::ICLTensor *>(ctx.input(0));
+ auto *out = dynamic_cast<arm_compute::ICLTensor *>(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::CLPoolingLayer>();
+ pool->configure(in, out, pool_info);
+
+ // Log info
+ ARM_COMPUTE_LOG_GRAPH_INFO("Instantiating CLPoolingLayer"
+ << " 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(CLSoftmaxLayerOperation, OPENCL, 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::ICLTensor *>(ctx.input(0)) == nullptr);
+ ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ICLTensor *>(ctx.output(0)) == nullptr);
+
+ // Extract IO and info
+ auto *in = dynamic_cast<arm_compute::ICLTensor *>(ctx.input(0));
+ auto *out = dynamic_cast<arm_compute::ICLTensor *>(ctx.output(0));
+
+ // Create and configure function
+ auto smx = arm_compute::support::cpp14::make_unique<arm_compute::CLSoftmaxLayer>();
+ smx->configure(in, out);
+
+ // Log info
+ ARM_COMPUTE_LOG_GRAPH_INFO("Instantiating CLSoftmaxLayer"
+ << " Data Type: " << in->info()->data_type()
+ << " Input shape: " << in->info()->tensor_shape()
+ << " Output shape: " << out->info()->tensor_shape()
+ << std::endl);
+
+ return std::move(smx);
+}
\ No newline at end of file