| /* |
| * Copyright (c) 2017-2018 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/graph/Error.h" |
| #include "arm_compute/graph/NodeContext.h" |
| #include "arm_compute/graph/OperationRegistry.h" |
| #include "support/ToolchainSupport.h" |
| |
| using namespace arm_compute::graph; |
| |
| std::unique_ptr<arm_compute::IFunction> BatchNormalizationLayer::instantiate_node(GraphContext &ctx, ITensorObject *input, ITensorObject *output) |
| { |
| ARM_COMPUTE_ERROR_ON_UNALLOCATED_TENSOR_OBJECT(input, output); |
| |
| arm_compute::ITensor *in = input->tensor(); |
| arm_compute::ITensor *out = output->tensor(); |
| _target_hint = ctx.hints().target_hint(); |
| |
| unsigned int batch_norm_size = in->info()->dimension(2); |
| if(_mean.tensor() == nullptr) |
| { |
| _mean.set_info(TensorInfo(TensorShape(batch_norm_size), in->info()->num_channels(), in->info()->data_type(), in->info()->fixed_point_position())); |
| } |
| if(_var.tensor() == nullptr) |
| { |
| _var.set_info(TensorInfo(TensorShape(batch_norm_size), in->info()->num_channels(), in->info()->data_type(), in->info()->fixed_point_position())); |
| } |
| if(_beta.tensor() == nullptr) |
| { |
| _beta.set_info(TensorInfo(TensorShape(batch_norm_size), in->info()->num_channels(), in->info()->data_type(), in->info()->fixed_point_position())); |
| } |
| if(_gamma.tensor() == nullptr) |
| { |
| _gamma.set_info(TensorInfo(TensorShape(batch_norm_size), in->info()->num_channels(), in->info()->data_type(), in->info()->fixed_point_position())); |
| } |
| |
| bool mean_is_loaded = _mean.tensor() != nullptr; |
| bool var_is_loaded = _var.tensor() != nullptr; |
| bool gamma_is_loaded = _gamma.tensor() != nullptr; |
| bool beta_is_loaded = _beta.tensor() != nullptr; |
| |
| // Set mean, var, gamma and beta target |
| _mean.set_target(_target_hint); |
| _var.set_target(_target_hint); |
| _gamma.set_target(_target_hint); |
| _beta.set_target(_target_hint); |
| |
| // Create node context |
| NodeContext node_ctx(OperationType::BatchNormalizationLayer); |
| node_ctx.set_target(_target_hint); |
| node_ctx.add_input(in); |
| node_ctx.add_input(_mean.tensor()); |
| node_ctx.add_input(_var.tensor()); |
| node_ctx.add_input(_beta.tensor()); |
| node_ctx.add_input(_gamma.tensor()); |
| node_ctx.add_output(out); |
| node_ctx.add_parameter<float>("epsilon", _epsilon); |
| node_ctx.add_parameter<ActivationLayerInfo>("act_info", _act_info); |
| |
| // Configure operation |
| auto func = OperationRegistry::get().find_operation(OperationType::BatchNormalizationLayer, _target_hint)->configure(node_ctx); |
| |
| // Fill tensors |
| if(!mean_is_loaded) |
| { |
| _mean.allocate_and_fill_if_needed(); |
| } |
| if(!var_is_loaded) |
| { |
| _var.allocate_and_fill_if_needed(); |
| } |
| if(!gamma_is_loaded) |
| { |
| _gamma.allocate_and_fill_if_needed(); |
| } |
| if(!beta_is_loaded) |
| { |
| _beta.allocate_and_fill_if_needed(); |
| } |
| |
| // Get function |
| return func; |
| } |