| /* |
| * 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/FullyConnectedLayer.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; |
| |
| namespace |
| { |
| TensorShape calculate_fullyconnected_layer_output_shape(const TensorShape &input_shape, unsigned int output_neurons) |
| { |
| // Note: Only 1D batch space is supported at the moment |
| unsigned int batches = input_shape[1]; |
| if(input_shape.num_dimensions() > 2) |
| { |
| batches = input_shape[3]; |
| } |
| return TensorShape(output_neurons, batches); |
| } |
| } // namespace |
| |
| std::unique_ptr<arm_compute::IFunction> FullyConnectedLayer::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(); |
| |
| if(_weights.tensor() == nullptr) |
| { |
| unsigned int num_weights = 1; |
| unsigned int num_dimensions = in->info()->num_dimensions(); |
| // Ignore the batch dimension if there is one: |
| if(num_dimensions == 2 || num_dimensions == 4) |
| { |
| num_dimensions--; |
| } |
| for(unsigned int i = 0; i < num_dimensions; i++) |
| { |
| num_weights *= in->info()->dimension(i); |
| } |
| _weights.set_info(TensorInfo(TensorShape(num_weights, _num_neurons), in->info()->num_channels(), in->info()->data_type(), in->info()->fixed_point_position())); |
| } |
| if(_biases.tensor() == nullptr) |
| { |
| _biases.set_info(TensorInfo(TensorShape(_num_neurons), in->info()->num_channels(), in->info()->data_type(), in->info()->fixed_point_position())); |
| } |
| |
| // Auto configure output |
| arm_compute::auto_init_if_empty(*out->info(), |
| calculate_fullyconnected_layer_output_shape(in->info()->tensor_shape(), _num_neurons), |
| in->info()->num_channels(), in->info()->data_type(), in->info()->fixed_point_position()); |
| |
| bool weights_are_loaded = _weights.tensor() != nullptr; |
| bool biases_are_loaded = _biases.tensor() != nullptr; |
| |
| // Create node context |
| NodeContext node_ctx(OperationType::FullyConnectedLayer); |
| node_ctx.set_target(_target_hint); |
| node_ctx.add_input(in); |
| node_ctx.add_input(_weights.set_target(_target_hint)); |
| node_ctx.add_input(_biases.set_target(_target_hint)); |
| node_ctx.add_output(out); |
| |
| // Fill biases |
| if(!weights_are_loaded) |
| { |
| _weights.allocate_and_fill_if_needed(); |
| } |
| if(!biases_are_loaded) |
| { |
| _biases.allocate_and_fill_if_needed(); |
| } |
| |
| // Get function |
| return OperationRegistry::get().find_operation(OperationType::FullyConnectedLayer, _target_hint)->configure(node_ctx); |
| } |