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Diffstat (limited to 'src/graph2/GraphBuilder.cpp')
| -rw-r--r-- | src/graph2/GraphBuilder.cpp | 394 |
1 files changed, 0 insertions, 394 deletions
diff --git a/src/graph2/GraphBuilder.cpp b/src/graph2/GraphBuilder.cpp deleted file mode 100644 index e6fc2afe21..0000000000 --- a/src/graph2/GraphBuilder.cpp +++ /dev/null @@ -1,394 +0,0 @@ -/* - * Copyright (c) 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/graph2/GraphBuilder.h" - -#include "arm_compute/graph2/Graph.h" -#include "arm_compute/graph2/Utils.h" -#include "arm_compute/graph2/algorithms/BFS.h" -#include "arm_compute/graph2/nodes/Nodes.h" - -#define CHECK_NODEIDX_PAIR(pair, g) \ - ARM_COMPUTE_ERROR_ON(((pair).node_id >= (g).nodes().size()) || ((g).node((pair).node_id) == nullptr) || ((pair).index >= (g).node((pair).node_id)->num_outputs())); - -namespace arm_compute -{ -namespace graph2 -{ -namespace -{ -Status set_node_params(Graph &g, NodeID nid, NodeParams ¶ms) -{ - INode *node = g.node(nid); - ARM_COMPUTE_RETURN_ERROR_ON(!node); - - node->set_common_node_parameters(params); - - return Status{}; -} - -Status set_accessor_on_node(Graph &g, NodeID nid, bool is_output, size_t idx, ITensorAccessorUPtr accessor) -{ - INode *node = g.node(nid); - ARM_COMPUTE_RETURN_ERROR_ON(!node); - - Tensor *tensor = is_output ? node->output(idx) : node->input(idx); - ARM_COMPUTE_RETURN_ERROR_ON(!tensor); - - tensor->set_accessor(std::move(accessor)); - - return Status{}; -} - -NodeID add_const_node_with_name(Graph &g, NodeParams params, const std::string &name, TensorDescriptor desc, ITensorAccessorUPtr accessor) -{ - params.name = params.name.empty() ? "" : params.name + name; - auto nid = GraphBuilder::add_const_node(g, params, desc, std::move(accessor)); - set_node_params(g, nid, params); - return nid; -} - -template <typename NT, typename... Args> -NodeID create_simple_single_input_output_node(Graph &g, NodeParams ¶ms, NodeIdxPair input, Args &&... args) -{ - CHECK_NODEIDX_PAIR(input, g); - - NodeID nid = g.add_node<NT>(std::forward<Args>(args)...); - g.add_connection(input.node_id, input.index, nid, 0); - set_node_params(g, nid, params); - - return nid; -} - -NodeID create_grouped_convolution(Graph &g, NodeParams ¶ms, NodeIdxPair input, NodeID weights, NodeID bias, - PadStrideInfo conv_info, ConvolutionMethod method, unsigned int num_groups) -{ - bool has_bias = (bias != EmptyNodeID); - - // Split input - NodeID input_split = GraphBuilder::add_split_node(g, params, input, num_groups, 2); - - // Split weights - NodeID weights_split = GraphBuilder::add_split_node(g, params, { weights, 0 }, num_groups, 3); - - // Split bias - NodeID bias_split = EmptyNodeID; - if(has_bias) - { - // Split bias - bias_split = GraphBuilder::add_split_node(g, params, { bias, 0 }, num_groups, 0); - } - - std::vector<NodeIdxPair> convolution_outputs; - for(unsigned int i = 0; i < num_groups; ++i) - { - NodeID conv_nid = g.add_node<ConvolutionLayerNode>(conv_info, method); - g.add_connection(input_split, i, conv_nid, 0); - g.add_connection(weights_split, i, conv_nid, 1); - if(has_bias) - { - g.add_connection(bias_split, i, conv_nid, 2); - } - set_node_params(g, conv_nid, params); - convolution_outputs.push_back({ conv_nid, 0 }); - } - - // Depth concatenate output - return GraphBuilder::add_depth_concatenate_node(g, params, convolution_outputs); -} -} // namespace - -NodeID GraphBuilder::add_const_node(Graph &g, NodeParams params, TensorDescriptor desc, ITensorAccessorUPtr accessor) -{ - auto nid = g.add_node<ConstNode>(desc); - set_node_params(g, nid, params); - set_accessor_on_node(g, nid, true, 0, std::move(accessor)); - return nid; -} - -NodeID GraphBuilder::add_input_node(Graph &g, NodeParams params, TensorDescriptor desc, ITensorAccessorUPtr accessor) -{ - auto nid = g.add_node<InputNode>(desc); - set_node_params(g, nid, params); - set_accessor_on_node(g, nid, true, 0, std::move(accessor)); - return nid; -} - -NodeID GraphBuilder::add_output_node(Graph &g, NodeParams params, NodeIdxPair input, ITensorAccessorUPtr accessor) -{ - CHECK_NODEIDX_PAIR(input, g); - - NodeID nid = g.add_node<OutputNode>(); - g.add_connection(input.node_id, input.index, nid, 0); - set_node_params(g, nid, params); - set_accessor_on_node(g, nid, false, 0, std::move(accessor)); - - return nid; -} - -NodeID GraphBuilder::add_activation_node(Graph &g, NodeParams params, NodeIdxPair input, ActivationLayerInfo act_info) -{ - return create_simple_single_input_output_node<ActivationLayerNode>(g, params, input, act_info); -} - -NodeID GraphBuilder::add_batch_normalization_node(Graph &g, NodeParams params, NodeIdxPair input, float epsilon, - ITensorAccessorUPtr mean_accessor, ITensorAccessorUPtr var_accessor, - ITensorAccessorUPtr beta_accessor, ITensorAccessorUPtr gamma_accessor) -{ - CHECK_NODEIDX_PAIR(input, g); - - bool has_beta = (beta_accessor != nullptr); - bool has_gamma = (gamma_accessor != nullptr); - - // Get input tensor descriptor - const TensorDescriptor input_tensor_desc = get_tensor_descriptor(g, g.node(input.node_id)->outputs()[0]); - - // Calculate Common Descriptor - TensorDescriptor common_desc = input_tensor_desc; - common_desc.shape = TensorShape(common_desc.shape.z()); - - // Create mean and nodes - auto mean_nid = add_const_node_with_name(g, params, "Mean", common_desc, std::move(mean_accessor)); - auto var_nid = add_const_node_with_name(g, params, "Variance", common_desc, std::move(var_accessor)); - - // Create beta node - NodeID beta_nid = EmptyNodeID; - if(has_beta) - { - beta_nid = add_const_node_with_name(g, params, "Beta", common_desc, std::move(beta_accessor)); - } - - // Create gamma node - NodeID gamma_nid = EmptyNodeID; - if(has_gamma) - { - gamma_nid = add_const_node_with_name(g, params, "Gamma", common_desc, std::move(gamma_accessor)); - } - - // Create batch normalization node and add connections - NodeID batch_norm_nid = g.add_node<BatchNormalizationLayerNode>(epsilon); - g.add_connection(input.node_id, input.index, batch_norm_nid, 0); - g.add_connection(mean_nid, 0, batch_norm_nid, 1); - g.add_connection(var_nid, 0, batch_norm_nid, 2); - if(has_beta) - { - g.add_connection(beta_nid, 0, batch_norm_nid, 3); - } - if(has_gamma) - { - g.add_connection(gamma_nid, 0, batch_norm_nid, 4); - } - set_node_params(g, batch_norm_nid, params); - - return batch_norm_nid; -} - -NodeID GraphBuilder::add_convolution_node(Graph &g, NodeParams params, NodeIdxPair input, - Size2D kernel_spatial_extend, unsigned int depth, PadStrideInfo conv_info, - unsigned int num_groups, ConvolutionMethod method, - ITensorAccessorUPtr weights_accessor, ITensorAccessorUPtr bias_accessor) -{ - CHECK_NODEIDX_PAIR(input, g); - ARM_COMPUTE_ERROR_ON(depth == 0); - ARM_COMPUTE_ERROR_ON((kernel_spatial_extend.width == 0) || (kernel_spatial_extend.height == 0)); - - bool has_bias = (bias_accessor != nullptr); - - // Get input tensor descriptor - const TensorDescriptor input_tensor_desc = get_tensor_descriptor(g, g.node(input.node_id)->outputs()[0]); - - // Create weights node - TensorDescriptor w_desc = input_tensor_desc; - w_desc.shape = TensorShape(kernel_spatial_extend.width, kernel_spatial_extend.height, w_desc.shape.z() / num_groups, depth); - NodeID w_nid = add_const_node_with_name(g, params, "Weights", w_desc, std::move(weights_accessor)); - - // Create bias nodes - NodeID b_nid = EmptyNodeID; - if(has_bias) - { - TensorDescriptor b_desc = input_tensor_desc; - b_desc.shape = TensorShape(depth); - b_nid = add_const_node_with_name(g, params, "Bias", b_desc, std::move(bias_accessor)); - } - - if(num_groups == 1) - { - // Create convolution node and connect - NodeID conv_nid = g.add_node<ConvolutionLayerNode>(conv_info, method); - g.add_connection(input.node_id, input.index, conv_nid, 0); - g.add_connection(w_nid, 0, conv_nid, 1); - if(has_bias) - { - g.add_connection(b_nid, 0, conv_nid, 2); - } - set_node_params(g, conv_nid, params); - - return conv_nid; - } - else - { - return create_grouped_convolution(g, params, input, w_nid, b_nid, conv_info, method, num_groups); - } -} - -NodeID GraphBuilder::add_depth_concatenate_node(Graph &g, NodeParams params, std::vector<NodeIdxPair> inputs) -{ - ARM_COMPUTE_ERROR_ON(inputs.size() == 0); - - NodeID nid = g.add_node<DepthConcatenateLayerNode>(inputs.size()); - - unsigned int i = 0; - for(const auto &input : inputs) - { - CHECK_NODEIDX_PAIR(input, g); - g.add_connection(input.node_id, input.index, nid, i++); - } - set_node_params(g, nid, params); - - return nid; -} - -NodeID GraphBuilder::add_depthwise_convolution_node(Graph &g, NodeParams params, NodeIdxPair input, Size2D kernel_spatial_extend, PadStrideInfo conv_info, - DepthwiseConvolutionMethod method, - ITensorAccessorUPtr weights_accessor, ITensorAccessorUPtr bias_accessor) -{ - CHECK_NODEIDX_PAIR(input, g); - ARM_COMPUTE_ERROR_ON((kernel_spatial_extend.width == 0) || (kernel_spatial_extend.height == 0)); - - bool has_bias = (bias_accessor != nullptr); - - // Get input tensor descriptor - const TensorDescriptor input_tensor_desc = get_tensor_descriptor(g, g.node(input.node_id)->outputs()[0]); - - // Create weights node - TensorDescriptor w_desc = input_tensor_desc; - w_desc.shape = TensorShape(kernel_spatial_extend.width, kernel_spatial_extend.height, w_desc.shape.z()); - NodeID w_nid = add_const_node_with_name(g, params, "Weights", w_desc, std::move(weights_accessor)); - - // Create bias nodes - NodeID b_nid = EmptyNodeID; - if(has_bias) - { - TensorDescriptor b_desc = input_tensor_desc; - b_desc.shape = TensorShape(b_desc.shape.z()); - b_nid = add_const_node_with_name(g, params, "Bias", b_desc, std::move(bias_accessor)); - } - - // Create convolution node and connect - NodeID conv_nid = g.add_node<DepthwiseConvolutionLayerNode>(conv_info, method); - g.add_connection(input.node_id, input.index, conv_nid, 0); - g.add_connection(w_nid, 0, conv_nid, 1); - if(has_bias) - { - g.add_connection(b_nid, 0, conv_nid, 2); - } - set_node_params(g, conv_nid, params); - - return conv_nid; -} - -NodeID GraphBuilder::add_elementwise_node(Graph &g, NodeParams params, NodeIdxPair input0, NodeIdxPair input1, EltwiseOperation operation) -{ - CHECK_NODEIDX_PAIR(input0, g); - CHECK_NODEIDX_PAIR(input1, g); - - NodeID nid = g.add_node<EltwiseLayerNode>(operation); - - g.add_connection(input0.node_id, input0.index, nid, 0); - g.add_connection(input1.node_id, input1.index, nid, 1); - - set_node_params(g, nid, params); - - return nid; -} - -NodeID GraphBuilder::add_flatten_node(Graph &g, NodeParams params, NodeIdxPair input) -{ - return create_simple_single_input_output_node<FlattenLayerNode>(g, params, input); -} - -NodeID GraphBuilder::add_fully_connected_layer(Graph &g, NodeParams params, NodeIdxPair input, unsigned int num_outputs, - ITensorAccessorUPtr weights_accessor, ITensorAccessorUPtr bias_accessor) -{ - CHECK_NODEIDX_PAIR(input, g); - ARM_COMPUTE_ERROR_ON(num_outputs == 0); - - bool has_bias = (bias_accessor != nullptr); - - // Get input tensor descriptor - const TensorDescriptor input_tensor_desc = get_tensor_descriptor(g, g.node(input.node_id)->outputs()[0]); - - // Create weights node - TensorDescriptor w_desc = input_tensor_desc; - w_desc.shape = FullyConnectedLayerNode::compute_weights_shape(input_tensor_desc.shape, num_outputs); - NodeID w_nid = add_const_node_with_name(g, params, "Weights", w_desc, std::move(weights_accessor)); - - // Create bias nodes - NodeID b_nid = EmptyNodeID; - if(has_bias) - { - TensorDescriptor b_desc = input_tensor_desc; - b_desc.shape = TensorShape(num_outputs); - b_nid = add_const_node_with_name(g, params, "Bias", b_desc, std::move(bias_accessor)); - } - - // Create convolution node and connect - NodeID fc_nid = g.add_node<FullyConnectedLayerNode>(num_outputs); - g.add_connection(input.node_id, input.index, fc_nid, 0); - g.add_connection(w_nid, 0, fc_nid, 1); - if(has_bias) - { - g.add_connection(b_nid, 0, fc_nid, 2); - } - - set_node_params(g, fc_nid, params); - - return fc_nid; -} - -NodeID GraphBuilder::add_normalization_node(Graph &g, NodeParams params, NodeIdxPair input, NormalizationLayerInfo norm_info) -{ - return create_simple_single_input_output_node<NormalizationLayerNode>(g, params, input, norm_info); -} - -NodeID GraphBuilder::add_pooling_node(Graph &g, NodeParams params, NodeIdxPair input, PoolingLayerInfo pool_info) -{ - return create_simple_single_input_output_node<PoolingLayerNode>(g, params, input, pool_info); -} - -NodeID GraphBuilder::add_reshape_node(Graph &g, NodeParams params, NodeIdxPair input, TensorShape shape) -{ - return create_simple_single_input_output_node<ReshapeLayerNode>(g, params, input, shape); -} - -NodeID GraphBuilder::add_softmax_node(Graph &g, NodeParams params, NodeIdxPair input, float beta) -{ - return create_simple_single_input_output_node<SoftmaxLayerNode>(g, params, input, beta); -} - -NodeID GraphBuilder::add_split_node(Graph &g, NodeParams params, NodeIdxPair input, unsigned int num_splits, unsigned int axis) -{ - return create_simple_single_input_output_node<SplitLayerNode>(g, params, input, num_splits, axis); -} -} // namespace graph2 -} // namespace arm_compute
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