From bffb41e06c1276af00e1605ef934d05fa61f7127 Mon Sep 17 00:00:00 2001 From: Manuel Bottini Date: Thu, 20 Jun 2019 16:00:27 +0100 Subject: COMPMID-2273: Fuse Batch Normalization with Depthwise Convolution layer at graph level (only for CL) Change-Id: I1d941c6e66722f39583bf68148c980bb28ff89a1 Signed-off-by: Manuel Bottini Reviewed-on: https://review.mlplatform.org/c/1423 Comments-Addressed: Arm Jenkins Reviewed-by: Michele Di Giorgio Tested-by: Arm Jenkins --- src/graph/backends/CL/CLFunctionsFactory.cpp | 7 +- src/graph/backends/NEON/NEFunctionFactory.cpp | 5 +- src/graph/mutators/NodeFusionMutator.cpp | 87 ++++++++++++- .../FusedConvolutionBatchNormalizationNode.cpp | 8 +- ...dDepthwiseConvolutionBatchNormalizationNode.cpp | 140 +++++++++++++++++++++ src/graph/printers/DotGraphPrinter.cpp | 8 ++ 6 files changed, 243 insertions(+), 12 deletions(-) create mode 100644 src/graph/nodes/FusedDepthwiseConvolutionBatchNormalizationNode.cpp (limited to 'src/graph') diff --git a/src/graph/backends/CL/CLFunctionsFactory.cpp b/src/graph/backends/CL/CLFunctionsFactory.cpp index c14100ab42..b9f22f6199 100644 --- a/src/graph/backends/CL/CLFunctionsFactory.cpp +++ b/src/graph/backends/CL/CLFunctionsFactory.cpp @@ -74,8 +74,9 @@ struct CLEltwiseFunctions /** Function and tensor types to be used inside a CL fused convolution/batch normalization layer */ struct CLFusedLayerTypes { - using ConvolutionLayer = CLConvolutionLayer; - using FuseBatchNormalization = CLFuseBatchNormalization; + using ConvolutionLayer = CLConvolutionLayer; + using DepthwiseConvolutionLayer = CLDepthwiseConvolutionLayer; + using FuseBatchNormalization = CLFuseBatchNormalization; }; // TODO (isagot01): Remove once we support heterogeneous scheduling at function level @@ -203,6 +204,8 @@ std::unique_ptr CLFunctionFactory::create(INode *node, GraphContext & return detail::create_fully_connected_layer(*polymorphic_downcast(node), ctx); case NodeType::FusedConvolutionBatchNormalizationLayer: return detail::create_fused_convolution_batch_normalization_layer(*polymorphic_downcast(node)); + case NodeType::FusedDepthwiseConvolutionBatchNormalizationLayer: + return detail::create_fused_depthwise_convolution_batch_normalization_layer(*polymorphic_downcast(node)); case NodeType::GenerateProposalsLayer: return detail::create_generate_proposals_layer(*polymorphic_downcast(node), ctx); case NodeType::NormalizationLayer: diff --git a/src/graph/backends/NEON/NEFunctionFactory.cpp b/src/graph/backends/NEON/NEFunctionFactory.cpp index d4892f53a6..ad96240a4b 100644 --- a/src/graph/backends/NEON/NEFunctionFactory.cpp +++ b/src/graph/backends/NEON/NEFunctionFactory.cpp @@ -80,8 +80,9 @@ struct NEEltwiseFunctions /** Function and tensor types to be used inside a NEON fused convolution/batch normalization layer */ struct NEFusedLayerTypes { - using ConvolutionLayer = NEConvolutionLayer; - using FuseBatchNormalization = NEFuseBatchNormalization; + using ConvolutionLayer = NEConvolutionLayer; + using DepthwiseConvolutionLayer = NEDepthwiseConvolutionLayer; + using FuseBatchNormalization = NEFuseBatchNormalization; }; namespace detail diff --git a/src/graph/mutators/NodeFusionMutator.cpp b/src/graph/mutators/NodeFusionMutator.cpp index 427d7b5095..83177a8431 100644 --- a/src/graph/mutators/NodeFusionMutator.cpp +++ b/src/graph/mutators/NodeFusionMutator.cpp @@ -64,7 +64,6 @@ void fuse_convolution_with_batch_normalization(Graph &g, const Edge *output_edge // Extract conv inputs const auto conv_input_id = conv_node->input_edge(0)->producer_id(); const auto conv_weights_id = conv_node->input_edge(1)->producer_id(); - const auto out_quant_info = conv_node->output(0)->desc().quant_info; const auto conv_info = conv_node->convolution_info(); const auto conv_method = conv_node->convolution_method(); const auto num_groups = conv_node->num_groups(); @@ -79,7 +78,7 @@ void fuse_convolution_with_batch_normalization(Graph &g, const Edge *output_edge const auto epsilon = bn_node->epsilon(); // Create the fused node - const NodeID fused_id = g.add_node(epsilon, conv_info, num_groups, conv_method, fast_math_hint, out_quant_info, act_info); + const NodeID fused_id = g.add_node(epsilon, conv_info, num_groups, conv_method, fast_math_hint, act_info); if(conv_node->input_edge(2) != nullptr) { @@ -125,6 +124,83 @@ void fuse_convolution_with_batch_normalization(Graph &g, const Edge *output_edge } } +void fuse_depthwise_convolution_with_batch_normalization(Graph &g, const Edge *output_edge) +{ + ARM_COMPUTE_ERROR_ON(output_edge == nullptr); + + auto *depth_conv_node = arm_compute::utils::cast::polymorphic_downcast(output_edge->producer()); + auto *bn_node = arm_compute::utils::cast::polymorphic_downcast(output_edge->consumer()); + + ARM_COMPUTE_LOG_GRAPH_VERBOSE("Fusing depthwise convolution node with ID : " << output_edge->producer_id() + << " with BatchNormalization Layer node with ID : " << output_edge->consumer_id() << std::endl); + + // Prevent fusion if fused node has an output accessor + if(depth_conv_node->output(0)->accessor() == nullptr) + { + const Target assigned_target = depth_conv_node->assigned_target(); + + // Extract conv inputs + const auto depth_conv_input_id = depth_conv_node->input_edge(0)->producer_id(); + const auto conv_weights_id = depth_conv_node->input_edge(1)->producer_id(); + const auto conv_info = depth_conv_node->convolution_info(); + const auto depth_conv_method = depth_conv_node->depthwise_convolution_method(); + const auto depth_multiplier = depth_conv_node->depth_multiplier(); + const auto act_info = bn_node->fused_activation(); + + // Extract bn inputs + const auto bn_mean_id = bn_node->input_edge(1)->producer_id(); + const auto bn_var_id = bn_node->input_edge(2)->producer_id(); + const auto bn_beta_id = bn_node->input_edge(3)->producer_id(); + const auto bn_gamma_id = bn_node->input_edge(4)->producer_id(); + const auto epsilon = bn_node->epsilon(); + + // Create the fused node + const NodeID fused_id = g.add_node(epsilon, conv_info, depth_multiplier, depth_conv_method, act_info); + + if(depth_conv_node->input_edge(2) != nullptr) + { + const auto conv_bias_id = depth_conv_node->input_edge(2)->producer_id(); + g.add_connection(conv_bias_id, 0, fused_id, 2); + } + + // Add connections from the conv/batch_norm inputs to the fused node + g.add_connection(depth_conv_input_id, 0, fused_id, 0); + g.add_connection(conv_weights_id, 0, fused_id, 1); + g.add_connection(bn_mean_id, 0, fused_id, 3); + g.add_connection(bn_var_id, 0, fused_id, 4); + g.add_connection(bn_beta_id, 0, fused_id, 5); + g.add_connection(bn_gamma_id, 0, fused_id, 6); + + auto fused_node = g.node(fused_id); + std::vector bn_driving_nodes = get_driving_nodes(*bn_node); + + // Extract batch normalization node accessor if any + auto bn_node_accessor = bn_node->output(0)->extract_accessor(); + auto bn_node_name = bn_node->name(); + + // Remove batch normalization node + g.remove_node(bn_node->id()); + + // Get driving nodes of batch normalization node + for(auto &driving_node : bn_driving_nodes) + { + g.add_connection(fused_id, 0, driving_node.node_id, driving_node.index); + configure_tensor(fused_node->output(0)); + } + // Update fused node outputs + fused_node->output(0)->set_accessor(std::move(bn_node_accessor)); + fused_node->set_assigned_target(assigned_target); + fused_node->set_common_node_parameters(NodeParams{ depth_conv_node->name() + "+" + bn_node_name, assigned_target }); + + // Remove convolution node + g.remove_node(depth_conv_node->id()); + } + else + { + ARM_COMPUTE_LOG_GRAPH_VERBOSE("Prevented fusion of depthwise convolution with batch normalization due to the presence of an output accessor\n"); + } +} + template void fuse_node_with_activation(Graph &g, const Edge *output_edge, const std::set &supported_fused_activations) { @@ -224,6 +300,8 @@ void NodeFusionMutator::mutate(Graph &g) return (output_qasymm8 && same_qinfo) || !output_qasymm8; }; + Target target = g.nodes()[0].get()->output(0)->desc().target; + // Fusion mutations detail::fuse_layer(g, empty_prec, detail::fuse_node_with_activation, supported_fused_activations); detail::fuse_layer(g, empty_prec, detail::fuse_node_with_activation, supported_fused_activations); @@ -231,6 +309,11 @@ void NodeFusionMutator::mutate(Graph &g) // TODO (COMPMID-2055): re-enable once we fuse bias and activations to convolution // detail::fuse_layer(g, empty_prec, detail::fuse_convolution_with_batch_normalization); + if(target == Target::CL) + { + //Depthwise Convolution and Batch Normalization Fusion active only for CL + detail::fuse_layer(g, empty_prec, detail::fuse_depthwise_convolution_with_batch_normalization); + } } } // namespace graph } // namespace arm_compute diff --git a/src/graph/nodes/FusedConvolutionBatchNormalizationNode.cpp b/src/graph/nodes/FusedConvolutionBatchNormalizationNode.cpp index 6496a71251..0a0c0c50e8 100644 --- a/src/graph/nodes/FusedConvolutionBatchNormalizationNode.cpp +++ b/src/graph/nodes/FusedConvolutionBatchNormalizationNode.cpp @@ -36,8 +36,8 @@ FusedConvolutionBatchNormalizationNode::FusedConvolutionBatchNormalizationNode(f unsigned int num_groups, ConvolutionMethod method, FastMathHint fast_math_hint, - QuantizationInfo out_quant_info, ActivationLayerInfo fused_activation) - : _epsilon(epsilon), _info(std::move(info)), _num_groups(num_groups), _method(method), _fast_math_hint(fast_math_hint), _out_quant_info(std::move(out_quant_info)), _fused_activation(fused_activation) + ActivationLayerInfo fused_activation) + : _epsilon(epsilon), _info(std::move(info)), _num_groups(num_groups), _method(method), _fast_math_hint(fast_math_hint), _fused_activation(fused_activation) { _input_edges.resize(7, EmptyEdgeID); _outputs.resize(1, NullTensorID); @@ -132,10 +132,6 @@ TensorDescriptor FusedConvolutionBatchNormalizationNode::configure_output(size_t ARM_COMPUTE_ERROR_ON(src == nullptr || weights == nullptr); TensorDescriptor output_info = compute_output_descriptor(src->desc(), weights->desc(), _info); - if(!_out_quant_info.empty()) - { - output_info.quant_info = _out_quant_info; - } return output_info; } diff --git a/src/graph/nodes/FusedDepthwiseConvolutionBatchNormalizationNode.cpp b/src/graph/nodes/FusedDepthwiseConvolutionBatchNormalizationNode.cpp new file mode 100644 index 0000000000..a04d75407a --- /dev/null +++ b/src/graph/nodes/FusedDepthwiseConvolutionBatchNormalizationNode.cpp @@ -0,0 +1,140 @@ +/* + * Copyright (c) 2019 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/FusedDepthwiseConvolutionBatchNormalizationNode.h" + +#include "arm_compute/core/Utils.h" +#include "arm_compute/graph/Graph.h" +#include "arm_compute/graph/INodeVisitor.h" +#include "arm_compute/graph/Utils.h" + +namespace arm_compute +{ +namespace graph +{ +FusedDepthwiseConvolutionBatchNormalizationNode::FusedDepthwiseConvolutionBatchNormalizationNode(float epsilon, + PadStrideInfo info, + unsigned int depth_multiplier, + DepthwiseConvolutionMethod method, + ActivationLayerInfo fused_activation) + : _epsilon(epsilon), _info(std::move(info)), _depth_multiplier(depth_multiplier), _method(method), _fused_activation(fused_activation) +{ + _input_edges.resize(7, EmptyEdgeID); + _outputs.resize(1, NullTensorID); +} + +void FusedDepthwiseConvolutionBatchNormalizationNode::set_depthwise_convolution_method(DepthwiseConvolutionMethod method) +{ + _method = method; +} + +DepthwiseConvolutionMethod FusedDepthwiseConvolutionBatchNormalizationNode::depthwise_convolution_method() const +{ + return _method; +} + +float FusedDepthwiseConvolutionBatchNormalizationNode::epsilon() const +{ + return _epsilon; +} + +PadStrideInfo FusedDepthwiseConvolutionBatchNormalizationNode::convolution_info() const +{ + return _info; +} + +unsigned int FusedDepthwiseConvolutionBatchNormalizationNode::depth_multiplier() const +{ + return _depth_multiplier; +} + +ActivationLayerInfo FusedDepthwiseConvolutionBatchNormalizationNode::fused_activation() const +{ + return _fused_activation; +} + +void FusedDepthwiseConvolutionBatchNormalizationNode::set_fused_activation(ActivationLayerInfo fused_activation) +{ + _fused_activation = fused_activation; +} + +TensorDescriptor FusedDepthwiseConvolutionBatchNormalizationNode::compute_output_descriptor(const TensorDescriptor &input_descriptor, + const TensorDescriptor &weights_descriptor, + const PadStrideInfo &info, + int depth_multiplier) +{ + unsigned int output_width = 0; + unsigned int output_height = 0; + + const unsigned int input_width = get_dimension_size(input_descriptor, DataLayoutDimension::WIDTH); + const unsigned int input_height = get_dimension_size(input_descriptor, DataLayoutDimension::HEIGHT); + const unsigned int input_channels = get_dimension_size(input_descriptor, DataLayoutDimension::CHANNEL); + const unsigned int kernel_width = get_dimension_size(weights_descriptor, DataLayoutDimension::WIDTH); + const unsigned int kernel_height = get_dimension_size(weights_descriptor, DataLayoutDimension::HEIGHT); + + std::tie(output_width, output_height) = scaled_dimensions(input_width, input_height, kernel_width, kernel_height, info); + + TensorDescriptor output_descriptor = input_descriptor; + output_descriptor.shape.set(get_dimension_idx(output_descriptor.layout, DataLayoutDimension::WIDTH), output_width); + output_descriptor.shape.set(get_dimension_idx(output_descriptor.layout, DataLayoutDimension::HEIGHT), output_height); + output_descriptor.shape.set(get_dimension_idx(output_descriptor.layout, DataLayoutDimension::CHANNEL), input_channels * depth_multiplier); + + return output_descriptor; +} + +bool FusedDepthwiseConvolutionBatchNormalizationNode::forward_descriptors() +{ + if((input_id(0) != NullTensorID) && (input_id(1) != NullTensorID) && (output_id(0) != NullTensorID)) + { + Tensor *dst = output(0); + ARM_COMPUTE_ERROR_ON(dst == nullptr); + dst->desc() = configure_output(0); + return true; + } + return false; +} + +TensorDescriptor FusedDepthwiseConvolutionBatchNormalizationNode::configure_output(size_t idx) const +{ + ARM_COMPUTE_UNUSED(idx); + const Tensor *src = input(0); + const Tensor *weights = input(1); + + ARM_COMPUTE_ERROR_ON(src == nullptr || weights == nullptr); + + TensorDescriptor output_info = compute_output_descriptor(src->desc(), weights->desc(), _info, _depth_multiplier); + + return output_info; +} + +NodeType FusedDepthwiseConvolutionBatchNormalizationNode::type() const +{ + return FusedDepthwiseConvolutionBatchNormalizationNode::node_type; +} + +void FusedDepthwiseConvolutionBatchNormalizationNode::accept(INodeVisitor &v) +{ + v.visit(*this); +} +} // namespace graph +} // namespace arm_compute diff --git a/src/graph/printers/DotGraphPrinter.cpp b/src/graph/printers/DotGraphPrinter.cpp index c939de1b64..46f6ee828e 100644 --- a/src/graph/printers/DotGraphPrinter.cpp +++ b/src/graph/printers/DotGraphPrinter.cpp @@ -85,6 +85,14 @@ void DotGraphVisitor::visit(FusedConvolutionBatchNormalizationNode &n) _info = ss.str(); } +void DotGraphVisitor::visit(FusedDepthwiseConvolutionBatchNormalizationNode &n) +{ + ARM_COMPUTE_UNUSED(n); + std::stringstream ss; + ss << "FusedDepthwiseConvolutionBatchNormalizationNode"; + _info = ss.str(); +} + void DotGraphVisitor::visit(NormalizationLayerNode &n) { std::stringstream ss; -- cgit v1.2.1