COMPMID-2273: Fuse Batch Normalization with Depthwise Convolution layer at graph level (only for CL)
Change-Id: I1d941c6e66722f39583bf68148c980bb28ff89a1
Signed-off-by: Manuel Bottini <manuel.bottini@arm.com>
Reviewed-on: https://review.mlplatform.org/c/1423
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
diff --git a/src/graph/backends/CL/CLFunctionsFactory.cpp b/src/graph/backends/CL/CLFunctionsFactory.cpp
index c14100a..b9f22f6 100644
--- a/src/graph/backends/CL/CLFunctionsFactory.cpp
+++ b/src/graph/backends/CL/CLFunctionsFactory.cpp
@@ -74,8 +74,9 @@
/** 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 @@
return detail::create_fully_connected_layer<CLFullyConnectedLayer, CLTargetInfo>(*polymorphic_downcast<FullyConnectedLayerNode *>(node), ctx);
case NodeType::FusedConvolutionBatchNormalizationLayer:
return detail::create_fused_convolution_batch_normalization_layer<CLFusedLayerTypes, CLTargetInfo>(*polymorphic_downcast<FusedConvolutionBatchNormalizationNode *>(node));
+ case NodeType::FusedDepthwiseConvolutionBatchNormalizationLayer:
+ return detail::create_fused_depthwise_convolution_batch_normalization_layer<CLFusedLayerTypes, CLTargetInfo>(*polymorphic_downcast<FusedDepthwiseConvolutionBatchNormalizationNode *>(node));
case NodeType::GenerateProposalsLayer:
return detail::create_generate_proposals_layer<CLGenerateProposalsLayer, CLTargetInfo>(*polymorphic_downcast<GenerateProposalsLayerNode *>(node), ctx);
case NodeType::NormalizationLayer:
diff --git a/src/graph/backends/NEON/NEFunctionFactory.cpp b/src/graph/backends/NEON/NEFunctionFactory.cpp
index d4892f5..ad96240 100644
--- a/src/graph/backends/NEON/NEFunctionFactory.cpp
+++ b/src/graph/backends/NEON/NEFunctionFactory.cpp
@@ -80,8 +80,9 @@
/** 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 427d7b5..83177a8 100644
--- a/src/graph/mutators/NodeFusionMutator.cpp
+++ b/src/graph/mutators/NodeFusionMutator.cpp
@@ -64,7 +64,6 @@
// 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 @@
const auto epsilon = bn_node->epsilon();
// Create the fused node
- const NodeID fused_id = g.add_node<FusedConvolutionBatchNormalizationNode>(epsilon, conv_info, num_groups, conv_method, fast_math_hint, out_quant_info, act_info);
+ const NodeID fused_id = g.add_node<FusedConvolutionBatchNormalizationNode>(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_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<DepthwiseConvolutionLayerNode *>(output_edge->producer());
+ auto *bn_node = arm_compute::utils::cast::polymorphic_downcast<BatchNormalizationLayerNode *>(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<FusedDepthwiseConvolutionBatchNormalizationNode>(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<NodeIdxPair> 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 <typename N>
void fuse_node_with_activation(Graph &g, const Edge *output_edge, const std::set<Activation> &supported_fused_activations)
{
@@ -224,6 +300,8 @@
return (output_qasymm8 && same_qinfo) || !output_qasymm8;
};
+ Target target = g.nodes()[0].get()->output(0)->desc().target;
+
// Fusion mutations
detail::fuse_layer<BatchNormalizationLayerNode, ActivationLayerNode>(g, empty_prec, detail::fuse_node_with_activation<BatchNormalizationLayerNode>, supported_fused_activations);
detail::fuse_layer<ConvolutionLayerNode, ActivationLayerNode>(g, empty_prec, detail::fuse_node_with_activation<ConvolutionLayerNode>, supported_fused_activations);
@@ -231,6 +309,11 @@
// TODO (COMPMID-2055): re-enable once we fuse bias and activations to convolution
// detail::fuse_layer<ConvolutionLayerNode, BatchNormalizationLayerNode>(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<DepthwiseConvolutionLayerNode, BatchNormalizationLayerNode>(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 6496a71..0a0c0c5 100644
--- a/src/graph/nodes/FusedConvolutionBatchNormalizationNode.cpp
+++ b/src/graph/nodes/FusedConvolutionBatchNormalizationNode.cpp
@@ -36,8 +36,8 @@
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 @@
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 0000000..a04d754
--- /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 c939de1..46f6ee8 100644
--- a/src/graph/printers/DotGraphPrinter.cpp
+++ b/src/graph/printers/DotGraphPrinter.cpp
@@ -85,6 +85,14 @@
_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;