From b75d62430e9871fcc6f19cf82879f65d2e7fb201 Mon Sep 17 00:00:00 2001 From: ramelg01 Date: Fri, 26 Nov 2021 19:12:40 +0000 Subject: Graph Fusion With Post Ops Fix - Fusing ConvolutionBatchNormalization Nodes with post ops (activation or element wise ops) Resolves: COMPMID-4982 Signed-off-by: Ramy Elgammal Change-Id: I5b2d32cad00f710fd744cb5aa2d59fd7e5c97e0a Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/6766 Tested-by: Arm Jenkins Comments-Addressed: Arm Jenkins Reviewed-by: Sheri Zhang --- arm_compute/graph/DataLayerVisitor.h | 1 + arm_compute/graph/INodeVisitor.h | 6 + arm_compute/graph/TypePrinter.h | 3 + arm_compute/graph/Types.h | 1 + arm_compute/graph/backends/FunctionHelpers.h | 88 ++++++- ...volutionBatchNormalizationWithPostOpsFunction.h | 136 +++++++++++ .../nodes/FusedConvolutionBatchNormalizationNode.h | 4 +- ...dConvolutionBatchNormalizationWithPostOpsNode.h | 127 ++++++++++ arm_compute/graph/nodes/Nodes.h | 1 + arm_compute/graph/nodes/NodesFwd.h | 1 + arm_compute/graph/printers/DotGraphPrinter.h | 1 + src/graph/DataLayerVisitor.cpp | 8 + src/graph/INodeVisitor.cpp | 6 +- src/graph/backends/CL/CLFunctionsFactory.cpp | 2 + src/graph/mutators/NodeFusionMutator.cpp | 269 ++++++++++++++++----- ...onvolutionBatchNormalizationWithPostOpsNode.cpp | 138 +++++++++++ src/graph/printers/DotGraphPrinter.cpp | 8 + 17 files changed, 734 insertions(+), 66 deletions(-) create mode 100644 arm_compute/graph/backends/FusedConvolutionBatchNormalizationWithPostOpsFunction.h create mode 100644 arm_compute/graph/nodes/FusedConvolutionBatchNormalizationWithPostOpsNode.h create mode 100644 src/graph/nodes/FusedConvolutionBatchNormalizationWithPostOpsNode.cpp diff --git a/arm_compute/graph/DataLayerVisitor.h b/arm_compute/graph/DataLayerVisitor.h index 670b9f02b6..ac7f1c84ee 100644 --- a/arm_compute/graph/DataLayerVisitor.h +++ b/arm_compute/graph/DataLayerVisitor.h @@ -48,6 +48,7 @@ public: void visit(ConvolutionLayerNode &n) override; void visit(DepthwiseConvolutionLayerNode &n) override; void visit(FusedConvolutionBatchNormalizationNode &n) override; + void visit(FusedConvolutionBatchNormalizationWithPostOpsNode &n) override; void visit(FusedDepthwiseConvolutionBatchNormalizationNode &n) override; void visit(OutputNode &n) override; diff --git a/arm_compute/graph/INodeVisitor.h b/arm_compute/graph/INodeVisitor.h index 4cb601fb02..97e95336ef 100644 --- a/arm_compute/graph/INodeVisitor.h +++ b/arm_compute/graph/INodeVisitor.h @@ -106,6 +106,11 @@ public: * @param[in] n Node to visit. */ virtual void visit(FusedConvolutionBatchNormalizationNode &n) = 0; + /** Visit FusedConvolutionBatchNormalizationWithPostOpsNode. + * + * @param[in] n Node to visit. + */ + virtual void visit(FusedConvolutionBatchNormalizationWithPostOpsNode &n) = 0; /** Visit FusedConvolutionWithPostOpNode. * * @param[in] n Node to visit. @@ -210,6 +215,7 @@ public: virtual void visit(FlattenLayerNode &n) override; virtual void visit(FullyConnectedLayerNode &n) override; virtual void visit(FusedConvolutionBatchNormalizationNode &n) override; + virtual void visit(FusedConvolutionBatchNormalizationWithPostOpsNode &n) override; virtual void visit(FusedConvolutionWithPostOpNode &n) override; virtual void visit(FusedDepthwiseConvolutionBatchNormalizationNode &n) override; virtual void visit(InputNode &n) override; diff --git a/arm_compute/graph/TypePrinter.h b/arm_compute/graph/TypePrinter.h index a8a20c9de8..8f97bbf845 100644 --- a/arm_compute/graph/TypePrinter.h +++ b/arm_compute/graph/TypePrinter.h @@ -116,6 +116,9 @@ inline ::std::ostream &operator<<(::std::ostream &os, const NodeType &node_type) case NodeType::FusedConvolutionBatchNormalizationLayer: os << "FusedConvolutionBatchNormalizationLayer"; break; + case NodeType::FusedConvolutionBatchNormalizationLayerWithPostOpsLayer: + os << "FusedConvolutionBatchNormalizationLayerWithPostOpsLayer"; + break; case NodeType::FusedConvolutionWithPostOp: os << "FusedConvolutionWithPostOp"; break; diff --git a/arm_compute/graph/Types.h b/arm_compute/graph/Types.h index e802e9dc77..ff33d5037b 100644 --- a/arm_compute/graph/Types.h +++ b/arm_compute/graph/Types.h @@ -216,6 +216,7 @@ enum class NodeType FullyConnectedLayer, FusedConvolutionBatchNormalizationLayer, FusedConvolutionWithPostOp, + FusedConvolutionBatchNormalizationLayerWithPostOpsLayer, FusedDepthwiseConvolutionBatchNormalizationLayer, GenerateProposalsLayer, L2NormalizeLayer, diff --git a/arm_compute/graph/backends/FunctionHelpers.h b/arm_compute/graph/backends/FunctionHelpers.h index 1e420a803f..a7e52d4d6d 100644 --- a/arm_compute/graph/backends/FunctionHelpers.h +++ b/arm_compute/graph/backends/FunctionHelpers.h @@ -32,6 +32,7 @@ #include "arm_compute/graph/Types.h" #include "arm_compute/graph/Utils.h" #include "arm_compute/graph/backends/FusedConvolutionBatchNormalizationFunction.h" +#include "arm_compute/graph/backends/FusedConvolutionBatchNormalizationWithPostOpsFunction.h" #include "arm_compute/graph/backends/FusedDepthwiseConvolutionBatchNormalizationFunction.h" #include "arm_compute/graph/backends/Utils.h" #include "arm_compute/graph/nodes/Nodes.h" @@ -540,7 +541,7 @@ std::unique_ptr create_convolution_layer(ConvolutionLayerNode &node, return std::move(func); } -/** Create a backend convolution layer function with post opreator +/** Create a backend convolution layer function with post operator * * @tparam ConvolutionLayerFunctions Backend convolution functions * @tparam TargetInfo Target-specific information @@ -629,6 +630,91 @@ std::unique_ptr create_fused_convolution_with_post_op(FusedConvolutio << " Output shape: " << output->info()->tensor_shape() << qss.str() << (fused_act.enabled() ? " " + to_string(fused_act.activation()) : "") + << " Post ops" << post_ops; + << std::endl); + return std::move(func); +} + +/** Create a backend convolution batch normalization layer function with post operator + * + * @tparam FusedLayerTypes Backend convolution functions + * @tparam TargetInfo Target-specific information + * + * @param[in] node Node to create the backend function for + * @param[in] ctx Graph context + * + * @return Backend fused convolution with batch normalization layer function + */ +template +std::unique_ptr create_fused_convolution_batch_normalization_with_post_op(FusedConvolutionBatchNormalizationWithPostOpsNode &node, GraphContext &ctx) +{ + validate_node(node, 8 /* expected inputs */, 1 /* expected outputs */); + + // Extract IO and info + typename TargetInfo::TensorType *input = get_backing_tensor(node.input(0)); + typename TargetInfo::TensorType *weights = get_backing_tensor(node.input(1)); + typename TargetInfo::TensorType *biases = get_backing_tensor(node.input(2)); + typename TargetInfo::TensorType *mean = get_backing_tensor(node.input(3)); + typename TargetInfo::TensorType *var = get_backing_tensor(node.input(4)); + typename TargetInfo::TensorType *beta = get_backing_tensor(node.input(5)); + typename TargetInfo::TensorType *gamma = get_backing_tensor(node.input(6)); + + typename TargetInfo::TensorType *output = get_backing_tensor(node.output(0)); + + const PadStrideInfo conv_info = node.convolution_info(); + const unsigned int num_groups = node.num_groups(); + const bool fast_math = node.fast_math_hint() == FastMathHint::Enabled; + const float epsilon = node.epsilon(); + + experimental::PostOpList post_ops; + + auto &post_op_info_list = node.post_op_info_list(); + for(const auto &post_op_info : post_op_info_list) + { + switch(post_op_info->type()) + { + case PostOpType::Activation: + { + const auto act_info = utils::cast::polymorphic_downcast(post_op_info.get()); + post_ops.template push_back_op>(act_info->_act); + break; + } + case PostOpType::Eltwise_Add: + { + typename TargetInfo::TensorType *add_input = get_backing_tensor(node.input(3)); + const auto eltwise_info = utils::cast::polymorphic_downcast(post_op_info.get()); + post_ops.template push_back_op>(add_input, eltwise_info->_prev_op_dst_pos, eltwise_info->_policy); + break; + } + default: + { + ARM_COMPUTE_ERROR("Unsupported PostOpType"); + } + } + } + + // Create and configure function (we assume that functions have been validated before creation) + std::shared_ptr mm = get_memory_manager(ctx, TargetInfo::TargetType); + std::unique_ptr func; + std::string func_name; + + using FType = FusedConvolutionBatchNormalizationWithPostOpsFunction; + + // Create and configure function + std::tie(func, func_name) = create_named_memory_managed_function( + std::string("FusedConvolutionBatchNormalizationLayerWithPostOpsLayer"), mm, input, weights, biases, output, mean, var, beta, gamma, epsilon, conv_info, num_groups, fast_math, post_ops); + + // Log info + ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated " + << node.name() + << " Type: " << node.type() + << " Target: " << TargetInfo::TargetType + << " Data Type: " << input->info()->data_type() + << " Input shape: " << input->info()->tensor_shape() + << " Weights shape: " << weights->info()->tensor_shape() + << " Output shape: " << output->info()->tensor_shape() + << (fused_act.enabled() ? " " + to_string(fused_act.activation()) : "") + << " Post Ops:" << post_ops; << std::endl); return std::move(func); } diff --git a/arm_compute/graph/backends/FusedConvolutionBatchNormalizationWithPostOpsFunction.h b/arm_compute/graph/backends/FusedConvolutionBatchNormalizationWithPostOpsFunction.h new file mode 100644 index 0000000000..10f2e5c25e --- /dev/null +++ b/arm_compute/graph/backends/FusedConvolutionBatchNormalizationWithPostOpsFunction.h @@ -0,0 +1,136 @@ +/* + * Copyright (c) 2021 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. + */ + +#ifndef ARM_COMPUTE_GRAPH_BACKENDS_FUSED_CONVOLUTION_BATCH_NORMAZLIZATION_WITH_POST_OPS_FUNCTION_H +#define ARM_COMPUTE_GRAPH_BACKENDS_FUSED_CONVOLUTION_BATCH_NORMAZLIZATION_WITH_POST_OPS_FUNCTION_H + +#include "arm_compute/core/Types.h" +#include "arm_compute/core/experimental/IPostOp.h" +#include "arm_compute/runtime/IFunction.h" + +namespace arm_compute +{ +namespace graph +{ +namespace backends +{ +/** Wrapper function to first apply {NE, CL}BatchNormalizationLayer on the weights and then run {NE, CL}ConvolutionLayer with the modified weights */ +template +class FusedConvolutionBatchNormalizationWithPostOpsFunction : public IFunction +{ +public: + using TensorType = typename TargetInfo::TensorType; + using TensorConcreteType = typename TargetInfo::TensorConcreteType; + + FusedConvolutionBatchNormalizationWithPostOpsFunction(std::shared_ptr memory_manager = nullptr) + : _conv_layer(memory_manager), _fused_batch_norm_layer(), _fused_bias(), _is_prepared(false) + { + } + + /** Set the input and output tensors. + * + * @param[in] input Source tensor. 3 lower dimensions represent a single input [width, height, IFM], + * while every optional dimension from 4 and above represent a batch of inputs. + * Data types supported: QASYMM8/F16/F32. + * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported: Same as @p input. + * @param[in] bias Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. + * Data type supported: Should match @p input data type. + * @param[out] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs. + * Data types supported: Same as @p input. + * @param[in] mean Mean values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input + * @param[in] var Variance values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input + * @param[in] beta Beta values tensor info. 1 dimension with size equal to the feature maps [FM]. If not provided, default value for beta is 0. Data types supported: Same as @p input + * @param[in] gamma Gamma values tensor info. 1 dimension with size equal to the feature maps [FM]. If not provided, default value for gamma is 1. Data types supported: Same as @p input + * @param[in] epsilon Small value to avoid division with zero. Default value is 0.001f. + * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo. + * @param[in] num_groups Number of groups when performing a grouped convolution. num_groups != 1 is only supported for NCHW data layout + * @param[in] fast_math Enable fast math computation. In case this flag were set, the function could dispatch the fastest implementation + * available which may introduce a drop of accuracy as well. Default is false + * @param[in] post_ops A sequence of post operations that are performed after the main operation. + * + */ + void configure(TensorType *input, + TensorType *weights, + TensorType *bias, + TensorType *output, + const TensorType *mean, + const TensorType *var, + const TensorType *beta, + const TensorType *gamma, + float epsilon, const PadStrideInfo &conv_info, unsigned int num_groups, bool fast_math, + const arm_compute::experimental::PostOpList &post_ops = experimental::PostOpList {}) + { + // We don't run any validate, as we assume that the layers have been already validated + const bool has_bias = (bias != nullptr); + const TensorType *bias_to_use; + + // We check if the layer has a bias. If yes, use it in-place. If not, we need to create one + // as batch normalization might end up with a bias != 0 + if(has_bias) + { + _fused_batch_norm_layer.configure(weights, mean, var, nullptr, nullptr, bias, beta, gamma, epsilon); + bias_to_use = bias; + } + else + { + _fused_batch_norm_layer.configure(weights, mean, var, nullptr, &_fused_bias, nullptr, beta, gamma, epsilon); + bias_to_use = &_fused_bias; + } + + ActivationLayerInfo fused_act = ActivationLayerInfo(); // Passing an empty ActivationLayerInfo. + _conv_layer.configure(input, weights, bias_to_use, output, conv_info, WeightsInfo(), Size2D(1U, 1U), fused_act, fast_math, num_groups, post_ops); + + if(!has_bias) + { + _fused_bias.allocator()->allocate(); + } + } + + // Inherited methods overridden: + void run() + { + prepare(); + _conv_layer.run(); + } + + void prepare() + { + if(!_is_prepared) + { + _fused_batch_norm_layer.run(); + _is_prepared = true; + } + } + +private: + typename FusedLayerTypes::ConvolutionLayer _conv_layer; + typename FusedLayerTypes::FuseBatchNormalization _fused_batch_norm_layer; + TensorConcreteType _fused_bias; + bool _is_prepared; +}; +} // namespace backends +} // namespace graph +} // namespace arm_compute + +#endif /* ARM_COMPUTE_GRAPH_BACKENDS_FUSED_CONVOLUTION_BATCH_NORMAZLIZATION_WITH_POST_OPS_FUNCTION_H */ diff --git a/arm_compute/graph/nodes/FusedConvolutionBatchNormalizationNode.h b/arm_compute/graph/nodes/FusedConvolutionBatchNormalizationNode.h index b3661c300f..b0051b1385 100644 --- a/arm_compute/graph/nodes/FusedConvolutionBatchNormalizationNode.h +++ b/arm_compute/graph/nodes/FusedConvolutionBatchNormalizationNode.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2019 Arm Limited. + * Copyright (c) 2019, 2021 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -100,7 +100,7 @@ public: */ ConvolutionMethod convolution_method() const; - /** Sets the fast math fast hint + /** Sets the fast math hint * * @param[in] hint Hint to use for convolution */ diff --git a/arm_compute/graph/nodes/FusedConvolutionBatchNormalizationWithPostOpsNode.h b/arm_compute/graph/nodes/FusedConvolutionBatchNormalizationWithPostOpsNode.h new file mode 100644 index 0000000000..a42e06d889 --- /dev/null +++ b/arm_compute/graph/nodes/FusedConvolutionBatchNormalizationWithPostOpsNode.h @@ -0,0 +1,127 @@ +/* + * Copyright (c) 2021 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. + */ +#ifndef ARM_COMPUTE_GRAPH_FUSED_CONVOLUTION_BATCH_NORMALIZATION_WITH_POST_OPS_NODE_H +#define ARM_COMPUTE_GRAPH_FUSED_CONVOLUTION_BATCH_NORMALIZATION_WITH_POST_OPS_NODE_H + +#include "arm_compute/graph/INode.h" + +namespace arm_compute +{ +namespace graph +{ +/** Batch Normalization node */ +class FusedConvolutionBatchNormalizationWithPostOpsNode final : public INode +{ +public: + /** Constructor + * + * @param[in] epsilon Epsilon parameter. + * @param[in] info Convolution layer attributes. + * @param[in] num_groups (Optional) Number of groups (Defaults to 1) + * @param[in] method (Optional) Convolution method to use + * @param[in] fast_math_hint (Optional) Fast math hint + */ + FusedConvolutionBatchNormalizationWithPostOpsNode(float epsilon, PadStrideInfo info, + unsigned int num_groups = 1, + ConvolutionMethod method = ConvolutionMethod::Default, + FastMathHint fast_math_hint = FastMathHint::Disabled); + + /** Epsilon parameter accessor + * + * @return Epsilon parameter + */ + float epsilon() const; + + /** Computes convolution output descriptor + * + * @param[in] input_descriptor Input descriptor + * @param[in] weights_descriptor Weights descriptor + * @param[in] info Convolution operation attributes + * + * @return Output descriptor + */ + static TensorDescriptor compute_output_descriptor(const TensorDescriptor &input_descriptor, + const TensorDescriptor &weights_descriptor, + const PadStrideInfo &info); + + /** Sets the convolution layer method to use + * + * @param[in] method Method to use for convolution + */ + void set_convolution_method(ConvolutionMethod method); + + /** Number of groups in convolution accessor + * + * @return Number of groups in convolution + */ + unsigned int num_groups() const; + + /** Convolution layer method accessor + * + * @note This is an indication on which convolution layer implementation to use, + * if it fails to be created the library's heuristic approach will be used + * + * @return Convolution layer method to be used by the node + */ + ConvolutionMethod convolution_method() const; + + /** Sets the fast math hint + * + * @param[in] hint Hint to use for convolution + */ + void set_fast_math_hint(FastMathHint hint); + + /** Fast math hint accessor + * + * @return Fast math hint to be used by the node + */ + FastMathHint fast_math_hint() const; + + /** Convolution metadata accessor + * + * @return Convolution information + */ + PadStrideInfo convolution_info() const; + + // Inherited overridden methods: + NodeType type() const override; + bool forward_descriptors() override; + TensorDescriptor configure_output(size_t idx) const override; + void accept(INodeVisitor &v) override; + +public: + static constexpr NodeType node_type = NodeType::FusedConvolutionBatchNormalizationLayerWithPostOpsLayer; + +private: + float _epsilon; + + PadStrideInfo _info; + unsigned int _num_groups; + ConvolutionMethod _method; + FastMathHint _fast_math_hint; +}; + +} // namespace graph +} // namespace arm_compute +#endif /* ARM_COMPUTE_GRAPH_BATCH_NORMALIZATION_LAYER_NODE_H */ diff --git a/arm_compute/graph/nodes/Nodes.h b/arm_compute/graph/nodes/Nodes.h index fb0eb155fd..3887eaeac6 100644 --- a/arm_compute/graph/nodes/Nodes.h +++ b/arm_compute/graph/nodes/Nodes.h @@ -43,6 +43,7 @@ #include "arm_compute/graph/nodes/FlattenLayerNode.h" #include "arm_compute/graph/nodes/FullyConnectedLayerNode.h" #include "arm_compute/graph/nodes/FusedConvolutionBatchNormalizationNode.h" +#include "arm_compute/graph/nodes/FusedConvolutionBatchNormalizationWithPostOpsNode.h" #include "arm_compute/graph/nodes/FusedConvolutionWithPostOpNode.h" #include "arm_compute/graph/nodes/FusedDepthwiseConvolutionBatchNormalizationNode.h" #include "arm_compute/graph/nodes/GenerateProposalsLayerNode.h" diff --git a/arm_compute/graph/nodes/NodesFwd.h b/arm_compute/graph/nodes/NodesFwd.h index 6393b1d5d4..f1576d6336 100644 --- a/arm_compute/graph/nodes/NodesFwd.h +++ b/arm_compute/graph/nodes/NodesFwd.h @@ -51,6 +51,7 @@ class FullyConnectedLayerNode; class FusedConvolutionBatchNormalizationNode; class FusedConvolutionWithPostOpNode; class FusedDepthwiseConvolutionBatchNormalizationNode; +class FusedConvolutionBatchNormalizationWithPostOpsNode; class GenerateProposalsLayerNode; class InputNode; class L2NormalizeLayerNode; diff --git a/arm_compute/graph/printers/DotGraphPrinter.h b/arm_compute/graph/printers/DotGraphPrinter.h index 42a20678fe..63b89272f4 100644 --- a/arm_compute/graph/printers/DotGraphPrinter.h +++ b/arm_compute/graph/printers/DotGraphPrinter.h @@ -57,6 +57,7 @@ public: void visit(DepthwiseConvolutionLayerNode &n) override; void visit(EltwiseLayerNode &n) override; void visit(FusedConvolutionBatchNormalizationNode &n) override; + void visit(FusedConvolutionBatchNormalizationWithPostOpsNode &n) override; void visit(FusedConvolutionWithPostOpNode &n) override; void visit(FusedDepthwiseConvolutionBatchNormalizationNode &n) override; void visit(NormalizationLayerNode &n) override; diff --git a/src/graph/DataLayerVisitor.cpp b/src/graph/DataLayerVisitor.cpp index 3d5d9578ca..85d24b4654 100644 --- a/src/graph/DataLayerVisitor.cpp +++ b/src/graph/DataLayerVisitor.cpp @@ -131,6 +131,14 @@ void DataLayerVisitor::visit(FusedConvolutionBatchNormalizationNode &n) add_convolution_layer_method(_layer_data, n); } +void DataLayerVisitor::visit(FusedConvolutionBatchNormalizationWithPostOpsNode &n) +{ + _layer_data.clear(); + add_generic_layer_data(_layer_data, n); + add_convolution_layer_data(_layer_data, n); + add_convolution_layer_method(_layer_data, n); +} + void DataLayerVisitor::visit(FusedDepthwiseConvolutionBatchNormalizationNode &n) { _layer_data.clear(); diff --git a/src/graph/INodeVisitor.cpp b/src/graph/INodeVisitor.cpp index ceaaeae7f2..f067d618bd 100644 --- a/src/graph/INodeVisitor.cpp +++ b/src/graph/INodeVisitor.cpp @@ -85,6 +85,10 @@ void DefaultNodeVisitor::visit(FusedConvolutionBatchNormalizationNode &n) { default_visit(n); } +void DefaultNodeVisitor::visit(FusedConvolutionBatchNormalizationWithPostOpsNode &n) +{ + default_visit(n); +} void DefaultNodeVisitor::visit(FusedConvolutionWithPostOpNode &n) { default_visit(n); @@ -147,4 +151,4 @@ void DefaultNodeVisitor::visit(StackLayerNode &n) } #endif /* DOXYGEN_SKIP_THIS */ } // namespace graph -} // namespace arm_compute \ No newline at end of file +} // namespace arm_compute diff --git a/src/graph/backends/CL/CLFunctionsFactory.cpp b/src/graph/backends/CL/CLFunctionsFactory.cpp index 838977e75c..c67f6a538b 100644 --- a/src/graph/backends/CL/CLFunctionsFactory.cpp +++ b/src/graph/backends/CL/CLFunctionsFactory.cpp @@ -318,6 +318,8 @@ std::unique_ptr CLFunctionFactory::create(INode *node, GraphContext & return detail::create_stack_layer(*polymorphic_downcast(node)); case NodeType::StridedSliceLayer: return detail::create_strided_slice_layer(*polymorphic_downcast(node)); + case NodeType::FusedConvolutionBatchNormalizationLayerWithPostOpsLayer: + return detail::create_fused_convolution_batch_normalization_with_post_op(*polymorphic_downcast(node), ctx); default: return nullptr; } diff --git a/src/graph/mutators/NodeFusionMutator.cpp b/src/graph/mutators/NodeFusionMutator.cpp index 78f275f3bb..5284fce806 100644 --- a/src/graph/mutators/NodeFusionMutator.cpp +++ b/src/graph/mutators/NodeFusionMutator.cpp @@ -28,6 +28,7 @@ #include "arm_compute/graph/Utils.h" #include "arm_compute/graph/backends/BackendRegistry.h" #include "arm_compute/graph/nodes/FusedConvolutionBatchNormalizationNode.h" +#include "arm_compute/graph/nodes/FusedConvolutionBatchNormalizationWithPostOpsNode.h" #include "arm_compute/graph/nodes/FusedConvolutionWithPostOpNode.h" #include "arm_compute/graph/nodes/Nodes.h" @@ -420,88 +421,91 @@ void fuse_convolution_with_post_op(Graph &g, INode *fused_node, std::list get_post_op_list(Graph &g, int &eltwise_operand_id, int &prev_op_dst_pos, int conv_node_id, const std::set &supported_fused_activations) +std::list get_post_op_list(Graph &g, int &eltwise_operand_id, int &prev_op_dst_pos, unsigned int conv_node_id, const std::set &supported_fused_activations) { std::list post_op_node_list = {}; NodeID prev_op_dst_id = conv_node_id; NodeType post_op_type_list[3] = { NodeType::Dummy, NodeType::Dummy, NodeType::Dummy }; int post_op_idx = 0; - for(unsigned int i = conv_node_id + 1; i < g.nodes().size(); ++i) + + // Get list of the connected nodes + auto current_node = g.node(conv_node_id); + + while(post_op_node_list.size() < 3) { - auto post_op_node = g.node(i); + // This convolution node must have only one output edge, otherwise this function would not have been called + + auto current_output_edge_id = current_node->output_edges().begin(); + auto current_output_edge = g.edge(*current_output_edge_id); + auto post_op_node = current_output_edge->consumer(); + bool fusable_post_op = false; if(post_op_node != nullptr && post_op_node->output_edges().size() > 0) { - const auto post_op_output_edge_id = *post_op_node->output_edges().begin(); - const auto post_op_output_edge = g.edge(post_op_output_edge_id); - - if(post_op_output_edge != nullptr) + switch(post_op_node->type()) { - switch(post_op_output_edge->producer()->type()) + case EltwiseLayerNode::node_type: { - case EltwiseLayerNode::node_type: + auto *eltwise_node = arm_compute::utils::cast::polymorphic_downcast(post_op_node); + ARM_COMPUTE_ERROR_ON(eltwise_node->output(0) == nullptr); + if(eltwise_node->output(0)->accessor() == nullptr) { - auto *eltwise_node = arm_compute::utils::cast::polymorphic_downcast(post_op_output_edge->producer()); - ARM_COMPUTE_ERROR_ON(eltwise_node->output(0) == nullptr); - if(eltwise_node->output(0)->accessor() == nullptr) + post_op_node_list.push_back(post_op_node); + fusable_post_op = true; + post_op_type_list[post_op_idx++] = eltwise_node->type(); + + // Extract elementwise inputs + const auto eltwise_input_id_0 = eltwise_node->input_edge(0)->producer_id(); + const auto eltwise_input_id_1 = eltwise_node->input_edge(1)->producer_id(); + if(eltwise_input_id_0 == prev_op_dst_id) { - post_op_node_list.push_back(post_op_output_edge->producer()); - fusable_post_op = true; - post_op_type_list[post_op_idx++] = eltwise_node->type(); - - // Extract elementwise inputs - const auto eltwise_input_id_0 = eltwise_node->input_edge(0)->producer_id(); - const auto eltwise_input_id_1 = eltwise_node->input_edge(1)->producer_id(); - if(eltwise_input_id_0 == prev_op_dst_id) - { - eltwise_operand_id = eltwise_input_id_1; - prev_op_dst_pos = 0; - } - else if(eltwise_input_id_1 == prev_op_dst_id) - { - eltwise_operand_id = eltwise_input_id_0; - prev_op_dst_pos = 1; - } + eltwise_operand_id = eltwise_input_id_1; + prev_op_dst_pos = 0; } - else + else if(eltwise_input_id_1 == prev_op_dst_id) { - ARM_COMPUTE_LOG_GRAPH_VERBOSE("Prevented fusion of convolution node with elementwise due to the presence of an output accessor\n"); + eltwise_operand_id = eltwise_input_id_0; + prev_op_dst_pos = 1; } - break; } - case ActivationLayerNode::node_type: + else { - auto *act_node = arm_compute::utils::cast::polymorphic_downcast(post_op_output_edge->producer()); - ARM_COMPUTE_ERROR_ON(act_node->output(0) == nullptr); - // Check if activation is supported for fusion - if(supported_fused_activations.count(act_node->activation_info().activation()) == 0) - { - break; - } - if(act_node->output(0)->accessor() == nullptr) - { - post_op_node_list.push_back(post_op_output_edge->producer()); - fusable_post_op = true; - post_op_type_list[post_op_idx++] = act_node->type(); - prev_op_dst_id = act_node->id(); - } - else - { - ARM_COMPUTE_LOG_GRAPH_VERBOSE("Prevented fusion of convolution node with activation due to the presence of an output accessor\n"); - } - break; + ARM_COMPUTE_LOG_GRAPH_VERBOSE("Prevented fusion of convolution node with elementwise due to the presence of an output accessor\n"); } - default: + break; + } + case ActivationLayerNode::node_type: + { + auto *act_node = arm_compute::utils::cast::polymorphic_downcast(post_op_node); + ARM_COMPUTE_ERROR_ON(act_node->output(0) == nullptr); + // Check if activation is supported for fusion + if(supported_fused_activations.count(act_node->activation_info().activation()) == 0) { break; } + if(act_node->output(0)->accessor() == nullptr) + { + post_op_node_list.push_back(post_op_node); + fusable_post_op = true; + post_op_type_list[post_op_idx++] = act_node->type(); + prev_op_dst_id = act_node->id(); + } + else + { + ARM_COMPUTE_LOG_GRAPH_VERBOSE("Prevented fusion of convolution node with post ops due to the presence of an output accessor\n"); + } + break; + } + default: + { + break; } } // Check if the node is not a branching node and current node is fusable - if(post_op_node->output_edges().size() == 1 && fusable_post_op == true && post_op_node_list.size() < 3) + if(post_op_node->output_edges().size() == 1 && fusable_post_op == true) { - continue; + current_node = post_op_node; } else { @@ -534,12 +538,11 @@ std::list get_post_op_list(Graph &g, int &eltwise_operand_id, int &prev * * Notes: currently, only GEMM supports fusion with post operator */ -template -void fuse_convolution(Graph &g, const Edge *output_edge, int conv_node_id, const std::set &supported_fused_activations) +void fuse_convolution_with_post_ops(Graph &g, const Edge *output_edge, unsigned int conv_node_id, const std::set &supported_fused_activations) { ARM_COMPUTE_ERROR_ON(output_edge == nullptr); - auto *conv_node = arm_compute::utils::cast::polymorphic_downcast(output_edge->producer()); + auto *conv_node = arm_compute::utils::cast::polymorphic_downcast(output_edge->producer()); ARM_COMPUTE_ERROR_ON(conv_node->output(0) == nullptr); const ConvolutionMethod conv_algorithm = conv_node->convolution_method(); @@ -552,14 +555,14 @@ void fuse_convolution(Graph &g, const Edge *output_edge, int conv_node_id, const // Prevent fusion if fused node has an output accessor if(conv_node->output(0)->accessor() == nullptr) { - // If data type is FP32/FP16, data layout is NHWC, and filter size if 1x1, fuse convolution with post op, as Conv1x1 always leads to GEMM. + // If data type is FP32/FP16, data layout is NHWC, and filter size is 1x1, fuse convolution with post op, as Conv1x1 always leads to GEMM. const Edge *input_edge = conv_node->input_edge(1); if(input_edge != nullptr && input_edge->tensor() != nullptr) { const DataLayout data_layout = input_edge->tensor()->desc().layout; const DataType data_type = input_edge->tensor()->desc().data_type; const TensorShape tensor_shape = input_edge->tensor()->desc().shape; - if(data_layout != DataLayout::NHWC || is_data_type_float(data_type) == false || tensor_shape.y() != 1 || tensor_shape.z() != 1) + if((data_layout != DataLayout::NHWC) || (is_data_type_float(data_type) == false) || (tensor_shape.y() != 1) || (tensor_shape.z() != 1)) { ARM_COMPUTE_LOG_GRAPH_VERBOSE("Prevented fusion of convolution node with post ops due to non GEMM convolution\n"); return; @@ -603,7 +606,18 @@ void fuse_convolution(Graph &g, const Edge *output_edge, int conv_node_id, const auto conv_bias_id = conv_node->input_edge(2)->producer_id(); g.add_connection(conv_bias_id, 0, fused_id, 2); } - g.add_connection(eltwise_operand_id, 0, fused_id, 3); + // Adding the Element wise operand in case the post op is element wise operation + auto it = std::find_if(post_op_node_list.begin(), + post_op_node_list.end(), + [&](const INode * nd) + { + return (nd->type() == graph::NodeType::EltwiseLayer); + }); + + if(it != post_op_node_list.end()) + { + g.add_connection(eltwise_operand_id, 0, fused_id, 3); + } g.remove_node(conv_node->id()); // Update fused node outputs @@ -623,6 +637,136 @@ void fuse_convolution(Graph &g, const Edge *output_edge, int conv_node_id, const } } +void fuse_convolution_batch_normalization_with_post_ops(Graph &g, const Edge *output_edge, unsigned int conv_node_id, const std::set &supported_fused_activations) +{ + ARM_COMPUTE_ERROR_ON(output_edge == nullptr); + + auto *conv_node = arm_compute::utils::cast::polymorphic_downcast(output_edge->producer()); + ARM_COMPUTE_ERROR_ON(conv_node->output(0) == nullptr); + const ConvolutionMethod conv_algorithm = conv_node->convolution_method(); + if(conv_algorithm != ConvolutionMethod::GEMM) + { + ARM_COMPUTE_LOG_GRAPH_VERBOSE("Prevented fusion of convolution node with post ops due to non GEMM convolution\n"); + return; + } + + // Prevent fusion if fused node has an output accessor + if(conv_node->output(0)->accessor() == nullptr) + { + // If data type is FP32/FP16, data layout is NHWC, and filter size is 1x1, fuse convolution with post op, as Conv1x1 always leads to GEMM. + const Edge *input_edge = conv_node->input_edge(1); + if(input_edge != nullptr && input_edge->tensor() != nullptr) + { + const DataLayout data_layout = input_edge->tensor()->desc().layout; + const DataType data_type = input_edge->tensor()->desc().data_type; + const TensorShape tensor_shape = input_edge->tensor()->desc().shape; + if((data_layout != DataLayout::NHWC) || (is_data_type_float(data_type) == false) || (tensor_shape.y() != 1) || (tensor_shape.z() != 1)) + { + ARM_COMPUTE_LOG_GRAPH_VERBOSE("Prevented fusion of convolution node with post ops due to non GEMM convolution\n"); + return; + } + } + else + { + return; + } + + // Get post op list + int eltwise_operand_id = 0; + int prev_op_dst_pos = 0; // Previous operator dst's postion in current operator + std::list post_op_node_list = get_post_op_list(g, eltwise_operand_id, prev_op_dst_pos, conv_node_id, supported_fused_activations); + + if(post_op_node_list.size() == 0) + { + return; + } + else // Do convolution fusion with post op if there're one(elementwise), two or more operators + { + const Target assigned_target = conv_node->assigned_target(); + + // 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 bn_mean_id = conv_node->input_edge(3)->producer_id(); + const auto bn_var_id = conv_node->input_edge(4)->producer_id(); + const auto conv_info = conv_node->convolution_info(); + const auto conv_method = conv_node->convolution_method(); + const auto num_groups = conv_node->num_groups(); + FastMathHint fast_math_hint = conv_node->fast_math_hint(); + + // Create the fused node + + const float epsilon = conv_node->epsilon(); + const NodeID fused_id = g.add_node(epsilon, conv_info, num_groups, conv_method, fast_math_hint); + + ARM_COMPUTE_LOG_GRAPH_VERBOSE("Fusing FusedConvolutionBatchNormalization node with ID : " << conv_node->id()); + + // Add connections from the conv inputs to the fused node + g.add_connection(conv_input_id, 0, fused_id, 0); + g.add_connection(conv_weights_id, 0, fused_id, 1); + + if(conv_node->input_edge(2) != nullptr) + { + auto conv_bias_id = conv_node->input_edge(2)->producer_id(); + g.add_connection(conv_bias_id, 0, fused_id, 2); + } + g.add_connection(bn_mean_id, 0, fused_id, 3); + g.add_connection(bn_var_id, 0, fused_id, 4); + + // Move connections of old FusedConvolutionBatchNormalization to the fused node + if(conv_node->input_edge(5) != nullptr) + { + const auto bn_beta_id = conv_node->input_edge(5)->producer_id(); + g.add_connection(bn_beta_id, 0, fused_id, 5); + } + + if(conv_node->input_edge(6) != nullptr) + { + const auto bn_gamma_id = conv_node->input_edge(6)->producer_id(); + g.add_connection(bn_gamma_id, 0, fused_id, 6); + } + + // Adding the Element wise operand in case the post op is element wise operation + auto it = std::find_if(post_op_node_list.begin(), + post_op_node_list.end(), + [&](const INode * nd) + { + return (nd->type() == graph::NodeType::EltwiseLayer); + }); + + if(it != post_op_node_list.end()) + { + g.add_connection(eltwise_operand_id, 0, fused_id, 7); + } + + // Update fused node outputs + auto fused_node = g.node(fused_id); + fused_node->set_assigned_target(assigned_target); + + auto conv_node_name = conv_node->name(); + + // collect the post ops names + std::string post_ops_name = ""; + for(auto &post_op : post_op_node_list) + { + post_ops_name += post_op->name(); + } + fused_node->set_common_node_parameters(NodeParams{ conv_node->name() + "+" + post_ops_name, assigned_target }); + + // Fuse convolution with post op + fuse_convolution_with_post_op(g, fused_node, post_op_node_list, prev_op_dst_pos); + + post_op_node_list.clear(); + g.remove_node(conv_node->id()); + ARM_COMPUTE_LOG_GRAPH_VERBOSE(std::endl); + } + } + else + { + ARM_COMPUTE_LOG_GRAPH_VERBOSE("Prevented fusion of convolution node with post ops due to the presence of an output accessor\n"); + } +} + template void fuse_layer(Graph &g, std::function const &prec, const F fuse_fcn, Args &&... optional_arguments) { @@ -697,7 +841,7 @@ void NodeFusionMutator::mutate(Graph &g) // The fusion of PostOps to ConvolutionLayer: // It must occur after the fusion of PadLayer into ConvolutionLayer // It must occur before the fusion of normal ActivationLayer into ConvolutionLayer as it takes precedence - detail::fuse_layer(g, cl_target_prec, detail::fuse_convolution, supported_fused_activations); + detail::fuse_layer(g, cl_target_prec, detail::fuse_convolution_with_post_ops, supported_fused_activations); 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); detail::fuse_layer(g, qs8_prec, detail::fuse_node_with_activation, supported_fused_activations); @@ -706,6 +850,7 @@ void NodeFusionMutator::mutate(Graph &g) // The fusion of BatchNormalizationLayer must occur after the fusion of ActivationLayer. Because FusedConvolutionBatchNormalizationNode assumes the BatchNormalization is already fused with activation, if any detail::fuse_layer(g, empty_prec, detail::fuse_convolution_with_batch_normalization); detail::fuse_layer(g, empty_prec, detail::fuse_depthwise_convolution_with_batch_normalization); + detail::fuse_layer(g, cl_target_prec, detail::fuse_convolution_batch_normalization_with_post_ops, supported_fused_activations); } } // namespace graph } // namespace arm_compute diff --git a/src/graph/nodes/FusedConvolutionBatchNormalizationWithPostOpsNode.cpp b/src/graph/nodes/FusedConvolutionBatchNormalizationWithPostOpsNode.cpp new file mode 100644 index 0000000000..af81f0369a --- /dev/null +++ b/src/graph/nodes/FusedConvolutionBatchNormalizationWithPostOpsNode.cpp @@ -0,0 +1,138 @@ +/* + * Copyright (c) 2021 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/FusedConvolutionBatchNormalizationWithPostOpsNode.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 +{ +FusedConvolutionBatchNormalizationWithPostOpsNode::FusedConvolutionBatchNormalizationWithPostOpsNode(float epsilon, PadStrideInfo info, + unsigned int num_groups, + ConvolutionMethod method, + FastMathHint fast_math_hint) + : _epsilon(epsilon), _info(std::move(info)), _num_groups(num_groups), _method(method), _fast_math_hint(fast_math_hint) +{ + _input_edges.resize(8, EmptyEdgeID); + _outputs.resize(1, NullTensorID); +} + +void FusedConvolutionBatchNormalizationWithPostOpsNode::set_convolution_method(ConvolutionMethod method) +{ + _method = method; +} + +float FusedConvolutionBatchNormalizationWithPostOpsNode::epsilon() const +{ + return _epsilon; +} + +ConvolutionMethod FusedConvolutionBatchNormalizationWithPostOpsNode::convolution_method() const +{ + return _method; +} + +void FusedConvolutionBatchNormalizationWithPostOpsNode::set_fast_math_hint(FastMathHint hint) +{ + _fast_math_hint = hint; +} + +FastMathHint FusedConvolutionBatchNormalizationWithPostOpsNode::fast_math_hint() const +{ + return _fast_math_hint; +} + +PadStrideInfo FusedConvolutionBatchNormalizationWithPostOpsNode::convolution_info() const +{ + return _info; +} + +unsigned int FusedConvolutionBatchNormalizationWithPostOpsNode::num_groups() const +{ + return _num_groups; +} + +TensorDescriptor FusedConvolutionBatchNormalizationWithPostOpsNode::compute_output_descriptor(const TensorDescriptor &input_descriptor, + const TensorDescriptor &weights_descriptor, + const PadStrideInfo &info) +{ + 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 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); + + const DataLayout data_layout = input_descriptor.layout; + TensorDescriptor output_descriptor = input_descriptor; + output_descriptor.shape.set(get_dimension_idx(data_layout, DataLayoutDimension::WIDTH), output_width); + output_descriptor.shape.set(get_dimension_idx(data_layout, DataLayoutDimension::HEIGHT), output_height); + output_descriptor.shape.set(get_dimension_idx(data_layout, DataLayoutDimension::CHANNEL), weights_descriptor.shape[3]); + + return output_descriptor; +} + +bool FusedConvolutionBatchNormalizationWithPostOpsNode::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 FusedConvolutionBatchNormalizationWithPostOpsNode::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); + + return output_info; +} + +NodeType FusedConvolutionBatchNormalizationWithPostOpsNode::type() const +{ + return FusedConvolutionBatchNormalizationWithPostOpsNode::node_type; +} + +void FusedConvolutionBatchNormalizationWithPostOpsNode::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 47371e34d5..1071d50197 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(FusedConvolutionBatchNormalizationWithPostOpsNode &n) +{ + ARM_COMPUTE_UNUSED(n); + std::stringstream ss; + ss << "FusedConvolutionBatchNormalizationWithPostOpsNode"; + _info = ss.str(); +} + void DotGraphVisitor::visit(FusedConvolutionWithPostOpNode &n) { ARM_COMPUTE_UNUSED(n); -- cgit v1.2.1