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author | Matthew Sloyan <matthew.sloyan@arm.com> | 2022-10-28 18:02:17 +0100 |
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committer | Matthew Sloyan <matthew.sloyan@arm.com> | 2022-11-02 15:08:37 +0000 |
commit | 164bf4f29f6f1b2a3e6714ef4f5a21fc0fd16c2b (patch) | |
tree | e7296130a787578e1be4d3a93de46a9c466944b4 /src/backends/tosaCommon | |
parent | 2e950f4fa774ac995230addea898f3b11bf146cc (diff) | |
download | armnn-164bf4f29f6f1b2a3e6714ef4f5a21fc0fd16c2b.tar.gz |
IVGCVSW-7164 Implement TosaRefBackend::OptimizeSubgraphView
* Added TosaRefBackend::OptimizeSubgraphView implementation.
* Generalised TosaRefLayerSupport::IsLayerSupported to work with any
operator.
* Changed TosaCommon.hpp utils to inline functions.
* Added source files for TosaMappings.hpp and AdditionOperator.hpp.
* Fixed multiple defines issue with HALF_ROUND_STYLE and
HALF_ROUND_TIES_TO_EVEN.
Signed-off-by: Matthew Sloyan <matthew.sloyan@arm.com>
Change-Id: Ib2576ec3fb97faa3a2256b2fb93ec16ac8745760
Diffstat (limited to 'src/backends/tosaCommon')
7 files changed, 119 insertions, 89 deletions
diff --git a/src/backends/tosaCommon/CMakeLists.txt b/src/backends/tosaCommon/CMakeLists.txt index 83737d3bd3..1b1cc55eab 100644 --- a/src/backends/tosaCommon/CMakeLists.txt +++ b/src/backends/tosaCommon/CMakeLists.txt @@ -9,6 +9,7 @@ include_directories(SYSTEM ${TOSA_SERIALIZATION_LIB_INCLUDE}) list(APPEND armnnTosaBackend_sources TosaMappings.hpp + TosaMappings.cpp TosaLayerSupportRules.hpp ) diff --git a/src/backends/tosaCommon/TosaMappings.cpp b/src/backends/tosaCommon/TosaMappings.cpp new file mode 100644 index 0000000000..3c14bfd1f9 --- /dev/null +++ b/src/backends/tosaCommon/TosaMappings.cpp @@ -0,0 +1,66 @@ +// +// Copyright © 2022 Arm Ltd and Contributors. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#include "TosaMappings.hpp" + +using namespace armnn; +using namespace tosa; + +void SetBasicBlockConstantTensorData(Layer* layer, TosaSerializationBasicBlock* /*basicBlock*/) +{ + switch (layer->GetType()) + { + case LayerType::Convolution2d: + { + // ToDo: using Convolution2d as an example as it has constant tensors for weights and bias. + // ToDo: manually set TosaOperator data of basicBlock where constant tensors exist. + } + default: + // If no switch statement for layer, no constant tensors exist in that layer, return + return; + } +} + +TosaSerializationBasicBlock* GetTosaMapping(const LayerType type, + const std::vector<const TensorInfo*>& inputs, + const std::vector<const TensorInfo*>& outputs, + const BaseDescriptor& /*descriptor*/) +{ + switch (type) + { + case LayerType::Addition: + { + return ConvertAdditionToTosaOperator(inputs, outputs); + } + default: + { + // empty basic block when no tosa mapping implemented/exists + TosaSerializationOperator* op = new TosaSerializationOperator(Op_UNKNOWN, Attribute_NONE, nullptr, {}, {}); + return new TosaSerializationBasicBlock("", {op}, {}, {}, {}); + } + } +} + +TosaSerializationBasicBlock* GetTosaMappingFromLayer(Layer* layer) +{ + std::vector<const TensorInfo*> inputs; + for (auto inputSlot : layer->GetInputSlots()) + { + inputs.push_back(&inputSlot.GetConnection()->GetTensorInfo()); + } + + std::vector<const TensorInfo*> outputs; + for (auto& outputSlot : layer->GetOutputSlots()) + { + outputs.push_back(&outputSlot.GetTensorInfo()); + } + + TosaSerializationBasicBlock* basicBlock = GetTosaMapping(layer->GetType(), + inputs, + outputs, + layer->GetParameters()); + SetBasicBlockConstantTensorData(layer, basicBlock); + return basicBlock; +} diff --git a/src/backends/tosaCommon/TosaMappings.hpp b/src/backends/tosaCommon/TosaMappings.hpp index 5728ff3203..c721bcaf59 100644 --- a/src/backends/tosaCommon/TosaMappings.hpp +++ b/src/backends/tosaCommon/TosaMappings.hpp @@ -15,20 +15,7 @@ using namespace tosa; // From the input armnn::Layer, set the corresponding data field in the // tosa::TosaSerializationTensor where constant tensor data exists in the armnn::Layer. -void SetBasicBlockConstantTensorData(Layer* layer, TosaSerializationBasicBlock* /*basicBlock*/) -{ - switch (layer->GetType()) - { - case LayerType::Convolution2d: - { - // ToDo: using Convolution2d as an example as it has constant tensors for weights and bias. - // ToDo: manually set TosaOperator data of basicBlock where constant tensors exist. - } - default: - // If no switch statement for layer, no constant tensors exist in that layer, return - return; - } -} +void SetBasicBlockConstantTensorData(Layer* layer, TosaSerializationBasicBlock* /*basicBlock*/); // Populates a tosa::TosaSerializationBasicBlock from constructing // tosa::TosaSerializationOperator(s) and tosa::TosaSerializationTensor(s) @@ -39,43 +26,8 @@ void SetBasicBlockConstantTensorData(Layer* layer, TosaSerializationBasicBlock* TosaSerializationBasicBlock* GetTosaMapping(const LayerType type, const std::vector<const TensorInfo*>& inputs, const std::vector<const TensorInfo*>& outputs, - const BaseDescriptor& /*descriptor*/) -{ - switch (type) - { - case LayerType::Addition: - { - return ConvertAdditionToTosaOperator(inputs, outputs); - } - default: - { - // empty basic block when no tosa mapping implemented/exists - TosaSerializationOperator* op = new TosaSerializationOperator(Op_UNKNOWN, Attribute_NONE, nullptr, {}, {}); - return new TosaSerializationBasicBlock("", {op}, {}, {}, {}); - } - } -} + const BaseDescriptor& /*descriptor*/); // Function called in armnn::OptimizeSubgraphView() when access to armnn::Layer is available // and there is an option to set tosa basic block data from constant layer tenors available from the input layer. -TosaSerializationBasicBlock* GetTosaMappingFromLayer(Layer* layer) -{ - std::vector<const TensorInfo*> inputs; - for (auto inputSlot : layer->GetInputSlots()) - { - inputs.push_back(&inputSlot.GetConnection()->GetTensorInfo()); - } - - std::vector<const TensorInfo*> outputs; - for (auto& outputSlot : layer->GetOutputSlots()) - { - outputs.push_back(&outputSlot.GetTensorInfo()); - } - - TosaSerializationBasicBlock* basicBlock = GetTosaMapping(layer->GetType(), - inputs, - outputs, - layer->GetParameters()); - SetBasicBlockConstantTensorData(layer, basicBlock); - return basicBlock; -} +TosaSerializationBasicBlock* GetTosaMappingFromLayer(Layer* layer); diff --git a/src/backends/tosaCommon/operatorMappings/AdditionOperator.cpp b/src/backends/tosaCommon/operatorMappings/AdditionOperator.cpp new file mode 100644 index 0000000000..98ea03ac3c --- /dev/null +++ b/src/backends/tosaCommon/operatorMappings/AdditionOperator.cpp @@ -0,0 +1,44 @@ +// +// Copyright © 2022 Arm Ltd and Contributors. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#include "AdditionOperator.hpp" + +TosaSerializationBasicBlock* ConvertAdditionToTosaOperator(const std::vector<const TensorInfo*>& inputs, + const std::vector<const TensorInfo*>& outputs) +{ + // A helper function with static global variables ensures uniqueness + // for dynamically generating input, output and block names + std::string input0Name = std::string("Op_ADD_input0_") + GetUniqueTosaMappingID(); + std::string input1Name = std::string("Op_ADD_input1_") + GetUniqueTosaMappingID(); + std::string outputName = std::string("Op_ADD_output0_") + GetUniqueTosaMappingID(); + std::string blockName = std::string("Op_ADD_block_") + GetUniqueTosaMappingID(); + + TosaSerializationOperator* op = new TosaSerializationOperator(Op_ADD, + Attribute_NONE, + nullptr, + {input0Name, input1Name}, + {outputName}); + + std::vector<int32_t> inputShape0 = GetTosaTensorShape(inputs[0]->GetShape()); + DType inputDType0 = ArmNNToDType(inputs[0]->GetDataType()); + + std::vector<int32_t> inputShape1 = GetTosaTensorShape(inputs[1]->GetShape()); + DType inputDType1 = ArmNNToDType(inputs[1]->GetDataType()); + + std::vector<int32_t> outputShape0 = GetTosaTensorShape(outputs[0]->GetShape()); + DType outputDType0 = ArmNNToDType(outputs[0]->GetDataType()); + + TosaSerializationTensor* inputTensor0 = new TosaSerializationTensor(input0Name, inputShape0, inputDType0, {}); + TosaSerializationTensor* inputTensor1 = new TosaSerializationTensor(input1Name, inputShape1, inputDType1, {}); + TosaSerializationTensor* outputTensor0 = new TosaSerializationTensor(outputName, outputShape0, outputDType0, {}); + + // operatorInputNames/operatorOutputNames ends up being the same as + // blockInputNames/blockOutputNames for one-to-one ArmNN to Tosa mappings + return new TosaSerializationBasicBlock(blockName, // name + {op}, // operators + {inputTensor0, inputTensor1, outputTensor0}, // tensors + {input0Name, input1Name}, // inputs + {outputName}); // outputs +}
\ No newline at end of file diff --git a/src/backends/tosaCommon/operatorMappings/AdditionOperator.hpp b/src/backends/tosaCommon/operatorMappings/AdditionOperator.hpp index 98c01e2cb8..2a9c479d8e 100644 --- a/src/backends/tosaCommon/operatorMappings/AdditionOperator.hpp +++ b/src/backends/tosaCommon/operatorMappings/AdditionOperator.hpp @@ -14,39 +14,5 @@ using namespace armnn; using namespace tosa; TosaSerializationBasicBlock* ConvertAdditionToTosaOperator(const std::vector<const TensorInfo*>& inputs, - const std::vector<const TensorInfo*>& outputs) -{ - // A helper function with static global variables ensures uniqueness - // for dynamically generating input, output and block names - std::string input0Name = std::string("Op_ADD_input0_") + GetUniqueTosaMappingID(); - std::string input1Name = std::string("Op_ADD_input1_") + GetUniqueTosaMappingID(); - std::string outputName = std::string("Op_ADD_output0_") + GetUniqueTosaMappingID(); - std::string blockName = std::string("Op_ADD_block_") + GetUniqueTosaMappingID(); + const std::vector<const TensorInfo*>& outputs); - TosaSerializationOperator* op = new TosaSerializationOperator(Op_ADD, - Attribute_NONE, - nullptr, - {input0Name, input1Name}, - {outputName}); - - std::vector<int32_t> inputShape0 = GetTosaTensorShape(inputs[0]->GetShape()); - DType inputDType0 = ArmNNToDType(inputs[0]->GetDataType()); - - std::vector<int32_t> inputShape1 = GetTosaTensorShape(inputs[1]->GetShape()); - DType inputDType1 = ArmNNToDType(inputs[1]->GetDataType()); - - std::vector<int32_t> outputShape0 = GetTosaTensorShape(outputs[0]->GetShape()); - DType outputDType0 = ArmNNToDType(outputs[0]->GetDataType()); - - TosaSerializationTensor* inputTensor0 = new TosaSerializationTensor(input0Name, inputShape0, inputDType0, {}); - TosaSerializationTensor* inputTensor1 = new TosaSerializationTensor(input1Name, inputShape1, inputDType1, {}); - TosaSerializationTensor* outputTensor0 = new TosaSerializationTensor(outputName, outputShape0, outputDType0, {}); - - // operatorInputNames/operatorOutputNames ends up being the same as - // blockInputNames/blockOutputNames for one-to-one ArmNN to Tosa mappings - return new TosaSerializationBasicBlock(blockName, // name - {op}, // operators - {inputTensor0, inputTensor1, outputTensor0}, // tensors - {input0Name, input1Name}, // inputs - {outputName}); // outputs -} diff --git a/src/backends/tosaCommon/operatorMappings/CMakeLists.txt b/src/backends/tosaCommon/operatorMappings/CMakeLists.txt index 3965a6ab04..9fc33e9205 100644 --- a/src/backends/tosaCommon/operatorMappings/CMakeLists.txt +++ b/src/backends/tosaCommon/operatorMappings/CMakeLists.txt @@ -5,6 +5,7 @@ list(APPEND armnnTosaBackendOperators_sources AdditionOperator.hpp + AdditionOperator.cpp TosaOperatorUtils.hpp ) diff --git a/src/backends/tosaCommon/operatorMappings/TosaOperatorUtils.hpp b/src/backends/tosaCommon/operatorMappings/TosaOperatorUtils.hpp index e11f293b12..f580a53ebc 100644 --- a/src/backends/tosaCommon/operatorMappings/TosaOperatorUtils.hpp +++ b/src/backends/tosaCommon/operatorMappings/TosaOperatorUtils.hpp @@ -14,7 +14,7 @@ using namespace armnn; using namespace tosa; // Function to return Tosa datatype from input ArmNN datatype. -DType ArmNNToDType(const DataType& type) +inline DType ArmNNToDType(const DataType& type) { switch (type) { @@ -43,7 +43,7 @@ DType ArmNNToDType(const DataType& type) } // Function to return Tosa tensor shape from input ArmNN tensor shape. -std::vector<int32_t> GetTosaTensorShape(const TensorShape& shape) +inline std::vector<int32_t> GetTosaTensorShape(const TensorShape& shape) { std::vector<int32_t> returnShape; for (u_int32_t i = 0; i < shape.GetNumDimensions(); i++) @@ -55,7 +55,7 @@ std::vector<int32_t> GetTosaTensorShape(const TensorShape& shape) // Function to return unique int as a string to ensure uniqueness between all input, output and block names. static int uniqueTosaMappingID = 0; -std::string GetUniqueTosaMappingID() +inline std::string GetUniqueTosaMappingID() { return std::to_string(++uniqueTosaMappingID); } |