IVGCVSW-7846 Refactor ElementBinaryOps to use ElementBinaryLayer
* Refactor all functions to convert Add, Div, Maximum, Minimum, Mul
and Sub to use ElementwiseBinary layers instead
* Add POW Operation support
* Add REDUCE_PROD Operation support
Signed-off-by: Kevin May <kevin.may@arm.com>
Change-Id: I8c91980e585f7ff2561610084e7c6b48fb278171
diff --git a/shim/sl/canonical/Converter.cpp b/shim/sl/canonical/Converter.cpp
index 90fd711..790fad6 100644
--- a/shim/sl/canonical/Converter.cpp
+++ b/shim/sl/canonical/Converter.cpp
@@ -1,5 +1,5 @@
//
-// Copyright © 2022 Arm Ltd and Contributors. All rights reserved.
+// Copyright © 2022-2023 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
@@ -25,7 +25,7 @@
case OperationType::ABS:
return ConvertElementwiseUnary(operation, model, data, UnaryOperation::Abs);
case OperationType::ADD:
- return ConvertAdd(operation, model, data);
+ return ConvertElementwiseBinary(operation, model, data, armnn::BinaryOperation::Add);
case OperationType::ARGMAX:
return ConvertArgMinMax(operation, model, data, ArgMinMaxFunction::Max);
case OperationType::ARGMIN:
@@ -49,7 +49,7 @@
case OperationType::DEQUANTIZE:
return ConvertDequantize(operation, model, data);
case OperationType::DIV:
- return ConvertDiv(operation, model, data);
+ return ConvertElementwiseBinary(operation, model, data, armnn::BinaryOperation::Div);
case OperationType::ELU:
return ConvertElu(operation, model, data);
case OperationType::EQUAL:
@@ -103,13 +103,13 @@
case OperationType::MAX_POOL_2D:
return ConvertMaxPool2d(operation, model, data);
case OperationType::MAXIMUM:
- return ConvertMaximum(operation, model, data);
+ return ConvertElementwiseBinary(operation, model, data, armnn::BinaryOperation::Maximum);
case OperationType::MEAN:
return ConvertMean(operation, model, data);
case OperationType::MINIMUM:
- return ConvertMinimum(operation, model, data);
+ return ConvertElementwiseBinary(operation, model, data, armnn::BinaryOperation::Minimum);
case OperationType::MUL:
- return ConvertMul(operation, model, data);
+ return ConvertElementwiseBinary(operation, model, data, armnn::BinaryOperation::Mul);
case OperationType::NEG:
return ConvertElementwiseUnary(operation, model, data, UnaryOperation::Neg);
case OperationType::NOT_EQUAL:
@@ -120,6 +120,8 @@
return ConvertPadV2(operation, model, data);
case OperationType::PRELU:
return ConvertPrelu(operation, model, data);
+ case OperationType::POW:
+ return ConvertElementwiseBinary(operation, model, data, BinaryOperation::Power);
case OperationType::QUANTIZE:
return ConvertQuantize(operation, model, data);
case OperationType::QUANTIZED_LSTM:
@@ -132,6 +134,8 @@
return ConvertReduce(operation, model, data, armnn::ReduceOperation::Max);
case OperationType::REDUCE_MIN:
return ConvertReduce(operation, model, data, armnn::ReduceOperation::Min);
+ case OperationType::REDUCE_PROD:
+ return ConvertReduce(operation, model, data, armnn::ReduceOperation::Prod);
case OperationType::REDUCE_SUM:
return ConvertReduce(operation, model, data, armnn::ReduceOperation::Sum);
case OperationType::RELU:
@@ -163,7 +167,7 @@
case OperationType::STRIDED_SLICE:
return ConvertStridedSlice(operation, model, data);
case OperationType::SUB:
- return ConvertSub(operation, model, data);
+ return ConvertElementwiseBinary(operation, model, data, BinaryOperation::Sub);
case OperationType::TRANSPOSE:
return ConvertTranspose(operation, model, data);
case OperationType::TRANSPOSE_CONV_2D:
@@ -176,80 +180,6 @@
}
}
-bool Converter::ConvertAdd(const Operation& operation, const Model& model, ConversionData& data)
-{
- VLOG(DRIVER) << "Converter::ConvertAdd()";
- LayerInputHandle input0 = ConvertToLayerInputHandle(operation, 0, model, data);
- LayerInputHandle input1 = ConvertToLayerInputHandle(operation, 1, model, data);
-
- if (!input0.IsValid() || !input1.IsValid())
- {
- return Fail("%s: Operation has invalid inputs", __func__);
- }
-
- // The FuseActivation parameter is always the input index 2, and it should be optional
- ActivationFn activationFunction;
- if (!GetOptionalInputActivation(operation, 2, activationFunction, model, data))
- {
- return Fail("%s: Operation has invalid inputs", __func__);
- }
-
- const Operand* outputOperand = GetOutputOperand(operation, 0, model);
- if (!outputOperand)
- {
- return false;
- }
-
- const armnn::TensorInfo& inputInfo0 = input0.GetTensorInfo();
- const armnn::TensorInfo& inputInfo1 = input1.GetTensorInfo();
-
- const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*outputOperand);
-
- bool isSupported = false;
- armnn::BackendId setBackend;
- auto validateFunc = [&](const armnn::TensorInfo& outputInfo, bool& isSupported)
- {
- ARMNN_NO_DEPRECATE_WARN_BEGIN
- FORWARD_LAYER_SUPPORT_FUNC(__func__,
- IsAdditionSupported,
- data.m_Backends,
- isSupported,
- setBackend,
- inputInfo0,
- inputInfo1,
- outputInfo);
- ARMNN_NO_DEPRECATE_WARN_END
- };
-
- if(!IsDynamicTensor(outputInfo))
- {
- validateFunc(outputInfo, isSupported);
- }
- else
- {
- isSupported = AreDynamicTensorsSupported();
- }
-
- if (!isSupported)
- {
- return false;
- }
-
- ARMNN_NO_DEPRECATE_WARN_BEGIN
- armnn::IConnectableLayer* const startLayer = data.m_Network->AddAdditionLayer();
- ARMNN_NO_DEPRECATE_WARN_END
- startLayer->SetBackendId(setBackend);
-
- bool isReshapeSupported = BroadcastTensor(input0, input1, startLayer, data);
- if (!isReshapeSupported)
- {
- return false;
- }
-
- return SetupAndTrackLayerOutputSlot(operation, 0, *startLayer, model,
- data, nullptr, validateFunc, activationFunction);
-}
-
bool Converter::ConvertArgMinMax(const Operation& operation,
const Model& model,
ConversionData& data,
@@ -786,7 +716,11 @@
}
}
- ARMNN_ASSERT(inputShapes.size() == inputHandles.size());
+ if (inputShapes.size() != inputHandles.size())
+ {
+ return Fail("%s: invalid model input shapes size doesn't match input handles size: %i != %i", __func__,
+ inputShapes.size(), inputHandles.size());
+ }
if (inputsHaveBeenReshaped)
{
@@ -1508,9 +1442,13 @@
return SetupAndTrackLayerOutputSlot(operation, 0, *layer, model, data, nullptr, validateFunc);
}
-bool Converter::ConvertDiv(const Operation& operation, const Model& model, ConversionData& data)
+bool Converter::ConvertElementwiseBinary(const Operation& operation,
+ const Model& model,
+ ConversionData& data,
+ armnn::BinaryOperation binaryOperation)
{
- VLOG(DRIVER) << "Converter::ConvertDiv()";
+ VLOG(DRIVER) << "Converter::ConvertElementwiseBinary()";
+ VLOG(DRIVER) << "binaryOperation = " << GetBinaryOperationAsCString(binaryOperation);
LayerInputHandle input0 = ConvertToLayerInputHandle(operation, 0, model, data);
LayerInputHandle input1 = ConvertToLayerInputHandle(operation, 1, model, data);
@@ -1520,39 +1458,38 @@
return Fail("%s: Operation has invalid inputs", __func__);
}
- // The FuseActivation parameter is always the input index 2
- // and it should be optional
+ // The FuseActivation parameter is always the input index 2, and it should be optional
ActivationFn activationFunction;
if (!GetOptionalInputActivation(operation, 2, activationFunction, model, data))
{
- return Fail("%s: Operation has invalid inputs", __func__);
+ return Fail("%s: Operation has invalid optional input: activation function", __func__);
}
const Operand* output = GetOutputOperand(operation, 0, model);
if (!output)
{
- return Fail("%s: Could not read output 0", __func__);
+ return Fail("%s: Could not read output", __func__);
}
const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*output);
+ armnn::ElementwiseBinaryDescriptor descriptor(binaryOperation);
+
bool isSupported = false;
- armnn::BackendId setBackend;
auto validateFunc = [&](const armnn::TensorInfo& outputInfo, bool& isSupported)
{
- ARMNN_NO_DEPRECATE_WARN_BEGIN
FORWARD_LAYER_SUPPORT_FUNC(__func__,
- IsDivisionSupported,
+ IsElementwiseBinarySupported,
data.m_Backends,
isSupported,
- setBackend,
+ armnn::BackendId(),
input0.GetTensorInfo(),
input1.GetTensorInfo(),
- outputInfo);
- ARMNN_NO_DEPRECATE_WARN_END
+ outputInfo,
+ binaryOperation);
};
- if(!IsDynamicTensor(outputInfo))
+ if (!IsDynamicTensor(outputInfo))
{
validateFunc(outputInfo, isSupported);
}
@@ -1566,18 +1503,18 @@
return false;
}
- ARMNN_NO_DEPRECATE_WARN_BEGIN
- armnn::IConnectableLayer* const startLayer = data.m_Network->AddDivisionLayer();
- ARMNN_NO_DEPRECATE_WARN_END
- startLayer->SetBackendId(setBackend);
-
- bool isReshapeSupported = BroadcastTensor(input0, input1, startLayer, data);
+ armnn::IConnectableLayer* layer = data.m_Network->AddElementwiseBinaryLayer(descriptor);
+ if (!layer)
+ {
+ return Fail("%s: Could not add the ElementwiseBinaryLayer", __func__);
+ }
+ bool isReshapeSupported = BroadcastTensor(input0, input1, layer, data);
if (!isReshapeSupported)
{
return false;
}
- return SetupAndTrackLayerOutputSlot(operation, 0, *startLayer, model,
+ return SetupAndTrackLayerOutputSlot(operation, 0, *layer, model,
data, nullptr, validateFunc, activationFunction);
}
@@ -2082,7 +2019,8 @@
{
return Fail("%s: Operation has invalid or unsupported axis operand", __func__);
}
- if (((axis < -inputDimensions) && (axis < 0)) || ((axis >= inputDimensions) && (axis > 0)))
+ int32_t inputDimensions_int = static_cast<int32_t>(inputDimensions);
+ if ((axis < -inputDimensions_int) || (inputDimensions_int <= axis))
{
return Fail("%s: Operation has invalid axis: %d. It is out of bounds [-%d, %d))", __func__, axis,
inputDimensions, inputDimensions);
@@ -3362,70 +3300,6 @@
return ConvertPooling2d(operation, __func__, PoolingAlgorithm::Max, model, data);
}
-bool Converter::ConvertMaximum(const Operation& operation, const Model& model, ConversionData& data)
-{
- VLOG(DRIVER) << "Converter::ConvertMaximum()";
-
- LayerInputHandle input0 = ConvertToLayerInputHandle(operation, 0, model, data);
- LayerInputHandle input1 = ConvertToLayerInputHandle(operation, 1, model, data);
-
- if (!input0.IsValid() || !input1.IsValid())
- {
- return Fail("%s: Operation has invalid inputs", __func__);
- }
-
- const Operand* outputOperand = GetOutputOperand(operation, 0, model);
- if (!outputOperand)
- {
- return Fail("%s: Could not read output", __func__);
- }
-
- const TensorInfo& outInfo = GetTensorInfoForOperand(*outputOperand);
-
- bool isSupported = false;
- armnn::BackendId setBackend;
- auto validateFunc = [&](const armnn::TensorInfo& outInfo, bool& isSupported)
- {
- ARMNN_NO_DEPRECATE_WARN_BEGIN
- FORWARD_LAYER_SUPPORT_FUNC(__func__,
- IsMaximumSupported,
- data.m_Backends,
- isSupported,
- setBackend,
- input0.GetTensorInfo(),
- input1.GetTensorInfo(),
- outInfo);
- ARMNN_NO_DEPRECATE_WARN_END
- };
-
- if(IsDynamicTensor(outInfo))
- {
- isSupported = AreDynamicTensorsSupported();
- }
- else
- {
- validateFunc(outInfo, isSupported);
- }
-
- if (!isSupported)
- {
- return false;
- }
-
- ARMNN_NO_DEPRECATE_WARN_BEGIN
- IConnectableLayer* layer = data.m_Network->AddMaximumLayer();
- ARMNN_NO_DEPRECATE_WARN_END
- layer->SetBackendId(setBackend);
- assert(layer != nullptr);
- bool isReshapeSupported = BroadcastTensor(input0, input1, layer, data);
- if (!isReshapeSupported)
- {
- return false;
- }
-
- return SetupAndTrackLayerOutputSlot(operation, 0, *layer, model, data, nullptr, validateFunc);
-}
-
bool Converter::ConvertMean(const Operation& operation, const Model& model, ConversionData& data)
{
VLOG(DRIVER) << "Converter::ConvertMean()";
@@ -3512,144 +3386,6 @@
return SetupAndTrackLayerOutputSlot(operation, 0, *layer, model, data, nullptr, validateFunc);
}
-bool Converter::ConvertMinimum(const Operation& operation, const Model& model, ConversionData& data)
-{
- VLOG(DRIVER) << "Converter::ConvertMinimum()";
-
- LayerInputHandle input0 = ConvertToLayerInputHandle(operation, 0, model, data);
- LayerInputHandle input1 = ConvertToLayerInputHandle(operation, 1, model, data);
-
- if (!input0.IsValid() || !input1.IsValid())
- {
- return Fail("%s: Operation has invalid inputs", __func__);
- }
-
- const Operand* output = GetOutputOperand(operation, 0, model);
- if (!output)
- {
- return Fail("%s: Could not read output 0", __func__);
- }
-
- const TensorInfo& outputInfo = GetTensorInfoForOperand(*output);
-
- bool isSupported = false;
- armnn::BackendId setBackend;
- auto validateFunc = [&](const armnn::TensorInfo& outputInfo, bool& isSupported)
- {
- ARMNN_NO_DEPRECATE_WARN_BEGIN
- FORWARD_LAYER_SUPPORT_FUNC(__func__,
- IsMinimumSupported,
- data.m_Backends,
- isSupported,
- setBackend,
- input0.GetTensorInfo(),
- input1.GetTensorInfo(),
- outputInfo);
- ARMNN_NO_DEPRECATE_WARN_END
- };
-
- if(IsDynamicTensor(outputInfo))
- {
- isSupported = AreDynamicTensorsSupported();
- }
- else
- {
- validateFunc(outputInfo, isSupported);
- }
-
- if (!isSupported)
- {
- return false;
- }
-
- ARMNN_NO_DEPRECATE_WARN_BEGIN
- IConnectableLayer* const layer = data.m_Network->AddMinimumLayer();
- ARMNN_NO_DEPRECATE_WARN_END
- layer->SetBackendId(setBackend);
- assert(layer != nullptr);
- bool isReshapeSupported = BroadcastTensor(input0, input1, layer, data);
- if (!isReshapeSupported)
- {
- return false;
- }
-
- return SetupAndTrackLayerOutputSlot(operation, 0, *layer, model, data, nullptr, validateFunc);
-}
-
-bool Converter::ConvertMul(const Operation& operation, const Model& model, ConversionData& data)
-{
- VLOG(DRIVER) << "Converter::ConvertMul()";
-
- LayerInputHandle input0 = ConvertToLayerInputHandle(operation, 0, model, data);
- LayerInputHandle input1 = ConvertToLayerInputHandle(operation, 1, model, data);
-
- if (!input0.IsValid() || !input1.IsValid())
- {
- return Fail("%s: Operation has invalid inputs", __func__);
- }
-
- // The FuseActivation parameter is always the input index 2
- // and it should be optional
- ActivationFn activationFunction;
- if (!GetOptionalInputActivation(operation, 2, activationFunction, model, data))
- {
- return Fail("%s: Operation has invalid inputs", __func__);
- }
-
- const Operand* outputOperand = GetOutputOperand(operation, 0, model);
-
- if (outputOperand == nullptr)
- {
- return false;
- }
-
- const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*outputOperand);
-
- bool isSupported = false;
- armnn::BackendId setBackend;
- auto validateFunc = [&](const armnn::TensorInfo& outputInfo, bool& isSupported)
- {
- ARMNN_NO_DEPRECATE_WARN_BEGIN
- FORWARD_LAYER_SUPPORT_FUNC(__func__,
- IsMultiplicationSupported,
- data.m_Backends,
- isSupported,
- setBackend,
- input0.GetTensorInfo(),
- input1.GetTensorInfo(),
- outputInfo);
- ARMNN_NO_DEPRECATE_WARN_END
- };
-
- if(!IsDynamicTensor(outputInfo))
- {
- validateFunc(outputInfo, isSupported);
- }
- else
- {
- isSupported = AreDynamicTensorsSupported();
- }
-
- if (!isSupported)
- {
- return false;
- }
-
- ARMNN_NO_DEPRECATE_WARN_BEGIN
- armnn::IConnectableLayer* const startLayer = data.m_Network->AddMultiplicationLayer();
- ARMNN_NO_DEPRECATE_WARN_END
- startLayer->SetBackendId(setBackend);
-
- bool isReshapeSupported = BroadcastTensor(input0, input1, startLayer, data);
- if (!isReshapeSupported)
- {
- return false;
- }
-
- return SetupAndTrackLayerOutputSlot(operation, 0, *startLayer, model,
- data, nullptr, validateFunc, activationFunction);
-}
-
bool Converter::ConvertPad(const Operation& operation, const Model& model, ConversionData& data)
{
VLOG(DRIVER) << "Converter::ConvertPad()";
@@ -5328,78 +5064,6 @@
return SetupAndTrackLayerOutputSlot(operation, 0, *layer, model, data, nullptr, validateFunc);
}
-bool Converter::ConvertSub(const Operation& operation, const Model& model, ConversionData& data)
-{
- VLOG(DRIVER) << "Converter::ConvertSub()";
-
- LayerInputHandle input0 = ConvertToLayerInputHandle(operation, 0, model, data);
- LayerInputHandle input1 = ConvertToLayerInputHandle(operation, 1, model, data);
-
- if (!input0.IsValid() || !input1.IsValid())
- {
- return Fail("%s: Operation has invalid inputs", __func__);
- }
-
- // The FuseActivation parameter is always the input index 2
- // and it should be optional
- ActivationFn activationFunction;
- if (!GetOptionalInputActivation(operation, 2, activationFunction, model, data))
- {
- return Fail("%s: Operation has invalid inputs", __func__);
- }
-
- const Operand* output = GetOutputOperand(operation, 0, model);
- if (!output)
- {
- return Fail("%s: Could not read output 0", __func__);
- }
-
- const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*output);
-
- bool isSupported = false;
- armnn::BackendId setBackend;
- auto validateFunc = [&](const armnn::TensorInfo& outputInfo, bool& isSupported)
- {
- ARMNN_NO_DEPRECATE_WARN_BEGIN
- FORWARD_LAYER_SUPPORT_FUNC(__func__,
- IsSubtractionSupported,
- data.m_Backends,
- isSupported,
- setBackend,
- input0.GetTensorInfo(),
- input1.GetTensorInfo(),
- outputInfo);
- ARMNN_NO_DEPRECATE_WARN_END
- };
-
- if(IsDynamicTensor(outputInfo))
- {
- isSupported = AreDynamicTensorsSupported();
- }
- else
- {
- validateFunc(outputInfo, isSupported);
- }
-
- if (!isSupported)
- {
- return false;
- }
-
- ARMNN_NO_DEPRECATE_WARN_BEGIN
- armnn::IConnectableLayer* const startLayer = data.m_Network->AddSubtractionLayer();
- ARMNN_NO_DEPRECATE_WARN_END
- startLayer->SetBackendId(setBackend);
-
- bool isReshapeSupported = BroadcastTensor(input0, input1, startLayer, data);
- if (!isReshapeSupported)
- {
- return false;
- }
- return SetupAndTrackLayerOutputSlot(operation, 0, *startLayer, model,
- data, nullptr, validateFunc, activationFunction);
-}
-
bool Converter::ConvertTanH(const Operation& operation, const Model& model, ConversionData& data)
{
VLOG(DRIVER) << "Converter::ConvertTanH()";
diff --git a/shim/sl/canonical/Converter.hpp b/shim/sl/canonical/Converter.hpp
index 7e4a89e..bf660b9 100644
--- a/shim/sl/canonical/Converter.hpp
+++ b/shim/sl/canonical/Converter.hpp
@@ -1,5 +1,5 @@
//
-// Copyright © 2022 Arm Ltd and Contributors. All rights reserved.
+// Copyright © 2022-2023 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
@@ -31,8 +31,6 @@
static bool ConvertOperation(const Operation& operation, const Model& model, ConversionData& data);
private:
- static bool ConvertAdd(const Operation& operation, const Model& model, ConversionData& data);
-
static bool ConvertArgMinMax(const Operation& operation,
const Model& model,
ConversionData& data,
@@ -61,13 +59,16 @@
static bool ConvertDequantize(const Operation& operation, const Model& model, ConversionData& data);
- static bool ConvertDiv(const Operation& operation, const Model& model, ConversionData& data);
-
static bool ConvertElementwiseUnary(const Operation& operation,
const Model& model,
ConversionData& data,
armnn::UnaryOperation unaryOperation);
+ static bool ConvertElementwiseBinary(const Operation& operation,
+ const Model& model,
+ ConversionData& data,
+ armnn::BinaryOperation binaryOperation);
+
static bool ConvertElu(const Operation& operation, const Model& model, ConversionData& data);
static bool ConvertExpandDims(const Operation& operation, const Model& model, ConversionData& data);
@@ -107,14 +108,8 @@
static bool ConvertMaxPool2d(const Operation& operation, const Model& model, ConversionData& data);
- static bool ConvertMaximum(const Operation& operation, const Model& model, ConversionData& data);
-
static bool ConvertMean(const Operation& operation, const Model& model, ConversionData& data);
- static bool ConvertMinimum(const Operation& operation, const Model& model, ConversionData& data);
-
- static bool ConvertMul(const Operation& operation, const Model& model, ConversionData& data);
-
static bool ConvertPad(const Operation& operation, const Model& model, ConversionData& data);
static bool ConvertPadV2(const Operation& operation, const Model& model, ConversionData& data);
@@ -154,8 +149,6 @@
static bool ConvertStridedSlice(const Operation& operation, const Model& model, ConversionData& data);
- static bool ConvertSub(const Operation& operation, const Model& model, ConversionData& data);
-
static bool ConvertTanH(const Operation& operation, const Model& model, ConversionData& data);
static bool ConvertTranspose(const Operation& operation, const Model& model, ConversionData& data);