diff options
| -rw-r--r-- | 1.0/HalPolicy.cpp | 61 | ||||
| -rw-r--r-- | 1.1/HalPolicy.cpp | 132 | ||||
| -rw-r--r-- | 1.2/HalPolicy.cpp | 191 | ||||
| -rw-r--r-- | Android.mk | 3 | ||||
| -rw-r--r-- | ConversionUtils.hpp | 78 | ||||
| -rw-r--r-- | OutputShapeUtils.cpp | 199 | ||||
| -rw-r--r-- | OutputShapeUtils.hpp | 40 |
7 files changed, 169 insertions, 535 deletions
diff --git a/1.0/HalPolicy.cpp b/1.0/HalPolicy.cpp index 8dd603a6..db0e2a2d 100644 --- a/1.0/HalPolicy.cpp +++ b/1.0/HalPolicy.cpp @@ -8,7 +8,6 @@ #include <armnn/Optional.hpp> #include "FullyConnected.hpp" -#include "OutputShapeUtils.hpp" #include "Utils.hpp" namespace armnn_driver @@ -122,7 +121,7 @@ bool HalPolicy::ConvertAdd(const Operation& operation, const Model& model, Conve const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*outputOperand); if (IsDynamicTensor(outputInfo)) { - return Fail("%s: Dynamic output shapes are not supported in this HAL version", __func__); + return Fail("%s: Dynamic output tensors are not supported", __func__); } bool isSupported = false; @@ -418,11 +417,10 @@ bool HalPolicy::ConvertDequantize(const Operation& operation, const Model& model return Fail("%s: Operation has invalid outputs", __func__); } - armnn::TensorInfo outputInfo = GetTensorInfoForOperand(*outputOperand); + const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*outputOperand); if (IsDynamicTensor(outputInfo)) { - ALOGD("Output shape not set, will infer from input"); - outputInfo.SetShape(input.GetTensorInfo().GetShape()); + return Fail("%s: Dynamic output tensors are not supported", __func__); } bool isSupported = false; @@ -441,12 +439,7 @@ bool HalPolicy::ConvertDequantize(const Operation& operation, const Model& model assert(layer != nullptr); input.Connect(layer->GetInputSlot(0)); - return SetupAndTrackLayerOutputSlot<hal_1_0::HalPolicy>(operation, - 0, - *layer, - model, - data, - armnn::Optional<armnn::TensorInfo>(outputInfo)); + return SetupAndTrackLayerOutputSlot<hal_1_0::HalPolicy>(operation, 0, *layer, model, data); } bool HalPolicy::ConvertFloor(const Operation& operation, const Model& model, ConversionData& data) @@ -465,13 +458,19 @@ bool HalPolicy::ConvertFloor(const Operation& operation, const Model& model, Con return Fail("%s: Operation has invalid outputs", __func__); } + const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*outputOperand); + if (IsDynamicTensor(outputInfo)) + { + return Fail("%s: Dynamic output tensors are not supported", __func__); + } + bool isSupported = false; FORWARD_LAYER_SUPPORT_FUNC(__func__, IsFloorSupported, data.m_Backends, isSupported, input.GetTensorInfo(), - GetTensorInfoForOperand(*outputOperand)); + outputInfo); if (!isSupported) { return false; @@ -500,13 +499,12 @@ bool HalPolicy::ConvertFullyConnected(const Operation& operation, const Model& m return Fail("%s: Could not read output 0", __func__); } - const armnn::TensorInfo& inputInfo = input.GetTensorInfo(); - armnn::TensorInfo outputInfo = GetTensorInfoForOperand(*output); + const armnn::TensorInfo& inputInfo = input.GetTensorInfo(); + const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*output); if (IsDynamicTensor(outputInfo)) { - ALOGD("Output shape not set, will infer from inputs"); - outputInfo.SetShape(inputInfo.GetShape()); + return Fail("%s: Dynamic output tensors are not supported", __func__); } // ArmNN does not currently support non-fixed weights or bias @@ -581,12 +579,7 @@ bool HalPolicy::ConvertFullyConnected(const Operation& operation, const Model& m input.Connect(startLayer->GetInputSlot(0)); } - return SetupAndTrackLayerOutputSlot<hal_1_0::HalPolicy>(operation, - 0, - *endLayer, - model, - data, - armnn::Optional<armnn::TensorInfo>(outputInfo)); + return SetupAndTrackLayerOutputSlot<hal_1_0::HalPolicy>(operation, 0, *endLayer, model, data); } else { @@ -1036,12 +1029,11 @@ bool HalPolicy::ConvertL2Normalization(const Operation& operation, const Model& } const armnn::TensorInfo& inputInfo = input.GetTensorInfo(); - armnn::TensorInfo outputInfo = GetTensorInfoForOperand(*output); + const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*output); if (IsDynamicTensor(outputInfo)) { - ALOGD("Output shape not set, will infer from inputs"); - outputInfo.SetShape(inputInfo.GetShape()); + return Fail("%s: Dynamic output tensors are not supported", __func__); } armnn::L2NormalizationDescriptor desc; @@ -1064,12 +1056,7 @@ bool HalPolicy::ConvertL2Normalization(const Operation& operation, const Model& assert(layer != nullptr); input.Connect(layer->GetInputSlot(0)); - return SetupAndTrackLayerOutputSlot<hal_1_0::HalPolicy>(operation, - 0, - *layer, - model, - data, - armnn::Optional<armnn::TensorInfo>(outputInfo)); + return SetupAndTrackLayerOutputSlot<hal_1_0::HalPolicy>(operation, 0, *layer, model, data); } bool HalPolicy::ConvertL2Pool2d(const Operation& operation, const Model& model, ConversionData& data) @@ -1177,11 +1164,10 @@ bool HalPolicy::ConvertSoftmax(const Operation& operation, const Model& model, C return Fail("%s: Operation has no outputs", __func__); } - armnn::TensorInfo outputInfo = GetTensorInfoForOperand(*outputOperand); + const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*outputOperand); if (IsDynamicTensor(outputInfo)) { - ALOGD("Output shape not set, will infer from input"); - outputInfo.SetShape(input.GetTensorInfo().GetShape()); + return Fail("%s: Dynamic output tensors are not supported", __func__); } armnn::SoftmaxDescriptor desc; @@ -1207,12 +1193,7 @@ bool HalPolicy::ConvertSoftmax(const Operation& operation, const Model& model, C assert(layer != nullptr); input.Connect(layer->GetInputSlot(0)); - return SetupAndTrackLayerOutputSlot<hal_1_0::HalPolicy>(operation, - 0, - *layer, - model, - data, - armnn::Optional<armnn::TensorInfo>(outputInfo)); + return SetupAndTrackLayerOutputSlot<hal_1_0::HalPolicy>(operation, 0, *layer, model, data); } bool HalPolicy::ConvertSpaceToDepth(const Operation& operation, const Model& model, ConversionData& data) diff --git a/1.1/HalPolicy.cpp b/1.1/HalPolicy.cpp index bbd289ee..ab8224a0 100644 --- a/1.1/HalPolicy.cpp +++ b/1.1/HalPolicy.cpp @@ -5,7 +5,6 @@ #include "HalPolicy.hpp" -#include "OutputShapeUtils.hpp" #include "Utils.hpp" #include "../1.0/HalPolicy.hpp" @@ -124,13 +123,17 @@ bool HalPolicy::ConvertDiv(const Operation& operation, const Model& model, Conve return Fail("%s: Operation has invalid inputs", __func__); } - const Operand* outputOperand = GetOutputOperand<hal_1_1::HalPolicy>(operation, 0, model); - if (!outputOperand) + const Operand* output = GetOutputOperand<hal_1_1::HalPolicy>(operation, 0, model); + if (!output) { - return false; + return Fail("%s: Could not read output 0", __func__); } - const armnn::TensorInfo& outInfo = GetTensorInfoForOperand(*outputOperand); + const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*output); + if (IsDynamicTensor(outputInfo)) + { + return Fail("%s: Dynamic output tensors are not supported", __func__); + } bool isSupported = false; FORWARD_LAYER_SUPPORT_FUNC(__func__, @@ -139,14 +142,14 @@ bool HalPolicy::ConvertDiv(const Operation& operation, const Model& model, Conve isSupported, input0.GetTensorInfo(), input1.GetTensorInfo(), - outInfo); + outputInfo); if (!isSupported) { return false; } armnn::IConnectableLayer* const startLayer = data.m_Network->AddDivisionLayer(); - armnn::IConnectableLayer* const endLayer = ProcessActivation(outInfo, activationFunction, startLayer, data); + armnn::IConnectableLayer* const endLayer = ProcessActivation(outputInfo, activationFunction, startLayer, data); const armnn::TensorInfo& inputTensorInfo0 = input0.GetTensorInfo(); const armnn::TensorInfo& inputTensorInfo1 = input1.GetTensorInfo(); @@ -180,17 +183,16 @@ bool HalPolicy::ConvertSub(const Operation& operation, const Model& model, Conve return Fail("%s: Operation has invalid inputs", __func__); } - const Operand* outputOperand = GetOutputOperand<hal_1_1::HalPolicy>(operation, 0, model); - if (!outputOperand) + const Operand* output = GetOutputOperand<hal_1_1::HalPolicy>(operation, 0, model); + if (!output) { - return false; + return Fail("%s: Could not read output 0", __func__); } - armnn::TensorInfo outputInfo = GetTensorInfoForOperand(*outputOperand); + const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*output); if (IsDynamicTensor(outputInfo)) { - ALOGD("Output shape not set, will infer from inputs"); - outputInfo.SetShape(InferSubOutputShape(input0.GetTensorInfo().GetShape(), input1.GetTensorInfo().GetShape())); + return Fail("%s: Dynamic output tensors are not supported", __func__); } bool isSupported = false; @@ -215,12 +217,7 @@ bool HalPolicy::ConvertSub(const Operation& operation, const Model& model, Conve if (endLayer) { BroadcastTensor(input0, input1, startLayer, *data.m_Network); - return SetupAndTrackLayerOutputSlot<hal_1_1::HalPolicy>(operation, - 0, - *endLayer, - model, - data, - armnn::Optional<armnn::TensorInfo>(outputInfo)); + return SetupAndTrackLayerOutputSlot<hal_1_1::HalPolicy>(operation, 0, *endLayer, model, data); } return Fail("%s: ProcessActivation failed", __func__); @@ -236,6 +233,18 @@ bool HalPolicy::ConvertMean(const Operation& operation, const Model& model, Conv return Fail("%s: Operation has invalid inputs", __func__); } + const Operand* output = GetOutputOperand<hal_1_1::HalPolicy>(operation, 0, model); + if (!output) + { + return Fail("%s: Could not read output 0", __func__); + } + + const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*output); + if (IsDynamicTensor(outputInfo)) + { + return Fail("%s: Dynamic output tensors are not supported", __func__); + } + const Operand* axisOperand = GetInputOperand<hal_1_1::HalPolicy>(operation, 1, model); if (!axisOperand) { @@ -268,14 +277,6 @@ bool HalPolicy::ConvertMean(const Operation& operation, const Model& model, Conv descriptor.m_Axis.assign(uniqueAxis.begin(), uniqueAxis.end()); descriptor.m_KeepDims = keepDims > 0; - const Operand* output = GetOutputOperand<hal_1_1::HalPolicy>(operation, 0, model); - if (!output) - { - return Fail("%s: Could not read output 0", __func__); - } - - const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*output); - bool isSupported = false; FORWARD_LAYER_SUPPORT_FUNC(__func__, IsMeanSupported, @@ -321,6 +322,18 @@ bool HalPolicy::ConvertSpaceToBatchNd(const Operation& operation, const Model& m Fail("%s: Only inputs with rank 4 are supported", __func__); } + const Operand* output = GetOutputOperand<hal_1_1::HalPolicy>(operation, 0, model); + if (!output) + { + return Fail("%s: Could not read output 0", __func__); + } + + const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*output); + if (IsDynamicTensor(outputInfo)) + { + return Fail("%s: Dynamic output tensors are not supported", __func__); + } + const Operand* blockShapeOperand = GetInputOperand<hal_1_1::HalPolicy>(operation, 1, model); const Operand* paddingsOperand = GetInputOperand<hal_1_1::HalPolicy>(operation, 2, model); @@ -363,14 +376,6 @@ bool HalPolicy::ConvertSpaceToBatchNd(const Operation& operation, const Model& m descriptor.m_BlockShape.assign(blockShape.cbegin(), blockShape.cend()); descriptor.m_PadList.assign(paddingList.cbegin(), paddingList.cend()); - const Operand* output = GetOutputOperand<hal_1_1::HalPolicy>(operation, 0, model); - if (!output) - { - return Fail("%s: Could not read output 0", __func__); - } - - const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*output); - bool isSupported = false; FORWARD_LAYER_SUPPORT_FUNC(__func__, IsSpaceToBatchNdSupported, @@ -402,13 +407,23 @@ bool HalPolicy::ConvertSqueeze(const Operation& operation, const Model& model, C } const armnn::TensorInfo& inputInfo = input.GetTensorInfo(); - unsigned int rank = inputInfo.GetNumDimensions(); if (rank > 4) { Fail("%s: Inputs with rank greater than 4 are not supported", __func__); } + const Operand* output = GetOutputOperand<hal_1_1::HalPolicy>(operation, 0, model); + if (!output) + { + return Fail("%s: Could not read output 0", __func__); + } + + if (IsDynamicTensor(GetTensorInfoForOperand(*output))) + { + return Fail("%s: Dynamic output tensors are not supported", __func__); + } + // NOTE: Axis is an optional parameter to SQUEEZE, therefore we do not want to generate a failure // if the operand index is out of bounds. const Operand* axisOperand = GetInputOperand<hal_1_1::HalPolicy>(operation, 1, model, false); @@ -446,12 +461,6 @@ bool HalPolicy::ConvertSqueeze(const Operation& operation, const Model& model, C armnn::ReshapeDescriptor reshapeDesc; reshapeDesc.m_TargetShape = outputInfo.GetShape(); - const Operand* output = GetOutputOperand<hal_1_1::HalPolicy>(operation, 0, model); - if (!output) - { - return Fail("%s: Could not read output 0", __func__); - } - bool isSupported = false; FORWARD_LAYER_SUPPORT_FUNC(__func__, IsReshapeSupported, @@ -488,6 +497,18 @@ bool HalPolicy::ConvertStridedSlice(const Operation& operation, const Model& mod Fail("%s: Inputs with rank greater than 4 are not supported", __func__); } + const Operand* output = GetOutputOperand<hal_1_1::HalPolicy>(operation, 0, model); + if (!output) + { + return Fail("%s: Could not read output 0", __func__); + } + + const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*output); + if (IsDynamicTensor(outputInfo)) + { + return Fail("%s: Dynamic output tensors are not supported", __func__); + } + const Operand* beginOperand = GetInputOperand<hal_1_1::HalPolicy>(operation, 1, model); const Operand* endOperand = GetInputOperand<hal_1_1::HalPolicy>(operation, 2, model); const Operand* stridesOperand = GetInputOperand<hal_1_1::HalPolicy>(operation, 3, model); @@ -539,13 +560,6 @@ bool HalPolicy::ConvertStridedSlice(const Operation& operation, const Model& mod return Fail("%s: Operation has invalid inputs", __func__); } - const Operand* output = GetOutputOperand<hal_1_1::HalPolicy>(operation, 0, model); - if (!output) - { - return Fail("%s: Could not read output 0", __func__); - } - const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*output); - bool isSupported = false; FORWARD_LAYER_SUPPORT_FUNC(__func__, IsStridedSliceSupported, @@ -652,6 +666,18 @@ bool HalPolicy::ConvertBatchToSpaceNd(const Operation& operation, const Model& m return Fail("%s: Operation has invalid inputs", __func__); } + const Operand* output = GetOutputOperand<hal_1_1::HalPolicy>(operation, 0, model); + if (!output) + { + return Fail("%s: Could not read output 0", __func__); + } + + const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*output); + if (IsDynamicTensor(outputInfo)) + { + return Fail("%s: Dynamic output tensors are not supported", __func__); + } + const Operand* blockOperand = GetInputOperand<hal_1_1::HalPolicy>(operation, 1, model); if (!blockOperand) { @@ -686,14 +712,6 @@ bool HalPolicy::ConvertBatchToSpaceNd(const Operation& operation, const Model& m // Setting crops to 0,0 0,0 as it is not supported in Android NN API batchToSpaceNdDesc.m_Crops = {{0, 0}, {0, 0}}; - const Operand* output = GetOutputOperand<hal_1_1::HalPolicy>(operation, 0, model); - if (!output) - { - return Fail("%s: Could not read output 0", __func__); - } - - const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*output); - bool isSupported = false; FORWARD_LAYER_SUPPORT_FUNC(__func__, IsBatchToSpaceNdSupported, diff --git a/1.2/HalPolicy.cpp b/1.2/HalPolicy.cpp index 4ef7ea4f..7515eb3e 100644 --- a/1.2/HalPolicy.cpp +++ b/1.2/HalPolicy.cpp @@ -5,7 +5,6 @@ #include "HalPolicy.hpp" -#include "OutputShapeUtils.hpp" #include "Utils.hpp" #include "../1.0/HalPolicy.hpp" @@ -184,8 +183,13 @@ bool HalPolicy::ConvertConv2d(const Operation& operation, const Model& model, Co return Fail("%s: Could not read output 0", __func__); } - const armnn::TensorInfo& inputInfo = input.GetTensorInfo(); - armnn::TensorInfo outputInfo = GetTensorInfoForOperand(*output); + const armnn::TensorInfo& inputInfo = input.GetTensorInfo(); + const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*output); + + if (IsDynamicTensor(outputInfo)) + { + return Fail("%s: Dynamic output tensors are not supported", __func__); + } armnn::Convolution2dDescriptor desc; desc.m_DataLayout = armnn::DataLayout::NHWC; @@ -279,21 +283,6 @@ bool HalPolicy::ConvertConv2d(const Operation& operation, const Model& model, Co desc.m_BiasEnabled = true; armnn::Optional<armnn::TensorInfo> biases(bias.GetInfo()); - if (IsDynamicTensor(outputInfo)) - { - try - { - ALOGD("Output shape not set, will infer from inputs"); - outputInfo.SetShape(InferConvolution2dOutputShape(inputInfo.GetShape(), - weights.GetInfo().GetShape(), - desc)); - } - catch (armnn::Exception& e) - { - return Fail("%s: Could not infer dynamic output shape: %s", __func__, e.what()); - } - } - bool isSupported = false; FORWARD_LAYER_SUPPORT_FUNC(__func__, IsConvolution2dSupported, @@ -327,12 +316,7 @@ bool HalPolicy::ConvertConv2d(const Operation& operation, const Model& model, Co input.Connect(startLayer->GetInputSlot(0)); - return SetupAndTrackLayerOutputSlot<hal_1_2::HalPolicy>(operation, - 0, - *endLayer, - model, - data, - armnn::Optional<armnn::TensorInfo>(outputInfo)); + return SetupAndTrackLayerOutputSlot<hal_1_2::HalPolicy>(operation, 0, *endLayer, model, data); } bool HalPolicy::ConvertDepthwiseConv2d(const Operation& operation, const Model& model, ConversionData& data) @@ -354,6 +338,12 @@ bool HalPolicy::ConvertDepthwiseConv2d(const Operation& operation, const Model& } const armnn::TensorInfo& inputInfo = input.GetTensorInfo(); + const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*output); + + if (IsDynamicTensor(outputInfo)) + { + return Fail("%s: Dynamic output tensors are not supported", __func__); + } // ArmNN does not currently support non-fixed weights or bias // Find the shape of the weights tensor. In AndroidNN this will be [ 1, H, W, I * M ] @@ -460,22 +450,6 @@ bool HalPolicy::ConvertDepthwiseConv2d(const Operation& operation, const Model& desc.m_BiasEnabled = true; armnn::Optional<armnn::TensorInfo> biases(bias.GetInfo()); - armnn::TensorInfo outputInfo = GetTensorInfoForOperand(*output); - if (IsDynamicTensor(outputInfo)) - { - try - { - ALOGD("Output shape not set, will infer from inputs"); - outputInfo.SetShape(InferDepthwiseConvolution2dOutputShape(inputInfo.GetShape(), - weights.GetInfo().GetShape(), - desc)); - } - catch (armnn::Exception& e) - { - return Fail("%s: Could not infer dynamic output shape: %s", __func__, e.what()); - } - } - bool isSupported = false; FORWARD_LAYER_SUPPORT_FUNC(__func__, IsDepthwiseConvolutionSupported, @@ -508,12 +482,7 @@ bool HalPolicy::ConvertDepthwiseConv2d(const Operation& operation, const Model& input.Connect(startLayer->GetInputSlot(0)); - return SetupAndTrackLayerOutputSlot<hal_1_2::HalPolicy>(operation, - 0, - *endLayer, - model, - data, - armnn::Optional<armnn::TensorInfo>(outputInfo)); + return SetupAndTrackLayerOutputSlot<hal_1_2::HalPolicy>(operation, 0, *endLayer, model, data); } bool HalPolicy::ConvertMaximum(const Operation& operation, const Model& model, ConversionData& data) @@ -534,11 +503,10 @@ bool HalPolicy::ConvertMaximum(const Operation& operation, const Model& model, C return Fail("%s: Could not read output", __func__); } - armnn::TensorInfo outInfo = GetTensorInfoForOperand(*outputOperand); + const armnn::TensorInfo& outInfo = GetTensorInfoForOperand(*outputOperand); if (IsDynamicTensor(outInfo)) { - ALOGD("Output shape not set, will infer from inputs"); - outInfo.SetShape(InferMaximumOutputShape(input0.GetTensorInfo().GetShape(), input1.GetTensorInfo().GetShape())); + return Fail("%s: Dynamic output tensors are not supported", __func__); } bool isSupported = false; @@ -559,12 +527,7 @@ bool HalPolicy::ConvertMaximum(const Operation& operation, const Model& model, C assert(layer != nullptr); BroadcastTensor(input0, input1, layer, *data.m_Network); - return SetupAndTrackLayerOutputSlot<hal_1_2::HalPolicy>(operation, - 0, - *layer, - model, - data, - armnn::Optional<armnn::TensorInfo>(outInfo)); + return SetupAndTrackLayerOutputSlot<hal_1_2::HalPolicy>(operation, 0, *layer, model, data); } bool HalPolicy::ConvertMinimum(const Operation& operation, const Model& model, ConversionData& data) @@ -585,12 +548,10 @@ bool HalPolicy::ConvertMinimum(const Operation& operation, const Model& model, C return Fail("%s: Could not read output 0", __func__); } - armnn::TensorInfo outputInfo = GetTensorInfoForOperand(*output); + const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*output); if (IsDynamicTensor(outputInfo)) { - ALOGD("Output shape not set, will infer from inputs"); - outputInfo.SetShape(InferMinimumOutputShape(input0.GetTensorInfo().GetShape(), - input1.GetTensorInfo().GetShape())); + return Fail("%s: Dynamic output tensors are not supported", __func__); } bool isSupported = false; @@ -611,12 +572,7 @@ bool HalPolicy::ConvertMinimum(const Operation& operation, const Model& model, C assert(layer != nullptr); BroadcastTensor(input0, input1, layer, *data.m_Network); - return SetupAndTrackLayerOutputSlot<hal_1_2::HalPolicy>(operation, - 0, - *layer, - model, - data, - armnn::Optional<armnn::TensorInfo>(outputInfo)); + return SetupAndTrackLayerOutputSlot<hal_1_2::HalPolicy>(operation, 0, *layer, model, data); } bool HalPolicy::ConvertPad(const Operation& operation, const Model& model, ConversionData& data) @@ -650,11 +606,10 @@ bool HalPolicy::ConvertPadV2(const Operation& operation, const Model& model, Con return Fail("%s: Could not convert paddings", __func__); } - armnn::TensorInfo outputInfo = GetTensorInfoForOperand(*output); + const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*output); if (IsDynamicTensor(outputInfo)) { - ALOGD("Output shape not set, will infer from inputs"); - outputInfo.SetShape(InferPadOutputShape(inputInfo.GetShape(), descriptor.m_PadList)); + return Fail("%s: Dynamic output tensors are not supported", __func__); } // Determine type of padding value @@ -717,12 +672,7 @@ bool HalPolicy::ConvertPadV2(const Operation& operation, const Model& model, Con input.Connect(layer->GetInputSlot(0)); layer->GetOutputSlot(0).SetTensorInfo(outputInfo); - return SetupAndTrackLayerOutputSlot<hal_1_2::HalPolicy>(operation, - 0, - *layer, - model, - data, - armnn::Optional<armnn::TensorInfo>(outputInfo)); + return SetupAndTrackLayerOutputSlot<hal_1_2::HalPolicy>(operation, 0, *layer, model, data); } bool HalPolicy::ConvertPrelu(const Operation& operation, const Model& model, ConversionData& data) @@ -746,12 +696,11 @@ bool HalPolicy::ConvertPrelu(const Operation& operation, const Model& model, Con const armnn::TensorInfo& inputInfo = input.GetTensorInfo(); const armnn::TensorInfo& alphaInfo = alpha.GetTensorInfo(); + const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*output); - armnn::TensorInfo outputInfo = GetTensorInfoForOperand(*output); if (IsDynamicTensor(outputInfo)) { - ALOGD("Output shape not set, will infer from inputs"); - outputInfo.SetShape(InferPreluOutputShape(inputInfo.GetShape(), alphaInfo.GetShape())); + return Fail("%s: Dynamic output tensors are not supported", __func__); } bool isSupported = false; @@ -776,12 +725,7 @@ bool HalPolicy::ConvertPrelu(const Operation& operation, const Model& model, Con BroadcastTensor(input, alpha, layer, *data.m_Network); - return SetupAndTrackLayerOutputSlot<hal_1_2::HalPolicy>(operation, - 0, - *layer, - model, - data, - armnn::Optional<armnn::TensorInfo>(outputInfo)); + return SetupAndTrackLayerOutputSlot<hal_1_2::HalPolicy>(operation, 0, *layer, model, data); } bool HalPolicy::ConvertReLu(const Operation& operation, const Model& model, ConversionData& data) @@ -821,8 +765,13 @@ bool HalPolicy::ConvertResize(const Operation& operation, return Fail("%s: Could not read output 0", __func__); } - const armnn::TensorInfo& inputInfo = input.GetTensorInfo(); - armnn::TensorInfo outputInfo = GetTensorInfoForOperand(*output); + const armnn::TensorInfo& inputInfo = input.GetTensorInfo(); + const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*output); + + if (IsDynamicTensor(outputInfo)) + { + return Fail("%s: Dynamic output tensors are not supported", __func__); + } armnn::ResizeDescriptor descriptor; descriptor.m_Method = resizeMethod; @@ -890,19 +839,6 @@ bool HalPolicy::ConvertResize(const Operation& operation, return false; } - if (IsDynamicTensor(outputInfo)) - { - try - { - ALOGD("Output shape not set, will infer from inputs"); - outputInfo.SetShape(InferResizeOutputShape(inputInfo.GetShape(), descriptor)); - } - catch (armnn::Exception& e) - { - return Fail("%s: Could not infer dynamic output shape: %s", __func__, e.what()); - } - } - bool isSupported = false; FORWARD_LAYER_SUPPORT_FUNC(__func__, IsResizeSupported, @@ -924,12 +860,7 @@ bool HalPolicy::ConvertResize(const Operation& operation, layer->GetOutputSlot(0).SetTensorInfo(outputInfo); input.Connect(layer->GetInputSlot(0)); - return SetupAndTrackLayerOutputSlot<hal_1_2::HalPolicy>(operation, - 0, - *layer, - model, - data, - armnn::Optional<armnn::TensorInfo>(outputInfo)); + return SetupAndTrackLayerOutputSlot<hal_1_2::HalPolicy>(operation, 0, *layer, model, data); } bool HalPolicy::ConvertSpaceToDepth(const Operation& operation, const Model& model, ConversionData& data) @@ -944,12 +875,23 @@ bool HalPolicy::ConvertSpaceToDepth(const Operation& operation, const Model& mod const armnn::TensorInfo& inputInfo = input.GetTensorInfo(); unsigned int rank = inputInfo.GetNumDimensions(); - if (rank != 4) { return Fail("%s: Only inputs with rank 4 are supported", __func__); } + const Operand* output = GetOutputOperand<hal_1_2::HalPolicy>(operation, 0, model); + if (!output) + { + return Fail("%s: Could not read output 0", __func__); + } + + const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*output); + if (IsDynamicTensor(outputInfo)) + { + return Fail("%s: Dynamic output tensors are not supported", __func__); + } + armnn::SpaceToDepthDescriptor desc; GetInputScalar<hal_1_2::HalPolicy>(operation, 1, OperandType::INT32, desc.m_BlockSize, model, data); @@ -961,26 +903,6 @@ bool HalPolicy::ConvertSpaceToDepth(const Operation& operation, const Model& mod desc.m_DataLayout = OptionalDataLayout<hal_1_2::HalPolicy>(operation, 2, model, data); - const Operand* output = GetOutputOperand<hal_1_2::HalPolicy>(operation, 0, model); - if (!output) - { - return Fail("%s: Could not read output 0", __func__); - } - - armnn::TensorInfo outputInfo = GetTensorInfoForOperand(*output); - if (IsDynamicTensor(outputInfo)) - { - try - { - ALOGD("Output shape not set, will infer from inputs"); - outputInfo.SetShape(InferSpaceToDepthOutputShape(inputInfo.GetShape(), desc)); - } - catch (armnn::Exception& e) - { - return Fail("%s: Could not infer dynamic output shape: %s", __func__, e.what()); - } - } - bool isSupported = false; FORWARD_LAYER_SUPPORT_FUNC(__func__, IsSpaceToDepthSupported, @@ -998,12 +920,7 @@ bool HalPolicy::ConvertSpaceToDepth(const Operation& operation, const Model& mod assert(layer != nullptr); input.Connect(layer->GetInputSlot(0)); - return SetupAndTrackLayerOutputSlot<hal_1_2::HalPolicy>(operation, - 0, - *layer, - model, - data, - armnn::Optional<armnn::TensorInfo>(outputInfo)); + return SetupAndTrackLayerOutputSlot<hal_1_2::HalPolicy>(operation, 0, *layer, model, data); } bool HalPolicy::ConvertSoftmax(const Operation& operation, const Model& model, ConversionData& data) @@ -1022,11 +939,10 @@ bool HalPolicy::ConvertSoftmax(const Operation& operation, const Model& model, C return Fail("%s: Operation has no outputs", __func__); } - armnn::TensorInfo outputInfo = GetTensorInfoForOperand(*outputOperand); + const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*outputOperand); if (IsDynamicTensor(outputInfo)) { - ALOGD("Output shape not set, will infer from input"); - outputInfo.SetShape(input.GetTensorInfo().GetShape()); + return Fail("%s: Dynamic output tensors are not supported", __func__); } armnn::SoftmaxDescriptor desc; @@ -1062,12 +978,7 @@ bool HalPolicy::ConvertSoftmax(const Operation& operation, const Model& model, C assert(layer != nullptr); input.Connect(layer->GetInputSlot(0)); - return SetupAndTrackLayerOutputSlot<hal_1_2::HalPolicy>(operation, - 0, - *layer, - model, - data, - armnn::Optional<armnn::TensorInfo>(outputInfo)); + return SetupAndTrackLayerOutputSlot<hal_1_2::HalPolicy>(operation, 0, *layer, model, data); } bool HalPolicy::ConvertTanH(const Operation& operation, const Model& model, ConversionData& data) @@ -114,7 +114,6 @@ LOCAL_SRC_FILES := \ ArmnnDevice.cpp \ ArmnnPreparedModel.cpp \ ModelToINetworkConverter.cpp \ - OutputShapeUtils.cpp \ RequestThread.cpp \ Utils.cpp \ ConversionUtils.cpp @@ -228,7 +227,6 @@ LOCAL_SRC_FILES := \ ArmnnDevice.cpp \ ArmnnPreparedModel.cpp \ ModelToINetworkConverter.cpp \ - OutputShapeUtils.cpp \ RequestThread.cpp \ Utils.cpp \ ConversionUtils.cpp @@ -336,7 +334,6 @@ LOCAL_SRC_FILES := \ ConversionUtils.cpp \ DriverOptions.cpp \ ModelToINetworkConverter.cpp \ - OutputShapeUtils.cpp \ RequestThread.cpp \ Utils.cpp diff --git a/ConversionUtils.hpp b/ConversionUtils.hpp index 694e1b20..9a2b08f0 100644 --- a/ConversionUtils.hpp +++ b/ConversionUtils.hpp @@ -5,7 +5,6 @@ #pragma once -#include "OutputShapeUtils.hpp" #include "Utils.hpp" #include <armnn/ArmNN.hpp> @@ -1079,8 +1078,7 @@ bool SetupAndTrackLayerOutputSlot(const HalOperation& operation, armnn::IConnectableLayer& layer, uint32_t layerOutputIndex, const HalModel& model, - ConversionData& data, - const armnn::Optional<armnn::TensorInfo>& outputInfo = armnn::EmptyOptional()) + ConversionData& data) { using HalOperand = typename HalPolicy::Operand; @@ -1095,15 +1093,7 @@ bool SetupAndTrackLayerOutputSlot(const HalOperation& operation, const uint32_t operandIndex = operation.outputs[operationOutputIndex]; data.m_OutputSlotForOperand[operandIndex] = &outputSlot; - if (outputInfo.has_value()) - { - outputSlot.SetTensorInfo(outputInfo.value()); - ALOGD("Output info overwritten"); - } - else - { - outputSlot.SetTensorInfo(GetTensorInfoForOperand(*outputOperand)); - } + outputSlot.SetTensorInfo(GetTensorInfoForOperand(*outputOperand)); return true; } @@ -1152,16 +1142,14 @@ bool SetupAndTrackLayerOutputSlot(const HalOperation& operation, uint32_t outputIndex, armnn::IConnectableLayer& layer, const HalModel& model, - ConversionData& data, - const armnn::Optional<armnn::TensorInfo>& outputInfo = armnn::EmptyOptional()) + ConversionData& data) { return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, outputIndex, layer, outputIndex, model, - data, - outputInfo); + data); } template<typename HalPolicy, @@ -1186,18 +1174,11 @@ bool ConvertToActivation(const HalOperation& operation, { return false; } - armnn::TensorInfo outInfo = GetTensorInfoForOperand(*outputOperand); + + const armnn::TensorInfo& outInfo = GetTensorInfoForOperand(*outputOperand); if (IsDynamicTensor(outInfo)) { - if (Is12Operand(*outputOperand)) - { - ALOGD("Output shape not set, will infer from input"); - outInfo.SetShape(input.GetTensorInfo().GetShape()); - } - else - { - return Fail("%s: Dynamic OutputShapes are not supported in this HAL version", __func__); - } + return Fail("%s: Dynamic output tensors are not supported", __func__); } bool isSupported = false; @@ -1217,11 +1198,7 @@ bool ConvertToActivation(const HalOperation& operation, BOOST_ASSERT(layer != nullptr); input.Connect(layer->GetInputSlot(0)); - return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, - 0, - *layer, - model, - data,armnn::Optional<armnn::TensorInfo>(outInfo)); + return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, 0, *layer, model, data); } template<typename HalPolicy, @@ -1343,6 +1320,11 @@ bool ConvertPooling2d(const HalOperation& operation, const armnn::TensorInfo& inputInfo = input.GetTensorInfo(); const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*output); + if (IsDynamicTensor(outputInfo)) + { + return Fail("%s: Dynamic output tensors are not supported", __func__); + } + armnn::Pooling2dDescriptor desc; desc.m_PoolType = poolType; desc.m_OutputShapeRounding = armnn::OutputShapeRounding::Floor; @@ -1438,7 +1420,7 @@ bool ConvertConv2d(const HalOperation& operation, const HalModel& model, Convers } const armnn::TensorInfo& inputInfo = input.GetTensorInfo(); - armnn::TensorInfo outputInfo = GetTensorInfoForOperand(*output); + const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*output); // ArmNN does not currently support non-fixed weights or bias const ConstTensorPin weightsPin = ConvertOperationInputToConstTensorPin<HalPolicy>(operation, 1, model, data); @@ -1504,7 +1486,7 @@ bool ConvertConv2d(const HalOperation& operation, const HalModel& model, Convers if (IsDynamicTensor(outputInfo)) { - return Fail("%s: Dynamic OutputShapes are not supported", __func__); + return Fail("%s: Dynamic output tensors are not supported", __func__); } bool isSupported = false; @@ -1539,12 +1521,7 @@ bool ConvertConv2d(const HalOperation& operation, const HalModel& model, Convers input.Connect(startLayer->GetInputSlot(0)); - return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, - 0, - *endLayer, - model, - data, - armnn::Optional<armnn::TensorInfo>(outputInfo)); + return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, 0, *endLayer, model, data); } template<typename HalPolicy, @@ -1570,7 +1547,7 @@ bool ConvertDepthwiseConv2d(const HalOperation& operation, const HalModel& model } const armnn::TensorInfo& inputInfo = input.GetTensorInfo(); - armnn::TensorInfo outputInfo = GetTensorInfoForOperand(*output); + const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*output); // ArmNN does not currently support non-fixed weights or bias @@ -1674,7 +1651,7 @@ bool ConvertDepthwiseConv2d(const HalOperation& operation, const HalModel& model if (IsDynamicTensor(outputInfo)) { - return Fail("%s: Dynamic OutputShapes are not supported", __func__); + return Fail("%s: Dynamic output tensors are not supported", __func__); } bool isSupported = false; @@ -1707,12 +1684,7 @@ bool ConvertDepthwiseConv2d(const HalOperation& operation, const HalModel& model input.Connect(startLayer->GetInputSlot(0)); - return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, - 0, - *endLayer, - model, - data, - armnn::Optional<armnn::TensorInfo>(outputInfo)); + return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, 0, *endLayer, model, data); } template<typename HalPolicy, @@ -1750,11 +1722,10 @@ bool ConvertPad(HalOperation& operation, const HalModel& model, ConversionData& return Fail("%s: Could not read output", __func__); } - armnn::TensorInfo outputInfo = GetTensorInfoForOperand(*output); + const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*output); if (IsDynamicTensor(outputInfo)) { - ALOGD("Output shape not set, will infer from inputs"); - outputInfo.SetShape(InferPadOutputShape(inputInfo.GetShape(), descriptor.m_PadList)); + return Fail("%s: Dynamic output tensors are not supported", __func__); } bool isSupported = false; @@ -1775,12 +1746,7 @@ bool ConvertPad(HalOperation& operation, const HalModel& model, ConversionData& input.Connect(layer->GetInputSlot(0)); layer->GetOutputSlot(0).SetTensorInfo(outputInfo); - return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, - 0, - *layer, - model, - data, - armnn::Optional<armnn::TensorInfo>(outputInfo)); + return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, 0, *layer, model, data); } } // namespace armnn_driver diff --git a/OutputShapeUtils.cpp b/OutputShapeUtils.cpp deleted file mode 100644 index ecec0b92..00000000 --- a/OutputShapeUtils.cpp +++ /dev/null @@ -1,199 +0,0 @@ -// -// Copyright © 2017 Arm Ltd. All rights reserved. -// SPDX-License-Identifier: MIT -// - -#include "OutputShapeUtils.hpp" - -#include <DataLayoutIndexed.hpp> - -#include <algorithm> -#include <numeric> -#include <vector> - -namespace -{ - -using namespace armnn; - -TensorShape CalculateMaxShape(const TensorShape& inShape0, const TensorShape& inShape1) -{ - // NOTE: The inferred output size will be the maximum size along each dimension - // of inShape0 and inShape1, starting with the trailing dimensions, and working its way forward. - // - // Example: inShape0={4, 1, 2}, inShape1={5, 4, 3, 1} => outputShape={5, 4, 3, 2} - - const unsigned int numInput0Dims = inShape0.GetNumDimensions(); - const unsigned int numInput1Dims = inShape1.GetNumDimensions(); - - const unsigned int maxNumDims = std::max(numInput0Dims, numInput1Dims); - - TensorShape outputShape = TensorShape(maxNumDims); - for (unsigned int reverseIdx = 1u; reverseIdx <= maxNumDims; ++reverseIdx) - { - const int input0Idx = numInput0Dims - reverseIdx; - const int input1Idx = numInput1Dims - reverseIdx; - - const unsigned int input0DimSize = input0Idx >= 0 ? inShape0[input0Idx] : 0u; - const unsigned int input1DimSize = input1Idx >= 0 ? inShape1[input1Idx] : 0u; - - const unsigned int outputIdx = maxNumDims - reverseIdx; - outputShape[outputIdx] = std::max(input0DimSize, input1DimSize); - } - - return outputShape; -} - -template<typename ConvolutionDescriptor> -TensorShape InferConvolution2dOutputShapeImpl(const TensorShape& inputShape, - const TensorShape& kernelShape, - const ConvolutionDescriptor& descriptor, - bool isDepthwiseConvolution) -{ - if (inputShape.GetNumDimensions() != 4) - { - throw InvalidArgumentException("Input shape must be 4D"); - } - - armnnUtils::DataLayoutIndexed dataLayoutIndex(descriptor.m_DataLayout); - - const unsigned int cIndex = dataLayoutIndex.GetChannelsIndex(); - const unsigned int wIndex = dataLayoutIndex.GetWidthIndex(); - const unsigned int hIndex = dataLayoutIndex.GetHeightIndex(); - - const unsigned int wInput = inputShape[wIndex]; - const unsigned int hInput = inputShape[hIndex]; - - const unsigned int wKernel = isDepthwiseConvolution ? kernelShape[2] : kernelShape[wIndex]; - const unsigned int wDilated = wKernel + (descriptor.m_DilationX - 1) * (wKernel - 1); - - const unsigned int wRead = (wInput + descriptor.m_PadLeft + descriptor.m_PadRight) - wDilated; - const unsigned int wOutput = 1 + (wRead / descriptor.m_StrideX); - - const unsigned int hKernel = isDepthwiseConvolution ? kernelShape[3] : kernelShape[hIndex]; - const unsigned int hDilated = hKernel + (descriptor.m_DilationY - 1) * (hKernel - 1); - - const unsigned int hRead = (hInput + descriptor.m_PadTop + descriptor.m_PadBottom) - hDilated; - const unsigned int hOutput = 1 + (hRead / descriptor.m_StrideY); - - TensorShape outputShape(4); - outputShape[0] = inputShape[0]; - outputShape[cIndex] = kernelShape[0]; - outputShape[wIndex] = wOutput; - outputShape[hIndex] = hOutput; - - if (isDepthwiseConvolution) - { - outputShape[cIndex] *= inputShape[cIndex]; - } - - return outputShape; -} - -} // anonymous namespace - -namespace armnn_driver -{ - -using namespace armnn; - -TensorShape InferConvolution2dOutputShape(const TensorShape& inputShape, - const TensorShape& kernelShape, - const Convolution2dDescriptor& descriptor) -{ - return InferConvolution2dOutputShapeImpl(inputShape, kernelShape, descriptor, false); -} - -TensorShape InferDepthwiseConvolution2dOutputShape(const TensorShape& inputShape, - const TensorShape& kernelShape, - const DepthwiseConvolution2dDescriptor& descriptor) -{ - return InferConvolution2dOutputShapeImpl(inputShape, kernelShape, descriptor, true); -} - -TensorShape InferMaximumOutputShape(const armnn::TensorShape& input0Shape, - const armnn::TensorShape& input1Shape) -{ - return CalculateMaxShape(input0Shape, input1Shape); -} - -TensorShape InferMinimumOutputShape(const armnn::TensorShape& input0Shape, - const armnn::TensorShape& input1Shape) -{ - return CalculateMaxShape(input0Shape, input1Shape); -} - -TensorShape InferPadOutputShape(const TensorShape& inputShape, - const std::vector<std::pair<unsigned int, unsigned int>>& padList) -{ - const unsigned int numDims = inputShape.GetNumDimensions(); - - std::vector<unsigned int> outputDims; - TensorShape outputShape = TensorShape(numDims); - for (unsigned int dim = 0; dim < numDims; ++dim) - { - unsigned int dimSize = inputShape[dim]; - const std::pair<unsigned int, unsigned int>& dimPadding = padList[dim]; - dimSize += dimPadding.first; - dimSize += dimPadding.second; - outputShape[dim] = dimSize; - } - return outputShape; -} - -TensorShape InferPreluOutputShape(const TensorShape& inputShape, const TensorShape& alphaShape) -{ - return CalculateMaxShape(inputShape, alphaShape); -} - -TensorShape InferResizeOutputShape(const TensorShape& inputShape, const ResizeDescriptor& descriptor) -{ - if (inputShape.GetNumDimensions() != 4) - { - throw InvalidArgumentException("Input shape for Resize must be 4D"); - } - - armnnUtils::DataLayoutIndexed dataLayoutIndexed(descriptor.m_DataLayout); - - const unsigned int cIndex = dataLayoutIndexed.GetChannelsIndex(); - const unsigned int wIndex = dataLayoutIndexed.GetWidthIndex(); - const unsigned int hIndex = dataLayoutIndexed.GetHeightIndex(); - - TensorShape outputShape(4); - outputShape[0] = inputShape[0]; - outputShape[cIndex] = inputShape[cIndex]; - outputShape[wIndex] = descriptor.m_TargetWidth; - outputShape[hIndex] = descriptor.m_TargetHeight; - - return outputShape; -} - -TensorShape InferSpaceToDepthOutputShape(const TensorShape& inputShape, const SpaceToDepthDescriptor& descriptor) -{ - TensorShape outputShape(inputShape); - - armnnUtils::DataLayoutIndexed dataLayoutIndexed(descriptor.m_DataLayout); - - const unsigned int cIndex = dataLayoutIndexed.GetChannelsIndex(); - const unsigned int wIndex = dataLayoutIndexed.GetWidthIndex(); - const unsigned int hIndex = dataLayoutIndexed.GetHeightIndex(); - - if (descriptor.m_BlockSize == 0) - { - throw InvalidArgumentException("Block size must be greater than zero"); - } - - outputShape[cIndex] = inputShape[cIndex] * descriptor.m_BlockSize * descriptor.m_BlockSize; - - outputShape[hIndex] = inputShape[hIndex] / descriptor.m_BlockSize; - outputShape[wIndex] = inputShape[wIndex] / descriptor.m_BlockSize; - - return outputShape; -} - -TensorShape InferSubOutputShape(const TensorShape& input0Shape, const TensorShape& input1Shape) -{ - return CalculateMaxShape(input0Shape, input1Shape); -} - -} // namespace armnn_driver diff --git a/OutputShapeUtils.hpp b/OutputShapeUtils.hpp deleted file mode 100644 index 85cafbf6..00000000 --- a/OutputShapeUtils.hpp +++ /dev/null @@ -1,40 +0,0 @@ -// -// Copyright © 2017 Arm Ltd. All rights reserved. -// SPDX-License-Identifier: MIT -// - -#pragma once - -#include <armnn/ArmNN.hpp> - -namespace armnn_driver -{ - -armnn::TensorShape InferConvolution2dOutputShape(const armnn::TensorShape& inputShape, - const armnn::TensorShape& kernelShape, - const armnn::Convolution2dDescriptor& descriptor); - -armnn::TensorShape InferDepthwiseConvolution2dOutputShape(const armnn::TensorShape& inputShape, - const armnn::TensorShape& kernelShape, - const armnn::DepthwiseConvolution2dDescriptor& descriptor); - -armnn::TensorShape InferMaximumOutputShape(const armnn::TensorShape& input0Shape, - const armnn::TensorShape& input1Shape); - -armnn::TensorShape InferMinimumOutputShape(const armnn::TensorShape& input0Shape, - const armnn::TensorShape& input1Shape); - -armnn::TensorShape InferPadOutputShape(const armnn::TensorShape& inputShape, - const std::vector<std::pair<unsigned int, unsigned int>>& padList); - -armnn::TensorShape InferPreluOutputShape(const armnn::TensorShape& inputShape, const armnn::TensorShape& alphaShape); - -armnn::TensorShape InferResizeOutputShape(const armnn::TensorShape& inputShape, - const armnn::ResizeDescriptor& descriptor); - -armnn::TensorShape InferSpaceToDepthOutputShape(const armnn::TensorShape& inputShape, - const armnn::SpaceToDepthDescriptor& descriptor); - -armnn::TensorShape InferSubOutputShape(const armnn::TensorShape& input0Shape, const armnn::TensorShape& input1Shape); - -} // namespace armnn_driver |