diff options
Diffstat (limited to 'src/backends/backendsCommon/WorkloadData.cpp')
| -rw-r--r-- | src/backends/backendsCommon/WorkloadData.cpp | 119 |
1 files changed, 52 insertions, 67 deletions
diff --git a/src/backends/backendsCommon/WorkloadData.cpp b/src/backends/backendsCommon/WorkloadData.cpp index ff97fc7f41..e9023b62e1 100644 --- a/src/backends/backendsCommon/WorkloadData.cpp +++ b/src/backends/backendsCommon/WorkloadData.cpp @@ -14,7 +14,7 @@ #include <string> #include <sstream> -#include <boost/format.hpp> +#include <fmt/format.h> using namespace armnnUtils; @@ -387,16 +387,15 @@ void ValidatePerAxisQuantizationDimension(const TensorInfo& tensorInfo, const Optional<unsigned int>& quantizationDim = tensorInfo.GetQuantizationDim(); if (!quantizationDim.has_value()) { - throw InvalidArgumentException(boost::str( - boost::format("%1%: Quantization dimension for per-axis quantization not set on tensor %2%.") - % descName % tensorName)); + throw InvalidArgumentException(fmt::format("{0}: Quantization dimension for per-axis quantization " + "not set on tensor {1}.", descName, tensorName)); } if (quantizationDim.value() != 0) { - throw InvalidArgumentException(boost::str( - boost::format("%1%: Quantization dimension for per-axis quantization expected to be 0 on tensor %2%, " - "but got: %3%") % descName % tensorName % quantizationDim.value())); + throw InvalidArgumentException(fmt::format( + "{0}: Quantization dimension for per-axis quantization expected to be 0 on tensor {1}, " + "but got: {2}", descName, tensorName, quantizationDim.value())); } } @@ -407,9 +406,9 @@ void ValidatePerAxisQuantizationOffset(const TensorInfo& tensorInfo, int32_t quantizationOffset = tensorInfo.GetQuantizationOffset(); if (quantizationOffset != 0) { - throw InvalidArgumentException(boost::str( - boost::format("%1%: Quantization offset for per-axis quantization expected to be 0 on tensor %2%, " - "but got: %3%") % descName % tensorName % quantizationOffset)); + throw InvalidArgumentException(fmt::format( + "{0}: Quantization offset for per-axis quantization expected to be 0 on tensor {1}, but got: {2}", + descName, tensorName, quantizationOffset)); } } @@ -428,9 +427,9 @@ void ValidatePerAxisQuantization(const TensorInfo& inputInfo, if (!canHavePerAxisQuantization) { - throw InvalidArgumentException(boost::str( - boost::format("%1%: Per-axis quantization parameters set on tensor %2%, " - "but data type does not support per-axis quantization.") % descName % "weight")); + throw InvalidArgumentException(fmt::format( + "{0}: Per-axis quantization parameters set on tensor {1}, but data type does not support " + "per-axis quantization.", descName, "weight")); } @@ -443,9 +442,9 @@ void ValidatePerAxisQuantization(const TensorInfo& inputInfo, const TensorInfo& biasInfo = optionalBiasInfo.value(); if (!biasInfo.HasPerAxisQuantization()) { - throw InvalidArgumentException(boost::str( - boost::format("%1%: Per-axis quantization parameters not set on bias tensor, despite being set on " - "weight tensor.") % descName)); + throw InvalidArgumentException(fmt::format( + "{}: Per-axis quantization parameters not set on bias tensor, " + "despite being set on weight tensor.", descName)); } ValidateTensorDataType(biasInfo, DataType::Signed32, descName, "bias"); @@ -480,23 +479,22 @@ void MemCopyQueueDescriptor::Validate(const WorkloadInfo& workloadInfo) const if (m_Inputs.size() != m_Outputs.size()) { - throw InvalidArgumentException(boost::str( - boost::format("%1%: Number of inputs (%2%) does not match the number of outputs (%3%).") % - descriptorName % m_Inputs.size() % m_Outputs.size())); + throw InvalidArgumentException(fmt::format( + "{0}: Number of inputs ({1}) does not match the number of outputs ({2}).", + descriptorName, m_Inputs.size(), m_Outputs.size())); } for (unsigned int i = 0; i < m_Inputs.size(); ++i) { if (!m_Inputs[i]) { - throw InvalidArgumentException(boost::str(boost::format("%1%: Invalid NULL input %2%.") % - descriptorName % i)); + throw InvalidArgumentException(fmt::format( + "{0}: Invalid NULL input {1}.", descriptorName, i)); } if (!m_Outputs[i]) { - throw InvalidArgumentException(boost::str(boost::format("%1%: Invalid NULL output %2%") % - descriptorName % i)); + throw InvalidArgumentException(fmt::format("{0}: Invalid NULL output {1}", descriptorName, i)); } } } @@ -509,17 +507,16 @@ void MemImportQueueDescriptor::Validate(const WorkloadInfo& workloadInfo) const if (workloadInfo.m_InputTensorInfos.size() != 1) { - throw InvalidArgumentException(boost::str( - boost::format("Number of input infos (%1%) is not 1.") - % workloadInfo.m_InputTensorInfos.size())); + throw InvalidArgumentException(fmt::format("Number of input infos ({}) is not 1.", + workloadInfo.m_InputTensorInfos.size())); } if (workloadInfo.m_InputTensorInfos.size() != workloadInfo.m_OutputTensorInfos.size()) { - throw InvalidArgumentException(boost::str( - boost::format("Number of input infos (%1%) does not match the number of output infos (%2%)") - % workloadInfo.m_InputTensorInfos.size() % workloadInfo.m_OutputTensorInfos.size())); + throw InvalidArgumentException(fmt::format( + "Number of input infos ({0}) does not match the number of output infos ({1})", + workloadInfo.m_InputTensorInfos.size(), workloadInfo.m_OutputTensorInfos.size())); } for (std::size_t i = 0; i < workloadInfo.m_InputTensorInfos.size(); ++i) @@ -527,36 +524,33 @@ void MemImportQueueDescriptor::Validate(const WorkloadInfo& workloadInfo) const if (workloadInfo.m_InputTensorInfos[i].GetNumElements() != workloadInfo.m_OutputTensorInfos[i].GetNumElements()) { - throw InvalidArgumentException(boost::str( - boost::format("Number of elements for tensor input and output %1% does not match") - % i )); + throw InvalidArgumentException(fmt::format( + "Number of elements for tensor input and output {} does not match", i )); } } if (m_Inputs.size() != 1) { - throw InvalidArgumentException(boost::str( - boost::format("Number of inputs (%1%) is not 1.") - % m_Inputs.size())); + throw InvalidArgumentException(fmt::format("Number of inputs ({}) is not 1.", m_Inputs.size())); } if (m_Inputs.size() != m_Outputs.size()) { - throw InvalidArgumentException(boost::str( - boost::format("Number of inputs (%1%) does not match the number of outputs (%2%)") - % m_Inputs.size() % m_Outputs.size())); + throw InvalidArgumentException(fmt::format( + "Number of inputs ({0}) does not match the number of outputs ({1})", + m_Inputs.size(), m_Outputs.size())); } for (unsigned int i = 0; i < m_Inputs.size(); ++i) { if (!m_Inputs[i]) { - throw InvalidArgumentException(boost::str(boost::format("Invalid null input %1%") % i)); + throw InvalidArgumentException(fmt::format("Invalid null input {}", i)); } if (!m_Outputs[i]) { - throw InvalidArgumentException(boost::str(boost::format("Invalid null output %1%") % i)); + throw InvalidArgumentException(fmt::format("Invalid null output {}", i)); } } } @@ -569,21 +563,17 @@ void MemSyncQueueDescriptor::Validate(const WorkloadInfo& workloadInfo) const if (m_Inputs.size() != 1) { - throw InvalidArgumentException(boost::str( - boost::format("Number of inputs (%1%) is not 1.") - % m_Inputs.size())); + throw InvalidArgumentException(fmt::format("Number of inputs ({}) is not 1.", m_Inputs.size())); } if (m_Outputs.size() != 0) { - throw InvalidArgumentException(boost::str( - boost::format("Number of outputs (%1%) is not 0.") - % m_Inputs.size() % m_Outputs.size())); + throw InvalidArgumentException(fmt::format("Number of outputs ({}) is not 0.", m_Outputs.size())); } if (!m_Inputs[0]) { - throw InvalidArgumentException(boost::str(boost::format("Invalid null input 0"))); + throw InvalidArgumentException(fmt::format("Invalid null input 0")); } } @@ -1288,9 +1278,9 @@ void DepthwiseConvolution2dQueueDescriptor::Validate(const WorkloadInfo& workloa if (m_Parameters.m_DilationX < 1 || m_Parameters.m_DilationY < 1 ) { throw InvalidArgumentException( - boost::str(boost::format("%1%: dilationX (provided %2%) and dilationY (provided %3%) " - "cannot be smaller than 1.") % descriptorName % - m_Parameters.m_DilationX % m_Parameters.m_DilationX)); + fmt::format("{}: dilationX (provided {}) and dilationY (provided {}) " + "cannot be smaller than 1.", + descriptorName, m_Parameters.m_DilationX, m_Parameters.m_DilationX)); } const unsigned int channelIndex = (m_Parameters.m_DataLayout == DataLayout::NCHW) ? 1 : 3; @@ -1302,11 +1292,10 @@ void DepthwiseConvolution2dQueueDescriptor::Validate(const WorkloadInfo& workloa const unsigned int numWeightOutputChannels = outputTensorInfo.GetShape()[channelIndex]; if (numWeightChannelMultiplier * numWeightInputChannels != numWeightOutputChannels) { - throw InvalidArgumentException( - boost::str(boost::format("%1%: output_channels (provided %2%) should be " - "equal to input_channels (provided %3%) multiplied by channel_multiplier " - "(provided %4%).") % descriptorName % numWeightOutputChannels % - numWeightInputChannels % numWeightChannelMultiplier)); + throw InvalidArgumentException(fmt::format( + "{0}: output_channels (provided {1}) should be equal to input_channels (provided {2}) " + "multiplied by channel_multiplier (provided {3}).", + descriptorName, numWeightOutputChannels, numWeightInputChannels, numWeightChannelMultiplier)); } ValidateWeightDataType(inputTensorInfo, weightTensorInfo, descriptorName); @@ -1430,9 +1419,8 @@ void ResizeBilinearQueueDescriptor::Validate(const WorkloadInfo& workloadInfo) c if (inputBatchSize != outputBatchSize) { throw InvalidArgumentException( - boost::str(boost::format("%1%: Input batch size (%2%) " - "does not match output batch size (%3%)") % - descriptorName % inputBatchSize % outputBatchSize)); + fmt::format("{}: Input batch size ({}) does not match output batch size ({})", + descriptorName, inputBatchSize, outputBatchSize)); } DataLayoutIndexed dimensionIndices(m_Parameters.m_DataLayout); @@ -1441,9 +1429,8 @@ void ResizeBilinearQueueDescriptor::Validate(const WorkloadInfo& workloadInfo) c if (inputChannelCount != outputChannelCount) { throw InvalidArgumentException( - boost::str(boost::format("%1%: Input channel count (%2%) " - "does not match output channel count (%3%)") % - descriptorName % inputChannelCount % outputChannelCount)); + fmt::format("{}: Input channel count ({}) does not match output channel count ({})", + descriptorName, inputChannelCount, outputChannelCount)); } } @@ -1479,9 +1466,8 @@ void ResizeQueueDescriptor::Validate(const WorkloadInfo& workloadInfo) const if (inputBatchSize != outputBatchSize) { throw InvalidArgumentException( - boost::str(boost::format("%1%: Input batch size (%2%) " - "does not match output batch size (%3%)") % - descriptorName % inputBatchSize % outputBatchSize)); + fmt::format("{}: Input batch size ({}) does not match output batch size ({})", + descriptorName, inputBatchSize, outputBatchSize)); } DataLayoutIndexed dimensionIndices(m_Parameters.m_DataLayout); @@ -1490,9 +1476,8 @@ void ResizeQueueDescriptor::Validate(const WorkloadInfo& workloadInfo) const if (inputChannelCount != outputChannelCount) { throw InvalidArgumentException( - boost::str(boost::format("%1%: Input channel count (%2%) " - "does not match output channel count (%3%)") % - descriptorName % inputChannelCount % outputChannelCount)); + fmt::format("{}: Input channel count ({}) does not match output channel count ({})", + descriptorName, inputChannelCount, outputChannelCount)); } } |