diff options
Diffstat (limited to 'src/armnnTfLiteParser/TfLiteParser.cpp')
| -rw-r--r-- | src/armnnTfLiteParser/TfLiteParser.cpp | 70 |
1 files changed, 53 insertions, 17 deletions
diff --git a/src/armnnTfLiteParser/TfLiteParser.cpp b/src/armnnTfLiteParser/TfLiteParser.cpp index c4d2942779..cb3426ea5b 100644 --- a/src/armnnTfLiteParser/TfLiteParser.cpp +++ b/src/armnnTfLiteParser/TfLiteParser.cpp @@ -604,6 +604,8 @@ TfLiteParserImpl::TfLiteParserImpl(const Optional<ITfLiteParser::TfLiteParserOpt { // register supported operators m_ParserFunctions[tflite::BuiltinOperator_ADD] = &TfLiteParserImpl::ParseAdd; + m_ParserFunctions[tflite::BuiltinOperator_ARG_MIN] = &TfLiteParserImpl::ParseArgMin; + m_ParserFunctions[tflite::BuiltinOperator_ARG_MAX] = &TfLiteParserImpl::ParseArgMax; m_ParserFunctions[tflite::BuiltinOperator_AVERAGE_POOL_2D] = &TfLiteParserImpl::ParseAveragePool2D; m_ParserFunctions[tflite::BuiltinOperator_BATCH_TO_SPACE_ND] = &TfLiteParserImpl::ParseBatchToSpaceND; m_ParserFunctions[tflite::BuiltinOperator_CONCATENATION] = &TfLiteParserImpl::ParseConcatenation; @@ -612,6 +614,7 @@ TfLiteParserImpl::TfLiteParserImpl(const Optional<ITfLiteParser::TfLiteParserOpt m_ParserFunctions[tflite::BuiltinOperator_DEPTH_TO_SPACE] = &TfLiteParserImpl::ParseDepthToSpace; m_ParserFunctions[tflite::BuiltinOperator_DEPTHWISE_CONV_2D] = &TfLiteParserImpl::ParseDepthwiseConv2D; m_ParserFunctions[tflite::BuiltinOperator_DEQUANTIZE] = &TfLiteParserImpl::ParseDequantize; + m_ParserFunctions[tflite::BuiltinOperator_DIV] = &TfLiteParserImpl::ParseDiv; m_ParserFunctions[tflite::BuiltinOperator_ELU] = &TfLiteParserImpl::ParseElu; m_ParserFunctions[tflite::BuiltinOperator_EXP] = &TfLiteParserImpl::ParseExp; m_ParserFunctions[tflite::BuiltinOperator_FULLY_CONNECTED] = &TfLiteParserImpl::ParseFullyConnected; @@ -649,8 +652,7 @@ TfLiteParserImpl::TfLiteParserImpl(const Optional<ITfLiteParser::TfLiteParserOpt m_ParserFunctions[tflite::BuiltinOperator_TRANSPOSE] = &TfLiteParserImpl::ParseTranspose; m_ParserFunctions[tflite::BuiltinOperator_TRANSPOSE_CONV] = &TfLiteParserImpl::ParseTransposeConv; m_ParserFunctions[tflite::BuiltinOperator_UNPACK] = &TfLiteParserImpl::ParseUnpack; - m_ParserFunctions[tflite::BuiltinOperator_DIV] = &TfLiteParserImpl::ParseDiv; - m_ParserFunctions[tflite::BuiltinOperator_ARG_MAX] = &TfLiteParserImpl::ParseArgMax; + // register supported custom operators m_CustomParserFunctions["TFLite_Detection_PostProcess"] = &TfLiteParserImpl::ParseDetectionPostProcess; } @@ -2939,8 +2941,18 @@ void TfLiteParserImpl::ParseSplitV(size_t subgraphIndex, size_t operatorIndex) RegisterOutputSlots(subgraphIndex, operatorIndex, layer, outputTensorIndexes); } +void TfLiteParserImpl::ParseArgMin(size_t subgraphIndex, size_t operatorIndex) +{ + ParseArgMinMax(subgraphIndex, operatorIndex, armnn::ArgMinMaxFunction::Min); +} + void TfLiteParserImpl::ParseArgMax(size_t subgraphIndex, size_t operatorIndex) { + ParseArgMinMax(subgraphIndex, operatorIndex, armnn::ArgMinMaxFunction::Max); +} + +void TfLiteParserImpl::ParseArgMinMax(size_t subgraphIndex, size_t operatorIndex, ArgMinMaxFunction argMinMaxFunction) +{ CHECK_MODEL(m_Model, subgraphIndex, operatorIndex); auto inputs = GetInputs(m_Model, subgraphIndex, operatorIndex); CHECK_VALID_SIZE(inputs.size(), 2); @@ -2948,22 +2960,11 @@ void TfLiteParserImpl::ParseArgMax(size_t subgraphIndex, size_t operatorIndex) auto outputs = GetOutputs(m_Model, subgraphIndex, operatorIndex); CHECK_VALID_SIZE(outputs.size(), 1); - auto layerName = fmt::format("ArgMax:{}:{}", subgraphIndex, operatorIndex); - - armnn::TensorInfo sizeTensorInfo0 = ToTensorInfo(inputs[0]); - armnn::TensorInfo sizeTensorInfo1 = ToTensorInfo(inputs[1]); - - // Get const axis value from model and set it to descriptor. - BufferRawPtr axisBufferPtr = GetBuffer(m_Model, inputs[1]->buffer); - - ArgMinMaxDescriptor desc; - desc.m_Axis = axisBufferPtr->data.data()[0]; - desc.m_Function = ArgMinMaxFunction::Max; - - // Register a ArgMax layer. - IConnectableLayer *layer = m_Network->AddArgMinMaxLayer(desc, layerName.c_str()); - + armnn::TensorInfo inputTensorInfo = ToTensorInfo(inputs[0]); + armnn::TensorInfo axisTensorInfo = ToTensorInfo(inputs[1]); armnn::TensorInfo outputTensorInfo = ToTensorInfo(outputs[0]); + + // Check if output tensor type is Signed32 or Signed64 if (outputTensorInfo.GetDataType() != armnn::DataType::Signed32 && outputTensorInfo.GetDataType() != armnn::DataType::Signed64) { @@ -2972,6 +2973,41 @@ void TfLiteParserImpl::ParseArgMax(size_t subgraphIndex, size_t operatorIndex) "Output tensor data type is not supported. (Supported types: Signed32 & Signed64) {}", CHECK_LOCATION().AsString())); } + + // Get const axis value from model and set it to descriptor. + BufferRawPtr axisBufferPtr = GetBuffer(m_Model, inputs[1]->buffer); + if (axisBufferPtr == nullptr) + { + throw ParseException( + fmt::format("Operation has invalid inputs. Failed to read axis. {}", + CHECK_LOCATION().AsString())); + } + + std::vector<int32_t> axisData(axisTensorInfo.GetNumElements()); + ::memcpy(axisData.data(), axisBufferPtr->data.data(), axisTensorInfo.GetNumBytes()); + int32_t axis = axisData.front(); + + auto inputDimensions = static_cast<int32_t>(inputTensorInfo.GetNumDimensions()); + if (((axis < -inputDimensions) && (axis < 0)) || ((axis >= inputDimensions) && (axis > 0))) + { + // Square bracket denotes inclusive n while parenthesis denotes exclusive n + // E.g. Rank 4 tensor can have axis in range [-4, 3) + // -1 == 3, -2 == 2, -3 == 1, -4 == 0 + throw ParseException( + fmt::format("Operation has invalid axis: {}. Axis must be in range [-n, n) {}", + axis, + CHECK_LOCATION().AsString())); + } + + ArgMinMaxDescriptor desc; + desc.m_Axis = axis; + desc.m_Function = argMinMaxFunction; + + // Register a ArgMin/ArgMax layer. + auto layerName = argMinMaxFunction == ArgMinMaxFunction::Max ? "ArgMax:{}:{}" : "ArgMin:{}:{}"; + auto layerNameFormatted = fmt::format(layerName, subgraphIndex, operatorIndex); + IConnectableLayer *layer = m_Network->AddArgMinMaxLayer(desc, layerNameFormatted.c_str()); + ARMNN_ASSERT(layer != nullptr); layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo); // Register input tensor to the layer. |