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path: root/src/armnnTfLiteParser/TfLiteParser.cpp
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Diffstat (limited to 'src/armnnTfLiteParser/TfLiteParser.cpp')
-rw-r--r--src/armnnTfLiteParser/TfLiteParser.cpp164
1 files changed, 106 insertions, 58 deletions
diff --git a/src/armnnTfLiteParser/TfLiteParser.cpp b/src/armnnTfLiteParser/TfLiteParser.cpp
index 5f8b08bf85..a68839c20e 100644
--- a/src/armnnTfLiteParser/TfLiteParser.cpp
+++ b/src/armnnTfLiteParser/TfLiteParser.cpp
@@ -394,6 +394,9 @@ armnn::TensorInfo ToTensorInfo(TfLiteParserImpl::TensorRawPtr tensorPtr,
case tflite::TensorType_INT64:
type = armnn::DataType::Signed64;
break;
+ case tflite::TensorType_BOOL:
+ type = armnn::DataType::Boolean;
+ break;
default:
{
CheckLocation location = CHECK_LOCATION();
@@ -603,6 +606,7 @@ TfLiteParserImpl::TfLiteParserImpl(const Optional<ITfLiteParser::TfLiteParserOpt
, m_ParserFunctions(tflite::BuiltinOperator_MAX+1, &TfLiteParserImpl::ParseUnsupportedOperator)
{
// register supported operators
+ m_ParserFunctions[tflite::BuiltinOperator_ABS] = &TfLiteParserImpl::ParseAbs;
m_ParserFunctions[tflite::BuiltinOperator_ADD] = &TfLiteParserImpl::ParseAdd;
m_ParserFunctions[tflite::BuiltinOperator_ARG_MIN] = &TfLiteParserImpl::ParseArgMin;
m_ParserFunctions[tflite::BuiltinOperator_ARG_MAX] = &TfLiteParserImpl::ParseArgMax;
@@ -622,6 +626,7 @@ TfLiteParserImpl::TfLiteParserImpl(const Optional<ITfLiteParser::TfLiteParserOpt
m_ParserFunctions[tflite::BuiltinOperator_GATHER] = &TfLiteParserImpl::ParseGather;
m_ParserFunctions[tflite::BuiltinOperator_HARD_SWISH] = &TfLiteParserImpl::ParseHardSwish;
m_ParserFunctions[tflite::BuiltinOperator_LEAKY_RELU] = &TfLiteParserImpl::ParseLeakyRelu;
+ m_ParserFunctions[tflite::BuiltinOperator_LOGICAL_NOT] = &TfLiteParserImpl::ParseLogicalNot;
m_ParserFunctions[tflite::BuiltinOperator_LOGISTIC] = &TfLiteParserImpl::ParseLogistic;
m_ParserFunctions[tflite::BuiltinOperator_L2_NORMALIZATION] = &TfLiteParserImpl::ParseL2Normalization;
m_ParserFunctions[tflite::BuiltinOperator_MAX_POOL_2D] = &TfLiteParserImpl::ParseMaxPool2D;
@@ -640,6 +645,7 @@ TfLiteParserImpl::TfLiteParserImpl(const Optional<ITfLiteParser::TfLiteParserOpt
m_ParserFunctions[tflite::BuiltinOperator_RESHAPE] = &TfLiteParserImpl::ParseReshape;
m_ParserFunctions[tflite::BuiltinOperator_RESIZE_BILINEAR] = &TfLiteParserImpl::ParseResizeBilinear;
m_ParserFunctions[tflite::BuiltinOperator_RESIZE_NEAREST_NEIGHBOR] = &TfLiteParserImpl::ParseResizeNearestNeighbor;
+ m_ParserFunctions[tflite::BuiltinOperator_RSQRT] = &TfLiteParserImpl::ParseRsqrt;
m_ParserFunctions[tflite::BuiltinOperator_SLICE] = &TfLiteParserImpl::ParseSlice;
m_ParserFunctions[tflite::BuiltinOperator_SOFTMAX] = &TfLiteParserImpl::ParseSoftmax;
m_ParserFunctions[tflite::BuiltinOperator_SPACE_TO_BATCH_ND] = &TfLiteParserImpl::ParseSpaceToBatchND;
@@ -1090,33 +1096,6 @@ void TfLiteParserImpl::ParseDequantize(size_t subgraphIndex, size_t operatorInde
RegisterOutputSlots(subgraphIndex, operatorIndex, layer, outputTensorIndexes);
}
-void TfLiteParserImpl::ParseExp(size_t subgraphIndex, size_t operatorIndex)
-{
- CHECK_MODEL(m_Model, subgraphIndex, operatorIndex);
-
- auto inputs = GetInputs(m_Model, subgraphIndex, operatorIndex);
- CHECK_VALID_SIZE(inputs.size(), 1);
-
- auto outputs = GetOutputs(m_Model, subgraphIndex, operatorIndex);
- CHECK_VALID_SIZE(outputs.size(), 1);
-
- auto layerName = fmt::format("Exp:{}:{}", subgraphIndex, operatorIndex);
-
- ElementwiseUnaryDescriptor desc;
- desc.m_Operation = UnaryOperation::Exp;
- IConnectableLayer* layer = m_Network->AddElementwiseUnaryLayer(desc, layerName.c_str());
- ARMNN_ASSERT(layer != nullptr);
-
- TensorInfo outputTensorInfo = ToTensorInfo(outputs[0], true);
- layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
-
- auto inputTensorIndexes = AsUnsignedVector(GetInputTensorIds(m_Model, subgraphIndex, operatorIndex));
- RegisterInputSlots(subgraphIndex, operatorIndex, layer, {inputTensorIndexes[0]});
-
- auto outputTensorIndexes = AsUnsignedVector(GetOutputTensorIds(m_Model, subgraphIndex, operatorIndex));
- RegisterOutputSlots(subgraphIndex, operatorIndex, layer, outputTensorIndexes);
-}
-
void TfLiteParserImpl::ParseTranspose(size_t subgraphIndex, size_t operatorIndex)
{
CHECK_MODEL(m_Model, subgraphIndex, operatorIndex);
@@ -1917,31 +1896,6 @@ void TfLiteParserImpl::ParseMean(size_t subgraphIndex, size_t operatorIndex)
RegisterOutputSlots(subgraphIndex, operatorIndex, layer, {outputTensorIndexes[0]});
}
-void TfLiteParserImpl::ParseNeg(size_t subgraphIndex, size_t operatorIndex)
-{
- CHECK_MODEL(m_Model, subgraphIndex, operatorIndex);
-
- auto inputs = GetInputs(m_Model, subgraphIndex, operatorIndex);
- CHECK_VALID_SIZE(inputs.size(), 1);
-
- auto outputs = GetOutputs(m_Model, subgraphIndex, operatorIndex);
- CHECK_VALID_SIZE(outputs.size(), 1);
-
- auto layerName = fmt::format("Neg:{}:{}", subgraphIndex, operatorIndex);
- armnn::ElementwiseUnaryDescriptor descriptor(armnn::UnaryOperation::Neg);
- IConnectableLayer* layer = m_Network->AddElementwiseUnaryLayer(descriptor, layerName.c_str());
- ARMNN_ASSERT(layer != nullptr);
-
- TensorInfo outputTensorInfo = ToTensorInfo(outputs[0], true);
- layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
-
- auto inputTensorIndexes = AsUnsignedVector(GetInputTensorIds(m_Model, subgraphIndex, operatorIndex));
- RegisterInputSlots(subgraphIndex, operatorIndex, layer, {inputTensorIndexes[0]});
-
- auto outputTensorIndexes = AsUnsignedVector(GetOutputTensorIds(m_Model, subgraphIndex, operatorIndex));
- RegisterOutputSlots(subgraphIndex, operatorIndex, layer, outputTensorIndexes);
-}
-
void TfLiteParserImpl::ParsePad(size_t subgraphIndex, size_t operatorIndex)
{
CHECK_MODEL(m_Model, subgraphIndex, operatorIndex);
@@ -2758,15 +2712,35 @@ void TfLiteParserImpl::ParseSplit(size_t subgraphIndex, size_t operatorIndex)
auto outputs = GetOutputs(m_Model, subgraphIndex, operatorIndex);
CHECK_VALID_SIZE(outputs.size(), numSplits);
- armnn::TensorInfo inputTensorInfo = ToTensorInfo(inputs[1]);
- armnn::TensorInfo axisTensorInfo = ToTensorInfo(inputs[0]);
+ armnn::TensorInfo inputTensorInfo = ToTensorInfo(inputs[1]);
+ armnn::TensorInfo axisTensorInfo = ToTensorInfo(inputs[0]);
+ ARMNN_ASSERT(axisTensorInfo.GetNumElements() == 1);
BufferRawPtr axisBufferPtr = GetBuffer(m_Model, inputs[0]->buffer);
- std::vector<unsigned int> axisData(axisTensorInfo.GetNumElements());
+ 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[0];
- ARMNN_ASSERT(axisTensorInfo.GetNumElements() == 1);
- const unsigned int splitDim = axisData[0];
+ 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()));
+ }
+
+ const unsigned int splitDim = armnnUtils::GetUnsignedAxis(inputTensorInfo.GetNumDimensions(), axis);
auto inputDimSize = inputTensorInfo.GetNumDimensions();
if (inputDimSize > MaxNumOfTensorDimensions)
@@ -2863,9 +2837,29 @@ void TfLiteParserImpl::ParseSplitV(size_t subgraphIndex, size_t operatorIndex)
// Get split axis
BufferRawPtr axisBufferPtr = GetBuffer(m_Model, axisTensor->buffer);
+ if (axisBufferPtr == nullptr)
+ {
+ throw ParseException(
+ fmt::format("Operation has invalid inputs. Failed to read axis. {}",
+ CHECK_LOCATION().AsString()));
+ }
+
std::vector<int> axisData(axisTensorInfo.GetNumElements());
::memcpy(axisData.data(), axisBufferPtr->data.data(), axisTensorInfo.GetNumBytes());
- const unsigned int splitDim = ComputeWrappedIndex(axisData[0], inputTensorInfo.GetNumDimensions());
+ int32_t axis = axisData[0];
+
+ 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()));
+ }
+ const unsigned int splitDim = ComputeWrappedIndex(axis, inputTensorInfo.GetNumDimensions());
// Set split sizes
CHECK_VALID_SIZE(splitsInfo.GetNumDimensions(), 1);
@@ -2988,6 +2982,7 @@ void TfLiteParserImpl::ParseArgMinMax(size_t subgraphIndex, size_t operatorIndex
armnn::TensorInfo inputTensorInfo = ToTensorInfo(inputs[0]);
armnn::TensorInfo axisTensorInfo = ToTensorInfo(inputs[1]);
armnn::TensorInfo outputTensorInfo = ToTensorInfo(outputs[0]);
+ ARMNN_ASSERT(axisTensorInfo.GetNumElements() == 1);
// Check if output tensor type is Signed32 or Signed64
if (outputTensorInfo.GetDataType() != armnn::DataType::Signed32 &&
@@ -3210,6 +3205,59 @@ void TfLiteParserImpl::ParseReduce(size_t subgraphIndex, size_t operatorIndex, R
RegisterOutputSlots(subgraphIndex, operatorIndex, layer, outputTensorIndexes);
}
+void TfLiteParserImpl::ParseAbs(size_t subgraphIndex, size_t operatorIndex)
+{
+ ParseElementwiseUnary(subgraphIndex, operatorIndex, armnn::UnaryOperation::Abs);
+}
+
+void TfLiteParserImpl::ParseExp(size_t subgraphIndex, size_t operatorIndex)
+{
+ ParseElementwiseUnary(subgraphIndex, operatorIndex, armnn::UnaryOperation::Exp);
+}
+
+void TfLiteParserImpl::ParseLogicalNot(size_t subgraphIndex, size_t operatorIndex)
+{
+ ParseElementwiseUnary(subgraphIndex, operatorIndex, armnn::UnaryOperation::LogicalNot);
+}
+
+void TfLiteParserImpl::ParseNeg(size_t subgraphIndex, size_t operatorIndex)
+{
+ ParseElementwiseUnary(subgraphIndex, operatorIndex, armnn::UnaryOperation::Neg);
+}
+
+void TfLiteParserImpl::ParseRsqrt(size_t subgraphIndex, size_t operatorIndex)
+{
+ ParseElementwiseUnary(subgraphIndex, operatorIndex, armnn::UnaryOperation::Rsqrt);
+}
+
+void TfLiteParserImpl::ParseElementwiseUnary(size_t subgraphIndex, size_t operatorIndex, UnaryOperation unaryOperation)
+{
+ CHECK_MODEL(m_Model, subgraphIndex, operatorIndex);
+
+ auto inputs = GetInputs(m_Model, subgraphIndex, operatorIndex);
+ CHECK_VALID_SIZE(inputs.size(), 1);
+
+ auto outputs = GetOutputs(m_Model, subgraphIndex, operatorIndex);
+ CHECK_VALID_SIZE(outputs.size(), 1);
+
+ std::string layerName = std::string(GetUnaryOperationAsCString(unaryOperation)) + ":{}:{}";
+ std::string layerNameFormatted = fmt::format(layerName, subgraphIndex, operatorIndex);
+
+ ElementwiseUnaryDescriptor desc;
+ desc.m_Operation = unaryOperation;
+ IConnectableLayer* layer = m_Network->AddElementwiseUnaryLayer(desc, layerNameFormatted.c_str());
+ ARMNN_ASSERT(layer != nullptr);
+
+ TensorInfo outputTensorInfo = ToTensorInfo(outputs[0], true);
+ layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
+
+ auto inputTensorIndexes = AsUnsignedVector(GetInputTensorIds(m_Model, subgraphIndex, operatorIndex));
+ RegisterInputSlots(subgraphIndex, operatorIndex, layer, {inputTensorIndexes[0]});
+
+ auto outputTensorIndexes = AsUnsignedVector(GetOutputTensorIds(m_Model, subgraphIndex, operatorIndex));
+ RegisterOutputSlots(subgraphIndex, operatorIndex, layer, outputTensorIndexes);
+}
+
armnn::IConnectableLayer* TfLiteParserImpl::AddFusedActivationLayer(armnn::IConnectableLayer* prevLayer,
unsigned int outputSlot,
tflite::ActivationFunctionType activationType)
generated by cgit v1.2.1 (git 2.23.0) at 2024-07-03 19:26:41 +0000