diff options
author | Teresa Charlin <teresa.charlinreyes@arm.com> | 2023-06-14 14:51:17 +0100 |
---|---|---|
committer | TeresaARM <teresa.charlinreyes@arm.com> | 2023-06-22 12:12:31 +0000 |
commit | a7a605a7554158a47127b1988b94c6bfac0a64b9 (patch) | |
tree | 9dce948707b266e45b0a5a6974ca940b54ce7f42 /src/armnnTfLiteParser/TfLiteParser.cpp | |
parent | a9c5c16154386fb1ec924c3778caf6b027bb57ee (diff) | |
download | armnn-a7a605a7554158a47127b1988b94c6bfac0a64b9.tar.gz |
IVGCVSW-7785 BugFix: ExpandDims not working when batch!=1
* This commit fixes partially the ticket.
In ToTensorInfo() we assume batch is 1 when it is unknown.
We call OutputTensorInfoFromInputs() to amend this assumption/
However, this does not work for reshape layer.
Therefore, we have to calculate the output shape in the ParseExpandDims().
Signed-off-by: Teresa Charlin <teresa.charlinreyes@arm.com>
Change-Id: Iedc32a44b4ec0d8b7d2cc0b08f38f0776402f7bd
Diffstat (limited to 'src/armnnTfLiteParser/TfLiteParser.cpp')
-rw-r--r-- | src/armnnTfLiteParser/TfLiteParser.cpp | 66 |
1 files changed, 33 insertions, 33 deletions
diff --git a/src/armnnTfLiteParser/TfLiteParser.cpp b/src/armnnTfLiteParser/TfLiteParser.cpp index 8b2d7a25bc..6354a1e13a 100644 --- a/src/armnnTfLiteParser/TfLiteParser.cpp +++ b/src/armnnTfLiteParser/TfLiteParser.cpp @@ -1509,57 +1509,57 @@ void TfLiteParserImpl::ParseExpandDims(size_t subgraphIndex, size_t operatorInde armnn::TensorInfo inputTensorInfo = InputTensorInfo(subgraphIndex, operatorIndex, 0); armnn::TensorInfo outputTensorInfo = ToTensorInfo(outputs[0], true); - CheckMatchingQuantization(inputTensorInfo, outputTensorInfo, layerName, "Input 0", "Output 0"); - ReshapeDescriptor reshapeDesc; + armnn::TensorInfo axisTensorInfo = InputTensorInfo(subgraphIndex, operatorIndex, 1); - if (outputTensorInfo.GetShape().AreAllDimensionsSpecified()) + BufferRawPtr axisBufferPtr = GetBuffer(m_Model, inputs[1]->buffer); + if (axisBufferPtr == nullptr) { - reshapeDesc.m_TargetShape = outputTensorInfo.GetShape(); + throw ParseException(fmt::format("{}: Operation has invalid inputs. Failed to read axis.", + CHECK_LOCATION().AsString())); } - else - { - int32_t axis = inputs[1]->shape[0]; - int32_t inputDimSize = static_cast<int32_t>(inputTensorInfo.GetShape().GetNumDimensions()); + std::vector<int32_t> axisData(axisTensorInfo.GetNumElements()); + ::memcpy(axisData.data(), axisBufferPtr->data.data(), axisTensorInfo.GetNumBytes()); + int32_t axis = axisData[0]; - if (axis > inputDimSize || axis < 0 - (inputDimSize + 1)) - { - throw ParseException("axis must be in range [0 - (inputDimSize + 1), inputDimSize] inclusive"); - } + auto inputRank = static_cast<int32_t>(inputTensorInfo.GetShape().GetNumDimensions()); + auto outputRank = inputRank + 1; + if((axis < -1 * outputRank) || (outputRank <= axis)) + { + throw ParseException(fmt::format("{}: Axis {} is not within [-{}, {}) range.", + CHECK_LOCATION().AsString(), axis, outputRank, outputRank)); + } + + axis = axis < 0 ? (axis + outputRank) : axis; - if(axis < 0) + std::vector<unsigned int> shape(static_cast<unsigned int>(outputRank)); + unsigned int inputShapeIndex = 0; + for (unsigned int i = 0; i < static_cast<unsigned int>(outputRank); ++i) + { + if (i == static_cast<unsigned int>(axis)) { - axis = inputDimSize + axis + 1; + shape[i] = 1; } - - std::vector<unsigned int> shape(static_cast<unsigned int>(inputDimSize) + 1); - unsigned int inputShapeIndex = 0; - for (unsigned int i = 0; i < static_cast<unsigned int>(inputDimSize + 1); ++i) + else { - if (i == static_cast<unsigned int>(axis)) - { - shape[i] = 1; - } - else - { - shape[i] = inputTensorInfo.GetShape()[inputShapeIndex]; - ++inputShapeIndex; - } + shape[i] = inputTensorInfo.GetShape()[inputShapeIndex]; + ++inputShapeIndex; } - - reshapeDesc.m_TargetShape = TensorShape(static_cast<unsigned int>(inputDimSize + 1), shape.data()); } - IConnectableLayer* layer = m_Network->AddReshapeLayer(reshapeDesc, layerName.c_str()); - ARMNN_ASSERT(layer != nullptr); - - reshapeDesc.m_TargetShape = OutputTensorInfoFromInputs(subgraphIndex, operatorIndex, layer, 0, {0}).GetShape(); + ReshapeDescriptor reshapeDesc; + reshapeDesc.m_TargetShape = TensorShape(static_cast<unsigned int>(outputRank), shape.data()); outputTensorInfo.SetShape(reshapeDesc.m_TargetShape); + IConnectableLayer* layer = m_Network->AddReshapeLayer(reshapeDesc, layerName.c_str()); + ARMNN_ASSERT(layer != nullptr); layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo); + auto outputTensorIds = GetOutputTensorIds(m_Model, subgraphIndex, operatorIndex); + m_TensorInfos[outputTensorIds[0]] = outputTensorInfo; + auto inputTensorIndexes = AsUnsignedVector(GetInputTensorIds(m_Model, subgraphIndex, operatorIndex)); RegisterInputSlots(subgraphIndex, operatorIndex, layer, {inputTensorIndexes[0]}); |