diff options
Diffstat (limited to 'src/armnnTfLiteParser/TfLiteParser.cpp')
| -rw-r--r-- | src/armnnTfLiteParser/TfLiteParser.cpp | 37 |
1 files changed, 19 insertions, 18 deletions
diff --git a/src/armnnTfLiteParser/TfLiteParser.cpp b/src/armnnTfLiteParser/TfLiteParser.cpp index 5f71ebcff6..7cb9f6a7bc 100644 --- a/src/armnnTfLiteParser/TfLiteParser.cpp +++ b/src/armnnTfLiteParser/TfLiteParser.cpp @@ -1227,7 +1227,6 @@ void TfLiteParserImpl::ParseDepthwiseConv2D(size_t subgraphIndex, size_t operato CHECK_SUPPORTED_FUSED_ACTIVATION(options, subgraphIndex, operatorIndex); DepthwiseConvolution2dDescriptor desc; - desc.m_BiasEnabled = false; desc.m_StrideX = CHECKED_NON_NEGATIVE(options->stride_w); desc.m_StrideY = CHECKED_NON_NEGATIVE(options->stride_h); desc.m_DataLayout = armnn::DataLayout::NHWC; @@ -1235,6 +1234,11 @@ void TfLiteParserImpl::ParseDepthwiseConv2D(size_t subgraphIndex, size_t operato auto inputs = GetInputs(m_Model, subgraphIndex, operatorIndex); CHECK_VALID_SIZE(inputs.size(), 2, 3); + if (inputs.size() == 3) + { + desc.m_BiasEnabled = true; + } + auto outputs = GetOutputs(m_Model, subgraphIndex, operatorIndex); CHECK_VALID_SIZE(outputs.size(), 1); desc.m_DilationX = CHECKED_NON_NEGATIVE(options->dilation_w_factor); @@ -1257,26 +1261,24 @@ void TfLiteParserImpl::ParseDepthwiseConv2D(size_t subgraphIndex, size_t operato desc.m_DilationX, desc.m_PadLeft, desc.m_PadRight, options->padding); // ArmNN uses the same filter tensor layout at TfLite [1, H, W, O] no need for any permutation - auto filterTensor = CreateConstTensorNonPermuted(inputs[1], filterTensorInfo, inputTensorInfo.GetDataType()); - armnn::IConnectableLayer* layer = nullptr; + auto filterTensor = CreateConstTensorNonPermuted(inputs[1], filterTensorInfo); auto layerName = fmt::format("DepthwiseConv2D:{}:{}", subgraphIndex, operatorIndex); - if (inputs.size() == 3) + auto inputTensorIndexes = AsUnsignedVector(GetInputTensorIds(m_Model, subgraphIndex, operatorIndex)); + // Add the first input and weights tensor to the registration list. + // The constant weights will be added by SetupConstantLayers. + std::vector<unsigned int> tensorIndexesToRegister = {inputTensorIndexes[0], inputTensorIndexes[1]}; + + armnn::IConnectableLayer* layer = m_Network->AddDepthwiseConvolution2dLayer(desc, layerName.c_str()); + + if (desc.m_BiasEnabled) { desc.m_BiasEnabled = true; TensorInfo biasTensorInfo = ToTensorInfo(inputs[2]); - auto biasTensorAndData = CreateConstTensorNonPermuted(inputs[2], biasTensorInfo, inputTensorInfo.GetDataType()); - layer = m_Network->AddDepthwiseConvolution2dLayer(desc, - filterTensor.first, - Optional<ConstTensor>(biasTensorAndData.first), - layerName.c_str()); - } - else - { - layer = m_Network->AddDepthwiseConvolution2dLayer(desc, - filterTensor.first, - EmptyOptional(), - layerName.c_str()); + auto biasTensorAndData = CreateConstTensorNonPermuted(inputs[2], biasTensorInfo); + + // Add the biases input to the registration list, a constant layer will be added by SetupConstantLayers. + tensorIndexesToRegister.emplace_back(inputTensorIndexes[2]); } ARMNN_ASSERT(layer != nullptr); @@ -1285,8 +1287,7 @@ void TfLiteParserImpl::ParseDepthwiseConv2D(size_t subgraphIndex, size_t operato // register the input connection slots for the layer, connections are made after all layers have been created // only the tensors for the inputs are relevant, exclude the const tensors - auto inputTensorIndexes = AsUnsignedVector(GetInputTensorIds(m_Model, subgraphIndex, operatorIndex)); - RegisterInputSlots(subgraphIndex, operatorIndex, layer, {inputTensorIndexes[0]}); + RegisterInputSlots(subgraphIndex, operatorIndex, layer, tensorIndexesToRegister); layer = AddFusedActivationLayer(layer, 0, options->fused_activation_function); // register the output connection slots for the layer, connections are made after all layers have been created |