diff options
Diffstat (limited to 'src/backends/neon/workloads/NeonUnidirectionalSequenceLstmFloatWorkload.cpp')
| -rw-r--r-- | src/backends/neon/workloads/NeonUnidirectionalSequenceLstmFloatWorkload.cpp | 40 |
1 files changed, 18 insertions, 22 deletions
diff --git a/src/backends/neon/workloads/NeonUnidirectionalSequenceLstmFloatWorkload.cpp b/src/backends/neon/workloads/NeonUnidirectionalSequenceLstmFloatWorkload.cpp index c911afb237..8dba719d91 100644 --- a/src/backends/neon/workloads/NeonUnidirectionalSequenceLstmFloatWorkload.cpp +++ b/src/backends/neon/workloads/NeonUnidirectionalSequenceLstmFloatWorkload.cpp @@ -39,7 +39,7 @@ NeonUnidirectionalSequenceLstmFloatWorkload::NeonUnidirectionalSequenceLstmFloat GetGuid()); const arm_compute::ITensor& input = static_cast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); - arm_compute::ITensor& output = static_cast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); + arm_compute::ITensor& output = static_cast<IAclTensorHandle*>(m_Data.m_Outputs[2])->GetTensor(); TensorInfo inputInfo = info.m_InputTensorInfos[0]; TensorInfo outputInfo = info.m_OutputTensorInfos[0]; @@ -49,7 +49,7 @@ NeonUnidirectionalSequenceLstmFloatWorkload::NeonUnidirectionalSequenceLstmFloat TensorShape inputLayerShape = static_cast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetShape(); TensorShape cellStateLayerShape = static_cast<IAclTensorHandle*>(m_Data.m_Inputs[2])->GetShape(); - TensorShape outputLayerShape = static_cast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetShape(); + TensorShape outputLayerShape = static_cast<IAclTensorHandle*>(m_Data.m_Outputs[2])->GetShape(); unsigned int maxTime = m_Data.m_Parameters.m_TimeMajor ? inputLayerShape[0] : inputLayerShape[1]; unsigned int batchSize = m_Data.m_Parameters.m_TimeMajor ? inputLayerShape[1] : inputLayerShape[0]; @@ -288,7 +288,7 @@ NeonUnidirectionalSequenceLstmFloatWorkload::NeonUnidirectionalSequenceLstmFloat // LSTM input/output cannot be > 2 dimensions so need to resize its TensorInfo. if (maxTime == 1 && m_Data.m_Parameters.m_TimeMajor) { - TensorShape inputShape = GetTensorShape((&input)->info()->tensor_shape(), 1U); + TensorShape inputShape = GetTensorShape(input.info()->tensor_shape(), 1U); TensorShape outputShape = GetTensorShape((&output)->info()->tensor_shape(), 1U); TensorShape inputShapeShrink({inputShape[1], inputShape[2]}); @@ -297,10 +297,10 @@ NeonUnidirectionalSequenceLstmFloatWorkload::NeonUnidirectionalSequenceLstmFloat auto acl_input_shape_shrink = BuildArmComputeTensorShape(inputShapeShrink); auto acl_output_shape_shrink = BuildArmComputeTensorShape(outputShapeShrink); - (&input)->info()->set_tensor_shape(acl_input_shape_shrink); + input.info()->set_tensor_shape(acl_input_shape_shrink); inputLSTM = const_cast<arm_compute::ITensor*>(&input); - (&output)->info()->set_tensor_shape(acl_output_shape_shrink); + output.info()->set_tensor_shape(acl_output_shape_shrink); outputLSTM = &output; } // If there is only one LSTM batch major batch, we will not concat, only permute. @@ -432,9 +432,9 @@ NeonUnidirectionalSequenceLstmFloatWorkload::NeonUnidirectionalSequenceLstmFloat unsigned int aclAxisConcat = CalcAclAxis(concatDescriptor.GetNumDimensions(), concatDescriptor.GetConcatAxis()); if (!m_Data.m_Parameters.m_TimeMajor) { - TensorInfo concatOuputTensorInfo = outputInfo; - concatOuputTensorInfo.SetShape(timeMajorShapeOutput); - BuildArmComputeTensor(concat_out, concatOuputTensorInfo); + TensorInfo concatOutputTensorInfo = outputInfo; + concatOutputTensorInfo.SetShape(timeMajorShapeOutput); + BuildArmComputeTensor(concat_out, concatOutputTensorInfo); armcomputetensorutils::InitialiseArmComputeTensorEmpty(concat_out); m_Concat->configure(m_ConcatInputs, &concat_out, aclAxisConcat); @@ -452,11 +452,11 @@ NeonUnidirectionalSequenceLstmFloatWorkload::NeonUnidirectionalSequenceLstmFloat { if (!m_Data.m_Parameters.m_TimeMajor) { - (&output)->info()->set_tensor_shape(BuildArmComputeTensorShape(shapeExpandBatchMajor)); + output.info()->set_tensor_shape(BuildArmComputeTensorShape(shapeExpandBatchMajor)); } else { - (&output)->info()->set_tensor_shape(BuildArmComputeTensorShape(shapeExpandTimeMajor)); + output.info()->set_tensor_shape(BuildArmComputeTensorShape(shapeExpandTimeMajor)); } } @@ -510,14 +510,12 @@ arm_compute::Status NeonUnidirectionalSequenceLstmFloatWorkloadValidate(const TensorInfo& input, const TensorInfo& outputStateIn, const TensorInfo& cellStateIn, + const TensorInfo& outputStateOut, + const TensorInfo& cellStateOut, const TensorInfo& output, - const Optional<TensorInfo>& hiddenStateOutput, - const Optional<TensorInfo>& cellStateOutput, const UnidirectionalSequenceLstmDescriptor& descriptor, const LstmInputParamsInfo& paramsInfo) { - IgnoreUnused(hiddenStateOutput, cellStateOutput); - TensorShape inputLayerShape = input.GetShape(); TensorShape outputLayerShape = outputStateIn.GetShape(); @@ -612,8 +610,6 @@ NeonUnidirectionalSequenceLstmFloatWorkloadValidate(const TensorInfo& input, arm_compute::LSTMParams<arm_compute::ITensorInfo> lstm_params_info; const TensorInfo& scratchBuffer = TensorInfo(cellStateIn.GetShape(), input.GetDataType()); - const TensorInfo& outputStateOut = TensorInfo(outputStateIn.GetShape(), input.GetDataType()); - const TensorInfo& cellStateOut = TensorInfo(cellStateIn.GetShape(), input.GetDataType()); // The inputs and outputs const arm_compute::TensorInfo aclOutputStateInInfo = BuildArmComputeTensorInfo(outputStateIn); @@ -704,7 +700,7 @@ NeonUnidirectionalSequenceLstmFloatWorkloadValidate(const TensorInfo& input, aclOutputLayerNormWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetOutputLayerNormWeights()); lstm_params_info.set_layer_normalization_params(descriptor.m_CifgEnabled ? nullptr : - &aclInputLayerNormWeightsInfo, + &aclInputLayerNormWeightsInfo, &aclForgetLayerNormWeightsInfo, &aclCellLayerNormWeightsInfo, &aclOutputLayerNormWeightsInfo); @@ -803,9 +799,9 @@ NeonUnidirectionalSequenceLstmFloatWorkloadValidate(const TensorInfo& input, TensorShape shapeExpandTimeMajor({1, shape[0], shape[1]}); TensorShape shapeExpandBatchMajor({shape[0], 1, shape[1]}); - TensorInfo concatOuputTensorInfo = TensorInfo(output); - concatOuputTensorInfo.SetShape(timeMajorShapeOutput); - arm_compute::TensorInfo aclConcatOuputTensorInfo= BuildArmComputeTensorInfo(concatOuputTensorInfo); + TensorInfo concatOutputTensorInfo = TensorInfo(output); + concatOutputTensorInfo.SetShape(timeMajorShapeOutput); + arm_compute::TensorInfo aclConcatOutputTensorInfo= BuildArmComputeTensorInfo(concatOutputTensorInfo); if (maxTime != 1) // ACL concat does not work with only one element to concatenate. { @@ -819,7 +815,7 @@ NeonUnidirectionalSequenceLstmFloatWorkloadValidate(const TensorInfo& input, if (!descriptor.m_TimeMajor) { statusConcat = arm_compute::NEConcatenateLayer::validate(concatInputsTensorInfosPtr, - &aclConcatOuputTensorInfo, + &aclConcatOutputTensorInfo, aclAxisConcat); } else @@ -853,7 +849,7 @@ NeonUnidirectionalSequenceLstmFloatWorkloadValidate(const TensorInfo& input, // Output now time major. Permute output back to batch major. if (maxTime != 1) { - statusPermute2 = arm_compute::NEPermute::validate(&aclConcatOuputTensorInfo, + statusPermute2 = arm_compute::NEPermute::validate(&aclConcatOutputTensorInfo, &aclOutputInfo, arm_compute::PermutationVector(0U, 2U, 1U)); } |