diff options
Diffstat (limited to 'src/backends/backendsCommon/test/LstmTestImpl.hpp')
-rw-r--r-- | src/backends/backendsCommon/test/LstmTestImpl.hpp | 64 |
1 files changed, 32 insertions, 32 deletions
diff --git a/src/backends/backendsCommon/test/LstmTestImpl.hpp b/src/backends/backendsCommon/test/LstmTestImpl.hpp index 56f40aba84..e300a529ce 100644 --- a/src/backends/backendsCommon/test/LstmTestImpl.hpp +++ b/src/backends/backendsCommon/test/LstmTestImpl.hpp @@ -29,15 +29,15 @@ LayerTestResult<float, 2> LstmNoCifgNoPeepholeNoProjectionTestImpl( unsigned numUnits = outputSize; - armnn::TensorInfo inputTensorInfo({batchSize , inputSize}, armnn::GetDataType<float>()); - armnn::TensorInfo cellStateInTensorInfo({batchSize , numUnits}, armnn::GetDataType<float>()); - armnn::TensorInfo outputStateInTensorInfo({batchSize , outputSize}, armnn::GetDataType<float>()); + armnn::TensorInfo inputTensorInfo({batchSize , inputSize}, armnn::DataType::Float32); + armnn::TensorInfo cellStateInTensorInfo({batchSize , numUnits}, armnn::DataType::Float32); + armnn::TensorInfo outputStateInTensorInfo({batchSize , outputSize}, armnn::DataType::Float32); - armnn::TensorInfo scratchBufferTensorInfo({batchSize, numUnits * 4}, armnn::GetDataType<float>()); - armnn::TensorInfo cellStateOutTensorInfo({batchSize, numUnits}, armnn::GetDataType<float>()); - armnn::TensorInfo outputStateOutTensorInfo({batchSize, outputSize}, armnn::GetDataType<float>()); - armnn::TensorInfo outputTensorInfo({batchSize, outputSize}, armnn::GetDataType<float>()); + armnn::TensorInfo scratchBufferTensorInfo({batchSize, numUnits * 4}, armnn::DataType::Float32); + armnn::TensorInfo cellStateOutTensorInfo({batchSize, numUnits}, armnn::DataType::Float32); + armnn::TensorInfo outputStateOutTensorInfo({batchSize, outputSize}, armnn::DataType::Float32); + armnn::TensorInfo outputTensorInfo({batchSize, outputSize}, armnn::DataType::Float32); LayerTestResult<float, 2> ret(outputTensorInfo); @@ -91,9 +91,9 @@ LayerTestResult<float, 2> LstmNoCifgNoPeepholeNoProjectionTestImpl( AddOutputToWorkload(data, info, cellStateOutTensorInfo, cellStateOutHandle.get()); AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); - armnn::TensorInfo tensorInfo4({numUnits}, armnn::GetDataType<float>()); - armnn::TensorInfo tensorInfo8({numUnits, 2}, armnn::GetDataType<float>()); - armnn::TensorInfo tensorInfo16({numUnits, 4}, armnn::GetDataType<float>()); + armnn::TensorInfo tensorInfo4({numUnits}, armnn::DataType::Float32); + armnn::TensorInfo tensorInfo8({numUnits, 2}, armnn::DataType::Float32); + armnn::TensorInfo tensorInfo16({numUnits, 4}, armnn::DataType::Float32); auto inputToInputWeights = MakeTensor<float, 2>(tensorInfo8, {-0.45018822f, -0.02338299f, -0.0870589f, -0.34550029f, 0.04266912f, -0.15680569f, @@ -232,15 +232,15 @@ LstmLayerNoCifgWithPeepholeWithProjectionTestImpl(armnn::IWorkloadFactory& workl unsigned int inputSize = 5; unsigned numUnits = 20; - armnn::TensorInfo inputTensorInfo({batchSize , inputSize}, armnn::GetDataType<float>()); - armnn::TensorInfo cellStateInTensorInfo({batchSize , numUnits}, armnn::GetDataType<float>()); - armnn::TensorInfo outputStateInTensorInfo({batchSize , outputSize}, armnn::GetDataType<float>()); + armnn::TensorInfo inputTensorInfo({batchSize , inputSize}, armnn::DataType::Float32); + armnn::TensorInfo cellStateInTensorInfo({batchSize , numUnits}, armnn::DataType::Float32); + armnn::TensorInfo outputStateInTensorInfo({batchSize , outputSize}, armnn::DataType::Float32); // Scratch buffer size without CIFG [batchSize, numUnits * 4] - armnn::TensorInfo scratchBufferTensorInfo({batchSize, numUnits * 4}, armnn::GetDataType<float>()); - armnn::TensorInfo cellStateOutTensorInfo({batchSize, numUnits}, armnn::GetDataType<float>()); - armnn::TensorInfo outputStateOutTensorInfo({batchSize, outputSize}, armnn::GetDataType<float>()); - armnn::TensorInfo outputTensorInfo({batchSize, outputSize}, armnn::GetDataType<float>()); + armnn::TensorInfo scratchBufferTensorInfo({batchSize, numUnits * 4}, armnn::DataType::Float32); + armnn::TensorInfo cellStateOutTensorInfo({batchSize, numUnits}, armnn::DataType::Float32); + armnn::TensorInfo outputStateOutTensorInfo({batchSize, outputSize}, armnn::DataType::Float32); + armnn::TensorInfo outputTensorInfo({batchSize, outputSize}, armnn::DataType::Float32); LayerTestResult<float, 2> ret(outputTensorInfo); @@ -292,11 +292,11 @@ LstmLayerNoCifgWithPeepholeWithProjectionTestImpl(armnn::IWorkloadFactory& workl AddOutputToWorkload(data, info, cellStateOutTensorInfo, cellStateOutHandle.get()); AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); - armnn::TensorInfo tensorInfo16({outputSize}, armnn::GetDataType<float>()); - armnn::TensorInfo tensorInfo20({numUnits}, armnn::GetDataType<float>()); - armnn::TensorInfo tensorInfo20x5({numUnits, inputSize}, armnn::GetDataType<float>()); - armnn::TensorInfo tensorInfo20x16({numUnits, outputSize}, armnn::GetDataType<float>()); - armnn::TensorInfo tensorInfo16x20({outputSize, numUnits}, armnn::GetDataType<float>()); + armnn::TensorInfo tensorInfo16({outputSize}, armnn::DataType::Float32); + armnn::TensorInfo tensorInfo20({numUnits}, armnn::DataType::Float32); + armnn::TensorInfo tensorInfo20x5({numUnits, inputSize}, armnn::DataType::Float32); + armnn::TensorInfo tensorInfo20x16({numUnits, outputSize}, armnn::DataType::Float32); + armnn::TensorInfo tensorInfo16x20({outputSize, numUnits}, armnn::DataType::Float32); auto inputToInputWeights = MakeTensor<float, 2>(tensorInfo20x5, {0.021393683f,0.06124551f, 0.046905167f,-0.014657677f,-0.03149463f, @@ -950,15 +950,15 @@ LayerTestResult<float, 2> LstmLayerWithCifgWithPeepholeNoProjectionTestImpl( const unsigned int cellSize = outputSize; // Decide the shape of all input tensors - armnn::TensorInfo inputTensorInfo({batchSize , inputSize}, armnn::GetDataType<float>()); - armnn::TensorInfo outputStateInTensorInfo({batchSize, outputSize}, armnn::GetDataType<float>()); - armnn::TensorInfo cellStateInTensorInfo({batchSize, cellSize}, armnn::GetDataType<float>()); + armnn::TensorInfo inputTensorInfo({batchSize , inputSize}, armnn::DataType::Float32); + armnn::TensorInfo outputStateInTensorInfo({batchSize, outputSize}, armnn::DataType::Float32); + armnn::TensorInfo cellStateInTensorInfo({batchSize, cellSize}, armnn::DataType::Float32); unsigned int scratchBufferSize = cifgEnabled ? cellSize * 3 : cellSize * 4; - armnn::TensorInfo scratchBufferTensorInfo({batchSize, scratchBufferSize}, armnn::GetDataType<float>()); - armnn::TensorInfo outputStateOutTensorInfo({batchSize, outputSize}, armnn::GetDataType<float>()); - armnn::TensorInfo cellStateOutTensorInfo({batchSize, cellSize}, armnn::GetDataType<float>()); - armnn::TensorInfo outputTensorInfo({batchSize, outputSize}, armnn::GetDataType<float>()); + armnn::TensorInfo scratchBufferTensorInfo({batchSize, scratchBufferSize}, armnn::DataType::Float32); + armnn::TensorInfo outputStateOutTensorInfo({batchSize, outputSize}, armnn::DataType::Float32); + armnn::TensorInfo cellStateOutTensorInfo({batchSize, cellSize}, armnn::DataType::Float32); + armnn::TensorInfo outputTensorInfo({batchSize, outputSize}, armnn::DataType::Float32); // List of inputs std::vector<float> inputData; @@ -974,9 +974,9 @@ LayerTestResult<float, 2> LstmLayerWithCifgWithPeepholeNoProjectionTestImpl( // Prepare all the weights in the descriptor for LSTM armnn::LstmQueueDescriptor data; - armnn::TensorInfo tensorInfoInput({cellSize, inputSize}, armnn::GetDataType<float>()); - armnn::TensorInfo tensorInfoOutput({cellSize, outputSize}, armnn::GetDataType<float>()); - armnn::TensorInfo tensorInfoNumUnits({cellSize}, armnn::GetDataType<float>()); + armnn::TensorInfo tensorInfoInput({cellSize, inputSize}, armnn::DataType::Float32); + armnn::TensorInfo tensorInfoOutput({cellSize, outputSize}, armnn::DataType::Float32); + armnn::TensorInfo tensorInfoNumUnits({cellSize}, armnn::DataType::Float32); auto inputToCellWeights = MakeTensor<float, 2>(tensorInfoInput, {-0.49770179f, -0.27711356f, -0.09624726f, 0.05100781f, |