IVGCVSW-3613 Add Quantized LSTM test to Android NN Driver
Signed-off-by: Ellen Norris-Thompson <ellen.norris-thompson@arm.com>
Change-Id: Ie3c535789186571df9000d75ad2a62ac8c94dcb4
diff --git a/1.2/HalPolicy.cpp b/1.2/HalPolicy.cpp
index 3cd7ce4..e08ae84 100644
--- a/1.2/HalPolicy.cpp
+++ b/1.2/HalPolicy.cpp
@@ -849,73 +849,73 @@
// [outputSize, inputSize] specifying input-to-input part of weights for fully-connected layer inside the
// LSTM cell. Quantization zero point and scale must be the same across all the weights.
const ConstTensorPin inputToInputWeightsPin =
- ConvertOperationInputToConstTensorPin<hal_1_2::HalPolicy>(operation, 0, model, data);
+ ConvertOperationInputToConstTensorPin<hal_1_2::HalPolicy>(operation, 1, model, data);
// 2: The input-to-forget weights. A 2-D tensor of type ANEURALNETWORKS_TENSOR_QUANT8_ASYMM and shape
// [outputSize, inputSize] specifying input-to-forget part of weights for fully-connected layer inside the
// LSTM cell. Quantization zero point and scale must be the same across all the weights.
const ConstTensorPin inputToForgetWeightsPin =
- ConvertOperationInputToConstTensorPin<hal_1_2::HalPolicy>(operation, 1, model, data);
+ ConvertOperationInputToConstTensorPin<hal_1_2::HalPolicy>(operation, 2, model, data);
// 3: The input-to-cell weights. A 2-D tensor of type ANEURALNETWORKS_TENSOR_QUANT8_ASYMM and shape
// [outputSize, inputSize] specifying input-to-cell part of weights for fully-connected layer inside the
// LSTM cell. Quantization zero point and scale must be the same across all the weights.
const ConstTensorPin inputToCellWeightsPin =
- ConvertOperationInputToConstTensorPin<hal_1_2::HalPolicy>(operation, 2, model, data);
+ ConvertOperationInputToConstTensorPin<hal_1_2::HalPolicy>(operation, 3, model, data);
// 4: The input-to-output weights. A 2-D tensor of type ANEURALNETWORKS_TENSOR_QUANT8_ASYMM and shape
// [outputSize, inputSize] specifying input-to-output part of weights for fully-connected layer inside the
// LSTM cell. Quantization zero point and scale must be the same across all the weights.
const ConstTensorPin inputToOutputWeightsPin =
- ConvertOperationInputToConstTensorPin<hal_1_2::HalPolicy>(operation, 3, model, data);
+ ConvertOperationInputToConstTensorPin<hal_1_2::HalPolicy>(operation, 4, model, data);
// 5: The recurrent-to-input weights. A 2-D tensor of type ANEURALNETWORKS_TENSOR_QUANT8_ASYMM and shape
// [outputSize, outputSize] specifying recurrent-to-input part of weights for fully-connected layer inside
// the LSTM cell. Quantization zero point and scale must be the same across all the weights.
const ConstTensorPin recurrentToInputWeightsPin =
- ConvertOperationInputToConstTensorPin<hal_1_2::HalPolicy>(operation, 4, model, data);
+ ConvertOperationInputToConstTensorPin<hal_1_2::HalPolicy>(operation, 5, model, data);
// 6: The recurrent-to-forget weights. A 2-D tensor of type ANEURALNETWORKS_TENSOR_QUANT8_ASYMM and shape
// [outputSize, outputSize] specifying recurrent-to-forget part of weights for fully-connected layer inside
// the LSTM cell. Quantization zero point and scale must be the same across all the weights.
const ConstTensorPin recurrentToForgetWeightsPin =
- ConvertOperationInputToConstTensorPin<hal_1_2::HalPolicy>(operation, 5, model, data);
+ ConvertOperationInputToConstTensorPin<hal_1_2::HalPolicy>(operation, 6, model, data);
// 7: The recurrent-to-cell weights. A 2-D tensor of type ANEURALNETWORKS_TENSOR_QUANT8_ASYMM and shape
// [outputSize, outputSize] specifying recurrent-to-cell part of weights for fully-connected layer inside
// the LSTM cell. Quantization zero point and scale must be the same across all the weights.
const ConstTensorPin recurrentToCellWeightsPin =
- ConvertOperationInputToConstTensorPin<hal_1_2::HalPolicy>(operation, 6, model, data);
+ ConvertOperationInputToConstTensorPin<hal_1_2::HalPolicy>(operation, 7, model, data);
// 8: The recurrent-to-output weights. A 2-D tensor of type ANEURALNETWORKS_TENSOR_QUANT8_ASYMM and shape
// [outputSize, outputSize] specifying recurrent-to-output part of weights for fully-connected layer inside
// the LSTM cell. Quantization zero point and scale must be the same across all the weights.
const ConstTensorPin recurrentToOutputWeightsPin =
- ConvertOperationInputToConstTensorPin<hal_1_2::HalPolicy>(operation, 7, model, data);
+ ConvertOperationInputToConstTensorPin<hal_1_2::HalPolicy>(operation, 8, model, data);
// 9: The input gate bias. A 1-D tensor of type ANEURALNETWORKS_TENSOR_INT32 and shape [outputSize] specifying the
// bias for the fully-connected layer inside the LSTM cell. Bias is quantized with scale being a product
// of input and weights scales and zeroPoint equal to 0.
const ConstTensorPin inputGateBiasPin =
- ConvertOperationInputToConstTensorPin<hal_1_2::HalPolicy>(operation, 8, model, data);
+ ConvertOperationInputToConstTensorPin<hal_1_2::HalPolicy>(operation, 9, model, data);
// 10: The forget gate bias. A 1-D tensor of type ANEURALNETWORKS_TENSOR_INT32 and shape [outputSize] specifying
// the bias for the fully-connected layer inside the LSTM cell. Bias is quantized with scale being a product
// of input and weights scales and zeroPoint equal to 0.
const ConstTensorPin forgetGateBiasPin =
- ConvertOperationInputToConstTensorPin<hal_1_2::HalPolicy>(operation, 9, model, data);
+ ConvertOperationInputToConstTensorPin<hal_1_2::HalPolicy>(operation, 10, model, data);
// 11:The cell bias. A 1-D tensor of type ANEURALNETWORKS_TENSOR_INT32 and shape [outputSize] specifying the bias
// for the fully-connected layer inside the LSTM cell. Bias is quantized with scale being a product of input
// and weights scales and zeroPoint equal to 0.
const ConstTensorPin cellBiasPin =
- ConvertOperationInputToConstTensorPin<hal_1_2::HalPolicy>(operation, 10, model, data);
+ ConvertOperationInputToConstTensorPin<hal_1_2::HalPolicy>(operation, 11, model, data);
// 12:The output gate bias. A 1-D tensor of type ANEURALNETWORKS_TENSOR_INT32 and shape [outputSize] specifying
// the bias for the fully-connected layer inside the LSTM cell. Bias is quantized with scale being a product
// of input and weights scales and zeroPoint equal to 0.
const ConstTensorPin outputGateBiasPin =
- ConvertOperationInputToConstTensorPin<hal_1_2::HalPolicy>(operation, 11, model, data);
+ ConvertOperationInputToConstTensorPin<hal_1_2::HalPolicy>(operation, 12, model, data);
if (!inputToInputWeightsPin.IsValid() ||
!inputToForgetWeightsPin.IsValid() ||
@@ -1014,8 +1014,8 @@
armnn::IConnectableLayer* const layer = data.m_Network->AddQuantizedLstmLayer(params, "QuantizedLstm");
input.Connect(layer->GetInputSlot(0));
- previousOutputIn.Connect(layer->GetInputSlot(1));
- previousCellStateIn.Connect(layer->GetInputSlot(2));
+ previousCellStateIn.Connect(layer->GetInputSlot(1));
+ previousOutputIn.Connect(layer->GetInputSlot(2));
return (SetupAndTrackLayerOutputSlot<hal_1_2::HalPolicy>(operation, 0, *layer, 0, model, data) &&
SetupAndTrackLayerOutputSlot<hal_1_2::HalPolicy>(operation, 1, *layer, 1, model, data));