IVGCVSW-4590 Fix Lstm layers CellToInputWeights
* CellToInputWeights were not handeled correctly
* Changed CellToInputWeights from Cifg to peephole parameter
* Modified exiting unit tests
* Added unit test to cover new configuration
* Added more descriptive error messages
Signed-off-by: Jan Eilers <jan.eilers@arm.com>
Change-Id: Ied5dc1253d3df1fd1a79b887a58603d0a9c8f396
diff --git a/src/armnn/Network.cpp b/src/armnn/Network.cpp
index 0272b3d..c2da4da 100644
--- a/src/armnn/Network.cpp
+++ b/src/armnn/Network.cpp
@@ -1520,27 +1520,24 @@
{
if(params.m_InputToInputWeights == nullptr)
{
- throw InvalidArgumentException("AddLstmLayer: Input To Input Weights cannot be NULL");
+ throw InvalidArgumentException("AddLstmLayer: Input To Input Weights cannot be NULL "
+ "when CIFG is disabled.");
}
if(params.m_RecurrentToInputWeights == nullptr)
{
throw InvalidArgumentException(
- "AddLstmLayer: Recurrent To Input Weights cannot be NULL");
+ "AddLstmLayer: Recurrent To Input Weights cannot be NULL "
+ "when CIFG is disabled.");
}
if(params.m_InputGateBias == nullptr)
{
- throw InvalidArgumentException("AddLstmLayer: Input Gate Bias cannot be NULL");
+ throw InvalidArgumentException("AddLstmLayer: Input Gate Bias cannot be NULL "
+ "when CIFG is disabled.");
}
layer->m_CifgParameters.m_InputToInputWeights =
std::make_unique<ScopedCpuTensorHandle>(*(params.m_InputToInputWeights));
layer->m_CifgParameters.m_RecurrentToInputWeights =
std::make_unique<ScopedCpuTensorHandle>(*(params.m_RecurrentToInputWeights));
- // In the VTS tests, cell-to-input weights may be null, even if the other CIFG params are not.
- if(params.m_CellToInputWeights != nullptr)
- {
- layer->m_CifgParameters.m_CellToInputWeights =
- std::make_unique<ScopedCpuTensorHandle>(*(params.m_CellToInputWeights));
- }
layer->m_CifgParameters.m_InputGateBias =
std::make_unique<ScopedCpuTensorHandle>(*(params.m_InputGateBias));
}
@@ -1550,7 +1547,8 @@
{
if(params.m_ProjectionWeights == nullptr)
{
- throw InvalidArgumentException("AddLstmLayer: Projection Weights cannot be NULL");
+ throw InvalidArgumentException("AddLstmLayer: Projection Weights cannot be NULL "
+ "when projection is enabled.");
}
layer->m_ProjectionParameters.m_ProjectionWeights =
std::make_unique<ScopedCpuTensorHandle>(*(params.m_ProjectionWeights));
@@ -1564,14 +1562,29 @@
//Lstm Peephole params
if(descriptor.m_PeepholeEnabled)
{
+ if(!descriptor.m_CifgEnabled)
+ {
+ if(params.m_CellToInputWeights == nullptr)
+ {
+ throw InvalidArgumentException("AddLstmLayer: Cell To Input Weights cannot be NULL "
+ "when Peephole is enabled and CIFG disabled.");
+ }
+
+ layer->m_PeepholeParameters.m_CellToInputWeights =
+ std::make_unique<ScopedCpuTensorHandle>(*(params.m_CellToInputWeights));
+ }
+
if(params.m_CellToForgetWeights == nullptr)
{
- throw InvalidArgumentException("AddLstmLayer: Cell To Forget Weights cannot be NULL");
+ throw InvalidArgumentException("AddLstmLayer: Cell To Forget Weights cannot be NULL "
+ "when Peephole is enabled.");
}
if(params.m_CellToOutputWeights == nullptr)
{
- throw InvalidArgumentException("AddLstmLayer: Cell To Output Weights cannot be NULL");
+ throw InvalidArgumentException("AddLstmLayer: Cell To Output Weights cannot be NULL "
+ "when Peephole is enabled.");
}
+
layer->m_PeepholeParameters.m_CellToForgetWeights =
std::make_unique<ScopedCpuTensorHandle>(*(params.m_CellToForgetWeights));
layer->m_PeepholeParameters.m_CellToOutputWeights =
@@ -1585,7 +1598,8 @@
{
if(params.m_InputLayerNormWeights == nullptr)
{
- throw InvalidArgumentException("AddLstmLayer: Input layer normalization weights cannot be NULL");
+ throw InvalidArgumentException("AddLstmLayer: Input layer normalization weights cannot be NULL "
+ "when layer normalization is enabled and CIFG disabled.");
}
layer->m_LayerNormParameters.m_InputLayerNormWeights =
std::make_unique<ScopedCpuTensorHandle>(*(params.m_InputLayerNormWeights));
@@ -1593,15 +1607,18 @@
if(params.m_ForgetLayerNormWeights == nullptr)
{
- throw InvalidArgumentException("AddLstmLayer: Forget layer normalization weights cannot be NULL");
+ throw InvalidArgumentException("AddLstmLayer: Forget layer normalization weights cannot be NULL "
+ "when layer normalization is enabled.");
}
if(params.m_CellLayerNormWeights == nullptr)
{
- throw InvalidArgumentException("AddLstmLayer: Cell layer normalization weights cannot be NULL");
+ throw InvalidArgumentException("AddLstmLayer: Cell layer normalization weights cannot be NULL "
+ "when layer normalization is enabled.");
}
if(params.m_OutputLayerNormWeights == nullptr)
{
- throw InvalidArgumentException("AddLstmLayer: Output layer normalization weights cannot be NULL");
+ throw InvalidArgumentException("AddLstmLayer: Output layer normalization weights cannot be NULL "
+ "when layer normalization is enabled.");
}
layer->m_LayerNormParameters.m_ForgetLayerNormWeights =
std::make_unique<ScopedCpuTensorHandle>(*(params.m_ForgetLayerNormWeights));
diff --git a/src/armnn/layers/LstmLayer.cpp b/src/armnn/layers/LstmLayer.cpp
index 581ba45..1d94569 100644
--- a/src/armnn/layers/LstmLayer.cpp
+++ b/src/armnn/layers/LstmLayer.cpp
@@ -39,7 +39,6 @@
{
descriptor.m_InputToInputWeights = m_CifgParameters.m_InputToInputWeights.get();
descriptor.m_RecurrentToInputWeights = m_CifgParameters.m_RecurrentToInputWeights.get();
- descriptor.m_CellToInputWeights = m_CifgParameters.m_CellToInputWeights.get();
descriptor.m_InputGateBias = m_CifgParameters.m_InputGateBias.get();
}
@@ -53,6 +52,10 @@
// Peephole parameters
if (m_Param.m_PeepholeEnabled)
{
+ if (!m_Param.m_CifgEnabled)
+ {
+ descriptor.m_CellToInputWeights = m_PeepholeParameters.m_CellToInputWeights.get();
+ }
descriptor.m_CellToForgetWeights = m_PeepholeParameters.m_CellToForgetWeights.get();
descriptor.m_CellToOutputWeights = m_PeepholeParameters.m_CellToOutputWeights.get();
}
@@ -102,8 +105,6 @@
std::make_unique<ScopedCpuTensorHandle>(*m_CifgParameters.m_InputToInputWeights) : nullptr;
layer->m_CifgParameters.m_RecurrentToInputWeights = m_CifgParameters.m_RecurrentToInputWeights ?
std::make_unique<ScopedCpuTensorHandle>(*m_CifgParameters.m_RecurrentToInputWeights) : nullptr;
- layer->m_CifgParameters.m_CellToInputWeights = m_CifgParameters.m_CellToInputWeights ?
- std::make_unique<ScopedCpuTensorHandle>(*m_CifgParameters.m_CellToInputWeights) : nullptr;
layer->m_CifgParameters.m_InputGateBias = m_CifgParameters.m_InputGateBias ?
std::make_unique<ScopedCpuTensorHandle>(*m_CifgParameters.m_InputGateBias) : nullptr;
}
@@ -118,6 +119,11 @@
if (m_Param.m_PeepholeEnabled)
{
+ if (!m_Param.m_CifgEnabled)
+ {
+ layer->m_PeepholeParameters.m_CellToInputWeights = m_PeepholeParameters.m_CellToInputWeights ?
+ std::make_unique<ScopedCpuTensorHandle>(*m_PeepholeParameters.m_CellToInputWeights) : nullptr;
+ }
layer->m_PeepholeParameters.m_CellToForgetWeights = m_PeepholeParameters.m_CellToForgetWeights ?
std::make_unique<ScopedCpuTensorHandle>(*m_PeepholeParameters.m_CellToForgetWeights) : nullptr;
layer->m_PeepholeParameters.m_CellToOutputWeights = m_PeepholeParameters.m_CellToOutputWeights ?
@@ -209,8 +215,6 @@
"LstmLayer: m_CifgParameters.m_InputToInputWeights should not have a value when CIFG is enabled.");
BOOST_ASSERT_MSG(m_CifgParameters.m_RecurrentToInputWeights == nullptr,
"LstmLayer: m_CifgParameters.m_RecurrentToInputWeights should not have a value when CIFG is enabled.");
- BOOST_ASSERT_MSG(m_CifgParameters.m_CellToInputWeights == nullptr,
- "LstmLayer: m_CifgParameters.m_CellToInputWeights should not have a value when CIFG is enabled.");
BOOST_ASSERT_MSG(m_CifgParameters.m_InputGateBias == nullptr,
"LstmLayer: m_CifgParameters.m_InputGateBias should not have a value when CIFG is enabled.");
@@ -228,6 +232,12 @@
if (m_Param.m_PeepholeEnabled)
{
+ if (!m_Param.m_CifgEnabled)
+ {
+ BOOST_ASSERT_MSG(m_PeepholeParameters.m_CellToInputWeights != nullptr,
+ "LstmLayer: m_PeepholeParameters.m_CellToInputWeights should not be null "
+ "when Peephole is enabled and CIFG is disabled.");
+ }
BOOST_ASSERT_MSG(m_PeepholeParameters.m_CellToForgetWeights != nullptr,
"LstmLayer: m_PeepholeParameters.m_CellToForgetWeights should not be null.");
BOOST_ASSERT_MSG(m_PeepholeParameters.m_CellToOutputWeights != nullptr,
@@ -278,7 +288,6 @@
// Cifg parameters
m_CifgParameters.m_InputToInputWeights,
m_CifgParameters.m_RecurrentToInputWeights,
- m_CifgParameters.m_CellToInputWeights,
m_CifgParameters.m_InputGateBias,
// Projection parameters
@@ -286,6 +295,7 @@
m_ProjectionParameters.m_ProjectionBias,
// Peephole parameters
+ m_PeepholeParameters.m_CellToInputWeights,
m_PeepholeParameters.m_CellToForgetWeights,
m_PeepholeParameters.m_CellToOutputWeights,
@@ -368,10 +378,10 @@
inputParams.m_RecurrentToOutputWeights = &recurrentToOutputWeightsTensor;
}
ConstTensor cellToInputWeightsTensor;
- if (m_CifgParameters.m_CellToInputWeights != nullptr)
+ if (m_PeepholeParameters.m_CellToInputWeights != nullptr)
{
- ConstTensor cellToInputWeightsTensorCopy(m_CifgParameters.m_CellToInputWeights->GetTensorInfo(),
- m_CifgParameters.m_CellToInputWeights->Map(true));
+ ConstTensor cellToInputWeightsTensorCopy(m_PeepholeParameters.m_CellToInputWeights->GetTensorInfo(),
+ m_PeepholeParameters.m_CellToInputWeights->Map(true));
cellToInputWeightsTensor = cellToInputWeightsTensorCopy;
inputParams.m_CellToInputWeights = &cellToInputWeightsTensor;
}
diff --git a/src/armnn/layers/LstmLayer.hpp b/src/armnn/layers/LstmLayer.hpp
index 21421f2..5ccb4bc 100644
--- a/src/armnn/layers/LstmLayer.hpp
+++ b/src/armnn/layers/LstmLayer.hpp
@@ -30,8 +30,6 @@
/// A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units].
std::unique_ptr<ScopedCpuTensorHandle> m_RecurrentToInputWeights;
/// A unique pointer to represent 1D weights tensor with dimensions [num_units].
- std::unique_ptr<ScopedCpuTensorHandle> m_CellToInputWeights;
- /// A unique pointer to represent 1D weights tensor with dimensions [num_units].
std::unique_ptr<ScopedCpuTensorHandle> m_InputGateBias;
};
@@ -46,6 +44,8 @@
struct LstmOptPeepholeParameters
{
/// A unique pointer to represent 1D weights tensor with dimensions [num_units].
+ std::unique_ptr<ScopedCpuTensorHandle> m_CellToInputWeights;
+ /// A unique pointer to represent 1D weights tensor with dimensions [num_units].
std::unique_ptr<ScopedCpuTensorHandle> m_CellToForgetWeights;
/// A unique pointer to represent 1D weights tensor with dimensions [num_units].
std::unique_ptr<ScopedCpuTensorHandle> m_CellToOutputWeights;
diff --git a/src/armnn/test/ConstTensorLayerVisitor.cpp b/src/armnn/test/ConstTensorLayerVisitor.cpp
index 7ef3dd2..ab83a89 100644
--- a/src/armnn/test/ConstTensorLayerVisitor.cpp
+++ b/src/armnn/test/ConstTensorLayerVisitor.cpp
@@ -861,11 +861,6 @@
ConstTensor recurrentToInputWeights(TensorInfo(
4, recurrentToInputWeightsDimensions.data(), DataType::Float32), recurrentToInputWeightsData);
- std::vector<float> cellToInputWeightsData = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0};
- std::vector<unsigned int> cellToInputWeightsDimensions = {1, 1, 3, 3};
- ConstTensor cellToInputWeights(
- TensorInfo(4, cellToInputWeightsDimensions.data(), DataType::Float32), cellToInputWeightsData);
-
std::vector<float> inputGateBiasData = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0};
std::vector<unsigned int> inputGateBiasDimensions = {1, 1, 3, 3};
ConstTensor inputGateBias(
@@ -884,7 +879,6 @@
params.m_InputToInputWeights = &inputToInputWeights;
params.m_RecurrentToInputWeights = &recurrentToInputWeights;
- params.m_CellToInputWeights = &cellToInputWeights;
params.m_InputGateBias = &inputGateBias;
TestLstmLayerVisitor visitor(descriptor, params);
@@ -959,11 +953,6 @@
ConstTensor recurrentToInputWeights(TensorInfo(
4, recurrentToInputWeightsDimensions.data(), DataType::Float32), recurrentToInputWeightsData);
- std::vector<float> cellToInputWeightsData = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0};
- std::vector<unsigned int> cellToInputWeightsDimensions = {1, 1, 3, 3};
- ConstTensor cellToInputWeights(
- TensorInfo(4, cellToInputWeightsDimensions.data(), DataType::Float32), cellToInputWeightsData);
-
std::vector<float> inputGateBiasData = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0};
std::vector<unsigned int> inputGateBiasDimensions = {1, 1, 3, 3};
ConstTensor inputGateBias(
@@ -982,7 +971,6 @@
params.m_InputToInputWeights = &inputToInputWeights;
params.m_RecurrentToInputWeights = &recurrentToInputWeights;
- params.m_CellToInputWeights = &cellToInputWeights;
params.m_InputGateBias = &inputGateBias;
TestLstmLayerVisitor visitor(descriptor, params, layerName);
@@ -1080,6 +1068,120 @@
layer->Accept(visitor);
}
+BOOST_AUTO_TEST_CASE(CheckLstmLayerPeepholeCifgDisabled)
+{
+ LstmDescriptor descriptor;
+ descriptor.m_ActivationFunc = 3;
+ descriptor.m_ClippingThresProj = 0.5f;
+ descriptor.m_ClippingThresCell = 0.3f;
+ descriptor.m_CifgEnabled = false;
+ descriptor.m_PeepholeEnabled = true;
+
+ std::vector<float> inputToForgetWeightsData = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0};
+ std::vector<unsigned int> inputToForgetWeightsDimensions = {1, 1, 3, 3};
+ ConstTensor inputToForgetWeights(
+ TensorInfo(4, inputToForgetWeightsDimensions.data(), DataType::Float32), inputToForgetWeightsData);
+
+ std::vector<float> inputToCellWeightsData = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0};
+ std::vector<unsigned int> inputToCellWeightsDimensions = {1, 1, 3, 3};
+ ConstTensor inputToCellWeights(
+ TensorInfo(4, inputToCellWeightsDimensions.data(), DataType::Float32), inputToCellWeightsData);
+
+ std::vector<float> inputToOutputWeightsData = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0};
+ std::vector<unsigned int> inputToOutputWeightsDimensions = {1, 1, 3, 3};
+ ConstTensor inputToOutputWeights(
+ TensorInfo(4, inputToOutputWeightsDimensions.data(), DataType::Float32), inputToOutputWeightsData);
+
+ std::vector<float> recurrentToForgetWeightsData = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0};
+ std::vector<unsigned int> recurrentToForgetWeightsDimensions = {1, 1, 3, 3};
+ ConstTensor recurrentToForgetWeights(TensorInfo(
+ 4, recurrentToForgetWeightsDimensions.data(), DataType::Float32), recurrentToForgetWeightsData);
+
+ std::vector<float> recurrentToCellWeightsData = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0};
+ std::vector<unsigned int> recurrentToCellWeightsDimensions = {1, 1, 3, 3};
+ ConstTensor recurrentToCellWeights(TensorInfo(
+ 4, recurrentToCellWeightsDimensions.data(), DataType::Float32), recurrentToCellWeightsData);
+
+ std::vector<float> recurrentToOutputWeightsData = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0};
+ std::vector<unsigned int> recurrentToOutputWeightsDimensions = {1, 1, 3, 3};
+ ConstTensor recurrentToOutputWeights(TensorInfo(
+ 4, recurrentToOutputWeightsDimensions.data(), DataType::Float32), recurrentToOutputWeightsData);
+
+ std::vector<float> forgetGateBiasData = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0};
+ std::vector<unsigned int> forgetGateBiasDimensions = {1, 1, 3, 3};
+ ConstTensor forgetGateBias(TensorInfo(
+ 4, forgetGateBiasDimensions.data(), DataType::Float32), forgetGateBiasData);
+
+ std::vector<float> cellBiasData = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0};
+ std::vector<unsigned int> cellBiasDimensions = {1, 1, 3, 3};
+ ConstTensor cellBias(TensorInfo(
+ 4, cellBiasDimensions.data(), DataType::Float32), cellBiasData);
+
+ std::vector<float> outputGateBiasData = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0};
+ std::vector<unsigned int> outputGateBiasDimensions = {1, 1, 3, 3};
+ ConstTensor outputGateBias(TensorInfo(
+ 4, outputGateBiasDimensions.data(), DataType::Float32), outputGateBiasData);
+
+ std::vector<float> cellToInputWeightsData = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0};
+ std::vector<unsigned int> cellToInputWeightsDimensions = {1, 1, 3, 3};
+ ConstTensor cellToInputWeights(
+ TensorInfo(4, cellToInputWeightsDimensions.data(), DataType::Float32), cellToInputWeightsData);
+
+ std::vector<float> cellToForgetWeightsData = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0};
+ std::vector<unsigned int> cellToForgetWeightsDimensions = {1, 1, 3, 3};
+ ConstTensor cellToForgetWeights(
+ TensorInfo(4, cellToForgetWeightsDimensions.data(), DataType::Float32), cellToForgetWeightsData);
+
+ std::vector<float> cellToOutputWeightsData = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0};
+ std::vector<unsigned int> cellToOutputWeightsDimensions = {1, 1, 3, 3};
+ ConstTensor cellToOutputWeights(
+ TensorInfo(4, cellToOutputWeightsDimensions.data(), DataType::Float32), cellToOutputWeightsData);
+
+ std::vector<float> inputToInputWeightsData = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0};
+ std::vector<unsigned int> inputToInputWeightsDimensions = {1, 1, 3, 3};
+ ConstTensor inputToInputWeights(
+ TensorInfo(4, inputToInputWeightsDimensions.data(), DataType::Float32), inputToInputWeightsData);
+
+ std::vector<float> recurrentToInputWeightsData = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0};
+ std::vector<unsigned int> recurrentToInputWeightsDimensions = {1, 1, 3, 3};
+ ConstTensor recurrentToInputWeights(TensorInfo(
+ 4, recurrentToInputWeightsDimensions.data(), DataType::Float32), recurrentToInputWeightsData);
+
+ std::vector<float> inputGateBiasData = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0};
+ std::vector<unsigned int> inputGateBiasDimensions = {1, 1, 3, 3};
+ ConstTensor inputGateBias(
+ TensorInfo(4, inputGateBiasDimensions.data(), DataType::Float32), inputGateBiasData);
+
+ LstmInputParams params;
+ // Basic params
+ params.m_InputToForgetWeights = &inputToForgetWeights;
+ params.m_InputToCellWeights = &inputToCellWeights;
+ params.m_InputToOutputWeights = &inputToOutputWeights;
+ params.m_RecurrentToForgetWeights = &recurrentToForgetWeights;
+ params.m_RecurrentToCellWeights = &recurrentToCellWeights;
+ params.m_RecurrentToOutputWeights = &recurrentToOutputWeights;
+ params.m_ForgetGateBias = &forgetGateBias;
+ params.m_CellBias = &cellBias;
+ params.m_OutputGateBias = &outputGateBias;
+
+ // Peephole params
+ params.m_CellToInputWeights = &cellToInputWeights;
+ params.m_CellToForgetWeights = &cellToForgetWeights;
+ params.m_CellToOutputWeights = &cellToOutputWeights;
+
+ // Cifg params
+ params.m_InputToInputWeights = &inputToInputWeights;
+ params.m_RecurrentToInputWeights = &recurrentToInputWeights;
+ params.m_InputGateBias = &inputGateBias;
+
+ TestLstmLayerVisitor visitor(descriptor, params);
+
+ Network net;
+
+ IConnectableLayer* const layer = net.AddLstmLayer(descriptor, params);
+ layer->Accept(visitor);
+}
+
BOOST_AUTO_TEST_CASE(CheckNamedLstmLayerPeephole)
{
const char* layerName = "LstmLayer";
diff --git a/src/armnn/test/OptimizerTests.cpp b/src/armnn/test/OptimizerTests.cpp
index 56032ad..a7b23db 100644
--- a/src/armnn/test/OptimizerTests.cpp
+++ b/src/armnn/test/OptimizerTests.cpp
@@ -78,13 +78,10 @@
(TensorInfo({ numUnits, inputSize }, DataType::Float32));
layer->m_CifgParameters.m_RecurrentToInputWeights = std::make_unique<ScopedCpuTensorHandle>
(TensorInfo({ numUnits, outputSize }, DataType::Float32));
- layer->m_CifgParameters.m_CellToInputWeights = std::make_unique<ScopedCpuTensorHandle>
- (TensorInfo({ numUnits }, DataType::Float32));
layer->m_CifgParameters.m_InputGateBias = std::make_unique<ScopedCpuTensorHandle>
(TensorInfo({ numUnits }, DataType::Float32));
layer->m_CifgParameters.m_InputToInputWeights->Allocate();
layer->m_CifgParameters.m_RecurrentToInputWeights->Allocate();
- layer->m_CifgParameters.m_CellToInputWeights->Allocate();
layer->m_CifgParameters.m_InputGateBias->Allocate();
}
@@ -100,6 +97,12 @@
if (layerDesc.m_PeepholeEnabled)
{
+ if (!layerDesc.m_CifgEnabled)
+ {
+ layer->m_PeepholeParameters.m_CellToInputWeights = std::make_unique<ScopedCpuTensorHandle>
+ (TensorInfo({ numUnits }, DataType::Float32));
+ layer->m_PeepholeParameters.m_CellToInputWeights->Allocate();
+ }
layer->m_PeepholeParameters.m_CellToForgetWeights = std::make_unique<ScopedCpuTensorHandle>
(TensorInfo({ numUnits }, DataType::Float32));
layer->m_PeepholeParameters.m_CellToOutputWeights = std::make_unique<ScopedCpuTensorHandle>
diff --git a/src/backends/backendsCommon/WorkloadFactory.cpp b/src/backends/backendsCommon/WorkloadFactory.cpp
index 40ab798..5628c36 100644
--- a/src/backends/backendsCommon/WorkloadFactory.cpp
+++ b/src/backends/backendsCommon/WorkloadFactory.cpp
@@ -529,12 +529,6 @@
optRecurrentToInputWeights =
OverrideDataType(cLayer->m_CifgParameters.m_RecurrentToInputWeights->GetTensorInfo(), dataType);
paramsInfo.m_RecurrentToInputWeights = &optRecurrentToInputWeights;
- if (cLayer->m_CifgParameters.m_CellToInputWeights != nullptr)
- {
- optCellToInputWeights =
- OverrideDataType(cLayer->m_CifgParameters.m_CellToInputWeights->GetTensorInfo(), dataType);
- paramsInfo.m_CellToInputWeights = &optCellToInputWeights;
- }
optInputGateBias =
OverrideDataType(cLayer->m_CifgParameters.m_InputGateBias->GetTensorInfo(), dataType);
paramsInfo.m_InputGateBias = &optInputGateBias;
@@ -555,6 +549,13 @@
if(descriptor.m_PeepholeEnabled)
{
+ if(!descriptor.m_CifgEnabled)
+ {
+ optCellToInputWeights =
+ OverrideDataType(cLayer->m_PeepholeParameters.m_CellToInputWeights->GetTensorInfo(),
+ dataType);
+ paramsInfo.m_CellToInputWeights = &optCellToInputWeights;
+ }
optCellToForgetWeights =
OverrideDataType(cLayer->m_PeepholeParameters.m_CellToForgetWeights->GetTensorInfo(), dataType);
paramsInfo.m_CellToForgetWeights = &optCellToForgetWeights;
diff --git a/src/backends/backendsCommon/test/IsLayerSupportedTestImpl.hpp b/src/backends/backendsCommon/test/IsLayerSupportedTestImpl.hpp
index 7534c8a..dccfd1e 100644
--- a/src/backends/backendsCommon/test/IsLayerSupportedTestImpl.hpp
+++ b/src/backends/backendsCommon/test/IsLayerSupportedTestImpl.hpp
@@ -288,8 +288,6 @@
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::Float32));
m_Layer->m_CifgParameters.m_RecurrentToInputWeights = std::make_unique<armnn::ScopedCpuTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::Float32));
- m_Layer->m_CifgParameters.m_CellToInputWeights = std::make_unique<armnn::ScopedCpuTensorHandle>(
- armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::Float32));
m_Layer->m_CifgParameters.m_InputGateBias = std::make_unique<armnn::ScopedCpuTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::Float32));
}