Remove use of PostAllocationConfigure from ExecuteAsync calls
* Resolves: IVGCVSW-6952
Signed-off-by: Finn Williams <finn.williams@arm.com>
Change-Id: Ic85bd5267cf94e0ee8461ff4e62b9db3cb80877a
diff --git a/include/armnn/backends/IWorkload.hpp b/include/armnn/backends/IWorkload.hpp
index 20be016..c7bc5da 100644
--- a/include/armnn/backends/IWorkload.hpp
+++ b/include/armnn/backends/IWorkload.hpp
@@ -23,6 +23,8 @@
public:
virtual ~IWorkload() {}
+ // Note: do not call for async networks via ExecuteAsync or otherwise,
+ // as async networks memory is allocated outside the workload.
virtual void PostAllocationConfigure() = 0;
virtual void Execute() const = 0;
diff --git a/src/backends/reference/workloads/RefConvolution2dWorkload.cpp b/src/backends/reference/workloads/RefConvolution2dWorkload.cpp
index fe97cb1..3ddbdce 100644
--- a/src/backends/reference/workloads/RefConvolution2dWorkload.cpp
+++ b/src/backends/reference/workloads/RefConvolution2dWorkload.cpp
@@ -15,6 +15,9 @@
RefConvolution2dWorkload::RefConvolution2dWorkload(const Convolution2dQueueDescriptor& descriptor,
const WorkloadInfo& info)
: RefBaseWorkload<Convolution2dQueueDescriptor>(descriptor, info)
+ , m_InputShape(info.m_InputTensorInfos[0].GetShape())
+ , m_FilterShape(info.m_InputTensorInfos[1].GetShape())
+ , m_OutputShape(info.m_OutputTensorInfos[0].GetShape())
{
WorkloadInfo detailsInfo;
detailsInfo.m_InputTensorInfos = info.m_InputTensorInfos;
@@ -27,33 +30,6 @@
this->GetGuid());
}
-void RefConvolution2dWorkload::PostAllocationConfigure()
-{
- PostAllocationConfigure(m_Data.m_Inputs, m_Data.m_Outputs);
-}
-
-void RefConvolution2dWorkload::PostAllocationConfigure(std::vector<ITensorHandle*> inputs,
- std::vector<ITensorHandle*> outputs)
-{
- const TensorInfo& inputInfo = GetTensorInfo(inputs[0]);
- ARMNN_ASSERT(inputInfo.GetNumDimensions() > 1);
- m_InputShape = inputInfo.GetShape();
-
- const TensorInfo& rFilterInfo = GetTensorInfo(inputs[1]);
- ARMNN_ASSERT(inputInfo.GetNumDimensions() > 1);
- m_FilterShape = rFilterInfo.GetShape();
- m_FilterDecoder = MakeDecoder<float>(rFilterInfo);
-
- if (m_Data.m_Parameters.m_BiasEnabled)
- {
- const TensorInfo& biasInfo = GetTensorInfo(inputs[2]);
- m_BiasDecoder = MakeDecoder<float>(biasInfo);
- }
-
- const TensorInfo& outputInfo = GetTensorInfo(outputs[0]);
- m_OutputShape = outputInfo.GetShape();
-}
-
void RefConvolution2dWorkload::Execute() const
{
Execute(m_Data.m_Inputs, m_Data.m_Outputs);
@@ -61,8 +37,6 @@
void RefConvolution2dWorkload::ExecuteAsync(WorkingMemDescriptor& workingMemDescriptor)
{
- PostAllocationConfigure(workingMemDescriptor.m_Inputs, workingMemDescriptor.m_Outputs);
-
Execute(workingMemDescriptor.m_Inputs, workingMemDescriptor.m_Outputs);
}
@@ -73,14 +47,16 @@
std::unique_ptr<Decoder<float>> inputDecoder = MakeDecoder<float>(GetTensorInfo(inputs[0]), inputs[0]->Map());
std::unique_ptr<Encoder<float>> outputEncoder = MakeEncoder<float>(GetTensorInfo(outputs[0]), outputs[0]->Map());
- m_FilterDecoder->Reset(inputs[1]->Map());
+ std::unique_ptr<Decoder<float>> weightsDecoder = MakeDecoder<float>(GetTensorInfo(inputs[1]), inputs[1]->Map());
+ std::unique_ptr<Decoder<float>> biasDecoder;
+
if (m_Data.m_Parameters.m_BiasEnabled)
{
- m_BiasDecoder->Reset(inputs[2]->Map());
+ biasDecoder = MakeDecoder<float>(GetTensorInfo(inputs[2]), inputs[2]->Map());
}
Convolve(m_InputShape, *inputDecoder, m_OutputShape, *outputEncoder, m_FilterShape,
- *m_FilterDecoder, m_Data.m_Parameters.m_BiasEnabled, m_BiasDecoder.get(),
+ *weightsDecoder, m_Data.m_Parameters.m_BiasEnabled, biasDecoder.get(),
m_Data.m_Parameters.m_DataLayout, m_Data.m_Parameters.m_PadTop, m_Data.m_Parameters.m_PadLeft,
m_Data.m_Parameters.m_StrideX, m_Data.m_Parameters.m_StrideY,
m_Data.m_Parameters.m_DilationX, m_Data.m_Parameters.m_DilationY);
diff --git a/src/backends/reference/workloads/RefConvolution2dWorkload.hpp b/src/backends/reference/workloads/RefConvolution2dWorkload.hpp
index 1cb30b6..f0d7037 100644
--- a/src/backends/reference/workloads/RefConvolution2dWorkload.hpp
+++ b/src/backends/reference/workloads/RefConvolution2dWorkload.hpp
@@ -19,21 +19,15 @@
explicit RefConvolution2dWorkload(const Convolution2dQueueDescriptor& descriptor,
const WorkloadInfo& info);
- void PostAllocationConfigure() override;
-
void Execute() const override;
void ExecuteAsync(WorkingMemDescriptor& workingMemDescriptor) override;
private:
- void PostAllocationConfigure(std::vector<ITensorHandle*> inputs, std::vector<ITensorHandle*> outputs);
void Execute(std::vector<ITensorHandle*> inputs, std::vector<ITensorHandle*> outputs) const;
- std::unique_ptr<Decoder<float>> m_FilterDecoder;
- std::unique_ptr<Decoder<float>> m_BiasDecoder;
-
- TensorShape m_InputShape;
- TensorShape m_OutputShape;
- TensorShape m_FilterShape;
+ const TensorShape m_InputShape;
+ const TensorShape m_FilterShape;
+ const TensorShape m_OutputShape;
};
} //namespace armnn
\ No newline at end of file
diff --git a/src/backends/reference/workloads/RefConvolution3dWorkload.cpp b/src/backends/reference/workloads/RefConvolution3dWorkload.cpp
index 5f54280..f6a0ee2 100644
--- a/src/backends/reference/workloads/RefConvolution3dWorkload.cpp
+++ b/src/backends/reference/workloads/RefConvolution3dWorkload.cpp
@@ -32,26 +32,6 @@
this->GetGuid());
}
-void RefConvolution3dWorkload::PostAllocationConfigure()
-{
- PostAllocationConfigure(m_Data.m_Inputs, m_Data.m_Outputs);
-}
-
-void RefConvolution3dWorkload::PostAllocationConfigure(std::vector<ITensorHandle*> inputs,
- std::vector<ITensorHandle*> outputs)
-{
- IgnoreUnused(outputs);
- const TensorInfo& rFilterInfo = GetTensorInfo(inputs[1]);
- m_FilterShape = rFilterInfo.GetShape();
- m_FilterDecoder = MakeDecoder<float>(rFilterInfo);
-
- if (m_Data.m_Parameters.m_BiasEnabled)
- {
- const TensorInfo& biasInfo = GetTensorInfo(inputs[2]);
- m_BiasDecoder = MakeDecoder<float>(biasInfo);
- }
-}
-
void RefConvolution3dWorkload::Execute() const
{
Execute(m_Data.m_Inputs, m_Data.m_Outputs);
@@ -59,8 +39,6 @@
void RefConvolution3dWorkload::ExecuteAsync(WorkingMemDescriptor& workingMemDescriptor)
{
- PostAllocationConfigure(workingMemDescriptor.m_Inputs, workingMemDescriptor.m_Outputs);
-
Execute(workingMemDescriptor.m_Inputs, workingMemDescriptor.m_Outputs);
}
@@ -74,14 +52,17 @@
const TensorShape& inputShape = GetTensorInfo(inputs[0]).GetShape();
const TensorShape& outputShape = GetTensorInfo(outputs[0]).GetShape();
- m_FilterDecoder->Reset(inputs[1]->Map());
+ const auto& filterInfo = GetTensorInfo(inputs[1]);
+ std::unique_ptr<Decoder<float>> filterDecoder = MakeDecoder<float>(GetTensorInfo(inputs[1]), inputs[1]->Map());
+ std::unique_ptr<Decoder<float>> biasDecoder;
+
if (m_Data.m_Parameters.m_BiasEnabled)
{
- m_BiasDecoder->Reset(inputs[2]->Map());
+ biasDecoder = MakeDecoder<float>(GetTensorInfo(inputs[2]), inputs[2]->Map());
}
- Convolve3d(inputShape, *inputDecoder, outputShape, *outputEncoder, m_FilterShape,
- *m_FilterDecoder, m_Data.m_Parameters.m_BiasEnabled, m_BiasDecoder.get(),
+ Convolve3d(inputShape, *inputDecoder, outputShape, *outputEncoder, filterInfo.GetShape(),
+ *filterDecoder, m_Data.m_Parameters.m_BiasEnabled, biasDecoder.get(),
m_Data.m_Parameters.m_DataLayout,
m_Data.m_Parameters.m_PadTop, m_Data.m_Parameters.m_PadLeft, m_Data.m_Parameters.m_PadFront,
m_Data.m_Parameters.m_StrideX, m_Data.m_Parameters.m_StrideY, m_Data.m_Parameters.m_StrideZ,
diff --git a/src/backends/reference/workloads/RefConvolution3dWorkload.hpp b/src/backends/reference/workloads/RefConvolution3dWorkload.hpp
index 6c74675..b53f3a5 100644
--- a/src/backends/reference/workloads/RefConvolution3dWorkload.hpp
+++ b/src/backends/reference/workloads/RefConvolution3dWorkload.hpp
@@ -19,19 +19,11 @@
explicit RefConvolution3dWorkload(const Convolution3dQueueDescriptor& descriptor,
const WorkloadInfo& info);
- void PostAllocationConfigure() override;
-
void Execute() const override;
void ExecuteAsync(WorkingMemDescriptor& workingMemDescriptor) override;
private:
- void PostAllocationConfigure(std::vector<ITensorHandle*> inputs, std::vector<ITensorHandle*> outputs);
void Execute(std::vector<ITensorHandle*> inputs, std::vector<ITensorHandle*> outputs) const;
-
- std::unique_ptr<Decoder<float>> m_FilterDecoder;
- std::unique_ptr<Decoder<float>> m_BiasDecoder;
-
- TensorShape m_FilterShape;
};
} //namespace armnn
diff --git a/src/backends/reference/workloads/RefFullyConnectedWorkload.cpp b/src/backends/reference/workloads/RefFullyConnectedWorkload.cpp
index c6ea147..087fc9d 100644
--- a/src/backends/reference/workloads/RefFullyConnectedWorkload.cpp
+++ b/src/backends/reference/workloads/RefFullyConnectedWorkload.cpp
@@ -12,45 +12,28 @@
namespace armnn
{
+
+unsigned int GetNumActivations(const TensorInfo& inputInfo)
+{
+ unsigned int numActivations = 1; // Total number of activations in the input.
+ for (unsigned int i = 1; i < inputInfo.GetNumDimensions(); i++)
+ {
+ numActivations *= inputInfo.GetShape()[i];
+ }
+ return numActivations;
+}
+
+
RefFullyConnectedWorkload::RefFullyConnectedWorkload(
const FullyConnectedQueueDescriptor& descriptor, const WorkloadInfo& info)
: RefBaseWorkload<FullyConnectedQueueDescriptor>(descriptor, info)
+ , m_InputShape(info.m_InputTensorInfos[0].GetShape())
+ , m_WeightShape(info.m_InputTensorInfos[1].GetShape())
+ , m_OutputShape(info.m_OutputTensorInfos[0].GetShape())
+ , m_NumActivations(GetNumActivations(info.m_InputTensorInfos[0]))
{
}
-void RefFullyConnectedWorkload::PostAllocationConfigure()
-{
- PostAllocationConfigure(m_Data.m_Inputs, m_Data.m_Outputs);
-}
-
-void RefFullyConnectedWorkload::PostAllocationConfigure(std::vector<ITensorHandle*> inputs,
- std::vector<ITensorHandle*> outputs)
-{
- const TensorInfo& inputInfo = GetTensorInfo(inputs[0]);
- ARMNN_ASSERT(inputInfo.GetNumDimensions() > 1);
- m_InputShape = inputInfo.GetShape();
-
- const TensorInfo& rWeightInfo = GetTensorInfo(inputs[1]);
- ARMNN_ASSERT(inputInfo.GetNumDimensions() > 1);
- m_WeightShape = rWeightInfo.GetShape();
- m_WeightDecoder = MakeDecoder<float>(rWeightInfo);
-
- if (m_Data.m_Parameters.m_BiasEnabled)
- {
- const TensorInfo& biasInfo = GetTensorInfo(inputs[2]);
- m_BiasDecoder = MakeDecoder<float>(biasInfo);
- }
-
- const TensorInfo& outputInfo = GetTensorInfo(outputs[0]);
- m_OutputShape = outputInfo.GetShape();
-
- m_NumActivations = 1; // Total number of activations in the input.
- for (unsigned int i = 1; i < inputInfo.GetNumDimensions(); i++)
- {
- m_NumActivations *= inputInfo.GetShape()[i];
- }
-}
-
void RefFullyConnectedWorkload::Execute() const
{
Execute(m_Data.m_Inputs, m_Data.m_Outputs);
@@ -58,8 +41,6 @@
void RefFullyConnectedWorkload::ExecuteAsync(WorkingMemDescriptor &workingMemDescriptor)
{
- PostAllocationConfigure(workingMemDescriptor.m_Inputs, workingMemDescriptor.m_Outputs);
-
Execute(workingMemDescriptor.m_Inputs, workingMemDescriptor.m_Outputs);
}
@@ -70,10 +51,12 @@
std::unique_ptr<Decoder<float>> inputDecoder = MakeDecoder<float>(GetTensorInfo(inputs[0]), inputs[0]->Map());
std::unique_ptr<Encoder<float>> OutputEncoder = MakeEncoder<float>(GetTensorInfo(outputs[0]), outputs[0]->Map());
- m_WeightDecoder->Reset(inputs[1]->Map());
+ std::unique_ptr<Decoder<float>> weightsDecoder = MakeDecoder<float>(GetTensorInfo(inputs[1]), inputs[1]->Map());
+ std::unique_ptr<Decoder<float>> biasDecoder;
+
if (m_Data.m_Parameters.m_BiasEnabled)
{
- m_BiasDecoder->Reset(inputs[2]->Map());
+ biasDecoder = MakeDecoder<float>(GetTensorInfo(inputs[2]), inputs[2]->Map());
}
FullyConnected(m_InputShape,
@@ -81,8 +64,8 @@
m_OutputShape,
*OutputEncoder,
m_WeightShape,
- *m_WeightDecoder,
- m_BiasDecoder.get(),
+ *weightsDecoder,
+ biasDecoder.get(),
m_Data.m_Parameters.m_BiasEnabled,
m_NumActivations,
m_Data.m_Parameters.m_TransposeWeightMatrix);
diff --git a/src/backends/reference/workloads/RefFullyConnectedWorkload.hpp b/src/backends/reference/workloads/RefFullyConnectedWorkload.hpp
index 432a887..3bdfb86 100644
--- a/src/backends/reference/workloads/RefFullyConnectedWorkload.hpp
+++ b/src/backends/reference/workloads/RefFullyConnectedWorkload.hpp
@@ -21,24 +21,16 @@
explicit RefFullyConnectedWorkload(const FullyConnectedQueueDescriptor& descriptor,
const WorkloadInfo& info);
- void PostAllocationConfigure() override;
-
void Execute() const override;
void ExecuteAsync(WorkingMemDescriptor& workingMemDescriptor) override;
private:
- void PostAllocationConfigure(std::vector<ITensorHandle*> inputs, std::vector<ITensorHandle*> outputs);
void Execute(std::vector<ITensorHandle*> inputs, std::vector<ITensorHandle*> outputs) const;
- std::unique_ptr<ScopedTensorHandle> m_Weight;
- std::unique_ptr<ScopedTensorHandle> m_Bias;
- std::unique_ptr<Decoder<float>> m_WeightDecoder;
- std::unique_ptr<Decoder<float>> m_BiasDecoder;
-
- TensorShape m_InputShape;
- TensorShape m_OutputShape;
- TensorShape m_WeightShape;
- unsigned int m_NumActivations;
+ const TensorShape m_InputShape;
+ const TensorShape m_WeightShape;
+ const TensorShape m_OutputShape;
+ const unsigned int m_NumActivations;
};
} //namespace armnn