IVGCVSW-6127 ConstTensorsAsInput: DepthwiseConvolution2d
!armnn:7417
Signed-off-by: Cathal Corbett <cathal.corbett@arm.com>
Change-Id: Ic37d6b8677e040c60a90358dd0a4a8eb33fb6ea0
diff --git a/ConversionUtils.cpp b/ConversionUtils.cpp
index 7eb7343..91c1ae4 100644
--- a/ConversionUtils.cpp
+++ b/ConversionUtils.cpp
@@ -59,6 +59,19 @@
return m_TensorInfo;
}
+void LayerInputHandle::SanitizeQuantizationScale(LayerInputHandle& weight,
+ LayerInputHandle& input)
+{
+ armnn::TensorInfo weightInfo = weight.GetTensorInfo();
+ armnn::TensorInfo inputInfo = input.GetTensorInfo();
+ armnn::TensorInfo biasInfo = GetTensorInfo();
+
+ SanitizeBiasQuantizationScale(biasInfo, weightInfo, inputInfo);
+
+ m_TensorInfo = biasInfo;
+ m_OutputSlot->SetTensorInfo(biasInfo);
+}
+
ConstTensorPin::ConstTensorPin(bool optional)
: m_Optional(optional)
{}
diff --git a/ConversionUtils.hpp b/ConversionUtils.hpp
index d06fad6..c8e7b0d 100644
--- a/ConversionUtils.hpp
+++ b/ConversionUtils.hpp
@@ -71,6 +71,9 @@
const armnn::TensorInfo& GetTensorInfo() const;
+ void SanitizeQuantizationScale(LayerInputHandle& weight,
+ LayerInputHandle& input);
+
private:
armnn::IOutputSlot* m_OutputSlot;
bool m_Valid;
@@ -2598,10 +2601,9 @@
// ArmNN does not currently support non-fixed weights or bias
// Find the shape of the weights tensor. In AndroidNN this will be [ 1, H, W, I * M ]
const HalOperand* weightsOperand = GetInputOperand<HalPolicy>(operation, 1, model);
-
- if (weightsOperand == nullptr)
+ if (!weightsOperand)
{
- return Fail("%s: Operand is invalid", __func__);
+ return Fail("%s: Could not read weights", __func__);
}
// Basic sanity check on the weights shape.
// ANEURALNETWORKS_DEPTHWISE_CONV_2D specifies a 4-D tensor, of shape
@@ -2614,24 +2616,27 @@
armnn::DepthwiseConvolution2dDescriptor desc;
desc.m_DataLayout = armnn::DataLayout::NHWC;
- // The layout for weights in depthwise is [ 1, H, W, O] and it's the same in ArmNN. No need to permute anything.
- const ConstTensorPin weightsPin =
- ConvertOperationInputToConstTensorPin<HalPolicy>(operation,
- 1,
- model,
- data);
-
- // Bias is a 1D tensor
- const ConstTensorPin biasPin = ConvertOperationInputToConstTensorPin<HalPolicy>(operation, 2, model, data);
-
- if (!weightsPin.IsValid() || !biasPin.IsValid())
+ LayerInputHandle weightsInput = ConvertToLayerInputHandle<HalPolicy>(operation, 1, model, data);
+ if (!weightsInput.IsValid())
{
return Fail("%s: Operation has invalid inputs", __func__);
}
- armnn::ConstTensor weights = weightsPin.GetConstTensor();
- armnn::ConstTensor bias = biasPin.GetConstTensor();
- SanitizeBiasQuantizationScale(bias.GetInfo(), weights.GetInfo(), inputInfo);
+ const HalOperand* biasOperand = GetInputOperand<HalPolicy>(operation, 2, model);
+ if (!biasOperand)
+ {
+ return Fail("%s: Could not read bias", __func__);
+ }
+
+ LayerInputHandle biasInput = ConvertToLayerInputHandle<HalPolicy>(operation, 2, model, data); // 1D
+ if (!biasInput.IsValid())
+ {
+ return Fail("%s: Operation has invalid inputs", __func__);
+ }
+
+ biasInput.SanitizeQuantizationScale(weightsInput, input);
+ armnn::TensorInfo weightsInfo = weightsInput.GetTensorInfo();
+ armnn::TensorInfo biasInfo = biasInput.GetTensorInfo();
ActivationFn activation;
@@ -2659,8 +2664,8 @@
return Fail("%s: Operation has invalid inputs", __func__);
}
- const uint32_t kernelX = weights.GetShape()[2];
- const uint32_t kernelY = weights.GetShape()[1];
+ const uint32_t kernelX = weightsInfo.GetShape()[2];
+ const uint32_t kernelY = weightsInfo.GetShape()[1];
const uint32_t inputX = inputInfo.GetShape()[2];
const uint32_t inputY = inputInfo.GetShape()[1];
@@ -2673,7 +2678,7 @@
}
desc.m_BiasEnabled = true;
- armnn::Optional<armnn::TensorInfo> biases(bias.GetInfo());
+ armnn::Optional<armnn::TensorInfo> biases(biasInfo);
bool isSupported = false;
auto validateFunc = [&](const armnn::TensorInfo& outputInfo, bool& isSupported)
@@ -2685,7 +2690,7 @@
inputInfo,
outputInfo,
desc,
- weights.GetInfo(),
+ weightsInfo,
biases);
};
@@ -2704,8 +2709,7 @@
return false;
}
- armnn::IConnectableLayer* startLayer =
- data.m_Network->AddDepthwiseConvolution2dLayer(desc, weights, armnn::Optional<armnn::ConstTensor>(bias));
+ armnn::IConnectableLayer* startLayer = data.m_Network->AddDepthwiseConvolution2dLayer(desc);
if (!startLayer)
{
return Fail("%s: AddDepthwiseConvolution2dLayer failed", __func__);
@@ -2713,6 +2717,10 @@
input.Connect(startLayer->GetInputSlot(0));
+ // Connect weights and bias inputs
+ weightsInput.Connect(startLayer->GetInputSlot(1));
+ biasInput.Connect(startLayer->GetInputSlot(2));
+
return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, 0, *startLayer, model,
data, nullptr, validateFunc, activation);
}
diff --git a/ConversionUtils_1_2.hpp b/ConversionUtils_1_2.hpp
index 0ff50cf..b1f2d05 100644
--- a/ConversionUtils_1_2.hpp
+++ b/ConversionUtils_1_2.hpp
@@ -523,12 +523,11 @@
// ArmNN does not currently support non-fixed weights or bias
// Find the shape of the weights tensor. In AndroidNN this will be [ 1, H, W, I * M ]
const HalOperand* weightsOperand = GetInputOperand<HalPolicy>(operation, 1, model);
-
- if (weightsOperand == nullptr)
+ if (!weightsOperand)
{
- return Fail("%s: Operand is invalid", __func__);
+ return Fail("%s: Could not read weights", __func__);
}
- if ( weightsOperand->dimensions[0] != 1)
+ if (weightsOperand->dimensions[0] != 1)
{
return Fail("%s: Invalid weights; for depthwise convolution, dimension 0 must be 1 but it is %i",
__func__, weightsOperand->dimensions[0] );
@@ -550,30 +549,27 @@
unsigned int widthIndex = dataLayoutIndexed.GetWidthIndex();
unsigned int heightIndex = dataLayoutIndexed.GetHeightIndex();
- // The layout for weights in depthwise is [ 1, H, W, O] and it's the same in ArmNN. No need to permute anything.
- const ConstTensorPin weightsPin =
- ConvertOperationInputToConstTensorPin<HalPolicy>(operation,
- 1,
- model,
- data);
-
- // Bias is a 1D tensor
- const ConstTensorPin biasPin =
- ConvertOperationInputToConstTensorPin<HalPolicy>(operation, 2, model, data);
-
- if (!weightsPin.IsValid())
+ LayerInputHandle weightsInput = ConvertToLayerInputHandle<HalPolicy>(operation, 1, model, data);
+ if (!weightsInput.IsValid())
{
- return Fail("%s: Operation has invalid weights", __func__);
+ return Fail("%s: Operation has invalid inputs", __func__);
}
- if (!biasPin.IsValid())
+ const HalOperand* biasOperand = GetInputOperand<HalPolicy>(operation, 2, model);
+ if (!biasOperand)
{
- return Fail("%s: Operation has invalid biases", __func__);
+ return Fail("%s: Could not read bias", __func__);
}
- ConstTensor weights = weightsPin.GetConstTensor();
- ConstTensor bias = biasPin.GetConstTensor();
- SanitizeBiasQuantizationScale(bias.GetInfo(), weights.GetInfo(), inputInfo);
+ LayerInputHandle biasInput = ConvertToLayerInputHandle<HalPolicy>(operation, 2, model, data); // 1D
+ if (!biasInput.IsValid())
+ {
+ return Fail("%s: Operation has invalid inputs", __func__);
+ }
+
+ biasInput.SanitizeQuantizationScale(weightsInput, input);
+ armnn::TensorInfo weightsInfo = weightsInput.GetTensorInfo();
+ armnn::TensorInfo biasInfo = biasInput.GetTensorInfo();
ActivationFn activation;
@@ -589,8 +585,8 @@
return Fail("%s: Operation has invalid inputs (implicit padding)", __func__);
}
- const uint32_t kernelX = weights.GetShape()[2];
- const uint32_t kernelY = weights.GetShape()[1];
+ const uint32_t kernelX = weightsInfo.GetShape()[2];
+ const uint32_t kernelY = weightsInfo.GetShape()[1];
const uint32_t inputX = inputInfo.GetShape()[widthIndex];
const uint32_t inputY = inputInfo.GetShape()[heightIndex];
@@ -618,7 +614,7 @@
}
desc.m_BiasEnabled = true;
- Optional<TensorInfo> biases(bias.GetInfo());
+ Optional<TensorInfo> biases(biasInfo);
bool isSupported = false;
auto validateFunc = [&](const armnn::TensorInfo& outputInfo, bool& isSupported)
@@ -630,7 +626,7 @@
inputInfo,
outputInfo,
desc,
- weights.GetInfo(),
+ weightsInfo,
biases);
};
@@ -648,8 +644,7 @@
return false;
}
- IConnectableLayer* startLayer =
- data.m_Network->AddDepthwiseConvolution2dLayer(desc, weights, Optional<ConstTensor>(bias));
+ armnn::IConnectableLayer* startLayer = data.m_Network->AddDepthwiseConvolution2dLayer(desc);
if (!startLayer)
{
@@ -658,6 +653,10 @@
input.Connect(startLayer->GetInputSlot(0));
+ // Connect weights and bias inputs
+ weightsInput.Connect(startLayer->GetInputSlot(1));
+ biasInput.Connect(startLayer->GetInputSlot(2));
+
return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, 0, *startLayer, model,
data, nullptr, validateFunc, activation);
}
diff --git a/test/Dilation.hpp b/test/Dilation.hpp
index 86c1336..dbd2493 100644
--- a/test/Dilation.hpp
+++ b/test/Dilation.hpp
@@ -51,6 +51,8 @@
armnn::IgnoreUnused(layer, constants, id, name);
switch (layer->GetType())
{
+ case armnn::LayerType::Constant:
+ break;
case armnn::LayerType::Convolution2d:
{
CheckDilationParams(static_cast<const armnn::Convolution2dDescriptor&>(descriptor));