IVGCVSW-3593 Remove HAL1.2-specific code from HAL1.0 ConvertConv2d() and ConvertDepthwiseConv2d()
* Removed code for reading data layout flag (only available in HAL1.2)
* Removed code for reading dilation parameters (only available in HAL1.2)
* Added more restrictive input size checks (== instead of >=, as none
of the inputs are optional in HAL1.0/1.1)
* Removed superfluous input size validation from 1.0/HalPolicy.cpp
Signed-off-by: Aron Virginas-Tar <Aron.Virginas-Tar@arm.com>
Change-Id: I8387120b9abcc8458f7fac6df577cb6453051be3
diff --git a/ConversionUtils.hpp b/ConversionUtils.hpp
index 0c00a16..52bfd5c 100644
--- a/ConversionUtils.hpp
+++ b/ConversionUtils.hpp
@@ -1035,7 +1035,7 @@
data.m_Backends,
isSupported,
tensorPin.GetConstTensor().GetInfo());
- if (!isSupported)
+ if (isSupported)
{
return LayerInputHandle();
}
@@ -1434,6 +1434,11 @@
const armnn::TensorInfo& inputInfo = input.GetTensorInfo();
const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*output);
+ if (IsDynamicTensor(outputInfo))
+ {
+ return Fail("%s: Dynamic output tensors are not supported", __func__);
+ }
+
// ArmNN does not currently support non-fixed weights or bias
const ConstTensorPin weightsPin = ConvertOperationInputToConstTensorPin<HalPolicy>(operation, 1, model, data);
const ConstTensorPin biasPin = ConvertOperationInputToConstTensorPin<HalPolicy>(operation, 2, model, data);
@@ -1444,14 +1449,14 @@
}
armnn::ConstTensor weights = weightsPin.GetConstTensor();
- armnn::ConstTensor bias = biasPin.GetConstTensor();
+ armnn::ConstTensor bias = biasPin.GetConstTensor();
SanitizeBiasQuantizationScale(bias.GetInfo(), weights.GetInfo(), inputInfo);
armnn::Convolution2dDescriptor desc;
desc.m_DataLayout = armnn::DataLayout::NHWC;
ActivationFn activation;
- if (operation.inputs.size() >= 10)
+ if (operation.inputs.size() == 10)
{
if (!GetInputScalar<HalPolicy>(operation, 3, HalOperandType::INT32, desc.m_PadLeft, model, data) ||
!GetInputScalar<HalPolicy>(operation, 4, HalOperandType::INT32, desc.m_PadRight, model, data) ||
@@ -1459,21 +1464,18 @@
!GetInputScalar<HalPolicy>(operation, 6, HalOperandType::INT32, desc.m_PadBottom, model, data) ||
!GetInputScalar<HalPolicy>(operation, 7, HalOperandType::INT32, desc.m_StrideX, model, data) ||
!GetInputScalar<HalPolicy>(operation, 8, HalOperandType::INT32, desc.m_StrideY, model, data) ||
- !GetInputActivationFunction<HalPolicy>(operation, 9, activation, model, data) ||
- !GetOptionalConvolutionDilationParams<HalPolicy>(operation, 11, desc, model, data))
+ !GetInputActivationFunction<HalPolicy>(operation, 9, activation, model, data))
{
return Fail("%s: Operation has invalid inputs", __func__);
}
- desc.m_DataLayout = OptionalDataLayout<HalPolicy>(operation, 10, model, data);
}
- else if (operation.inputs.size() >= 7)
+ else if (operation.inputs.size() == 7)
{
android::nn::PaddingScheme paddingScheme;
if (!GetInputPaddingScheme<HalPolicy>(operation, 3, paddingScheme, model, data) ||
!GetInputScalar<HalPolicy>(operation, 4, HalOperandType::INT32, desc.m_StrideX, model, data) ||
!GetInputScalar<HalPolicy>(operation, 5, HalOperandType::INT32, desc.m_StrideY, model, data) ||
- !GetInputActivationFunction<HalPolicy>(operation, 6, activation, model, data) ||
- !GetOptionalConvolutionDilationParams<HalPolicy>(operation, 8, desc, model, data))
+ !GetInputActivationFunction<HalPolicy>(operation, 6, activation, model, data))
{
return Fail("%s: Operation has invalid inputs", __func__);
}
@@ -1485,8 +1487,6 @@
CalcPadding(inputX, kernelX, desc.m_StrideX, desc.m_PadLeft, desc.m_PadRight, paddingScheme);
CalcPadding(inputY, kernelY, desc.m_StrideY, desc.m_PadTop, desc.m_PadBottom, paddingScheme);
-
- desc.m_DataLayout = OptionalDataLayout<HalPolicy>(operation, 7, model, data);
}
else
{
@@ -1496,11 +1496,6 @@
desc.m_BiasEnabled = true;
armnn::Optional<armnn::TensorInfo> biases(bias.GetInfo());
- if (IsDynamicTensor(outputInfo))
- {
- return Fail("%s: Dynamic output tensors are not supported", __func__);
- }
-
bool isSupported = false;
FORWARD_LAYER_SUPPORT_FUNC(__func__,
IsConvolution2dSupported,
@@ -1561,8 +1556,12 @@
const armnn::TensorInfo& inputInfo = input.GetTensorInfo();
const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*output);
- // ArmNN does not currently support non-fixed weights or bias
+ if (IsDynamicTensor(outputInfo))
+ {
+ return Fail("%s: Dynamic output tensors are not supported", __func__);
+ }
+ // 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);
@@ -1573,26 +1572,11 @@
armnn::DepthwiseConvolution2dDescriptor desc;
desc.m_DataLayout = armnn::DataLayout::NHWC;
- // Look ahead to find the optional DataLayout, if present
- if (operation.inputs.size() >= 12)
- {
- desc.m_DataLayout = OptionalDataLayout<HalPolicy>(operation, 11, model, data);
- }
- else if (operation.inputs.size() >= 9)
- {
- desc.m_DataLayout = OptionalDataLayout<HalPolicy>(operation, 8, model, data);
- }
-
- armnnUtils::DataLayoutIndexed dataLayoutIndexed(desc.m_DataLayout);
- unsigned int channelsIndex = dataLayoutIndexed.GetChannelsIndex();
- unsigned int widthIndex = dataLayoutIndexed.GetWidthIndex();
- unsigned int heightIndex = dataLayoutIndexed.GetHeightIndex();
-
// Reinterpret weight data as [ H, W, I, M ]
armnn::TensorShape weightsShape({ weightsOperand->dimensions[1],
weightsOperand->dimensions[2],
- inputInfo.GetShape()[channelsIndex],
- weightsOperand->dimensions[3] / inputInfo.GetShape()[channelsIndex] });
+ inputInfo.GetShape()[3],
+ weightsOperand->dimensions[3] / inputInfo.GetShape()[3] });
// Swizzle weight data [ H, W, I, M ] -> [ M, I, H, W ]
const armnn::PermutationVector HWIMToMIHW = { 2U, 3U, 1U, 0U };
@@ -1619,7 +1603,7 @@
ActivationFn activation;
- if (operation.inputs.size() >= 11)
+ if (operation.inputs.size() == 11)
{
if (!GetInputScalar<HalPolicy>(operation, 3, HalOperandType::INT32, desc.m_PadLeft, model, data) ||
!GetInputScalar<HalPolicy>(operation, 4, HalOperandType::INT32, desc.m_PadRight, model, data) ||
@@ -1627,28 +1611,26 @@
!GetInputScalar<HalPolicy>(operation, 6, HalOperandType::INT32, desc.m_PadBottom, model, data) ||
!GetInputScalar<HalPolicy>(operation, 7, HalOperandType::INT32, desc.m_StrideX, model, data) ||
!GetInputScalar<HalPolicy>(operation, 8, HalOperandType::INT32, desc.m_StrideY, model, data) ||
- !GetInputActivationFunction<HalPolicy>(operation, 10, activation, model, data) ||
- !GetOptionalConvolutionDilationParams<HalPolicy>(operation, 12, desc, model, data))
+ !GetInputActivationFunction<HalPolicy>(operation, 10, activation, model, data))
{
return Fail("%s: Operation has invalid inputs", __func__);
}
}
- else if (operation.inputs.size() >= 8)
+ else if (operation.inputs.size() == 8)
{
android::nn::PaddingScheme paddingScheme;
if (!GetInputPaddingScheme<HalPolicy>(operation, 3, paddingScheme, model, data) ||
!GetInputScalar<HalPolicy>(operation, 4, HalOperandType::INT32, desc.m_StrideX, model, data) ||
!GetInputScalar<HalPolicy>(operation, 5, HalOperandType::INT32, desc.m_StrideY, model, data) ||
- !GetInputActivationFunction<HalPolicy>(operation, 7, activation, model, data) ||
- !GetOptionalConvolutionDilationParams<HalPolicy>(operation, 9, desc, model, data))
+ !GetInputActivationFunction<HalPolicy>(operation, 7, activation, model, data))
{
return Fail("%s: Operation has invalid inputs", __func__);
}
const uint32_t kernelX = weights.GetShape()[3];
const uint32_t kernelY = weights.GetShape()[2];
- const uint32_t inputX = inputInfo.GetShape()[widthIndex];
- const uint32_t inputY = inputInfo.GetShape()[heightIndex];
+ const uint32_t inputX = inputInfo.GetShape()[2];
+ const uint32_t inputY = inputInfo.GetShape()[1];
CalcPadding(inputX, kernelX, desc.m_StrideX, desc.m_PadLeft, desc.m_PadRight, paddingScheme);
CalcPadding(inputY, kernelY, desc.m_StrideY, desc.m_PadTop, desc.m_PadBottom, paddingScheme);
@@ -1661,11 +1643,6 @@
desc.m_BiasEnabled = true;
armnn::Optional<armnn::TensorInfo> biases(bias.GetInfo());
- if (IsDynamicTensor(outputInfo))
- {
- return Fail("%s: Dynamic output tensors are not supported", __func__);
- }
-
bool isSupported = false;
FORWARD_LAYER_SUPPORT_FUNC(__func__,
IsDepthwiseConvolutionSupported,