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-rw-r--r--ConversionUtils_1_2.hpp18
1 files changed, 4 insertions, 14 deletions
diff --git a/ConversionUtils_1_2.hpp b/ConversionUtils_1_2.hpp
index eec87bf5..f884f7c0 100644
--- a/ConversionUtils_1_2.hpp
+++ b/ConversionUtils_1_2.hpp
@@ -467,22 +467,12 @@ bool ConvertDepthwiseConv2d_1_2(const HalOperation& operation, const HalModel& m
unsigned int widthIndex = dataLayoutIndexed.GetWidthIndex();
unsigned int heightIndex = dataLayoutIndexed.GetHeightIndex();
- // Reinterpret weight data as [ H, W, I, M ]
- TensorShape weightsShape({ weightsOperand->dimensions[1],
- weightsOperand->dimensions[2],
- inputInfo.GetShape()[channelsIndex],
- weightsOperand->dimensions[3] / inputInfo.GetShape()[channelsIndex] });
-
- // Swizzle weight data [ H, W, I, M ] -> [ M, I, H, W ]
- const PermutationVector HWIMToMIHW = { 2U, 3U, 1U, 0U };
-
+ // 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,
- HWIMToMIHW,
- &weightsShape);
+ data);
// Bias is a 1D tensor
const ConstTensorPin biasPin =
@@ -516,8 +506,8 @@ bool ConvertDepthwiseConv2d_1_2(const HalOperation& operation, const HalModel& m
return Fail("%s: Operation has invalid inputs (implicit padding)", __func__);
}
- const uint32_t kernelX = weights.GetShape()[3];
- const uint32_t kernelY = weights.GetShape()[2];
+ const uint32_t kernelX = weights.GetShape()[2];
+ const uint32_t kernelY = weights.GetShape()[1];
const uint32_t inputX = inputInfo.GetShape()[widthIndex];
const uint32_t inputY = inputInfo.GetShape()[heightIndex];