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TensorDesc::Placement test failure - cherry pick Vibranium fix. (#2328)

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Dwayne Robinson 2019-11-05 18:18:31 -08:00 committed by GitHub
parent 67ec626d88
commit db454beacf
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GPG key ID: 4AEE18F83AFDEB23
1 changed files with 31 additions and 8 deletions
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39
onnxruntime/core/providers/dml/DmlExecutionProvider/src/TensorDesc.cpp
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@ -48,8 +48,8 @@ TensorDesc::TensorDesc(MLOperatorTensorDataType dataType)
TensorDesc::TensorDesc(
MLOperatorTensorDataType dataType,
gsl::span<const uint32_t> dimensions,
gsl::span<const uint32_t> nonBroadcastDimensions,
gsl::span<const uint32_t> dimensions, // Desired dimensions
gsl::span<const uint32_t> nonBroadcastDimensions, // Actual physical dimensions
uint32_t coerceAxis,
int32_t placement, // Adjustment offset of the passed dimensions within the minDimensionCount.
int32_t leftAlignedDimensionCount, // Number of dimensions that remain left aligned when expanded to minimum count (INT32_MAX means all, 0 means all right aligned).
@ -63,11 +63,6 @@ TensorDesc::TensorDesc(
m_bufferTensorDesc.DataType = GetDmlDataTypeFromMlDataType(dataType);
ML_CHECK_VALID_ARGUMENT(ApiTraits::IsValidEnumValue(m_bufferTensorDesc.DataType));
// Flattening coercion isn't always possible when striding is used to broadcast tensors.
// Also, placement and split alignment is not implemented in combination with broadcasting.
ML_CHECK_VALID_ARGUMENT((nonBroadcastDimensions == dimensions)
|| ((coerceAxis == TensorAxis::DoNotCoerce) && (placement == W) && (leftAlignedDimensionCount == RightAligned)));
gsl::span<const uint32_t> sizes;
// If needed, flatten the tensor dimensions to a 2D tensor of size [a_0 * ... * a_{coerceAxis-1}, a_{coerceAxis} * ... * a_{n-1}]
@ -98,6 +93,9 @@ TensorDesc::TensorDesc(
sizes = dimensions;
}
////////////////////////////////////////
// Align dimensions
// Determine the number of dimensions that should be aligned to the left edge when promoting to the minimum dimension count.
// Negative values mean align from the right.
const int32_t rank = gsl::narrow_cast<int32_t>(sizes.size());
@ -134,17 +132,39 @@ TensorDesc::TensorDesc(
while (j < MaximumDimensionCount) { m_sizes[j++] = 1; }
}
////////////////////////////////////////
// Coerce the physical shape to the desired shape.
// By default, assume strides are not necessary.
bool useStrides = false;
if (dimensions != nonBroadcastDimensions)
{
// This broadcasting and subset logic is only applicable to the simple case where all
// dimensions are contiguously right aligned, which means no flattening coercion,
// placement offset, or split alignment. In such cases, the right side of m_sizes
// should match the original dimensions.
ML_CHECK_VALID_ARGUMENT(std::equal(
dimensions.begin(),
dimensions.end(),
&m_sizes[m_bufferTensorDesc.DimensionCount - rank],
&m_sizes[m_bufferTensorDesc.DimensionCount]
));
// Stretch any dimensions with a single element.
//
// e.g. physical [2,1,4]
// desired [2,3,4]
// output [2,3,4]
// strides [4,0,1]
//
// If broadcasting is used, then strides are used.
useStrides = true;
// Walk backwards through both input shapes and broadcast or default each dimension
// Walk backwards through both input shapes and broadcast or default each dimension.
auto nonBroadcastDimsIter = nonBroadcastDimensions.rbegin();
uint32_t elementCount = 1;
for (int descDimIndex = m_bufferTensorDesc.DimensionCount - 1; descDimIndex >= 0; --descDimIndex)
{
if (nonBroadcastDimsIter == nonBroadcastDimensions.rend() || (*nonBroadcastDimsIter == 1))
@ -164,6 +184,9 @@ TensorDesc::TensorDesc(
}
}
////////////////////////////////////////
// Handle 64-bit tensors.
uint64_t endPaddingInBytes = 0;
if (dataType == MLOperatorTensorDataType::UInt64 || dataType == MLOperatorTensorDataType::Int64)