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Batched autodiff #2181

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merged 22 commits into from
Dec 27, 2024
Merged

Batched autodiff #2181

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8d3ef08
add type conversions for width != 1.
jumerckx Nov 28, 2024
5e647e5
add code to tblgen generator, this eventually needs to be a single fu…
jumerckx Nov 28, 2024
f69f974
a test and formatting
jumerckx Nov 28, 2024
623fccf
use tensor splatop
jumerckx Dec 2, 2024
f860e19
remove stale enzyme-tblgen changes
jumerckx Dec 2, 2024
3a3bdf8
do the simple batching in enzyme-tblgen
jumerckx Dec 4, 2024
f1b2a6d
include tensor in all AutoDiffOpInterfaceImpls
jumerckx Dec 4, 2024
396a29b
add enzyme broadcastop
jumerckx Dec 6, 2024
64489a5
getShadowType for TensorTypeInterface
jumerckx Dec 6, 2024
0ccb37f
create broadcastop in enzyme-tblgen
jumerckx Dec 6, 2024
123a985
Revert "include tensor in all AutoDiffOpInterfaceImpls"
jumerckx Dec 6, 2024
3d2911d
test
jumerckx Dec 6, 2024
8a3f3c7
DenseI64ArrayAttr for shape instead of scalar width
Dec 22, 2024
aa4e598
`llvm::SmallVector` --> `ArrayRef`
jumerckx Dec 22, 2024
fa190a4
formatting
jumerckx Dec 23, 2024
1802949
use getShadowType in BroadcastOp builder
jumerckx Dec 25, 2024
f9746ac
unstructured control flow test
jumerckx Dec 25, 2024
2fb1412
scf.for
jumerckx Dec 25, 2024
2c4f1fb
formatting
jumerckx Dec 25, 2024
236b65d
support `scf.if` test
jumerckx Dec 25, 2024
9ceb922
formatting
jumerckx Dec 25, 2024
50522a0
forgotten includes
jumerckx Dec 25, 2024
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getShadowType for TensorTypeInterface
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@jumerckx
jumerckx committed Dec 16, 2024
commit 64489a5662e6daec445141686ac4cede52468069
9 changes: 8 additions & 1 deletion enzyme/Enzyme/MLIR/Implementations/BuiltinAutoDiffTypeInterfaceImpl.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -110,7 +110,14 @@ class TensorTypeInterface
}

Type getShadowType(Type self, unsigned width) const {
assert(width == 1 && "unsupported width != 1");
if (width != 1) {
auto tenType = self.cast<TensorType>();
auto shape = tenType.getShape();
SmallVector<int64_t, 4> newShape;
newShape.push_back(width);
newShape.append(shape.begin(), shape.end());
return RankedTensorType::get(newShape, tenType.getElementType());
}
return self;
}

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