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[Torch] fix cross_entropy_loss decomposition #3839

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[Torch] fix cross_entropy_loss decomposition #3839

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21005a7
[Torch] fix cross_entropy_loss decomposition
yyp0 Oct 31, 2024
92e0098
update
yyp0 Oct 31, 2024
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17 changes: 16 additions & 1 deletion lib/Dialect/Torch/Transforms/DecomposeComplexOps.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -8896,6 +8896,12 @@ class DecomposeAtenCrossEntropyLossOp
op, "Unimplemented: unranked target tensor");
unsigned targetRank = maybeRank.value();

Value reduction = op.getReduction();
int64_t reductionInt;
if (!matchPattern(reduction, m_TorchConstantInt(&reductionInt))) {
return rewriter.notifyMatchFailure(op,
"reduction should be a constant int!");
}
// When the input is 2-d i.e. of the form [minibatch, C] and target is 1-d
// of the form [minibatch] the cross entropy loss decomposes to the
// combination of softmax and nll loss as follows:
Expand Down Expand Up @@ -8925,10 +8931,19 @@ class DecomposeAtenCrossEntropyLossOp
loc, rewriter.getI64IntegerAttr(1));
Value logSoftmax = rewriter.create<AtenLogSoftmaxIntOp>(
loc, self.getType(), self, dim, /*dtype=*/noneVal);

Type secondType;
if (reductionInt == 0) {
secondType = target.getType();
} else {
auto targetType = dyn_cast<BaseTensorType>(target.getType());
secondType = targetType.getWithSizesAndDtype({}, targetType.getDtype());
}

Comment on lines +8934 to +8942
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Suggested change
Type secondType;
if (reductionInt == 0) {
secondType = target.getType();
} else {
auto targetType = dyn_cast<BaseTensorType>(target.getType());
secondType = targetType.getWithSizesAndDtype({}, targetType.getDtype());
}
Type secondType = target.getType();
if (reductionInt != 0) {
auto targetType = dyn_cast<BaseTensorType>(target.getType());
secondType = targetType.getWithSizesAndDtype({}, targetType.getDtype());
}

Value nllLoss =
rewriter
.create<AtenNllLossForwardOp>(
loc, op.getType(), target.getType(), logSoftmax, target,
loc, op.getType(), secondType, logSoftmax, target,
op.getWeight(), op.getReduction(), op.getIgnoreIndex())
->getResult(0);
rewriter.replaceOp(op, nllLoss);
Expand Down
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