mirror of https://github.com/llvm/torch-mlir
[Torch Op] Add unbind.int support with ListUnpack (#2058)
* add unbind int * reformat * use unpack canonicalize * address comments * Empty commit, trigger test * add ltc blacklist * clean up * address comments * check permute list * erase in recompose --------- Co-authored-by: zhekun.zhang <zhekun.zhang@bytedance.com>pull/2134/head snapshot-20230519.843
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1333674905
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@ -7,6 +7,9 @@ blacklist:
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- index_put # Error: TODO not sure if there are other valid types to handle here
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- index_put_ # Error: TODO not sure if there are other valid types to handle here
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# Ops with list of tensors output
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- unbind.int
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# Additional ops which autogen is supported for but don't compile yet
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- _convolution
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- detach
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@ -259,6 +259,10 @@ TORCHDYNAMO_XFAIL_SET = {
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"AtenComplexImagModule_basic",
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"AtenComplexRealModule_basic",
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# END tests failing due to: complex floating point ops
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# ERROR: Exception: Unsupported: return type List[Tensor] in schema for aten.unbind.int
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"UnbindIntListUnpack_Module_basic",
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"UnbindIntGetItem_Module_basic",
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}
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TORCHDYNAMO_CRASHING_SET = {
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@ -722,6 +726,8 @@ STABLEHLO_PASS_SET = {
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"PrimsViewOfModule_basic",
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"PrimsViewOfZeroRankModule_basic",
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"AtenComplex64Module_basic",
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"UnbindIntListUnpack_Module_basic",
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"UnbindIntGetItem_Module_basic",
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}
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# Write the TOSA set as a "passing" set as it is very early in development
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@ -1001,6 +1007,8 @@ TOSA_PASS_SET = {
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"PrimsViewOfModule_basic",
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"PrimsViewOfZeroRankModule_basic",
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"DetachModule_basic",
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"UnbindIntListUnpack_Module_basic",
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"UnbindIntGetItem_Module_basic",
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"TensorsConcatStaticModule_basic",
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"TensorsConcatNegativeDimStaticModule_basic",
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"AtenComplex64Module_basic",
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@ -1182,5 +1190,7 @@ LTC_XFAIL_SET = {
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"VarMeanDimBiasedModule_basic",
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"AtenComplexImagModule_basic",
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"AtenComplexRealModule_basic",
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"AtenComplexViewModule_basic"
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"AtenComplexViewModule_basic",
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"UnbindIntListUnpack_Module_basic",
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"UnbindIntGetItem_Module_basic",
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}
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@ -9521,6 +9521,29 @@ def Torch_AtenSortOp : Torch_Op<"aten.sort", [
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}];
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}
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def Torch_AtenUnbindIntOp : Torch_Op<"aten.unbind.int", [
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AllowsTypeRefinement,
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ReadOnly
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]> {
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let summary = "Generated op for `aten::unbind.int : (Tensor, int) -> (Tensor[])`";
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let arguments = (ins
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AnyTorchTensorType:$self,
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Torch_IntType:$dim
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);
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let results = (outs
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AnyTorchListOfTensorType:$result
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);
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let hasCustomAssemblyFormat = 1;
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let extraClassDefinition = [{
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ParseResult AtenUnbindIntOp::parse(OpAsmParser &parser, OperationState &result) {
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return parseDefaultTorchOp(parser, result, 2, 1);
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}
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void AtenUnbindIntOp::print(OpAsmPrinter &printer) {
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printDefaultTorchOp(printer, *this, 2, 1);
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}
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}];
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}
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def Torch_AtenAddStrOp : Torch_Op<"aten.add.str", [
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AllowsTypeRefinement,
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HasValueSemantics,
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@ -121,6 +121,66 @@ public:
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return success();
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}
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};
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class RecomposeUnbindListUnpack : public OpRewritePattern<PrimListUnpackOp> {
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public:
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using OpRewritePattern::OpRewritePattern;
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LogicalResult matchAndRewrite(PrimListUnpackOp op,
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PatternRewriter &rewriter) const override {
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// recompose AtenUnbindOp + PrimListUnpackOp to select.int
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auto unbind = dyn_cast<AtenUnbindIntOp>(op.getOperand().getDefiningOp());
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if (!unbind)
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return failure();
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if (isListPotentiallyMutated(unbind.getResult()))
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return failure();
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Value dim = unbind.getDim();
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Value input = unbind.getSelf();
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SmallVector<Value> slices;
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for (int i = 0; i < op.getNumResults(); i++) {
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// rewrite to slice op
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auto resultTy = op.getResult(i).getType();
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auto index = rewriter.create<Torch::ConstantIntOp>(
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op->getLoc(), rewriter.getI64IntegerAttr(i));
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auto newSelect = rewriter.create<AtenSelectIntOp>(op->getLoc(), resultTy,
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input, dim, index);
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slices.push_back(newSelect);
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}
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rewriter.replaceOp(op, slices);
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if (unbind.getResult().use_empty())
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rewriter.eraseOp(unbind);
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return success();
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}
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};
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class RecomposeUnbindGetItem : public OpRewritePattern<Aten__Getitem__TOp> {
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public:
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using OpRewritePattern::OpRewritePattern;
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LogicalResult matchAndRewrite(Aten__Getitem__TOp op,
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PatternRewriter &rewriter) const override {
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// recompose AtenUnbindIntOp + __getitem__t to select.int
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auto unbind = dyn_cast<AtenUnbindIntOp>(op.getList().getDefiningOp());
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if (!unbind)
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return failure();
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if (isListPotentiallyMutated(unbind.getResult()))
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return failure();
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int64_t index;
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if (!matchPattern(op.getIdx(), m_TorchConstantInt(&index)))
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return rewriter.notifyMatchFailure(
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op, "Expected `idx` of `Aten__Getitem__TOp` to be a constant int");
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Location loc = op.getLoc();
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Value dim = unbind.getDim();
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Value input = unbind.getSelf();
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// rewrite to slice op
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auto resultTy = op.getResult().getType();
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Value newSelect = rewriter.create<AtenSelectIntOp>(loc, resultTy, input,
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dim, op.getIdx());
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rewriter.replaceOp(op, newSelect);
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if (unbind.getResult().use_empty())
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rewriter.eraseOp(unbind);
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return success();
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}
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};
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} // namespace
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namespace {
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@ -134,6 +194,8 @@ public:
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// pattern.add calls go here
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patterns.add<RecomposeSliceCopy_>(context);
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patterns.add<RecomposeSelectFill_>(context);
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patterns.add<RecomposeUnbindListUnpack>(context);
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patterns.add<RecomposeUnbindGetItem>(context);
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GreedyRewriteConfig config;
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config.useTopDownTraversal = true;
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@ -589,6 +589,7 @@ def emit_ops(emitter_td: TextEmitter, registry: Registry):
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emit("aten::any.bool : (bool[]) -> (bool)")
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emit("aten::sort.int : (int[], bool) -> ()", has_canonicalizer=True)
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emit("aten::sort : (Tensor, int, bool) -> (Tensor, Tensor)")
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emit("aten::unbind.int : (Tensor, int) -> (Tensor[])")
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# Str ops.
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emit("aten::add.str : (str, str) -> (str)")
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@ -542,3 +542,42 @@ class SliceCopyNegative_Module(torch.nn.Module):
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@register_test_case(module_factory=lambda: SliceCopyNegative_Module())
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def SliceCopyNegative_Module_basic(module, tu: TestUtils):
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module.forward(tu.rand(10, 4, 4), tu.rand(4, 4, 4))
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# ==============================================================================
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class UnbindIntListUnpack_Module(torch.nn.Module):
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def __init__(self):
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super().__init__()
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@export
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@annotate_args([
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None,
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([2, 3, 4], torch.float32, True),
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])
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def forward(self, x):
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unbind_0, unbind_1 = torch.unbind(x, 0)
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return torch.ops.aten.sub(unbind_0, unbind_1)
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@register_test_case(module_factory=lambda: UnbindIntListUnpack_Module())
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def UnbindIntListUnpack_Module_basic(module, tu: TestUtils):
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module.forward(tu.rand(2, 3, 4))
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# ==============================================================================
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class UnbindIntGetItem_Module(torch.nn.Module):
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def __init__(self):
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super().__init__()
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@export
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@annotate_args([
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None,
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([2, 3, 4], torch.float32, True),
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])
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def forward(self, x):
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unbind = torch.unbind(x, 0)
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return torch.ops.aten.sub(unbind[0], unbind[1])
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@register_test_case(module_factory=lambda: UnbindIntGetItem_Module())
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def UnbindIntGetItem_Module_basic(module, tu: TestUtils):
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module.forward(tu.rand(2, 3, 4))
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