[TORCH][MLIR] Add E2E support for aten.empty_like op

This commit adds decomposition of `aten.empty_like` into `aten.empty`
op.

Signed-Off-by: Gaurav Shukla <[email protected]>

Author: Gaurav Shukla

e2e_testing/torchscript/basic.py

@@ -663,7 +663,7 @@ def __init__(self):
         None,
     ])
     def forward(self):
-        return torch.abs(torch.empty((3, 4), dtype=torch.float32)) > -1.0
+        return torch.pow(torch.empty((3, 4), dtype=torch.float32), 0)
 
 @register_test_case(module_factory=lambda: EmptyFloatModule())
 def EmptyModule_float(module, tu: TestUtils):
@@ -679,15 +679,51 @@ def __init__(self):
         None,
     ])
     def forward(self):
-        return torch.abs(torch.empty((3, 4), dtype=torch.float32, 
-                                     pin_memory=False)) > -1.0 
+        return torch.pow(torch.empty((3, 4), dtype=torch.float32, 
+                                     pin_memory=False), 0)
 
 @register_test_case(module_factory=lambda: EmptyFalsePinMemoryModule())
 def EmptyModule_falsePinMemory(module, tu: TestUtils):
     module.forward()
 
 # ==============================================================================
 
+class EmptyLikeIntModule(torch.nn.Module):
+    def __init__(self):
+        super().__init__()
+
+    @export
+    @annotate_args([
+        None,
+        ([-1, -1], torch.int64, True),
+    ])
+    def forward(self, a):
+        return 0 * torch.empty_like(a, dtype=torch.int64)
+
+@register_test_case(module_factory=lambda: EmptyLikeIntModule())
+def EmptyLikeModule_int(module, tu: TestUtils):
+    module.forward(torch.randint(10, (3, 5)))
+
+# ==============================================================================
+
+class EmptyLikeFloatModule(torch.nn.Module):
+    def __init__(self):
+        super().__init__()
+
+    @export
+    @annotate_args([
+        None,
+        ([-1, -1], torch.float32, True),
+    ])
+    def forward(self, a):
+        return torch.pow(torch.empty_like(a, dtype=torch.float32), 0)
+
+@register_test_case(module_factory=lambda: EmptyLikeFloatModule())
+def EmptyLikeModule_float(module, tu: TestUtils):
+    module.forward(tu.rand(4, 5))
+
+# ==============================================================================
+
 class ContiguousModule(torch.nn.Module):
     def __init__(self):
         super().__init__()

lib/Dialect/Torch/Transforms/DecomposeComplexOps.cpp

@@ -506,6 +506,33 @@ class DecomposeAtenLayerNormOp : public OpRewritePattern<AtenLayerNormOp> {
 };
 } // namespace
 
+// Decompose `aten.empty_like` op into `aten.size` and `aten.empty` ops.
+namespace {
+class DecomposeAtenEmptyLikeOp : public OpRewritePattern<AtenEmptyLikeOp> {
+public:
+  using OpRewritePattern::OpRewritePattern;
+  LogicalResult matchAndRewrite(AtenEmptyLikeOp op,
+                                PatternRewriter &rewriter) const override {
+    auto sizeListType =
+        Torch::ListType::get(Torch::IntType::get(op.getContext()));
+    Value sizeList =
+        rewriter.create<AtenSizeOp>(op.getLoc(), sizeListType, op.self());
+
+    // TODO: Handle the case when `dtype` is NoneType.
+    Type dtype = op.dtype().getType();
+    if (dtype.isa<OptionalType>() || dtype.isa<Torch::NoneType>() ||
+        dtype.isa<mlir::NoneType>())
+      return rewriter.notifyMatchFailure(
+          op, "unimplemented: None dtype is not supported");
+
+    rewriter.replaceOpWithNewOp<AtenEmptyMemoryFormatOp>(
+        op, op.getType(), sizeList, op.dtype(), op.layout(), op.device(),
+        op.pin_memory(), op.memory_format());
+    return success();
+  }
+};
+} // namespace
+
 namespace {
 class DecomposeComplexOpsPass
     : public DecomposeComplexOpsBase<DecomposeComplexOpsPass> {
@@ -521,6 +548,8 @@ class DecomposeComplexOpsPass
     target.addIllegalOp<Aten_SoftmaxOp>();
     patterns.add<DecomposeAtenLogSoftmaxIntOp>(context);
     target.addIllegalOp<AtenLogSoftmaxIntOp>();
+    patterns.add<DecomposeAtenEmptyLikeOp>(context);
+    target.addIllegalOp<AtenEmptyLikeOp>();
     patterns.add<DecomposeAtenExpandOp>(context);
     target.addIllegalOp<AtenExpandOp>();
     patterns.add<DecomposeAtenSizeOp>(context);

lib/Dialect/Torch/Transforms/RefineTypes.cpp

@@ -237,7 +237,7 @@ class TypeAnalyzer : public ForwardDataFlowAnalysis<ValueKnowledge> {
             AtenTanhOp, AtenBatchNormOp, AtenReluOp, AtenGeluOp,
             AtenGeluBackwardOp, AtenBitwiseNotOp, AtenExpOp, AtenSinOp,
             AtenCosOp, AtenSigmoidOp, DerefineOp, AtenToPrimDeviceOp, AtenCpuOp,
-            AtenContiguousOp, AtenFill_ScalarOp, AtenDetachOp,
+            AtenContiguousOp, AtenFill_ScalarOp, AtenDetachOp, AtenEmptyLikeOp,
             AtenMaskedFill_ScalarOp, AtenCopy_Op, AtenCumsumOp, AtenLayerNormOp,
             AtenClampOp, AtenLogOp, AtenNegOp, AtenSqrtOp, AtenFloorOp,
             AtenLog2Op, Aten_SoftmaxBackwardDataOp, AtenRsqrtOp, AtenDropoutOp,