Add e2e support for aten.expm1

include/torch-mlir/Dialect/Torch/IR/GeneratedTorchOps.td

@@ -565,6 +565,51 @@ def Torch_AtenExp_Op : Torch_Op<"aten.exp_", [
   }];
 }
 
+def Torch_AtenExpm1Op : Torch_Op<"aten.expm1", [
+    AllowsTypeRefinement,
+    HasValueSemantics,
+    ReadOnly
+  ]> {
+  let summary = "Generated op for `aten::expm1 : (Tensor) -> (Tensor)`";
+  let arguments = (ins
+    AnyTorchTensorType:$self
+  );
+  let results = (outs
+    AnyTorchTensorType:$result
+  );
+  let hasCustomAssemblyFormat = 1;
+  let extraClassDefinition = [{
+    ParseResult AtenExpm1Op::parse(OpAsmParser &parser, OperationState &result) {
+      return parseDefaultTorchOp(parser, result, 1, 1);
+    }
+    void AtenExpm1Op::print(OpAsmPrinter &printer) {
+      printDefaultTorchOp(printer, *this, 1, 1);
+    }
+  }];
+}
+
+def Torch_AtenExpm1_Op : Torch_Op<"aten.expm1_", [
+    IsTrailingUnderscoreInplaceVariant,
+    AllowsTypeRefinement
+  ]> {
+  let summary = "Generated op for `aten::expm1_ : (Tensor) -> (Tensor)`";
+  let arguments = (ins
+    AnyTorchTensorType:$self
+  );
+  let results = (outs
+    AnyTorchTensorType:$result
+  );
+  let hasCustomAssemblyFormat = 1;
+  let extraClassDefinition = [{
+    ParseResult AtenExpm1_Op::parse(OpAsmParser &parser, OperationState &result) {
+      return parseDefaultTorchOp(parser, result, 1, 1);
+    }
+    void AtenExpm1_Op::print(OpAsmPrinter &printer) {
+      printDefaultTorchOp(printer, *this, 1, 1);
+    }
+  }];
+}
+
 def Torch_AtenCosOp : Torch_Op<"aten.cos", [
     AllowsTypeRefinement,
     HasValueSemantics,

lib/Conversion/TorchToLinalg/Uncategorized.cpp

@@ -131,6 +131,10 @@ static Value createLinalgPayloadCalculationForElementwiseOp(
     return createCalculationForMathOpWithDtypeConversion<math::ExpOp>(
         b, converter, payloadArgs[0], op);
   }
+  if (isa<AtenExpm1Op>(op)) {
+    return createCalculationForMathOpWithDtypeConversion<math::ExpM1Op>(
+        b, converter, payloadArgs[0], op);
+  }
   if (isa<AtenLogOp>(op)) {
     return createCalculationForMathOpWithDtypeConversion<math::LogOp>(
         b, converter, payloadArgs[0], op);
@@ -923,15 +927,15 @@ public:
     if (!isa<AtenTanhOp, AtenReluOp, AtenLeakyReluOp, AtenGeluOp,
              AtenGeluBackwardOp, AtenAddTensorOp, AtenMulTensorOp,
              AtenDivTensorOp, AtenDivTensorModeOp, AtenSubTensorOp,
-             AtenLerpTensorOp, AtenSigmoidOp, AtenExpOp, AtenMinimumOp,
+             AtenLerpTensorOp, AtenSigmoidOp, AtenExpOp, AtenExpm1Op,
-             AtenMaximumOp, AtenToDtypeOp, AtenClampOp, AtenRsubScalarOp,
+             AtenMinimumOp, AtenMaximumOp, AtenToDtypeOp, AtenClampOp,
-             AtenMulScalarOp, AtenLogOp, AtenErfOp, AtenSqrtOp, AtenFloorOp,
+             AtenRsubScalarOp, AtenMulScalarOp, AtenLogOp, AtenErfOp,
-             AtenPowTensorScalarOp, AtenLog2Op, AtenLog1pOp, AtenRsqrtOp,
+             AtenSqrtOp, AtenFloorOp, AtenPowTensorScalarOp, AtenLog2Op,
-             AtenDivScalarOp, AtenAbsOp, AtenReciprocalOp,
+             AtenLog1pOp, AtenRsqrtOp, AtenDivScalarOp, AtenAbsOp,
-             AtenBitwiseAndTensorOp, AtenGtScalarOp, AtenGeScalarOp,
+             AtenReciprocalOp, AtenBitwiseAndTensorOp, AtenGtScalarOp,
-             AtenEqScalarOp, AtenLtScalarOp, AtenLeScalarOp, AtenWhereSelfOp,
+             AtenGeScalarOp, AtenEqScalarOp, AtenLtScalarOp, AtenLeScalarOp,
-             AtenCeilOp, AtenGtTensorOp, AtenEqTensorOp, AtenLtTensorOp,
+             AtenWhereSelfOp, AtenCeilOp, AtenGtTensorOp, AtenEqTensorOp,
-             AtenSubScalarOp, AtenAddScalarOp, AtenThresholdOp,
+             AtenLtTensorOp, AtenSubScalarOp, AtenAddScalarOp, AtenThresholdOp,
              AtenThresholdBackwardOp, AtenCloneOp, AtenSinOp, AtenCosOp,
              AtenNeScalarOp, AtenNegOp, AtenMaskedFillScalarOp, AtenLogicalOrOp,
              AtenTriuOp>(op))

lib/Dialect/Torch/Transforms/RefineTypes.cpp

@@ -663,9 +663,9 @@ void TypeAnalysis::visitOperation(Operation *op,
   }
 
   // Dtype is always float32, except for bfloat16, float64 and nullptr.
-  if (isa<AtenTanhOp, AtenExpOp, AtenSinOp, AtenCosOp, AtenSigmoidOp,
+  if (isa<AtenTanhOp, AtenExpOp, AtenExpm1Op, AtenSinOp, AtenCosOp,
-          AtenReciprocalOp, AtenLogOp, AtenSqrtOp, AtenLog2Op, AtenLog1pOp,
+          AtenSigmoidOp, AtenReciprocalOp, AtenLogOp, AtenSqrtOp, AtenLog2Op,
-          AtenRsqrtOp, AtenErfOp, AtenSoftplusOp>(op)) {
+          AtenLog1pOp, AtenRsqrtOp, AtenErfOp, AtenSoftplusOp>(op)) {
     ValueKnowledge knowledge =
         ValueKnowledge::getTensorPessimisticValueState(op->getContext());
     Type dtype = operands[0]->getValue().dtype;

lib/Dialect/Torch/Transforms/ShapeLibrary.cpp

@@ -5337,6 +5337,10 @@ module {
     %0 = call @__torch__.torch.jit._shape_functions.unary(%arg0) : (!torch.list<int>) -> !torch.list<int>
     return %0 : !torch.list<int>
   }
+  func.func @"__torch_mlir_shape_fn.aten.expm1"(%arg0: !torch.list<int>) -> !torch.list<int> {
+    %0 = call @__torch__.torch.jit._shape_functions.unary(%arg0) : (!torch.list<int>) -> !torch.list<int>
+    return %0 : !torch.list<int>
+  }
   func.func @"__torch_mlir_shape_fn.aten.sin"(%arg0: !torch.list<int>) -> !torch.list<int> {
     %0 = call @__torch__.torch.jit._shape_functions.unary(%arg0) : (!torch.list<int>) -> !torch.list<int>
     return %0 : !torch.list<int>

python/torch_mlir/dialects/torch/importer/jit_ir/build_tools/shape_lib_gen.py

@@ -315,6 +315,9 @@ def aten〇silu(self: List[int]) -> List[int]:
 def aten〇exp(self: List[int]) -> List[int]:
     return upstream_shape_functions.unary(self)
 
+def aten〇expm1(self: List[int]) -> List[int]:
+    return upstream_shape_functions.unary(self)
+
 def aten〇sin(self: List[int]) -> List[int]:
     return upstream_shape_functions.unary(self)
 

python/torch_mlir/dialects/torch/importer/jit_ir/build_tools/torch_ods_gen.py

@@ -250,6 +250,7 @@ def emit_ops(emitter_td: TextEmitter, registry: Registry):
             "aten::silu : (Tensor) -> (Tensor)",
             "aten::sin : (Tensor) -> (Tensor)",
             "aten::exp : (Tensor) -> (Tensor)",
+            "aten::expm1 : (Tensor) -> (Tensor)",
             "aten::cos : (Tensor) -> (Tensor)",
             "aten::neg : (Tensor) -> (Tensor)",
             "aten::floor : (Tensor) -> (Tensor)",

python/torch_mlir_e2e_test/test_suite/elementwise.py

@@ -1528,6 +1528,50 @@ def ElementwiseExpIntModule_basic(module, tu: TestUtils):
 # ==============================================================================
 
 
+class ElementwiseExpm1Module(torch.nn.Module):
+
+    def __init__(self):
+        super().__init__()
+
+    @export
+    @annotate_args([
+        None,
+        ([-1, -1], torch.float32, True),
+    ])
+    def forward(self, a):
+        return torch.special.expm1(a)
+
+
+@register_test_case(module_factory=lambda: ElementwiseExpm1Module())
+def ElementwiseExpm1Module_basic(module, tu: TestUtils):
+    module.forward(tu.rand(3, 4))
+
+
+# ==============================================================================
+
+
+class ElementwiseExpm1IntModule(torch.nn.Module):
+
+    def __init__(self):
+        super().__init__()
+
+    @export
+    @annotate_args([
+        None,
+        ([-1, -1], torch.int32, True),
+    ])
+    def forward(self, a):
+        return torch.special.expm1(a)
+
+
+@register_test_case(module_factory=lambda: ElementwiseExpm1IntModule())
+def ElementwiseExpm1IntModule_basic(module, tu: TestUtils):
+    module.forward(torch.randint(1, 10, (3, 4), dtype=torch.int32))
+
+
+# ==============================================================================
+
+
 class ElementwiseSinModule(torch.nn.Module):
 
     def __init__(self):