torch-mlir/include/npcomp/Dialect/Torch/IR/GeneratedPrimOps.td

//===-------------------------------------------------------*- tablegen -*-===//
//
// This file is licensed under the Apache License v2.0 with LLVM Exceptions.
// See https://llvm.org/LICENSE.txt for license information.
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
//
// Operation summaries and descriptions were systematically derived from public
// API docstrings and are licensed accordingly:
//   https://github.com/pytorch/pytorch/blob/master/LICENSE
//===----------------------------------------------------------------------===//
//
// This file is automatically generated.  Please do not edit.
// Generated via:
//   python -m torch_mlir_utils.codegen.torch_ods_gen
//
//===----------------------------------------------------------------------===//

def Torch_PrimLayoutOp : Torch_Op<"prim.layout", [
    AllowsTypeRefinement,
    HasValueSemantics
  ]> {
  let summary = "Generated op for `prim::layout : (Tensor) -> (int)`";
  let arguments = (ins
    AnyTorchTensorType:$a
  );
  let results = (outs
    AnyTorchIntType:$result
  );
  let assemblyFormat = "$a attr-dict `:` type($a) `->` type($result)";
}

def Torch_PrimTupleIndexOp : Torch_Op<"prim.TupleIndex", [
    AllowsTypeRefinement,
    HasValueSemantics
  ]> {
  let summary = "Generated op for `prim::TupleIndex : (Any, int) -> (Any)`";
  let arguments = (ins
    AnyTorchType:$tup,
    AnyTorchIntType:$i
  );
  let results = (outs
    AnyTorchType:$result
  );
  let assemblyFormat = "$tup `,` $i attr-dict `:` type($tup) `,` type($i) `->` type($result)";
}

def Torch_PrimDeviceOp : Torch_Op<"prim.device", [
    AllowsTypeRefinement,
    HasValueSemantics
  ]> {
  let summary = "Generated op for `prim::device : (Tensor) -> (Device)`";
  let arguments = (ins
    AnyTorchTensorType:$a
  );
  let results = (outs
    Torch_DeviceType:$result
  );
  let assemblyFormat = "$a attr-dict `:` type($a) `->` type($result)";
}

def Torch_PrimDtypeOp : Torch_Op<"prim.dtype", [
    AllowsTypeRefinement,
    HasValueSemantics
  ]> {
  let summary = "Generated op for `prim::dtype : (Tensor) -> (int)`";
  let arguments = (ins
    AnyTorchTensorType:$a
  );
  let results = (outs
    AnyTorchIntType:$result
  );
  let assemblyFormat = "$a attr-dict `:` type($a) `->` type($result)";
}

def Torch_PrimTupleUnpackOp : Torch_Op<"prim.TupleUnpack", [
    AllowsTypeRefinement
  ]> {
  let summary = "Generated op for `prim::TupleUnpack : (Any) -> (...)`";
  let arguments = (ins
    AnyTorchType:$tup
  );
  let results = (outs
    Variadic<AnyTorchType>:$results
  );
  let assemblyFormat = "$tup attr-dict `:` type($tup) `->` type($results)";
}

def Torch_PrimNumToTensorScalarOp : Torch_Op<"prim.NumToTensor.Scalar", [
    AllowsTypeRefinement,
    HasValueSemantics
  ]> {
  let summary = "Generated op for `prim::NumToTensor.Scalar : (Scalar) -> (Tensor)`";
  let arguments = (ins
    AnyTorchScalarType:$a
  );
  let results = (outs
    AnyTorchTensorType:$result
  );
  let assemblyFormat = "$a attr-dict `:` type($a) `->` type($result)";
}

def Torch_PrimMinSelfIntOp : Torch_Op<"prim.min.self_int", [
    AllowsTypeRefinement,
    HasValueSemantics
  ]> {
  let summary = "Generated op for `prim::min.self_int : (int[]) -> (int)`";
  let arguments = (ins
    AnyTorchIntListType:$self
  );
  let results = (outs
    AnyTorchIntType:$result
  );
  let assemblyFormat = "$self attr-dict `:` type($self) `->` type($result)";
}

def Torch_PrimMinIntOp : Torch_Op<"prim.min.int", [
    AllowsTypeRefinement,
    HasValueSemantics
  ]> {
  let summary = "Generated op for `prim::min.int : (int, int) -> (int)`";
  let arguments = (ins
    AnyTorchIntType:$a,
    AnyTorchIntType:$b
  );
  let results = (outs
    AnyTorchIntType:$result
  );
  let assemblyFormat = "$a `,` $b attr-dict `:` type($a) `,` type($b) `->` type($result)";
}

def Torch_PrimMaxSelfIntOp : Torch_Op<"prim.max.self_int", [
    AllowsTypeRefinement,
    HasValueSemantics
  ]> {
  let summary = "Generated op for `prim::max.self_int : (int[]) -> (int)`";
  let arguments = (ins
    AnyTorchIntListType:$self
  );
  let results = (outs
    AnyTorchIntType:$result
  );
  let assemblyFormat = "$self attr-dict `:` type($self) `->` type($result)";
}

def Torch_PrimMaxIntOp : Torch_Op<"prim.max.int", [
    AllowsTypeRefinement,
    HasValueSemantics
  ]> {
  let summary = "Generated op for `prim::max.int : (int, int) -> (int)`";
  let arguments = (ins
    AnyTorchIntType:$a,
    AnyTorchIntType:$b
  );
  let results = (outs
    AnyTorchIntType:$result
  );
  let assemblyFormat = "$a `,` $b attr-dict `:` type($a) `,` type($b) `->` type($result)";
}

def Torch_PrimRaiseExceptionOp : Torch_Op<"prim.RaiseException", [
    AllowsTypeRefinement,
    HasValueSemantics
  ]> {
  let summary = "Generated op for `prim::RaiseException : (str) -> ()`";
  let arguments = (ins
    Basicpy_BytesType:$msg
  );
  let results = (outs
  );
  let assemblyFormat = "$msg attr-dict `:` type($msg)";
}

def Torch_PrimUninitializedOp : Torch_Op<"prim.Uninitialized", [
    AllowsTypeRefinement,
    HasValueSemantics
  ]> {
  let summary = "Generated op for `prim::Uninitialized : () -> (Any)`";
  let arguments = (ins
  );
  let results = (outs
    AnyTorchType:$result
  );
  let assemblyFormat = " attr-dict `:` type($result)";
}

def Torch_PrimUncheckedCastOp : Torch_Op<"prim.unchecked_cast", [
    AllowsTypeRefinement,
    HasValueSemantics
  ]> {
  let summary = "Generated op for `prim::unchecked_cast : (t) -> (t)`";
  let arguments = (ins
    AnyTorchType:$x
  );
  let results = (outs
    AnyTorchType:$result
  );
  let assemblyFormat = "$x attr-dict `:` type($x) `->` type($result)";
}

def Torch_PrimPrintOp : Torch_Op<"prim.Print", [
    AllowsTypeRefinement
  ]> {
  let summary = "Generated op for `prim::Print : (...) -> ()`";
  let arguments = (ins
    Variadic<AnyTorchType>:$operands
  );
  let results = (outs
  );
  let assemblyFormat = "`(` $operands `)` attr-dict `:` type($operands)";
}