torch-mlir/include/npcomp/Dialect/Numpy/NumpyDialect.td

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//===- NumpyDialect.td - Core numpy dialect ----------------*- 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
//
//===----------------------------------------------------------------------===//
#ifndef NPCOMP_DIALECT_NUMPY_NUMPY_DIALECT
#define NPCOMP_DIALECT_NUMPY_NUMPY_DIALECT
include "mlir/IR/OpBase.td"
include "npcomp/Dialect/Basicpy/BasicpyDialect.td"
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//===----------------------------------------------------------------------===//
// Dialect definition
//===----------------------------------------------------------------------===//
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def Numpy_Dialect : Dialect {
let name = "numpy";
let summary = "Core numpy dialect";
let description = [{
Dialect of types and core numpy ops and abstractions.
}];
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let cppNamespace = "Numpy";
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}
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//===----------------------------------------------------------------------===//
// Op templates
//===----------------------------------------------------------------------===//
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class Numpy_Op<string mnemonic, list<OpTrait> traits = []> :
Op<Numpy_Dialect, mnemonic, traits> {
let parser = [{ return parse$cppClass(parser, &result); }];
let printer = [{ return print$cppClass(p, *this); }];
}
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//===----------------------------------------------------------------------===//
// Dialect types
//===----------------------------------------------------------------------===//
def Numpy_AnyDtype : DialectType<Numpy_Dialect,
CPred<"$_self.isa<::mlir::NPCOMP::Numpy::AnyDtypeType>()">, "any dtype">,
BuildableType<"$_builder.getType<::mlir::NPCOMP::Numpy::AnyDtypeType>()"> {
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let typeDescription = [{
Placeholder for an unknown dtype in a tensor.
}];
}
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//===----------------------------------------------------------------------===//
// Type predicates
//===----------------------------------------------------------------------===//
// Any type, at any stage of analysis that can represent a numpy array.
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def Numpy_AnyArray : TensorOf<[AnyType]>;
def Numpy_SliceTupleElement : AnyTypeOf<[
// Supports both "Index Arrays" and "Boolean mask index arrays".
Numpy_AnyArray,
// Indicates that an axis should be added (np.newaxis == None).
Basicpy_NoneType,
// Indicates that intervening axes should be preserved.
Basicpy_EllipsisType,
// A discrete numeric index (represented as IndexType so that a proper
// width can be target dependent).
Index,
// A generalized slice object.
Basicpy_SliceSlotObjectType,
], "types that are legal elements of a __getitem__ tuple operating on arrays">;
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#endif // NPCOMP_DIALECT_NUMPY_NUMPY_DIALECT