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torch-mlir/include/npcomp/Dialect/Numpy/IR/NumpyOps.h

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Add stub numpy dialect.
2020-04-27 08:20:58 +08:00
//===- NumpyOps.h - Core numpy dialect ops ----------------------*- C++ -*-===//
//
// 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
//
//===----------------------------------------------------------------------===//
Move Basicpy and Numpy dialect IR to IR/ folder.
2020-06-10 10:22:24 +08:00
#ifndef NPCOMP_DIALECT_NUMPY_IR_NUMPY_OPS_H
#define NPCOMP_DIALECT_NUMPY_IR_NUMPY_OPS_H
Add stub numpy dialect.
2020-04-27 08:20:58 +08:00
Add builtin_ufunc and generic_ufunc ops.
2020-04-29 11:32:49 +08:00
#include "mlir/IR/Attributes.h"
Bump llvm-project to 444822d77a7fea28aa49edf24533c987efa1b2ee Fixes: - renames StandardTypes -> BuiltinTypes - std.extract_element -> tensor.extract
2020-12-12 06:43:38 +08:00
#include "mlir/IR/BuiltinTypes.h"
Add stub numpy dialect.
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#include "mlir/IR/Dialect.h"
Add builtin_ufunc and generic_ufunc ops.
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#include "mlir/IR/FunctionSupport.h"
Add stub numpy dialect.
2020-04-27 08:20:58 +08:00
#include "mlir/IR/OpDefinition.h"
Add builtin_ufunc and generic_ufunc ops.
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#include "mlir/IR/SymbolTable.h"
Add torch-adjust-calling-conventions pass. This pass incorporates torch.type_bound info and also removes NoneType returns (eventually it will rewrite tuple types too, but can't yet because !basicpy.TupleType doesn't track element types). Recommend looking at adjust-calling-conventions.mlir first to see what it is doing, and holding your nose for the implementation of the pass. I decided to implement this with the conversion framework, because it gives us *some* goodies for type conversion -- mainly avoiding large amounts of tricky RAUW dances. Unfortunately, the conversion framework isn't a perfect fit for a couple reasons: - the incorporation of torch.type_bound is a context-sensitive rewrite (requires looking at the arg attr, not just the type). - NoneType conversion is 1->0, which requires some special handling - (not implemented yet) 1->N tuple type conversions require special handling. It's a little bit scary, but on balance doing it the other way would have its own downsides.
2021-04-02 08:36:18 +08:00
#include "mlir/Interfaces/CastInterfaces.h"
Update llvm-project to 753a21928413f8a7e76978cb1354e09150e114e0
2020-05-22 04:09:06 +08:00
#include "mlir/Interfaces/SideEffectInterfaces.h"
NFC: Move CPA typing analysis down a directory.
2020-07-05 07:40:02 +08:00
#include "npcomp/Typing/Analysis/CPA/Interfaces.h"
Add stub numpy dialect.
2020-04-27 08:20:58 +08:00
#define GET_OP_CLASSES
Move Basicpy and Numpy dialect IR to IR/ folder.
2020-06-10 10:22:24 +08:00
#include "npcomp/Dialect/Numpy/IR/NumpyOps.h.inc"
Add stub numpy dialect.
2020-04-27 08:20:58 +08:00
Move Basicpy and Numpy dialect IR to IR/ folder.
2020-06-10 10:22:24 +08:00
#endif // NPCOMP_DIALECT_NUMPY_IR_NUMPY_OPS_H