Tianqi Chen
275114b327
## Summary - Make `PrimExpr` a typed C++ view over `Expr` values whose `ExprNode::ty` is `PrimType`, instead of using a separate runtime node class as the proof of primitive-ness. - Use the shared `ir::Call` node for Relax, TIRX, and primitive-valued calls, while keeping primitive-only APIs explicit at their semantic boundaries. - Keep Python on the general `Expr` surface for primitive-typed values so `isinstance` behavior does not imply a nominal primitive-expression subclass. ## Design Rationale The main advantage of this change is that common expression nodes such as `Call` can be unified without specializing each one to `PrimType`. A single `ir::Call` can represent a Relax tensor call, a Relax scalar call, or a primitive-valued intrinsic call; the result type stored in `ExprNode::ty` determines whether that particular value can be viewed as `PrimExpr`. This keeps the IR node hierarchy focused on expression structure rather than result-type categories. Nodes that are intrinsically primitive, such as integer and floating-point literals or TIRX primitive operators, still have strongly typed C++ APIs and data structures. General nodes whose result type may vary, such as `Call`, remain general `Expr` nodes and are narrowed to `PrimExpr` only where primitive-only semantics are required. The PR also keeps the compatibility surface practical: C++ primitive-only APIs continue to accept `PrimExpr`, Python exposes a compatibility predicate for checking the primitive typed category, and visitors/printers use one natural `Call` path rather than duplicating Relax and primitive call handling. Missing expression types are represented explicitly with `Type::Missing()` so constructors can leave type inference to later analysis without relying on nullable `Type` values.
161 lines
4.4 KiB
Python
161 lines
4.4 KiB
Python
# Licensed to the Apache Software Foundation (ASF) under one
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# or more contributor license agreements. See the NOTICE file
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# distributed with this work for additional information
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# regarding copyright ownership. The ASF licenses this file
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# to you under the Apache License, Version 2.0 (the
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# "License"); you may not use this file except in compliance
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# with the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing,
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# software distributed under the License is distributed on an
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# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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# KIND, either express or implied. See the License for the
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# specific language governing permissions and limitations
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# under the License.
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"""Wrapping existing analysis utils."""
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# pylint: disable=invalid-name
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from tvm.ir import IRModule
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from tvm.tirx.expr import Var
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from tvm.tirx.stmt import Expr
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from .. import Stmt
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from ..function import PrimFunc
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from . import _ffi_api
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def expr_deep_equal(lhs: Expr, rhs: Expr) -> bool:
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"""Deeply compare two nested expressions.
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Parameters
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----------
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lhs : Expr
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The left operand.
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rhs : Expr
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The right operand.
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Returns
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-------
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result : bool
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The comparison result
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Note
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----
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This function does not remap variable bindings, it will not
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return true for (let x = 1 in x + 1) vs (let y = 1 in y + 1), unless x.same_as(y).
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Use py:func:`tvm_ffi.structural_equal` to handle structural variable remapping.
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Due to the restriction of not remapping variables, this function can run
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faster than StructuralEqual and can be used as a utility function during arithmetic
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simplifications.
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Always consider py:func:`tvm_ffi.structural_equal` first, which handles
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the structural remapping.
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See Also
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--------
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tvm_ffi.structural_equal
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"""
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return _ffi_api.expr_deep_equal(lhs, rhs) # type: ignore
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def verify_ssa(func: PrimFunc) -> bool:
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"""Verify if the func is in SSA form.
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Parameters
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----------
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func: tvm.tirx.PrimFunc
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The module to be verified.
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Returns
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-------
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result : bool
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The result of verification.
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"""
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return _ffi_api.verify_ssa(func) # type: ignore
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def verify_memory(func: PrimFunc) -> bool:
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"""Verify if func contains illegal host side direct memory access.
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Parameters
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----------
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func: tvm.tirx.PrimFunc
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The module to be verified.
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Returns
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-------
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result : bool
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The result of verification.
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"""
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return _ffi_api.verify_memory(func) # type: ignore
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def undefined_vars(node: Stmt | Expr, defs: list[Var] | None = None) -> list[Var]:
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"""Find undefined vars in a TIR statement or expression.
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Parameters
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----------
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node: Union[Stmt, Expr]
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The TIR statement or expression to be checked.
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defs: Optional[List[Var]]
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The vars that is defined
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Returns
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-------
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result : List[Var]
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The undefined vars.
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"""
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defs = defs or []
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return _ffi_api.UndefinedVars(node, defs) # type: ignore # pylint: disable=no-member
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def verify_well_formed(obj: PrimFunc | IRModule, assert_mode: bool = True) -> bool:
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"""Verify if the given TIR is well-formed. The verification includes:
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- Check if expressions not contain vars that is defined outside the block.
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Parameters
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----------
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obj: Union[tvm.tirx.PrimFunc, tvm.ir.IRModule]
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The function or module to be verified.
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assert_mode: bool
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The indicator if it raises an error when the function is not well-formed.
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Returns
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-------
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result: bool
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Whether it is a well-formed TIR function.
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"""
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return _ffi_api.VerifyWellFormed(obj, assert_mode) # type: ignore # pylint: disable=no-member
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def verify_tirx_well_formed(
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obj: PrimFunc | IRModule, assert_mode: bool = True, device_func: bool = False
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) -> bool:
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"""Verify if the given TIRX is well-formed.
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Parameters
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----------
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obj: Union[tvm.tirx.PrimFunc, tvm.ir.IRModule]
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The function or module to be verified.
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assert_mode: bool
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The indicator if it raises an error when the function is not well-formed.
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device_func: bool
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The indicator if it is a device function.
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Returns
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-------
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result: bool
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Whether it is a well-formed TIRX function.
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"""
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return _ffi_api.VerifyTIRxWellFormed(obj, assert_mode, device_func) # type: ignore # pylint: disable=no-member
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