DriverTrac/venv/lib/python3.12/site-packages/jaxlib/mlir/dialects/scf.py

257 lines
7.9 KiB
Python
Executable File

# Part of the LLVM Project, 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
from ._scf_ops_gen import *
from ._scf_ops_gen import _Dialect
from .arith import constant
try:
from ..ir import *
from ._ods_common import (
get_op_result_or_value as _get_op_result_or_value,
get_op_results_or_values as _get_op_results_or_values,
_cext as _ods_cext,
)
except ImportError as e:
raise RuntimeError("Error loading imports from extension module") from e
from typing import List, Optional, Sequence, Tuple, Union
@_ods_cext.register_operation(_Dialect, replace=True)
class ForOp(ForOp):
"""Specialization for the SCF for op class."""
def __init__(
self,
lower_bound,
upper_bound,
step,
iter_args: Optional[Union[Operation, OpView, Sequence[Value]]] = None,
*,
loc=None,
ip=None,
):
"""Creates an SCF `for` operation.
- `lower_bound` is the value to use as lower bound of the loop.
- `upper_bound` is the value to use as upper bound of the loop.
- `step` is the value to use as loop step.
- `iter_args` is a list of additional loop-carried arguments or an operation
producing them as results.
"""
if iter_args is None:
iter_args = []
iter_args = _get_op_results_or_values(iter_args)
results = [arg.type for arg in iter_args]
super().__init__(
results, lower_bound, upper_bound, step, iter_args, loc=loc, ip=ip
)
self.regions[0].blocks.append(self.operands[0].type, *results)
@property
def body(self):
"""Returns the body (block) of the loop."""
return self.regions[0].blocks[0]
@property
def induction_variable(self):
"""Returns the induction variable of the loop."""
return self.body.arguments[0]
@property
def inner_iter_args(self):
"""Returns the loop-carried arguments usable within the loop.
To obtain the loop-carried operands, use `iter_args`.
"""
return self.body.arguments[1:]
def _dispatch_index_op_fold_results(
ofrs: Sequence[Union[Operation, OpView, Value, int]],
) -> Tuple[List[Value], List[int]]:
"""`mlir::dispatchIndexOpFoldResults`"""
dynamic_vals = []
static_vals = []
for ofr in ofrs:
if isinstance(ofr, (Operation, OpView, Value)):
val = _get_op_result_or_value(ofr)
dynamic_vals.append(val)
static_vals.append(ShapedType.get_dynamic_size())
else:
static_vals.append(ofr)
return dynamic_vals, static_vals
@_ods_cext.register_operation(_Dialect, replace=True)
class ForallOp(ForallOp):
"""Specialization for the SCF forall op class."""
def __init__(
self,
lower_bounds: Sequence[Union[Operation, OpView, Value, int]],
upper_bounds: Sequence[Union[Operation, OpView, Value, int]],
steps: Sequence[Union[Value, int]],
shared_outs: Optional[Union[Operation, OpView, Sequence[Value]]] = None,
*,
mapping=None,
loc=None,
ip=None,
):
"""Creates an SCF `forall` operation.
- `lower_bounds` are the values to use as lower bounds of the loop.
- `upper_bounds` are the values to use as upper bounds of the loop.
- `steps` are the values to use as loop steps.
- `shared_outs` is a list of additional loop-carried arguments or an operation
producing them as results.
"""
assert (
len(lower_bounds) == len(upper_bounds) == len(steps)
), "Mismatch in length of lower bounds, upper bounds, and steps"
if shared_outs is None:
shared_outs = []
shared_outs = _get_op_results_or_values(shared_outs)
dynamic_lbs, static_lbs = _dispatch_index_op_fold_results(lower_bounds)
dynamic_ubs, static_ubs = _dispatch_index_op_fold_results(upper_bounds)
dynamic_steps, static_steps = _dispatch_index_op_fold_results(steps)
results = [arg.type for arg in shared_outs]
super().__init__(
results,
dynamic_lbs,
dynamic_ubs,
dynamic_steps,
static_lbs,
static_ubs,
static_steps,
shared_outs,
mapping=mapping,
loc=loc,
ip=ip,
)
rank = len(static_lbs)
iv_types = [IndexType.get()] * rank
self.regions[0].blocks.append(*iv_types, *results)
@property
def body(self) -> Block:
"""Returns the body (block) of the loop."""
return self.regions[0].blocks[0]
@property
def rank(self) -> int:
"""Returns the number of induction variables the loop has."""
return len(self.staticLowerBound)
@property
def induction_variables(self) -> BlockArgumentList:
"""Returns the induction variables usable within the loop."""
return self.body.arguments[: self.rank]
@property
def inner_iter_args(self) -> BlockArgumentList:
"""Returns the loop-carried arguments usable within the loop.
To obtain the loop-carried operands, use `iter_args`.
"""
return self.body.arguments[self.rank :]
def terminator(self) -> InParallelOp:
"""
Returns the loop terminator if it exists.
Otherwise, creates a new one.
"""
ops = self.body.operations
with InsertionPoint(self.body):
if not ops:
return InParallelOp()
last = ops[len(ops) - 1]
return last if isinstance(last, InParallelOp) else InParallelOp()
@_ods_cext.register_operation(_Dialect, replace=True)
class InParallelOp(InParallelOp):
"""Specialization of the SCF forall.in_parallel op class."""
def __init__(self, loc=None, ip=None):
super().__init__(loc=loc, ip=ip)
self.region.blocks.append()
@property
def block(self) -> Block:
return self.region.blocks[0]
@_ods_cext.register_operation(_Dialect, replace=True)
class IfOp(IfOp):
"""Specialization for the SCF if op class."""
def __init__(self, cond, results_=None, *, hasElse=False, loc=None, ip=None):
"""Creates an SCF `if` operation.
- `cond` is a MLIR value of 'i1' type to determine which regions of code will be executed.
- `hasElse` determines whether the if operation has the else branch.
"""
if results_ is None:
results_ = []
operands = []
operands.append(cond)
results = []
results.extend(results_)
super().__init__(results, cond, loc=loc, ip=ip)
self.regions[0].blocks.append(*[])
if hasElse:
self.regions[1].blocks.append(*[])
@property
def then_block(self):
"""Returns the then block of the if operation."""
return self.regions[0].blocks[0]
@property
def else_block(self):
"""Returns the else block of the if operation."""
return self.regions[1].blocks[0]
def for_(
start,
stop=None,
step=None,
iter_args: Optional[Sequence[Value]] = None,
*,
loc=None,
ip=None,
):
if step is None:
step = 1
if stop is None:
stop = start
start = 0
params = [start, stop, step]
for i, p in enumerate(params):
if isinstance(p, int):
p = constant(IndexType.get(), p)
elif isinstance(p, float):
raise ValueError(f"{p=} must be int.")
params[i] = p
start, stop, step = params
for_op = ForOp(start, stop, step, iter_args, loc=loc, ip=ip)
iv = for_op.induction_variable
iter_args = tuple(for_op.inner_iter_args)
with InsertionPoint(for_op.body):
if len(iter_args) > 1:
yield iv, iter_args, for_op.results
elif len(iter_args) == 1:
yield iv, iter_args[0], for_op.results[0]
else:
yield iv