from __future__ import print_function, division, absolute_import from . import analysis, ir, transforms, utils class YieldPoint(object): def __init__(self, block, inst): assert isinstance(block, ir.Block) assert isinstance(inst, ir.Yield) self.block = block self.inst = inst self.live_vars = None self.weak_live_vars = None class GeneratorInfo(object): def __init__(self): # { index: YieldPoint } self.yield_points = {} # Ordered list of variable names self.state_vars = [] def get_yield_points(self): """ Return an iterable of YieldPoint instances. """ return self.yield_points.values() class VariableLifetime(object): """ For lazily building information of variable lifetime """ def __init__(self, blocks): self._blocks = blocks @utils.cached_property def cfg(self): return analysis.compute_cfg_from_blocks(self._blocks) @utils.cached_property def usedefs(self): return analysis.compute_use_defs(self._blocks) @utils.cached_property def livemap(self): return analysis.compute_live_map(self.cfg, self._blocks, self.usedefs.usemap, self.usedefs.defmap) @utils.cached_property def deadmaps(self): return analysis.compute_dead_maps(self.cfg, self._blocks, self.livemap, self.usedefs.defmap) # other packages that define new nodes add calls for inserting dels # format: {type:function} ir_extension_insert_dels = {} class PostProcessor(object): """ A post-processor for Numba IR. """ def __init__(self, func_ir): self.func_ir = func_ir def run(self): """ Run the following passes over Numba IR: - canonicalize the CFG - emit explicit `del` instructions for variables - compute lifetime of variables - compute generator info (if function is a generator function) """ self.func_ir.blocks = transforms.canonicalize_cfg(self.func_ir.blocks) vlt = VariableLifetime(self.func_ir.blocks) self.func_ir.variable_lifetime = vlt # Emit del nodes self._insert_var_dels() bev = analysis.compute_live_variables(vlt.cfg, self.func_ir.blocks, vlt.usedefs.defmap, vlt.deadmaps.combined) for offset, ir_block in self.func_ir.blocks.items(): self.func_ir.block_entry_vars[ir_block] = bev[offset] if self.func_ir.is_generator: self.func_ir.generator_info = GeneratorInfo() self._compute_generator_info() else: self.func_ir.generator_info = None def _populate_generator_info(self): """ Fill `index` for the Yield instruction and create YieldPoints. """ dct = self.func_ir.generator_info.yield_points assert not dct, 'rerunning _populate_generator_info' for block in self.func_ir.blocks.values(): for inst in block.body: if isinstance(inst, ir.Assign): yieldinst = inst.value if isinstance(yieldinst, ir.Yield): index = len(dct) + 1 yieldinst.index = index yp = YieldPoint(block, yieldinst) dct[yieldinst.index] = yp def _compute_generator_info(self): """ Compute the generator's state variables as the union of live variables at all yield points. """ self._populate_generator_info() gi = self.func_ir.generator_info for yp in gi.get_yield_points(): live_vars = set(self.func_ir.get_block_entry_vars(yp.block)) weak_live_vars = set() stmts = iter(yp.block.body) for stmt in stmts: if isinstance(stmt, ir.Assign): if stmt.value is yp.inst: break live_vars.add(stmt.target.name) elif isinstance(stmt, ir.Del): live_vars.remove(stmt.value) else: assert 0, "couldn't find yield point" # Try to optimize out any live vars that are deleted immediately # after the yield point. for stmt in stmts: if isinstance(stmt, ir.Del): name = stmt.value if name in live_vars: live_vars.remove(name) weak_live_vars.add(name) else: break yp.live_vars = live_vars yp.weak_live_vars = weak_live_vars st = set() for yp in gi.get_yield_points(): st |= yp.live_vars st |= yp.weak_live_vars gi.state_vars = sorted(st) def _insert_var_dels(self): """ Insert del statements for each variable. Returns a 2-tuple of (variable definition map, variable deletion map) which indicates variables defined and deleted in each block. The algorithm avoids relying on explicit knowledge on loops and distinguish between variables that are defined locally vs variables that come from incoming blocks. We start with simple usage (variable reference) and definition (variable creation) maps on each block. Propagate the liveness info to predecessor blocks until it stabilize, at which point we know which variables must exist before entering each block. Then, we compute the end of variable lives and insert del statements accordingly. Variables are deleted after the last use. Variable referenced by terminators (e.g. conditional branch and return) are deleted by the successors or the caller. """ vlt = self.func_ir.variable_lifetime self._patch_var_dels(vlt.deadmaps.internal, vlt.deadmaps.escaping) def _patch_var_dels(self, internal_dead_map, escaping_dead_map): """ Insert delete in each block """ for offset, ir_block in self.func_ir.blocks.items(): # for each internal var, insert delete after the last use internal_dead_set = internal_dead_map[offset].copy() delete_pts = [] # for each statement in reverse order for stmt in reversed(ir_block.body[:-1]): # internal vars that are used here live_set = set(v.name for v in stmt.list_vars()) dead_set = live_set & internal_dead_set for T, def_func in ir_extension_insert_dels.items(): if isinstance(stmt, T): done_dels = def_func(stmt, dead_set) dead_set -= done_dels internal_dead_set -= done_dels # used here but not afterwards delete_pts.append((stmt, dead_set)) internal_dead_set -= dead_set # rewrite body and insert dels body = [] lastloc = ir_block.loc for stmt, delete_set in reversed(delete_pts): lastloc = stmt.loc # Ignore dels (assuming no user inserted deletes) if not isinstance(stmt, ir.Del): body.append(stmt) # note: the reverse sort is not necessary for correctness # it is just to minimize changes to test for now for var_name in sorted(delete_set, reverse=True): body.append(ir.Del(var_name, loc=lastloc)) body.append(ir_block.body[-1]) # terminator ir_block.body = body # vars to delete at the start escape_dead_set = escaping_dead_map[offset] for var_name in sorted(escape_dead_set): ir_block.prepend(ir.Del(var_name, loc=ir_block.body[0].loc))