ai-content-maker/.venv/Lib/site-packages/numba/core/environment.py

65 lines
1.6 KiB
Python

import weakref
import importlib
from numba import _dynfunc
class Environment(_dynfunc.Environment):
"""Stores globals and constant pyobjects for runtime.
It is often needed to convert b/w nopython objects and pyobjects.
"""
__slots__ = ('env_name', '__weakref__')
# A weak-value dictionary to store live environment with env_name as the
# key.
_memo = weakref.WeakValueDictionary()
@classmethod
def from_fndesc(cls, fndesc):
try:
# Avoid creating new Env
return cls._memo[fndesc.env_name]
except KeyError:
inst = cls(fndesc.lookup_globals())
inst.env_name = fndesc.env_name
cls._memo[fndesc.env_name] = inst
return inst
def can_cache(self):
is_dyn = '__name__' not in self.globals
return not is_dyn
def __reduce__(self):
return _rebuild_env, (
self.globals.get('__name__'),
self.consts,
self.env_name,
)
def __del__(self):
return
def __repr__(self):
return f"<Environment {self.env_name!r} >"
def _rebuild_env(modname, consts, env_name):
env = lookup_environment(env_name)
if env is not None:
return env
mod = importlib.import_module(modname)
env = Environment(mod.__dict__)
env.consts[:] = consts
env.env_name = env_name
# Cache loaded object
Environment._memo[env_name] = env
return env
def lookup_environment(env_name):
"""Returns the Environment object for the given name;
or None if not found
"""
return Environment._memo.get(env_name)