How to clear cache (or force recompilation) in numba

Question

I have a fairly large codebase written in numba, and I have noticed that when the cache is enabled for a function calling another numba compiled function in another file, changes in the called function are not picked up when the called function is changed. The situation occurs when I have two files:

testfile2:

import numba

@numba.njit(cache=True)
def function1(x):
    return x * 10

testfile:

import numba
from tests import file1

@numba.njit(cache=True)
def function2(x, y):
    return y + file1.function1(x)

If in a jupyter notebook, I run the following:

# INSIDE JUPYTER NOTEBOOK
import sys
sys.path.insert(1, "path/to/files/")
from tests import testfile

testfile.function2(3, 4)
>>> 34   # good value

However, if I change then change testfile2 to the following:

import numba

@numba.njit(cache=True)
def function1(x):
    return x * 1

Then I restart the jupyter notebook kernel and rerun the notebook, I get the following

import sys
sys.path.insert(1, "path/to/files/")
from tests import testfile

testfile.function2(3, 4)
>>> 34   # bad value, should be 7

Importing both files into the notebook has no effect on the bad result. Also, setting cache=False only on function1 also has no effect. What does work is setting cache=False on all njit'ted functions, then restarting the kernel, then rerunning.

I believe that LLVM is probably inlining some of the called functions and then never checking them again.

I looked in the source and discovered there is a method that returns the cache object numba.caching.NullCache(), instantiated a cache object and ran the following:

cache = numba.caching.NullCache()
cache.flush()

Unfortunately that appears to have no effect.

Is there a numba environment setting, or another way I can manually clear all cached functions within a conda env? Or am I simply doing something wrong?

I am running numba 0.33 with Anaconda Python 3.6 on Mac OS X 10.12.3.

Update: killing all of the files in the `__pycache__` directory numba uses *does* seem to work. Not sure if there is a better way, however. — Greg Jennings, May 23 '17 at 10:40

score 8 · Accepted Answer · answered May 23 '17 at 12:21

I "solved" this with a hack solution after seeing Josh's answer, by creating a utility in the project method to kill off the cache.

There is probably a better way, but this works. I'm leaving the question open in case someone has a less hacky way of doing this.

import os


def kill_files(folder):
    for the_file in os.listdir(folder):
        file_path = os.path.join(folder, the_file)
        try:
            if os.path.isfile(file_path):
                os.unlink(file_path)
        except Exception as e:
            print("failed on filepath: %s" % file_path)


def kill_numba_cache():

    root_folder = os.path.realpath(__file__ + "/../../")

    for root, dirnames, filenames in os.walk(root_folder):
        for dirname in dirnames:
            if dirname == "__pycache__":
                try:
                    kill_files(root + "/" + dirname)
                except Exception as e:
                    print("failed on %s", root)

A couple years later, I haven't found a better way and I'm still using the above function without issue, so I'm marking it as the correct one. Anyone from the numba project who has a better way, let me know! — Greg Jennings, Jul 10 '19 at 18:13

score 6 · Answer 2 · answered May 23 '17 at 10:54

This is a bit of a hack, but it's something I've used before. If you put this function in the top-level of where your numba functions are (for this example, in testfile), it should recompile everything:

import inspect
import sys

def recompile_nb_code():
    this_module = sys.modules[__name__]
    module_members = inspect.getmembers(this_module)

    for member_name, member in module_members:
        if hasattr(member, 'recompile') and hasattr(member, 'inspect_llvm'):
            member.recompile()

and then call it from your jupyter notebook when you want to force a recompile. The caveat is that it only works on files in the module where this function is located and their dependencies. There might be another way to generalize it.

Thanks Josh. It didn't quite work for me because I have a large project with a lot of files and packages. But upvoted, because I your this idea to solve it with another "hack" solution, which I put below. — Greg Jennings, May 23 '17 at 12:17

J. Choi · Answer 3 · 2023-02-26T22:34:57.017

The official document of Numba recommends to remove the cache directory for clearing the cache [link].

The Numba cache is saved in these four directories [link]:

numba.config.CACHE_DIR
__pycache__
numba.misc.appdirs.user_cache_dir()
IPython.paths.get_ipython_cache_dir()

It is possible to find the Numba cache by searching *.nbi files [link].

I personally use the following two codes. The former one is referenced from Python3 project remove __pycache__ folders and .pyc files.

import pathlib
import shutil

_ = [shutil.rmtree(p) for p in pathlib.Path('.').rglob('__pycache__')]

import IPython
import shutil

path_parent = IPython.paths.get_ipython_cache_dir()
path_child = os.path.join(path_parent, 'numba_cache')

if path_parent:
    if os.path.isdir(path_child):
        shutil.rmtree(path_child)

How to clear cache (or force recompilation) in numba

3 Answers3

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