[bug] Dynamo graph break when using pyton module heapq (manipulates with lists), although succeeds when placing heapq.py near the test script
#106885
Labels
low priority
We're unlikely to get around to doing this in the near future
triaged
This issue has been looked at a team member, and triaged and prioritized into an appropriate module
Comments
janeyx99
added
triaged
|
Out of curiosity, have you seen heaps used in model code - curious what kinds of applications you're thinking of |
|
I have my own reimpl of selective search, which is an iterative graph merging procedure and has a kind of tight Python loop. So I was wondering if Dynamo can compile the whole thing and approach C++ in loop codegen :) Or you might want to have Dikjstra / Prim algorithms as well |
anijain2305
added
the
low priority
|
It seems that dynamo does not want to trace into Python stdlib's If I download Important I commented at the bottom of the file # If available, use C implementation
#try:
# from _heapq import *
#except ImportError:
# pass
#try:
# from _heapq import _heapreplace_max
#except ImportError:
# pass
#try:
# from _heapq import _heapify_max
#except ImportError:
# pass
#try:
# from _heapq import _heappop_max
#except ImportError:
# pass
#
#
#if __name__ == "__main__":
#
# import doctest # pragma: no cover
# print(doctest.testmod()) # pragma: no coverHow could we make the graph capture dynamic? E.g. so that |
|
E.g. this at least not breaks in regular Python: import heapq
import torch
# @torch.compile(fullgraph=True)
def program(x):
h = []
heapq.heappush(h, x)
val = heapq.heappop(h)
return val * torch.randn(10)
program(torch.tensor(1))import heapq
import torch
@torch.compile(fullgraph=True)
def program(x):
h = []
heapq.heappush(h, x)
val = heapq.heappop(h)
return val * torch.randn(10)
program(torch.tensor(1))produces |
vadimkantorov
changed the title
heapq (manipulates with lists)heapq (manipulates with lists), although succeeds when placing heapq.py near the test script
|
any updates? does it work in eager mode? |
|
I'll check, but for scalars it should work, yeah (as comparisons should work). Even with torch.compile it seems that it might work if heapq.py is copied to be near the script. It breaks straight up if heapq is used from the system library - and this is strange... |
anijain2305
added
low priority
|
@anijain2305 I would say that this is still a |
|
I ran into this today while working on a PyTorch implementation of farthest-first traversal. |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
馃悰 Describe the bug
OP: https://discuss.pytorch.org/t/is-heapq-module-supported-for-compilation-by-dynamo/185863:
heapqis a standard python's module useful for priority queue loops for Dijkstra-like algos:@msaroufim: @voznesenskym on github might say this is a good dynamo starter task XD
Versions
N/A
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @Xia-Weiwen @wenzhe-nrv @jiayisunx @chenyang78 @aakhundov @kadeng @anijain2305 @ipiszy
The text was updated successfully, but these errors were encountered: