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https://github.com/zebrajr/pytorch.git
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e836ee1955
---- - We now record on CacheEntry what the compile id that populated it was, so now we can say why a specific frame was rejected - Add structured log for recompiles under name artifact "recompile_reasons". As it stands, it's not terribly structured, but this was the easiest thing I could do to start - Slightly reformat multi-reason printing; since we only report one guard failure seems better to have it as a single line Example output: ``` V0703 10:34:13.273000 140345997743104 torch/_dynamo/guards.py:2590] [0/1] [__recompiles] Recompiling function f in /data/users/ezyang/a/pytorch/b.py:3 V0703 10:34:13.273000 140345997743104 torch/_dynamo/guards.py:2590] [0/1] [__recompiles] triggered by the following guard failure(s): V0703 10:34:13.273000 140345997743104 torch/_dynamo/guards.py:2590] [0/1] [__recompiles] - 0/0: tensor 'L['x']' size mismatch at index 0. expected 4, actual 5 ``` Signed-off-by: Edward Z. Yang <ezyang@meta.com> Pull Request resolved: https://github.com/pytorch/pytorch/pull/130043 Approved by: https://github.com/anijain2305
129 lines
3.9 KiB
Python
129 lines
3.9 KiB
Python
# Owner(s): ["module: dynamo"]
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import torch
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import torch._dynamo.test_case
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from torch._guards import CompileId
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def target_with_varkwargs(arg1, /, positional_only_arg, *, keyword_only_arg, **kwargs):
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local = 1
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return {
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"local": local,
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"arg1": arg1,
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"positional_only_arg": positional_only_arg,
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"keyword_only_arg": keyword_only_arg,
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"kwargs": kwargs,
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}
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def varkwargs_code1(arg1, /, positional_only_arg, *, keyword_only_arg, **kwargs):
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# remove a local variable: local = 1
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return {
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"local": 1,
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"arg1": arg1,
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"positional_only_arg": positional_only_arg,
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"keyword_only_arg": keyword_only_arg,
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"kwargs": kwargs,
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}
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def varkwargs_code2(arg1, /, positional_only_arg, *, keyword_only_arg, **kwargs):
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# introduce a local variable
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local1 = 0
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local2 = 1
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return {
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"local": local1 + local2,
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"arg1": arg1,
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"positional_only_arg": positional_only_arg,
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"keyword_only_arg": keyword_only_arg,
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"kwargs": kwargs,
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}
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def target_with_varargs(arg1, /, positional_only_arg, *varargs, **kwargs):
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local = 1
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return {
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"local": local,
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"arg1": arg1,
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"positional_only_arg": positional_only_arg,
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"varargs": varargs,
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"kwargs": kwargs,
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}
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def varargs_code1(arg1, /, positional_only_arg, *varargs, **kwargs):
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# remove a local variable: local = 1
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return {
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"local": 1,
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"arg1": arg1,
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"positional_only_arg": positional_only_arg,
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"varargs": varargs,
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"kwargs": kwargs,
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}
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def varargs_code2(arg1, /, positional_only_arg, *varargs, **kwargs):
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# introduce a local variable
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local1 = 0
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local2 = 1
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return {
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"local": local1 + local2,
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"arg1": arg1,
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"positional_only_arg": positional_only_arg,
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"varargs": varargs,
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"kwargs": kwargs,
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}
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class FrameInitTests(torch._dynamo.test_case.TestCase):
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def test_frame_init(self):
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code_map1 = {
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target_with_varargs.__code__: varargs_code1.__code__,
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target_with_varkwargs.__code__: varkwargs_code1.__code__,
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}
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code_map2 = {
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target_with_varargs.__code__: varargs_code2.__code__,
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target_with_varkwargs.__code__: varkwargs_code2.__code__,
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}
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def callback1(frame, cache_entry, frame_state):
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if frame.f_code in code_map1:
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transformed_code = code_map1[frame.f_code]
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return torch._dynamo.types.GuardedCode(
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transformed_code, lambda f_locals: True, CompileId(0, 0)
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)
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return None
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def callback2(frame, cache_entry, frame_state):
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if frame.f_code in code_map2:
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transformed_code = code_map2[frame.f_code]
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return torch._dynamo.types.GuardedCode(
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transformed_code, lambda f_locals: True, CompileId(0, 0)
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)
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return None
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for callback in [callback1, callback2]:
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torch._dynamo.reset()
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expected_varargs_output = target_with_varargs(
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1, 2, 3, 4, name1=1, name2=2, name3=3
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)
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expected_kwargs_output = target_with_varkwargs(
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1, 2, keyword_only_arg=1, name2=2, name3=3
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)
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original = torch._dynamo.eval_frame.set_eval_frame(callback1)
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real_varargs_output = target_with_varargs(
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1, 2, 3, 4, name1=1, name2=2, name3=3
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)
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real_kwargs_output = target_with_varkwargs(
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1, 2, keyword_only_arg=1, name2=2, name3=3
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)
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self.assertEqual(real_varargs_output, expected_varargs_output)
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self.assertEqual(real_kwargs_output, expected_kwargs_output)
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torch._dynamo.eval_frame.set_eval_frame(original)
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if __name__ == "__main__":
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from torch._dynamo.test_case import run_tests
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run_tests()
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