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And do profiling #177

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Parent: Add test for gradients in the bitwise equivalent test
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And do profiling #177

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10 changes: 8 additions & 2 deletions tests/test_aot_eager.py
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Original file line number Diff line number Diff line change
Expand Up @@ -53,10 +53,16 @@ def test_aot_eager_bitwise_equivalent(llama3_debug_model):
x = torch.randint(0, vocab_size, (batch_size, seqlen), device="cuda")
torch.manual_seed(3999)
r1 = llama3_debug_model(x)
grads1 = torch.autograd.grad(r1.sum(), llama3_debug_model.parameters())
with torch.profiler.profile(with_stack=True) as prof1:
grads1 = torch.autograd.grad(r1.sum(), llama3_debug_model.parameters())
prof1.export_chrome_trace("/tmp/profile/prof1.json")
torch.manual_seed(3999)
r2 = torch.compile(backend="aot_eager")(llama3_debug_model)(x)
grads2 = torch.autograd.grad(r2.sum(), llama3_debug_model.parameters())
with torch.profiler.profile() as prof2:
grads2 = torch.autograd.grad(r2.sum(), llama3_debug_model.parameters())
from torch.fx.traceback import populate_stack_traces_to_kineto_trace
prof2.export_chrome_trace("/tmp/profile/prof2.json")
populate_stack_traces_to_kineto_trace("/tmp/profile/prof2.json")
assert torch.equal(r1, r2) # bitwise equal
for g1, g2 in zip(grads1, grads2):
assert torch.equal(g1, g2)
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