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Unconditionally enable python dispatcher in AOTAutograd (#88365)

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Signed-off-by: Edward Z. Yang <ezyang@fb.com>
Pull Request resolved: https://github.com/pytorch/pytorch/pull/88365
Approved by: https://github.com/Chillee
This commit is contained in:
Edward Z. Yang
2022-11-02 18:55:33 -07:00
committed by PyTorch MergeBot
parent a689502275
commit 97d3b200ca
2 changed files with 17 additions and 16 deletions
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31
functorch/_src/aot_autograd.py
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@ -391,24 +391,25 @@ def aot_dispatch_autograd(flat_fn, flat_args: List[Tensor], aot_config: AOTConfi
disable_amp = torch._C._is_any_autocast_enabled()
if config.use_functionalize:
# Trace once without decompositions, into a graph of ATen ops.
# NB: tracing_mode is real, as it's assumed the calling context setup
# fake tensor mode / symbolic shapes if that is needed
fx_g = make_fx(joint_forward_backward)(*joint_inputs)
with enable_python_dispatcher():
# Trace once without decompositions, into a graph of ATen ops.
# NB: tracing_mode is real, as it's assumed the calling context setup
# fake tensor mode / symbolic shapes if that is needed
fx_g = make_fx(joint_forward_backward)(*joint_inputs)
context = disable_autocast_manager if disable_amp else nullcontext
context = disable_autocast_manager if disable_amp else nullcontext
def fake_fn(primals, tangents):
with torch.fx.traceback.override_stack_trace():
return torch.fx.Interpreter(fx_g).run(primals, tangents)
def fake_fn(primals, tangents):
with torch.fx.traceback.override_stack_trace():
return torch.fx.Interpreter(fx_g).run(primals, tangents)
# Trace a second time, running functionalization, and THEN running decompositions.
# functionalization only acts on ATen today, and doesn't currently handle
# view and inplace ops that come from primtorch.
# Eventually, functionalization should support primtorch view/inplace ops,
# which will make it ok to run decompositions before functionalization.
with context():
fx_g = make_fx(functionalize(fake_fn), aot_config.decompositions)(*joint_inputs)
# Trace a second time, running functionalization, and THEN running decompositions.
# functionalization only acts on ATen today, and doesn't currently handle
# view and inplace ops that come from primtorch.
# Eventually, functionalization should support primtorch view/inplace ops,
# which will make it ok to run decompositions before functionalization.
with context():
fx_g = make_fx(functionalize(fake_fn), aot_config.decompositions)(*joint_inputs)
fx_g.graph.eliminate_dead_code()
fx_g.recompile()
else:

2
torch/_ops.py
View File

@ -103,7 +103,7 @@ def resolve_key(op: PyOperatorABC, k: DispatchKey): # type: ignore[valid-type]
# The dispatch key itself will implicitly route to backend fallback.
# This is probably not great for the pure Python implementation.
return k
raise RuntimeError("could not find kernel")
raise NotImplementedError(f"could not find kernel for {op} at dispatch key {k}")
pyop_namespace = {}