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Remove duplicate backend registration from torch 2.5 #27245

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merged 4 commits into from
Oct 27, 2024
Merged

Remove duplicate backend registration from torch 2.5 #27245

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e6374fd
Remove duplicate backend registration from torch 2.5
suryasidd Oct 25, 2024
56d1d79
Added more robust version checking
suryasidd Oct 25, 2024
fcb21ad
Addressed PR comments
suryasidd Oct 25, 2024
0485102
Merge branch 'master' into torch_2.5_fix
suryasidd Oct 25, 2024
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38 changes: 25 additions & 13 deletions src/bindings/python/src/openvino/frontend/pytorch/torchdynamo/backend.py
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Original file line number Diff line number Diff line change
Expand Up @@ -49,18 +49,26 @@

openvino_options = {}

@register_backend

@fake_tensor_unsupported
def openvino(subgraph, example_inputs, options=None):
if (_get_aot_autograd(options)):
if _get_aot_autograd(options):
global openvino_options
openvino_options = options
decompositions = _get_decompositions(options) + get_inf_decomposition_list() + get_aot_decomposition_list()
return aot_autograd(fw_compiler=fx_openvino,
bw_compiler=fx_openvino,
decompositions=get_decompositions(decompositions))(subgraph, example_inputs)
return aot_autograd(fw_compiler=fx_openvino, bw_compiler=fx_openvino, decompositions=get_decompositions(decompositions))(subgraph, example_inputs)
return fx_openvino(subgraph, example_inputs, options)


try:
from packaging import version

if version.parse(torch.__version__) < version.parse("2.5.0"):
register_backend(compiler_fn=openvino, name="openvino")
except ImportError:
Comment on lines +64 to +68
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may be it is better to check if backend is registered by this code?

if not hasattr(torch.backends, 'openvino') or not torch.backends.openvino.is_available()

that is torch version agnostic approach

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@mvafin mvafin Oct 25, 2024 •
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Agree, this can be improved. However I am not sure if the registered backends list can be easily accessible. Lets merge this PR as is and consider this improvement for future @suryasidd

logger.warning("The 'packaging' module is required but not installed")


def fx_openvino(subgraph, example_inputs, options=None):
try:
if len(openvino_options) != 0:
Expand All @@ -70,7 +78,7 @@ def fx_openvino(subgraph, example_inputs, options=None):
openvino_model_caching = _get_model_caching(options)
if openvino_model_caching is not None and openvino_model_caching:
# Create a hash to be used for caching
model_hash_str = sha256(subgraph.code.encode('utf-8')).hexdigest()
model_hash_str = sha256(subgraph.code.encode("utf-8")).hexdigest()
executor_parameters = {"model_hash_str": model_hash_str}
# Check if the model was fully supported and already cached
example_inputs.reverse()
Expand All @@ -79,15 +87,17 @@ def fx_openvino(subgraph, example_inputs, options=None):
if os.path.isfile(maybe_fs_cached_name + ".xml") and os.path.isfile(maybe_fs_cached_name + ".bin"):
# Model is fully supported and already cached. Run the cached OV model directly.
compiled_model = openvino_compile_cached_model(maybe_fs_cached_name, options, *example_inputs)

def _call(*args):
res = execute_cached(compiled_model, *args)
return res

return _call
if inputs_reversed:
example_inputs.reverse()

preserved_arg_indices = []
if (_get_aot_autograd(options)):
if _get_aot_autograd(options):
if tracing_context := torch._guards.TracingContext.try_get():
fw_metadata = tracing_context.fw_metadata
params_flat = tracing_context.params_flat
Expand All @@ -97,6 +107,7 @@ def _call(*args):
model = subgraph
else:
from torch._subclasses.fake_tensor import FakeTensorMode

decompositions = _get_decompositions(options) + get_inf_decomposition_list()
with FakeTensorMode(allow_non_fake_inputs=True):
model = make_fx(subgraph, decomposition_table=get_decompositions(decompositions))(*example_inputs)
Expand All @@ -106,26 +117,27 @@ def _call(*args):
partitioner = Partitioner(options)
compiled_model = partitioner.make_partitions(model, options)

if executor_parameters is not None and 'model_hash_str' in executor_parameters:
if executor_parameters is not None and "model_hash_str" in executor_parameters:
# Check if the model is fully supported.
fully_supported = partitioner.check_fully_supported(compiled_model)
if fully_supported:
executor_parameters["model_hash_str"] += "_fs"

def _call(*args):
if(_get_aot_autograd(options)):
if _get_aot_autograd(options):
args_list = args[0]
args_new = [args_list[i] for i in preserved_arg_indices]
args = args_new
res = execute(compiled_model, *args, executor="openvino",
executor_parameters=executor_parameters, options=options)
res = execute(compiled_model, *args, executor="openvino", executor_parameters=executor_parameters, options=options)
return res
if(_get_aot_autograd(options)):
_call._boxed_call = True # type: ignore[attr-defined]

if _get_aot_autograd(options):
_call._boxed_call = True # type: ignore[attr-defined]
return _call
except Exception as e:
logger.debug(f"Failed in OpenVINO execution: {e}")
return compile_fx(subgraph, example_inputs)


def reset():
clear_caches()
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