def _graph_def_from_concrete_fn(self, cfs):
if len(cfs) != 1:
raise NotImplementedError(
"Only a single concrete function is supported.")
if _get_version(_tf.__version__) >= _StrictVersion("2.2.0"):
frozen_fn = _convert_variables_to_constants_v2(
cfs[0], lower_control_flow=False, aggressive_inlining=True)
else:
frozen_fn = _convert_variables_to_constants_v2(
cfs[0], lower_control_flow=False)
graph_def = frozen_fn.graph.as_graph_def(add_shapes=True)
# run a Grappler's constant folding pass.
fn_inputs = [
t for t in frozen_fn.inputs if t.dtype != _dtypes.resource
]
grappler_optimizers_list = self._get_grappler_optimizers_list()
graph_def = _run_graph_optimizations(
graph_def,
fn_inputs,
frozen_fn.outputs,
config=_get_grappler_config(grappler_optimizers_list),
graph=frozen_fn.graph,
)
return graph_def
def _graph_def_from_concrete_fn(cfs):
if len(cfs) != 1:
raise NotImplementedError(
"Only a single concrete function is supported.")
frozen_fn = _convert_variables_to_constants_v2(
cfs[0], lower_control_flow=False)
graph_def = frozen_fn.graph.as_graph_def(add_shapes=True)
# run a Grappler's constant folding pass.
fn_inputs = [
t for t in frozen_fn.inputs if t.dtype != _dtypes.resource
]
graph_def = _run_graph_optimizations(
graph_def,
fn_inputs,
frozen_fn.outputs,
config=_get_grappler_config(["constfold", "dependency"]),
graph=frozen_fn.graph,
)
return graph_def