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Turn on graph tf optimize grappler dependency #2020

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Merged
merged 2 commits into from
Aug 12, 2022
Merged

Turn on graph tf optimize grappler dependency #2020

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41b9296
Turn on graph tf optimize grappler dependency
hwangdeyu Aug 5, 2022
a1f1d86
Aviod output name rewrite in random normal
hwangdeyu Aug 10, 2022
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16 changes: 11 additions & 5 deletions tf2onnx/rewriter/random_normal_rewriter.py
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Original file line number Diff line number Diff line change
Expand Up @@ -33,16 +33,22 @@ def rewrite_random_normal(g, ops):
match_results = list(matcher.match_ops(ops))
for match in match_results:
output = match.get_op('output')
if output.type == 'Add':
input2 = match.get_op('input2')
is_output = False
for output_name in g.outputs:
# input2 and output can not be output node.
if input2.name in output_name or output.name in output_name:
is_output = True
break
if is_output:
continue
if output.type == 'Add' and input2.type == 'Mul':
# pattern 1
mean = output.inputs[1].get_tensor_value()
scale = input2.inputs[1].get_tensor_value()
else:
# pattern 2
mean = 0.0
input2 = match.get_op('input2')
if input2.type == 'Mul':
scale = input2.inputs[1].get_tensor_value()
else:
scale = 1.0
dtype = g.get_dtype(output.output[0])
op_name = utils.make_name("RandomNormal")
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8 changes: 6 additions & 2 deletions tf2onnx/tf_loader.py
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Original file line number Diff line number Diff line change
Expand Up @@ -687,6 +687,10 @@ def tf_optimize_grappler(input_names, output_names, graph_def):
'constfold', 'function'
]

if is_tf2():
# add for tf2.x lstm optimization.
rewrite_options.optimizers.append('dependency')

if Version(tf.__version__) >= Version("2.5"):
# This flag disables folding QDQ nodes around constants in the network (eg: around conv/FC weights)
rewrite_options.experimental_disable_folding_quantization_emulation = True
Expand Down Expand Up @@ -771,8 +775,8 @@ def toposort(data):
try:
func = function_def_to_graph(fdef, input_shapes=input_shapes)
except: # pylint: disable=bare-except
# if there is a missmatch between caller and function use the functions shape
logger.warning("shape missmatch between caller and function: %s", k)
# if there is a mismatch between caller and function use the functions shape
logger.warning("shape mismatch between caller and function: %s", k)
func = function_def_to_graph(fdef)
_FUNCTIONS[k] = func
_, _, _, _, _, tfunctions = tflist_to_onnx(func, {})
Expand Down