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Add op_block_list arg to float16 converter #190

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merged 3 commits into from
Jun 22, 2021
Merged

Add op_block_list arg to float16 converter #190

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775251c
Add op_block_list arg to float16 converter
TomWildenhain-Microsoft Jun 21, 2021
51a5d32
Merge branch 'master' into tom/float16_op_block_list
TomWildenhain-Microsoft Jun 21, 2021
1e738b0
fix style
TomWildenhain-Microsoft Jun 21, 2021
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25 changes: 15 additions & 10 deletions onnxconverter_common/float16.py
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Original file line number Diff line number Diff line change
Expand Up @@ -78,8 +78,16 @@ def make_value_info_from_tensor(tensor):
return helper.make_tensor_value_info(tensor.name, tensor.data_type, shape)


DEFAULT_OP_BLOCK_LIST = ['ArrayFeatureExtractor', 'Binarizer', 'CastMap', 'CategoryMapper', 'DictVectorizer',
'FeatureVectorizer', 'Imputer', 'LabelEncoder', 'LinearClassifier', 'LinearRegressor',
'Normalizer', 'OneHotEncoder', 'SVMClassifier', 'SVMRegressor', 'Scaler',
'TreeEnsembleClassifier', 'TreeEnsembleRegressor', 'ZipMap', 'NonMaxSuppression', 'TopK',
'RoiAlign', 'Resize', 'Range', 'CumSum', 'Min', 'Max', 'Upsample']


def convert_float_to_float16(model, min_positive_val=1e-7, max_finite_val=1e4,
keep_io_types=False, disable_shape_infer=False):
keep_io_types=False, disable_shape_infer=False,
op_block_list=None):
'''
Convert tensor float type in the ONNX ModelProto input to tensor float16.

Expand Down Expand Up @@ -115,12 +123,9 @@ def convert_float_to_float16(model, min_positive_val=1e-7, max_finite_val=1e4,
if not isinstance(model, onnx_proto.ModelProto):
raise ValueError('Expected model type is an ONNX ModelProto but got %s' % type(model))

# create black list
op_black_list = ['ArrayFeatureExtractor', 'Binarizer', 'CastMap', 'CategoryMapper', 'DictVectorizer',
'FeatureVectorizer', 'Imputer', 'LabelEncoder', 'LinearClassifier', 'LinearRegressor',
'Normalizer', 'OneHotEncoder', 'SVMClassifier', 'SVMRegressor', 'Scaler', 'TreeEnsembleClassifier',
'TreeEnsembleRegressor', 'ZipMap', 'NonMaxSuppression', 'TopK', 'RoiAlign', 'Resize',
'Range', 'CumSum', 'Min', 'Max', 'Upsample']
# create blocklist
if op_block_list is None:
op_block_list = DEFAULT_OP_BLOCK_LIST
# create a queue for BFS
queue = []
value_info_list = []
Expand Down Expand Up @@ -176,7 +181,7 @@ def convert_float_to_float16(model, min_positive_val=1e-7, max_finite_val=1e4,
# if q is model.graph, push q.node.attribute (AttributeProto)
if isinstance(q, onnx_proto.GraphProto):
for n in q.node:
# if n is in the black list (doesn't support float16), no conversion for the node,
# if n is in the block list (doesn't support float16), no conversion for the node,
# and save the node for further processing
if n.name in io_casts:
continue
Expand All @@ -186,7 +191,7 @@ def convert_float_to_float16(model, min_positive_val=1e-7, max_finite_val=1e4,
for i in range(len(n.output)):
if n.output[i] in name_mapping:
n.output[i] = name_mapping[n.output[i]]
if n.op_type in op_black_list:
if n.op_type in op_block_list:
node_list.append(n)
else:
if n.op_type == 'Cast':
Expand Down Expand Up @@ -220,7 +225,7 @@ def convert_float_to_float16(model, min_positive_val=1e-7, max_finite_val=1e4,
value_info_list.append(n)
queue = next_level

# process the nodes in black list that doesn't support tensor(float16)
# process the nodes in block list that doesn't support tensor(float16)
for node in node_list:
# if input's name is in the value_info_list meaning input is tensor(float16) type,
# insert a float16 to float Cast node before the node,
Expand Down