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Added some mo optimizations to improve performance (#1674)

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Signed-off-by: suryasidd <surya.siddharth.pemmaraju@intel.com>
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suryasidd 2019-08-22 19:16:01 -07:00 committed by jywu-msft
parent addf32fa2a
commit 7408dec0bf
1 changed files with 31 additions and 5 deletions
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36
onnxruntime/core/providers/openvino/openvino_mo/openvino_mo.py
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@ -251,6 +251,21 @@ def driver_R5(onnx_modelproto_bytes, precision: str, output_model_name: str, out
convert_batch_norm(graph)
graph_clean_up(graph)
convert_scale_shift_to_mul_add(graph)
graph_clean_up(graph)
fuse_mul_add_sequence(graph)
graph_clean_up(graph)
fuse_linear_ops(graph)
graph_clean_up(graph)
grouped_convolutions_fusing(graph)
graph_clean_up(graph)
fuse_linear_ops(graph)
graph_clean_up(graph)
convert_muladd_to_scaleshift_or_power(graph)
graph_clean_up(graph)
@ -308,9 +323,7 @@ def driver_R1(onnx_modelproto_bytes, precision: str, output_model_name: str, out
input=None, input_model=None, input_shape=None, keep_shape_ops=False, log_level='ERROR', mean_scale_values={}, mean_values=(), model_name=None, move_to_preprocess=False, output=None, output_dir='.', placeholder_shapes=None, reverse_input_channels=False, scale=None, scale_values=(), silent=False, version=False)
graph.graph['fw'] = 'onnx'
graph.graph['feature_dim'] = 1 if graph.graph['layout'] == 'NCHW' else 3
graph.graph['ir_version'] = 4
extract_node_attrs(graph, lambda node: (
True, common_onnx_fields(node)))
graph.graph['ir_version'] = 5
except Exception as e:
raise Error(
'Cannot pre-process ONNX graph after reading from model file "{}". '
@ -327,8 +340,6 @@ def driver_R1(onnx_modelproto_bytes, precision: str, output_model_name: str, out
# --------------------------------- LOAD END ------------------------------------------------------
class_registration.apply_replacements(
graph, class_registration.ClassType.FRONT_REPLACER)
partial_infer(graph)
graph.check_empty_graph('partial_infer')
class_registration.apply_replacements(
graph, class_registration.ClassType.MIDDLE_REPLACER)
@ -339,6 +350,21 @@ def driver_R1(onnx_modelproto_bytes, precision: str, output_model_name: str, out
convert_batch_norm(graph)
graph_clean_up_onnx(graph)
convert_scale_shift_to_mul_add(graph)
graph_clean_up_onnx(graph)
fuse_mul_add_sequence(graph)
graph_clean_up_onnx(graph)
fuse_linear_ops(graph)
graph_clean_up_onnx(graph)
grouped_convolutions_fusing(graph)
graph_clean_up_onnx(graph)
fuse_linear_ops(graph)
graph_clean_up_onnx(graph)
convert_muladd_to_scaleshift_or_power(graph)
graph_clean_up_onnx(graph)