Transition from Legacy Conversion API¶

In the 2023.1 OpenVINO release OpenVINO Model Converter was introduced with the corresponding Python API: openvino.convert_model method. ovc and openvino.convert_model represent a lightweight alternative of mo and openvino.tools.mo.convert_model which are considered legacy API now. In this article, all the differences between mo and ovc are summarized and the transition guide from the legacy API to the new API is provided.

Parameters Comparison¶

The comparison of parameters between ov.convert_model() / OVC and mo.convert_model() / MO.

mo.convert_model() / MO	ov.convert_model() / OVC	Differences description
input_model	input_model	Along with model object or path to input model ov.convert_model() accepts list of model parts, for example, the path to TensorFlow weights plus the path to TensorFlow checkpoint. OVC tool accepts an unnamed input model.
output_dir	output_model	output_model in OVC tool sets both output model name and output directory.
model_name	output_model	output_model in OVC tool sets both output model name and output directory.
input	input	ov.convert_model() accepts tuples for setting multiple parameters. OVC tool ‘input’ does not have type setting and freezing functionality. ov.convert_model() does not allow input cut.
output	output	ov.convert_model() does not allow output cut.
input_shape	N/A	Not available in ov.convert_model() / OVC. Can be replaced by `input` parameter.
example_input	example_input	No differences.
batch	N/A	Not available in ov.convert_model() / OVC. Can be replaced by model reshape functionality. See details below.
mean_values	N/A	Not available in ov.convert_model() / OVC. Can be replaced by functionality from `PrePostProcessor`. See details below.
scale_values	N/A	Not available in ov.convert_model() / OVC. Can be replaced by functionality from `PrePostProcessor`. See details below.
scale	N/A	Not available in ov.convert_model() / OVC. Can be replaced by functionality from `PrePostProcessor`. See details below.
reverse_input_channels	N/A	Not available in ov.convert_model() / OVC. Can be replaced by functionality from `PrePostProcessor`. See details below.
source_layout	N/A	Not available in ov.convert_model() / OVC. Can be replaced by functionality from `PrePostProcessor`. See details below.
target_layout	N/A	Not available in ov.convert_model() / OVC. Can be replaced by functionality from `PrePostProcessor`. See details below.
layout	N/A	Not available in ov.convert_model() / OVC. Can be replaced by functionality from `PrePostProcessor`. See details below.
compress_to_fp16	compress_to_fp16	OVC provides ‘compress_to_fp16’ for command line tool only, as compression is performed during saving a model to IR (Intermediate Representation).
extensions	extension	No differences.
transform	N/A	Not available in ov.convert_model() / OVC. Can be replaced by functionality from `PrePostProcessor`. See details below.
transformations_config	N/A	Not available in ov.convert_model() / OVC.
static_shape	N/A	Not available in ov.convert_model() / OVC.
freeze_placeholder_with_value	N/A	Not available in ov.convert_model() / OVC.
use_legacy_frontend	N/A	Not available in ov.convert_model() / OVC.
use_legacy_frontend	N/A	Not available in ov.convert_model() / OVC.
silent	verbose	OVC / ov.convert_model provides ‘verbose’ parameter instead of ‘silent’ for printing of detailed conversion information if ‘verbose’ is set to True.
log_level	N/A	Not available in ov.convert_model() / OVC.
version	version	N/A
progress	N/A	Not available in ov.convert_model() / OVC.
stream_output	N/A	Not available in ov.convert_model() / OVC.
share_weights	share_weights	No differences.
framework	N/A	Not available in ov.convert_model() / OVC.
help / -h	help / -h	OVC provides help parameter only in command line tool.
example_output	output	OVC / ov.convert_model ‘output’ parameter includes capabilities of MO ‘example_output’ parameter.
input_model_is_text	N/A	Not available in ov.convert_model() / OVC.
input_checkpoint	input_model	All supported model formats can be passed to ‘input_model’.
input_meta_graph	input_model	All supported model formats can be passed to ‘input_model’.
saved_model_dir	input_model	All supported model formats can be passed to ‘input_model’.
saved_model_tags	N/A	Not available in ov.convert_model() / OVC.
tensorflow_custom_operations_config_update	N/A	Not available in ov.convert_model() / OVC.
tensorflow_object_detection_api_pipeline_config	N/A	Not available in ov.convert_model() / OVC.
tensorboard_logdir	N/A	Not available in ov.convert_model() / OVC.
tensorflow_custom_layer_libraries	N/A	Not available in ov.convert_model() / OVC.
input_symbol	N/A	Not available in ov.convert_model() / OVC.
nd_prefix_name	N/A	Not available in ov.convert_model() / OVC.
pretrained_model_name	N/A	Not available in ov.convert_model() / OVC.
save_params_from_nd	N/A	Not available in ov.convert_model() / OVC.
legacy_mxnet_model	N/A	Not available in ov.convert_model() / OVC.
enable_ssd_gluoncv	N/A	Not available in ov.convert_model() / OVC.
input_proto	N/A	Not available in ov.convert_model() / OVC.
caffe_parser_path	N/A	Not available in ov.convert_model() / OVC.
k	N/A	Not available in ov.convert_model() / OVC.
disable_omitting_optional	N/A	Not available in ov.convert_model() / OVC.
enable_flattening_nested_params	N/A	Not available in ov.convert_model() / OVC.
counts	N/A	Not available in ov.convert_model() / OVC.
remove_output_softmax	N/A	Not available in ov.convert_model() / OVC.
remove_memory	N/A	Not available in ov.convert_model() / OVC.

Transition from Legacy API to New API¶

mo.convert_model() provides a wide range of preprocessing parameters. Most of these parameters have analogs in OVC or can be replaced with functionality from ov.PrePostProcessor class. Here is the guide to transition from legacy model preprocessing to new API preprocessing.

`input_shape`¶

Python

Legacy API	New API
from openvino.tools import mo ov_model = mo.convert_model(model, input_shape=[[1, 3, 100, 100],[1]])	import openvino as ov ov_model = ov.convert_model(model, input=[[1, 3, 100, 100],[1]])

CLI

Legacy API	New API
mo --input_model MODEL_NAME --input_shape [1,3,100,100],[1] --output_dir OUTPUT_DIR	ovc MODEL_NAME --input [1,3,100,100],[1] --output_model OUTPUT_MODEL

`batch`¶

Python

Legacy API	New API
from openvino.tools import mo ov_model = mo.convert_model(model, batch=2)	import openvino as ov ov_model = ov.convert_model(model) input_shape = ov_model.inputs[0].partial_shape input_shape[0] = 2 # batch size ov_model.reshape(input_shape)

Legacy API

New API

from openvino.tools import mo

ov_model = mo.convert_model(model, batch=2)

import openvino as ov

ov_model = ov.convert_model(model)
input_shape = ov_model.inputs[0].partial_shape
input_shape[0] = 2 # batch size
ov_model.reshape(input_shape)

CLI

Legacy API	New API
mo --input_model MODEL_NAME --batch 2 --output_dir OUTPUT_DIR	Not available in OVC tool. Please check Python API.

`mean_values`¶

Python

Legacy API	New API
from openvino.tools import mo ov_model = mo.convert_model(model, mean_values=[0.5, 0.5, 0.5])	import openvino as ov ov_model = ov.convert_model(model) prep = ov.preprocess.PrePostProcessor(ov_model) prep.input(input_name).tensor().set_layout(ov.Layout("NHWC")) prep.input(input_name).preprocess().mean([0.5, 0.5, 0.5]) ov_model = prep.build() There is currently no heuristic for automatic detection of the channel to which mean, scale or reverse channels should be applied. `Layout` needs to be explicitly specified with “C” channel. For example “NHWC”, “NCHW”, “?C??”. See also Layout API overview.

Legacy API

New API

from openvino.tools import mo

ov_model = mo.convert_model(model, mean_values=[0.5, 0.5, 0.5])

import openvino as ov

ov_model = ov.convert_model(model)

prep = ov.preprocess.PrePostProcessor(ov_model)
prep.input(input_name).tensor().set_layout(ov.Layout("NHWC"))
prep.input(input_name).preprocess().mean([0.5, 0.5, 0.5])
ov_model = prep.build()

There is currently no heuristic for automatic detection of the channel to which mean, scale or reverse channels should be applied. Layout needs to be explicitly specified with “C” channel. For example “NHWC”, “NCHW”, “?C??”. See also Layout API overview.

CLI

Legacy API	New API
mo --input_model MODEL_NAME --mean_values [0.5,0.5,0.5] --output_dir OUTPUT_DIR	Not available in OVC tool. Please check Python API.

`scale_values`¶

Python

Legacy API	New API
from openvino.tools import mo ov_model = mo.convert_model(model, scale_values=[255., 255., 255.])	import openvino as ov ov_model = ov.convert_model(model) prep = ov.preprocess.PrePostProcessor(ov_model) prep.input(input_name).tensor().set_layout(ov.Layout("NHWC")) prep.input(input_name).preprocess().scale([255., 255., 255.]) ov_model = prep.build() There is currently no heuristic for automatic detection of the channel to which mean, scale or reverse channels should be applied. `Layout` needs to be explicitly specified with “C” channel. For example “NHWC”, “NCHW”, “?C??”. See also Layout API overview.

Legacy API

New API

from openvino.tools import mo

ov_model = mo.convert_model(model, scale_values=[255., 255., 255.])

import openvino as ov

ov_model = ov.convert_model(model)

prep = ov.preprocess.PrePostProcessor(ov_model)
prep.input(input_name).tensor().set_layout(ov.Layout("NHWC"))
prep.input(input_name).preprocess().scale([255., 255., 255.])
ov_model = prep.build()

CLI

Legacy API	New API
mo --input_model MODEL_NAME --scale_values [255,255,255] --output_dir OUTPUT_DIR	Not available in OVC tool. Please check Python API.

`reverse_input_channels`¶

Python

Legacy API	New API
from openvino.tools import mo ov_model = mo.convert_model(model, reverse_input_channels=True)	import openvino as ov ov_model = ov.convert_model(model) prep = ov.preprocess.PrePostProcessor(ov_model) prep.input(input_name).tensor().set_layout(ov.Layout("NHWC")) prep.input(input_name).preprocess().reverse_channels() ov_model = prep.build() There is currently no heuristic for automatic detection of the channel to which mean, scale or reverse channels should be applied. `Layout` needs to be explicitly specified with “C” channel. For example “NHWC”, “NCHW”, “?C??”. See also Layout API overview.

Legacy API

New API

from openvino.tools import mo

ov_model = mo.convert_model(model, reverse_input_channels=True)

import openvino as ov

ov_model = ov.convert_model(model)

prep = ov.preprocess.PrePostProcessor(ov_model)
prep.input(input_name).tensor().set_layout(ov.Layout("NHWC"))
prep.input(input_name).preprocess().reverse_channels()
ov_model = prep.build()

CLI

Legacy API	New API
mo --input_model MODEL_NAME --reverse_input_channels --output_dir OUTPUT_DIR	Not available in OVC tool. Please check Python API.

`source_layout`¶

Python

Legacy API	New API
import openvino as ov from openvino.tools import mo ov_model = mo.convert_model(model, source_layout={input_name: ov.Layout("NHWC")})	import openvino as ov ov_model = ov.convert_model(model) prep = ov.preprocess.PrePostProcessor(ov_model) prep.input(input_name).model().set_layout(ov.Layout("NHWC")) ov_model = prep.build()

Legacy API

New API

import openvino as ov
from openvino.tools import mo

ov_model = mo.convert_model(model, source_layout={input_name: ov.Layout("NHWC")})

import openvino as ov

ov_model = ov.convert_model(model)

prep = ov.preprocess.PrePostProcessor(ov_model)
prep.input(input_name).model().set_layout(ov.Layout("NHWC"))
ov_model = prep.build()

CLI

Legacy API	New API
mo --input_model MODEL_NAME --source_layout input_name(NHWC) --output_dir OUTPUT_DIR	Not available in OVC tool. Please check Python API.

`target_layout`¶

Python

Legacy API	New API
import openvino as ov from openvino.tools import mo ov_model = mo.convert_model(model, target_layout={input_name: ov.Layout("NHWC")})	import openvino as ov ov_model = ov.convert_model(model) prep = ov.preprocess.PrePostProcessor(ov_model) prep.input(input_name).tensor().set_layout(ov.Layout("NHWC")) ov_model = prep.build()

Legacy API

New API

import openvino as ov
from openvino.tools import mo

ov_model = mo.convert_model(model, target_layout={input_name: ov.Layout("NHWC")})

import openvino as ov

ov_model = ov.convert_model(model)

prep = ov.preprocess.PrePostProcessor(ov_model)
prep.input(input_name).tensor().set_layout(ov.Layout("NHWC"))
ov_model = prep.build()

CLI

Legacy API	New API
mo --input_model MODEL_NAME --target_layout input_name(NHWC) --output_dir OUTPUT_DIR	Not available in OVC tool. Please check Python API.

`layout`¶

Python

Legacy API	New API
from openvino.tools import mo ov_model = mo.convert_model(model, layout={input_name: mo.LayoutMap("NCHW", "NHWC")})	import openvino as ov ov_model = ov.convert_model(model) prep = ov.preprocess.PrePostProcessor(ov_model) prep.input(input_name).model().set_layout(ov.Layout("NCHW")) prep.input(input_name).tensor().set_layout(ov.Layout("NHWC")) ov_model = prep.build()

Legacy API

New API

from openvino.tools import mo

ov_model = mo.convert_model(model, layout={input_name: mo.LayoutMap("NCHW", "NHWC")})

import openvino as ov

ov_model = ov.convert_model(model)

prep = ov.preprocess.PrePostProcessor(ov_model)
prep.input(input_name).model().set_layout(ov.Layout("NCHW"))
prep.input(input_name).tensor().set_layout(ov.Layout("NHWC"))
ov_model = prep.build()

CLI

Legacy API	New API
mo --input_model MODEL_NAME --layout "input_name(NCHW->NHWC)" --output_dir OUTPUT_DIR	Not available in OVC tool. Please check Python API.

`transform`¶

Python

Legacy API	New API
from openvino.tools import mo ov_model = mo.convert_model(model, transform=[('LowLatency2', {'use_const_initializer': False}), 'Pruning', ('MakeStateful', {'param_res_names': {'input_name': 'output_name'}})])	import openvino as ov from openvino._offline_transformations import apply_low_latency_transformation, apply_pruning_transformation, apply_make_stateful_transformation ov_model = ov.convert_model(model) apply_low_latency_transformation(model, use_const_initializer=False) apply_pruning_transformation(model) apply_make_stateful_transformation(model, param_res_names={'input_name': 'output_name'})

Legacy API

New API

from openvino.tools import mo

ov_model = mo.convert_model(model, transform=[('LowLatency2', {'use_const_initializer': False}), 'Pruning', ('MakeStateful', {'param_res_names': {'input_name': 'output_name'}})])

import openvino as ov
from openvino._offline_transformations import apply_low_latency_transformation, apply_pruning_transformation, apply_make_stateful_transformation

ov_model = ov.convert_model(model)
apply_low_latency_transformation(model, use_const_initializer=False)
apply_pruning_transformation(model)
apply_make_stateful_transformation(model, param_res_names={'input_name': 'output_name'})

CLI

Legacy API	New API
mo --input_model MODEL_NAME --transform LowLatency2[use_const_initializer=False],Pruning,MakeStateful[param_res_names={'input_name':'output_name'}] --output_dir OUTPUT_DIR	Not available in OVC tool. Please check Python API.

Supported Frameworks in MO vs OVC¶

ov.convert_model() and OVC tool support conversion from PyTorch, TF, TF Lite, ONNX, PaddlePaddle. The following frameworks are supported only in MO and mo.convert_model(): Caffe, MxNet, Kaldi.

Transition from Legacy Conversion API¶

Parameters Comparison¶

Transition from Legacy API to New API¶

input_shape¶

batch¶

mean_values¶

scale_values¶

reverse_input_channels¶

source_layout¶

target_layout¶

layout¶

transform¶

Supported Frameworks in MO vs OVC¶

`input_shape`¶

`batch`¶

`mean_values`¶

`scale_values`¶

`reverse_input_channels`¶

`source_layout`¶

`target_layout`¶

`layout`¶

`transform`¶