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* Modified the workflow diagram * Moved supported topology lists to separate topics * Additional changes * Removed Supported Topologies list and Deprecated pages * Created the Model Conversion Tutorials section for instructions for specific models * Topic names alignment, removed Default_Model_Optimizer_Optimizations.md * Additional structural changes * Fixed links * heading fixes
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General Conversion Parameters
To get the full list of general (framework-agnostic) conversion parameters available in Model Optimizer, run the following command:
mo --help
Paragraphs below provide useful details on relevant parameters.
When to Specify --input_shape Command Line Parameter
There are situations when Model Optimizer is unable to deduce input shapes of the model, for example, in case of model cutting due to unsupported operations. The solution is to provide input shapes of a static rank explicitly.
When to Specify --static_shape Command Line Parameter
If the --static_shape command line parameter is specified the Model Optimizer evaluates shapes of all operations in the model (shape propagation) for a fixed input(s) shape(s). During the shape propagation the Model Optimizer evaluates operations Shape and removes them from the computation graph. With that approach, the initial model which can consume inputs of different shapes may be converted to IR working with the input of one fixed shape only. For example, consider the case when some blob is reshaped from 4D of a shape [N, C, H, W] to a shape [N, C, H * W]. During the model conversion the Model Optimize calculates output shape as a constant 1D blob with values [N, C, H * W]. So if the input shape changes to some other value [N,C,H1,W1] (it is possible scenario for a fully convolutional model) then the reshape layer becomes invalid.
Resulting Intermediate Representation will not be resizable with the help of OpenVINO Runtime API.
Parameters for Pre-Processing
Input data may require pre-processing such as RGB<->BGR conversion and mean and scale normalization. To learn about Model Optimizer parameters used for pre-processing, refer to Optimize Preprocessing Computation.