Model Optimizer Python API documentaion. (#14696)

docs/MO_DG/Deep_Learning_Model_Optimizer_DevGuide.md

@@ -14,6 +14,7 @@
    openvino_docs_MO_DG_prepare_model_convert_model_Cutting_Model
    openvino_docs_MO_DG_Additional_Optimization_Use_Cases
    openvino_docs_MO_DG_FP16_Compression
+   openvino_docs_MO_DG_Python_API
    openvino_docs_MO_DG_prepare_model_Model_Optimizer_FAQ
 
 @endsphinxdirective

docs/MO_DG/prepare_model/MO_Python_API.md

@@ -0,0 +1,72 @@
+## Model Optimizer Python API {#openvino_docs_MO_DG_Python_API}
+
+Model Optimizer (MO) has a Python API for model conversion, which is represented by the `convert_model()` method in the openvino.tools.mo namespace.
+  `convert_model()` has all the functionality available from the command-line tool.
+  `convert_model()` returns an openvino.runtime.Model object which can be compiled and inferred or serialized to IR.
+
+```sh
+from openvino.tools.mo import convert_model
+
+ov_model = convert_model("resnet.onnx")
+```
+
+`convert_model()` accepts all parameters available in the MO command-line tool. Parameters can be specified by Python classes or string analogs, similar to the command-line tool.
+Example 1:
+
+```sh
+from openvino.runtime import PartialShape, Layout
+
+ov_model = convert_model(model, input_shape=PartialShape([1,3,100,100]), mean_values=[127, 127, 127], layout=Layout("NCHW"))
+```
+
+Example 2:
+
+```sh
+ov_model = convert_model(model, input_shape="[1,3,100,100]", mean_values="[127,127,127]", layout="NCHW")
+```
+
+Command-line flags, like `--compress_to_fp16`, can be set in the Python API by providing a boolean value (`True` or `False`).
+
+```sh
+ov_model = convert_model(model, compress_to_fp16=True)
+```
+
+The `input` parameter can be set by a `tuple` with a name, shape, and type. The input name of the type string is required in the tuple. The shape and type are optional.
+The shape can be a `list` or `tuple` of dimensions (`int` or `openvino.runtime.Dimension`), or `openvino.runtime.PartialShape`, or `openvino.runtime.Shape`. The type can be of numpy type or `openvino.runtime.Type`.
+
+```sh
+ov_model = convert_model(model, input=("input_name", [3], np.float32))
+```
+
+For complex cases, when a value needs to be set in the `input` parameter, the `InputCutInfo` class can be used. `InputCutInfo` accepts four parameters: `name`, `shape`, `type`, and `value`. 
+
+`InputCutInfo("input_name", [3], np.float32, [0.5, 2.1, 3.4])` is equivalent of `InputCutInfo(name="input_name", shape=[3], type=np.float32, value=[0.5, 2.1, 3.4])`.
+Supported types for `InputCutInfo`:
+- name: `string`.
+- shape: `list` or `tuple` of dimensions (`int` or `openvino.runtime.Dimension`), `openvino.runtime.PartialShape`,` openvino.runtime.Shape`.
+- type: `numpy type`, `openvino.runtime.Type`.
+- value: `numpy.ndarray`, `list` of numeric values, `bool`.
+
+```sh
+from openvino.tools.mo import convert_model, InputCutInfo
+
+ov_model = convert_model(model, input=InputCutInfo("input_name", [3], np.float32, [0.5, 2.1, 3.4]))
+```
+
+`layout`, `source_layout` and `dest_layout` accept an `openvino.runtime.Layout` object or `string`.
+
+```sh
+from openvino.runtime import Layout
+from openvino.tools.mo import convert_model
+
+ov_model = convert_model(model, source_layout=Layout("NCHW"))
+```
+
+To set both source and destination layouts in the `layout` parameter, the `LayoutMap` class can be used. `LayoutMap` accepts two parameters: `source_layout` and `target_layout`.
+`LayoutMap("NCHW", "NHWC")` is equivalent to `LayoutMap(source_layout="NCHW", target_layout="NHWC")`.
+
+```sh
+from openvino.tools.mo import convert_model, LayoutMap
+
+ov_model = convert_model(model, layout=LayoutMap("NCHW", "NHWC"))
+```