[Opset13][pyAPI] Python API FakeConvert-13 (#21155)

* [Opset13][pyAPI] Python API FakeConvert-13

* Fix typo

* Add experimental warning

* Add missing py opset in docs

* Fix flake

* Apply suggestions from code review

Co-authored-by: Anastasia Kuporosova <anastasia.kuporosova@intel.com>

* Apply suggestions from code review

Co-authored-by: Katarzyna Mitrus <katarzyna.mitrus@intel.com>

* Apply requested changes

---------

Co-authored-by: Anastasia Kuporosova <anastasia.kuporosova@intel.com>
Co-authored-by: Katarzyna Mitrus <katarzyna.mitrus@intel.com>

src/bindings/python/src/openvino/runtime/opset13/__init__.py

@@ -56,6 +56,7 @@ from openvino.runtime.opset1.ops import equal
 from openvino.runtime.opset1.ops import erf
 from openvino.runtime.opset1.ops import exp
 from openvino.runtime.opset9.ops import eye
+from openvino.runtime.opset13.ops import fake_convert
 from openvino.runtime.opset1.ops import fake_quantize
 from openvino.runtime.opset1.ops import floor
 from openvino.runtime.opset1.ops import floor_mod

src/bindings/python/src/openvino/runtime/opset13/ops.py

@@ -4,7 +4,7 @@
 
 """Factory functions for ops added to openvino opset13."""
 from functools import partial
-from typing import Optional, Union
+from typing import Literal, Optional, Union
 import logging
 
 import numpy as np
@@ -117,6 +117,39 @@ def bitwise_xor(
     )
 
 
+@nameable_op
+def fake_convert(
+    data: NodeInput,
+    scale: NodeInput,
+    shift: Optional[NodeInput] = None,
+    destination_type: Literal["f8e4m3", "f8e5m2"] = "f8e4m3",
+    name: Optional[str] = None,
+) -> Node:
+    """Return a node which performs FakeConvert.
+
+    FakeConvert is experimental and may change in the future.
+    .. warning:: FakeConvert is experimental and may change in the future.
+
+    :param data: The node with data tensor with FP16, BF16 or FP32 datatype.
+    :param scale: Tensor with a scale factor for the data input value,
+                  of the same type as the data, and shape Numpy-broadcastable to data.
+    :param shift: Optional tensor with value to subtract before and add after conversion of the data input value,
+                  of the same type as the data, and shape Numpy-broadcastable to data.
+    :param destination_type: Type to emulate, string of either "f8e4m3" or "f8e5m2".
+    :param name: The optional new name for output node.
+
+    :return: The new node performing FakeConvert operation.
+    """
+    nodes = [data, scale]
+    if shift is not None:
+        nodes.append(shift)
+    return _get_node_factory_opset13().create(
+        "FakeConvert",
+        as_nodes(*nodes),
+        {"destination_type": destination_type},
+    )
+
+
 @nameable_op
 def multinomial(
     probs: NodeInput,

src/bindings/python/tests/test_graph/test_fake_convert.py

@@ -0,0 +1,57 @@
+# -*- coding: utf-8 -*-
+# Copyright (C) 2018-2023 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+import numpy as np
+import pytest
+
+import openvino.runtime.opset13 as ops
+from openvino.runtime import PartialShape, Type
+
+
+@pytest.mark.parametrize(
+    ("data_shape", "scale_shape", "shift_shape", "input_type", "destination_type"),
+    [
+        ([2, 3, 8, 6], [], None, np.float32, None),
+        ([2, 3, -1, 6], [], [], np.float16, "f8e4m3"),
+        ([4, 4], [4], [4], np.float16, "f8e5m2"),
+    ],
+)
+def test_fake_convert_param_inputs(data_shape, scale_shape, shift_shape, input_type, destination_type):
+    data = ops.parameter(data_shape, dtype=input_type)
+    scale = ops.parameter(scale_shape, dtype=input_type)
+    input_kwargs = {"data": data, "scale": scale}
+    if shift_shape is not None:
+        input_kwargs["shift"] = ops.parameter(shift_shape, dtype=input_type)
+    if destination_type:
+        input_kwargs["destination_type"] = destination_type
+
+    op = ops.fake_convert(**input_kwargs)
+    assert op.get_output_size() == 1
+    assert op.get_type_name() == "FakeConvert"
+    assert op.get_output_partial_shape(0) == PartialShape(data_shape)
+    assert op.get_output_element_type(0) == Type(input_type)
+
+
+@pytest.mark.parametrize(
+    ("data_array", "scale_array", "shift_array", "input_type", "destination_type"),
+    [
+        (np.random.random([2, 3, 8, 6]), np.random.random([]), None, np.float32, None),
+        (np.random.random([2, 3, 1, 6]), np.random.random([]), np.random.random([]), np.float16, "f8e4m3"),
+        (np.random.random([4, 4]), np.random.random([4]), np.random.random([4]), np.float16, "f8e5m2"),
+    ],
+)
+def test_fake_convert_const_inputs(data_array, scale_array, shift_array, input_type, destination_type):
+    data = ops.constant(data_array, dtype=input_type)
+    scale = ops.constant(scale_array, dtype=input_type)
+    input_kwargs = {"data": data, "scale": scale}
+    if shift_array is not None:
+        input_kwargs["shift"] = ops.constant(shift_array, dtype=input_type)
+    if destination_type:
+        input_kwargs["destination_type"] = destination_type
+
+    op = ops.fake_convert(**input_kwargs)
+    assert op.get_output_size() == 1
+    assert op.get_type_name() == "FakeConvert"
+    assert op.get_output_partial_shape(0) == PartialShape(data_array.shape)
+    assert op.get_output_element_type(0) == Type(input_type)