[Opset15][Spec] Col2Im-15 specification (#23947)

### Details:
- Similar in functionality to
https://pytorch.org/docs/stable/generated/torch.nn.Fold.html, `Col2Im`
is `torch.nn.Fold` restricted to two output spatial dimensions
- Some `Col2Im` related discussions:
#20549

### Related PRs
- #24197

### Tickets:
 - CVS-133358

docs/articles_en/documentation/openvino-ir-format/operation-sets/operation-specs/movement/col2im-15.rst

@@ -0,0 +1,225 @@
+.. {#openvino_docs_ops_type_Col2Im_15}
+
+Col2Im
+===================
+
+
+.. meta::
+  :description: Learn about Col2Im-15 - data movement operation which combines sliding blocks into an image tensor.
+
+**Versioned name**: *Col2Im-15*
+
+**Category**: *Data movement*
+
+**Short description**: *Col2Im* operation constructs an image based on ``input`` tensor containing sliding data blocks (blocks of the image) and desired ``output_size``. 
+
+**Detailed description**
+
+Consider an ``input`` tensor containing batches of image blocks of shape ``(N, C * Product(kernel_size), L)``, where:
+
+* ``N`` is the batch dimension,
+* ``C * Product(kernel_size)`` is the number of elements within a block (each block contains ``Product(kernel_size)`` vectors containing values from each channel ``C``),
+* ``L`` is the total number of blocks calculated as follows:
+
+L = product from d=1 to 2 of floor((output_size[d] + pads_begin[d] + pads_end[d] - dilation[d] * (kernel_size[d] - 1) - 1) / stride[d] + 1)
+
+where ``d`` is over all spatial dimensions.
+
+The ``input`` blocks are being moved into the ``output`` tensor of shape ``(N, C, output_size[0], output_size[1])`` by combining the values contained in blocks.
+
+Non-batched inputs are also supported, in which case the ``input`` has shape ``(C * Product(kernel_size), L)`` and the output has shape ``(C, output_size[0], output_size[1])``.
+
+**Attributes**:
+
+* *strides*
+
+  * **Description**: stride in the sliding blocks in the input spatial dimensions.
+  * **Range of values**: 1D tensor of positive integer numbers
+  * **Type**: *T_IDX*
+  * **Default value**: [1, 1]
+  * **Required**: *no*
+
+* *dilations*
+
+  * **Description**: controls local stride of the elements.
+  * **Range of values**: 1D tensor of non-negative integer numbers
+  * **Type**: *T_IDX*
+  * **Default value**: [1, 1]
+  * **Required**: *no*
+
+* *pads_begin*
+
+  * **Description**: *pads_begin* is a number of zero-value pixels to add to the beginning along each axis. For example, *pads_begin* equal "1,2" means adding 1 pixel to the top of the input and 2 to the left of the input.
+  * **Range of values**: 1D tensor of non-negative integer numbers
+  * **Type**: *T_IDX*
+  * **Default value**: [0, 0]
+  * **Required**: *no*
+
+* *pads_end*
+
+  * **Description**: *pads_end* is a number of zero-value pixels to add to the ending along each axis. For example, *pads_end* equal "1,2" means adding 1 pixel to the bottom of the input and 2 to the right of the input.
+  * **Range of values**: 1D tensor of non-negative integer numbers
+  * **Type**: *T_IDX*
+  * **Default value**: [0, 0]
+  * **Required**: *no*
+
+**Inputs**
+
+* **1**: *data*
+
+  * **Description**: A batched 3D tensor of type *T* and shape ``(N, C * Product(kernel_size), L)`` or an unbatched 2D tensor of type *T* and shape ``(C * Product(kernel_size), L)``. **Required.**
+  * **Range of values**: 1D tensor of non-negative integer numbers
+  * **Type**: *T*
+
+* **2**: *output_size*
+
+  * **Description**: controls the shape of the spatial dimensions of the output image. **Required.**
+  * **Range of values**: 1D tensor of two positive integer numbers (height and width)
+  * **Type**: *T_IDX*
+
+* **3**: *kernel_size*
+
+  * **Description**: size of the sliding blocks. **Required.**
+  * **Range of values**: 1D tensor of non-negative integer numbers
+  * **Type**: *T_IDX*
+
+**Outputs**
+
+* **1**: The output tensor the output image of type *T* and shape:
+
+  * ``(N, C, output_size[0], output_size[1])`` in case of batched input,
+  * ``(C, output_size[0], output_size[1])`` in case of non-batched input.
+
+**Types**
+
+* *T*: any supported data type.
+* *T_IDX*: ``int64`` or ``int32``.
+
+**Examples**
+
+All examples assume ``C = 3``.
+
+*Example 1: default optional Parameters*
+
+For inputs ``output_size`` = [16, 16] and ``kernel_size`` = [2, 2]
+
+.. code-block:: xml
+   :force:
+
+    <layer ... type="Col2Im" ... >
+        <input>
+            <port id="0" precision="I32">
+                <dim>3</dim>     <!-- batch_axis -->
+                <dim>12</dim>    <!-- C * Product(kernel_size) -->
+                <dim>225</dim>   <!-- L -->
+            </port>
+            <port id="1" precision="I32">
+                <dim>2</dim>     <!-- output_size -->
+            </port>
+            <port id="2" precision="I32">
+                <dim>2</dim>     <!-- kernel_size -->
+            </port>
+        </input>
+        <output>
+            <port id="1" precision="I32">
+                <dim>3</dim>     <!-- batch_axis -->
+                <dim>3</dim>     <!-- C -->
+                <dim>16</dim>    <!-- output_size[0] -->
+                <dim>16</dim>    <!-- output_size[1] -->
+            </port>
+        </output>
+    </layer>
+
+
+*Example 2: non-default dilations, padding and strides*
+
+For inputs ``output_size`` = [16, 16] and ``kernel_size`` = [3, 3]
+
+.. code-block:: xml
+   :force:
+
+    <layer ... type="Col2Im" ... >
+        <data dilations="2,2" pads_begin="1,1" pads_end="1,1" strides="2,2"/>
+        <input>
+            <port id="0" precision="I32">
+                <dim>1</dim>     <!-- batch_axis -->
+                <dim>27/dim>     <!-- C * Product(kernel_size) -->
+                <dim>25</dim>    <!-- L -->
+            </port>
+            <port id="1" precision="I32">
+                <dim>2</dim>     <!-- output_size -->
+            </port>
+            <port id="2" precision="I32">
+                <dim>2</dim>     <!-- kernel_size -->
+            </port>
+        </input>
+        <output>
+            <port id="1" precision="I32">
+                <dim>1</dim>     <!-- batch_axis -->
+                <dim>3</dim>     <!-- C -->
+                <dim>16</dim>    <!-- output_size[0] -->
+                <dim>16</dim>    <!-- output_size[1] -->
+            </port>
+        </output>
+    </layer>
+
+*Example 3: non-default dilations and padding*
+
+For inputs ``output_size`` = [32, 32] and ``kernel_size`` = [2, 2]
+
+.. code-block:: xml
+   :force:
+
+    <layer ... type="Col2Im" ... >
+        <data dilations="2,2" pads_begin="3,3" pads_end="3,3"/>
+        <input>
+            <port id="0" precision="I32">
+                <dim>12</dim>    <!-- batch_axis -->
+                <dim>12/dim>     <!-- C * Product(kernel_size) -->
+                <dim>324</dim>   <!-- L -->
+            </port>
+            <port id="1" precision="I32">
+                <dim>2</dim>     <!-- output_size -->
+            </port>
+            <port id="2" precision="I32">
+                <dim>2</dim>     <!-- kernel_size -->
+            </port>
+        </input>
+        <output>
+            <port id="1" precision="I32">
+                <dim>12</dim>    <!-- batch_axis -->
+                <dim>3</dim>     <!-- C -->
+                <dim>32</dim>    <!-- output_size[0] -->
+                <dim>32</dim>    <!-- output_size[1] -->
+            </port>
+        </output>
+    </layer>
+
+*Example 4: default optional Parameters, unbatched*
+
+For inputs ``output_size`` = [16, 16] and ``kernel_size`` = [2, 2]
+
+.. code-block:: xml
+   :force:
+
+    <layer ... type="Col2Im" ... >
+        <input>
+            <port id="0" precision="I32">
+                <dim>12</dim>    <!-- C * Product(kernel_size) -->
+                <dim>225</dim>   <!-- L -->
+            </port>
+            <port id="1" precision="I32">
+                <dim>2</dim>     <!-- output_size -->
+            </port>
+            <port id="2" precision="I32">
+                <dim>2</dim>     <!-- kernel_size -->
+            </port>
+        </input>
+        <output>
+            <port id="1" precision="I32">
+                <dim>3</dim>     <!-- C -->
+                <dim>16</dim>    <!-- output_size[0] -->
+                <dim>16</dim>    <!-- output_size[1] -->
+            </port>
+        </output>
+    </layer>