diff --git a/docs/ops/opset4.md b/docs/ops/opset4.md
index e377428d38b..8f8842fe5b2 100644
--- a/docs/ops/opset4.md
+++ b/docs/ops/opset4.md
@@ -99,6 +99,7 @@ declared in `namespace opset4`.
 * [Range](generation/Range_1.md)
 * [ReLU](activation/ReLU_1.md)
 * [ReadValue](infrastructure/ReadValue_3.md)
+* [ReduceLp](reduction/ReduceLp_4.md)
 * [ReduceLogicalAnd](reduction/ReduceLogicalAnd_1.md)
 * [ReduceLogicalOr](reduction/ReduceLogicalOr_1.md)
 * [ReduceMax](reduction/ReduceMax_1.md)
diff --git a/docs/ops/reduction/ReduceLp_4.md b/docs/ops/reduction/ReduceLp_4.md
new file mode 100644
index 00000000000..10f5cf3a82e
--- /dev/null
+++ b/docs/ops/reduction/ReduceLp_4.md
@@ -0,0 +1,149 @@
+## ReduceLp <a name="ReduceLp"></a>
+
+**Versioned name**: *ReduceLp-4*
+
+**Category**: *Reduction*
+
+**Short description**: *ReduceLp* operation performs reduction with finding the Lp norm of the 1st input tensor in slices specified by the 2nd input.
+
+**Attributes**
+
+* *keep_dims*
+
+  * **Description**: If set to `True` it holds axes that are used for reduction. For each such axis, output dimension is equal to 1.
+  * **Range of values**: True or False
+  * **Type**: `boolean`
+  * **Default value**: False
+  * **Required**: *no*
+
+**Inputs**
+
+* **1**: Input tensor x of type *T1*. **Required.**
+
+* **2**: Scalar or 1D tensor of type *T_IND* with axis indices for the 1st input along which reduction is performed. Accepted range is `[-r, r-1]` where where `r` is the rank of input tensor, all values must be unique, repeats are not allowed. **Required.**
+
+* **3**: Scalar of type *T2* with value order `p` of the normalization. Possible values: `1` for L1 or `2` for L2. **Required.**
+
+**Outputs**
+
+* **1**: Tensor of the same type as the 1st input tensor and `shape[i] = shapeOf(input1)[i]` for all `i` that is not in the list of axes from the 2nd input. For dimensions from the 2nd input tensor, `shape[i] == 1` if `keep_dims == True`, or `i`-th dimension is removed from the output otherwise.
+
+**Types**
+
+* *T1*: any supported numeric type.
+* *T2*: any supported integer type.
+* *T_IND*: `int64` or `int32`.
+
+**Detailed Description**
+
+Each element in the output is the result of reduction with finding a Lp norm operation along dimensions specified by the 2nd input:
+
+   `output[i0, i1, ..., iN] = Lp[j0,..., jN](x[j0, ..., jN]))`
+
+Where indices i0, ..., iN run through all valid indices for the 1st input and finding the Lp norm `Lp[j0, ..., jN]` have `jk = ik` for those dimensions `k` that are not in the set of indices specified by the 2nd input of the operation. 
+Corner cases:
+
+1. When the 2nd input is an empty list, then this operation does nothing, it is an identity. 
+2. When the 2nd input contains all dimensions of the 1st input, this means that a single reduction scalar value is calculated for entire input tensor. 
+
+**Example**
+
+```xml
+<layer id="1" type="ReduceLp" ...>
+    <data keep_dims="True" />
+    <input>
+        <port id="0">
+            <dim>6</dim>
+            <dim>12</dim>
+            <dim>10</dim>
+            <dim>24</dim>
+        </port>
+        <port id="1">
+            <dim>2</dim>         <!-- value is [2, 3] that means independent reduction in each channel and batch -->
+        </port>
+        <port id="2"/>
+    </input>
+    <output>
+        <port id="3">
+            <dim>6</dim>
+            <dim>12</dim>
+            <dim>1</dim>
+            <dim>1</dim>
+        </port>
+    </output>
+</layer>
+```
+
+```xml
+<layer id="1" type="ReduceLp" ...>
+    <data keep_dims="False" />
+    <input>
+        <port id="0">
+            <dim>6</dim>
+            <dim>12</dim>
+            <dim>10</dim>
+            <dim>24</dim>
+        </port>
+        <port id="1">
+            <dim>2</dim>         <!-- value is [2, 3] that means independent reduction in each channel and batch -->
+        </port>
+        <port id="2"/>
+    </input>
+    <output>
+        <port id="3">
+            <dim>6</dim>
+            <dim>12</dim>
+        </port>
+    </output>
+</layer>
+```
+
+```xml
+<layer id="1" type="ReduceLp" ...>
+    <data keep_dims="False" />
+    <input>
+        <port id="0">
+            <dim>6</dim>
+            <dim>12</dim>
+            <dim>10</dim>
+            <dim>24</dim>
+        </port>
+        <port id="1">
+            <dim>1</dim>         <!-- value is [1] that means independent reduction in each channel and spatial dimensions -->
+        </port>
+        <port id="2"/>
+    </input>
+    <output>
+        <port id="3">
+            <dim>6</dim>
+            <dim>10</dim>
+            <dim>24</dim>
+        </port>
+    </output>
+</layer>
+```
+
+```xml
+<layer id="1" type="ReduceLp" ...>
+    <data keep_dims="False" />
+    <input>
+        <port id="0">
+            <dim>6</dim>
+            <dim>12</dim>
+            <dim>10</dim>
+            <dim>24</dim>
+        </port>
+        <port id="1">
+            <dim>1</dim>         <!-- value is [-2] that means independent reduction in each channel, batch and second spatial dimension -->
+        </port>
+        <port id="2"/>
+    </input>
+    <output>
+        <port id="3">
+            <dim>6</dim>
+            <dim>12</dim>
+            <dim>24</dim>
+        </port>
+    </output>
+</layer>
+```
\ No newline at end of file