diff --git "a/ov_models/bert_ZH_static_int8.xml" "b/ov_models/bert_ZH_static_int8.xml"
new file mode 100644--- /dev/null
+++ "b/ov_models/bert_ZH_static_int8.xml"
@@ -0,0 +1,18411 @@
+<?xml version="1.0"?>
+<net name="Model0" version="11">
+	<layers>
+		<layer id="2" name="input_ids" type="Parameter" version="opset1">
+			<data shape="1,64" element_type="i64" />
+			<output>
+				<port id="0" precision="I64" names="input_ids">
+					<dim>1</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1" name="attention_mask" type="Parameter" version="opset1">
+			<data shape="1,64" element_type="i64" />
+			<output>
+				<port id="0" precision="I64" names="43,attention_mask">
+					<dim>1</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="0" name="token_type_ids" type="Parameter" version="opset1">
+			<data shape="1,64" element_type="i64" />
+			<output>
+				<port id="0" precision="I64" names="token_type_ids">
+					<dim>1</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="3" name="Constant_356280" type="Const" version="opset1">
+			<data element_type="i8" shape="105879, 768" offset="0" size="81315072" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>105879</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="4" name="Convert_356281" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>105879</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>105879</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="5" name="Constant_356282" type="Const" version="opset1">
+			<data element_type="f32" shape="105879, 1" offset="81315072" size="423516" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>105879</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="6" name="__module.model.bert.embeddings.word_embeddings/aten::embedding/Gather/fq_weights_0" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>105879</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>105879</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>105879</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="7" name="__module.model.bert.embeddings.word_embeddings/aten::embedding/Convert" type="Convert" version="opset1">
+			<data destination_type="i32" />
+			<input>
+				<port id="0" precision="I64">
+					<dim>1</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="I32">
+					<dim>1</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="8" name="__module.model.bert.embeddings.word_embeddings/aten::embedding/Constant" type="Const" version="opset1">
+			<data element_type="i32" shape="" offset="81738588" size="4" />
+			<output>
+				<port id="0" precision="I32" />
+			</output>
+		</layer>
+		<layer id="9" name="__module.model.bert.embeddings.word_embeddings/aten::embedding/Gather" type="Gather" version="opset8">
+			<data batch_dims="0" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>105879</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I32">
+					<dim>1</dim>
+					<dim>64</dim>
+				</port>
+				<port id="2" precision="I32" />
+			</input>
+			<output>
+				<port id="3" precision="FP32" names="63,inputs_embeds">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="10" name="Constant_356284" type="Const" version="opset1">
+			<data element_type="i8" shape="2, 768" offset="81738592" size="1536" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>2</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="11" name="Convert_356285" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>2</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>2</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="12" name="Constant_356286" type="Const" version="opset1">
+			<data element_type="f32" shape="2, 1" offset="81740128" size="8" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>2</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="13" name="__module.model.bert.embeddings.token_type_embeddings/aten::embedding/Gather/fq_weights_0" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>2</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>2</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>2</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="14" name="__module.model.bert.embeddings.token_type_embeddings/aten::embedding/Convert" type="Convert" version="opset1">
+			<data destination_type="i32" />
+			<input>
+				<port id="0" precision="I64">
+					<dim>1</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="I32">
+					<dim>1</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="15" name="__module.model.bert.embeddings.token_type_embeddings/aten::embedding/Constant" type="Const" version="opset1">
+			<data element_type="i32" shape="" offset="81738588" size="4" />
+			<output>
+				<port id="0" precision="I32" />
+			</output>
+		</layer>
+		<layer id="16" name="__module.model.bert.embeddings.token_type_embeddings/aten::embedding/Gather" type="Gather" version="opset8">
+			<data batch_dims="0" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>2</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I32">
+					<dim>1</dim>
+					<dim>64</dim>
+				</port>
+				<port id="2" precision="I32" />
+			</input>
+			<output>
+				<port id="3" precision="FP32" names="65,token_type_embeddings.1">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="17" name="__module.model.bert.embeddings/aten::add/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="66_1">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="18" name="Constant_356288" type="Const" version="opset1">
+			<data element_type="i8" shape="512, 768" offset="81740136" size="393216" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>512</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="19" name="Convert_356289" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>512</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>512</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="20" name="Constant_356290" type="Const" version="opset1">
+			<data element_type="f32" shape="512, 1" offset="82133352" size="2048" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>512</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="21" name="__module.model.bert.embeddings.position_embeddings/aten::embedding/Gather/fq_weights_0" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>512</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>512</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>512</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="22" name="__module.model.bert.embeddings/aten::slice/Slice" type="Const" version="opset1">
+			<data element_type="i64" shape="1, 512" offset="82135400" size="4096" />
+			<output>
+				<port id="0" precision="I64" names="60">
+					<dim>1</dim>
+					<dim>512</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="23" name="__module.model.bert.embeddings/aten::slice/Reshape" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="82139496" size="8" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="24" name="ShapeOf_8560" type="ShapeOf" version="opset3">
+			<data output_type="i64" />
+			<input>
+				<port id="0" precision="I64">
+					<dim>1</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="I64">
+					<dim>2</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="25" name="Constant_8669" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="82139504" size="8" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="26" name="Constant_8562" type="Const" version="opset1">
+			<data element_type="i64" shape="" offset="82139496" size="8" />
+			<output>
+				<port id="0" precision="I64" />
+			</output>
+		</layer>
+		<layer id="27" name="Gather_8563" type="Gather" version="opset8">
+			<data batch_dims="0" />
+			<input>
+				<port id="0" precision="I64">
+					<dim>2</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>1</dim>
+				</port>
+				<port id="2" precision="I64" />
+			</input>
+			<output>
+				<port id="3" precision="I64" names="56,58,59">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="28" name="__module.model.bert.embeddings/aten::slice/Reshape_2" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="82139504" size="8" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="29" name="__module.model.bert.embeddings/aten::slice/Reshape_3" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="82139504" size="8" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="30" name="__module.model.bert.embeddings/aten::slice/Slice_1" type="Slice" version="opset8">
+			<input>
+				<port id="0" precision="I64">
+					<dim>1</dim>
+					<dim>512</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>1</dim>
+				</port>
+				<port id="2" precision="I64">
+					<dim>1</dim>
+				</port>
+				<port id="3" precision="I64">
+					<dim>1</dim>
+				</port>
+				<port id="4" precision="I64">
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="5" precision="I64" names="61">
+					<dim>1</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="31" name="__module.model.bert.embeddings.position_embeddings/aten::embedding/Convert" type="Convert" version="opset1">
+			<data destination_type="i32" />
+			<input>
+				<port id="0" precision="I64">
+					<dim>1</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="I32">
+					<dim>1</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="32" name="__module.model.bert.embeddings.position_embeddings/aten::embedding/Constant" type="Const" version="opset1">
+			<data element_type="i32" shape="" offset="81738588" size="4" />
+			<output>
+				<port id="0" precision="I32" />
+			</output>
+		</layer>
+		<layer id="33" name="__module.model.bert.embeddings.position_embeddings/aten::embedding/Gather" type="Gather" version="opset8">
+			<data batch_dims="0" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>512</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I32">
+					<dim>1</dim>
+					<dim>64</dim>
+				</port>
+				<port id="2" precision="I32" />
+			</input>
+			<output>
+				<port id="3" precision="FP32" names="68,position_embeddings.1">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="34" name="__module.model.bert.embeddings/aten::add_/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="66,embeddings.1">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="35" name="__module.model.bert.embeddings.LayerNorm/aten::layer_norm/Multiply" type="Const" version="opset1">
+			<data element_type="i32" shape="1" offset="82139512" size="4" />
+			<output>
+				<port id="0" precision="I32">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="36" name="__module.model.bert.embeddings.LayerNorm/aten::layer_norm/MVN" type="MVN" version="opset6">
+			<data eps="9.999999960041972e-13" normalize_variance="true" eps_mode="INSIDE_SQRT" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I32">
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="37" name="Constant_8397" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="82139516" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="38" name="__module.model.bert.embeddings.LayerNorm/aten::layer_norm/Multiply_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="39" name="Constant_8398" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="82142588" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="40" name="__module.model.bert.embeddings.LayerNorm/aten::layer_norm/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="73,input.1">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="41" name="__module.model.bert.embeddings.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/scale" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="82145660" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="42" name="__module.model.bert.embeddings.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="43" name="__module.model.bert.embeddings.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="82148732" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="44" name="__module.model.bert.embeddings.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="82148736" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="45" name="__module.model.bert.embeddings.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="82148732" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="46" name="__module.model.bert.embeddings.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="82148736" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="47" name="__module.model.bert.embeddings.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="48" name="Constant_356292" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 768" offset="82148740" size="589824" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="49" name="Convert_356293" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="50" name="Constant_356294" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="82738564" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="51" name="__module.model.bert.encoder.layer.0.attention.self.query/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="52" name="__module.model.bert.encoder.layer.0.attention.self.query/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="53" name="Constant_8399" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="82741636" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="54" name="__module.model.bert.encoder.layer.0.attention.self.query/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="109,x.9">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="55" name="__module.model.bert.encoder.layer.0.attention.self.query/aten::linear/Add/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="82744708" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="56" name="__module.model.bert.encoder.layer.0.attention.self.query/aten::linear/Add/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="82744712" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="57" name="__module.model.bert.encoder.layer.0.attention.self.query/aten::linear/Add/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="82744708" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="58" name="__module.model.bert.encoder.layer.0.attention.self.query/aten::linear/Add/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="82744712" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="59" name="__module.model.bert.encoder.layer.0.attention.self.query/aten::linear/Add/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="60" name="__module.model.bert.encoder.layer.0.attention.self/prim::ListConstruct/Concat" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744716" size="32" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="61" name="__module.model.bert.encoder.layer.0.attention.self/aten::view/Reshape" type="Reshape" version="opset1">
+			<data special_zero="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="131,x.11">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="62" name="Constant_241" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744748" size="32" />
+			<output>
+				<port id="0" precision="I64" names="132">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="63" name="__module.model.bert.encoder.layer.0.attention.self/aten::permute/Transpose" type="Transpose" version="opset1">
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="133">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="64" name="Constant_356296" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 768" offset="82744780" size="589824" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="65" name="Convert_356297" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="66" name="Constant_356298" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="83334604" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="67" name="__module.model.bert.encoder.layer.0.attention.self.key/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="68" name="__module.model.bert.encoder.layer.0.attention.self.key/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="69" name="Constant_8400" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="83337676" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="70" name="__module.model.bert.encoder.layer.0.attention.self.key/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="112,x.1">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="71" name="__module.model.bert.encoder.layer.0.attention.self.key/aten::linear/Add/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="83340748" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="72" name="__module.model.bert.encoder.layer.0.attention.self.key/aten::linear/Add/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="83340752" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="73" name="__module.model.bert.encoder.layer.0.attention.self.key/aten::linear/Add/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="83340748" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="74" name="__module.model.bert.encoder.layer.0.attention.self.key/aten::linear/Add/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="83340752" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="75" name="__module.model.bert.encoder.layer.0.attention.self.key/aten::linear/Add/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="76" name="__module.model.bert.encoder.layer.0.attention.self/prim::ListConstruct/Concat_1" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744716" size="32" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="77" name="__module.model.bert.encoder.layer.0.attention.self/aten::view/Reshape_1" type="Reshape" version="opset1">
+			<data special_zero="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="116,x.3">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="78" name="Constant_201" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744748" size="32" />
+			<output>
+				<port id="0" precision="I64" names="117">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="79" name="__module.model.bert.encoder.layer.0.attention.self/aten::permute/Transpose_1" type="Transpose" version="opset1">
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="118,key_layer.1">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="80" name="__module.model.bert.encoder.layer.0.attention.self/aten::matmul/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="135,attention_scores.1">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="81" name="Constant_8401" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 1, 1" offset="83340756" size="4" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="82" name="__module.model.bert.encoder.layer.0.attention.self/aten::div/Divide" type="Divide" version="opset1">
+			<data auto_broadcast="numpy" m_pythondiv="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="136,attention_scores.3">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="83" name="Constant_8403" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 1, 1" offset="83340760" size="4" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="84" name="16" type="Const" version="opset1">
+			<data element_type="i64" shape="" offset="82139504" size="8" />
+			<output>
+				<port id="0" precision="I64" names="16" />
+			</output>
+		</layer>
+		<layer id="85" name="__module.model.bert/aten::unsqueeze/Unsqueeze" type="Unsqueeze" version="opset1">
+			<input>
+				<port id="0" precision="I64">
+					<dim>1</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64" />
+			</input>
+			<output>
+				<port id="2" precision="I64" names="44">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="86" name="17" type="Const" version="opset1">
+			<data element_type="i64" shape="" offset="83340764" size="8" />
+			<output>
+				<port id="0" precision="I64" names="17" />
+			</output>
+		</layer>
+		<layer id="87" name="__module.model.bert/aten::unsqueeze/Unsqueeze_1" type="Unsqueeze" version="opset1">
+			<input>
+				<port id="0" precision="I64">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64" />
+			</input>
+			<output>
+				<port id="2" precision="I64" names="45,46,extended_attention_mask">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="88" name="__module.model.bert/aten::to/Convert" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I64">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="47">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="89" name="Constant_8402" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 1, 1" offset="83340760" size="4" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="90" name="__module.model.bert/aten::rsub/Multiply" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="91" name="__module.model.bert/aten::rsub/Subtract" type="Subtract" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="48">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="92" name="Constant_8404" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 1, 1" offset="83340772" size="4" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="93" name="__module.model.bert/aten::mul/Multiply" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="49,attention_mask">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="94" name="__module.model.bert.encoder.layer.0.attention.self/aten::add/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="137,input.3">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="95" name="__module.model.bert.encoder.layer.0.attention.self/aten::softmax/Softmax" type="SoftMax" version="opset8">
+			<data axis="-1" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="138,input.5">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="96" name="Constant_356300" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 768" offset="83340776" size="589824" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="97" name="Convert_356301" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="98" name="Constant_356302" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="83930600" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="99" name="__module.model.bert.encoder.layer.0.attention.self.value/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="100" name="__module.model.bert.encoder.layer.0.attention.self.value/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="101" name="Constant_8405" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="83933672" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="102" name="__module.model.bert.encoder.layer.0.attention.self.value/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="121,x.5">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="103" name="__module.model.bert.encoder.layer.0.attention.self/prim::ListConstruct/Concat_2" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744716" size="32" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="104" name="__module.model.bert.encoder.layer.0.attention.self/aten::view/Reshape_2" type="Reshape" version="opset1">
+			<data special_zero="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="125,x.7">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="105" name="Constant_224" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744748" size="32" />
+			<output>
+				<port id="0" precision="I64" names="126">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="106" name="__module.model.bert.encoder.layer.0.attention.self/aten::permute/Transpose_2" type="Transpose" version="opset1">
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="127">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="107" name="__module.model.bert.encoder.layer.0.attention.self/aten::matmul/MatMul_1" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="false" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="140,context_layer.1">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="108" name="Constant_322" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744748" size="32" />
+			<output>
+				<port id="0" precision="I64" names="141">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="109" name="__module.model.bert.encoder.layer.0.attention.self/aten::permute/Transpose_3" type="Transpose" version="opset1">
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="142">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="110" name="__module.model.bert.encoder.layer.0.attention.self/prim::ListConstruct/Concat_3" type="Const" version="opset1">
+			<data element_type="i64" shape="3" offset="83936744" size="24" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="111" name="__module.model.bert.encoder.layer.0.attention.self/aten::view/Reshape_3" type="Reshape" version="opset1">
+			<data special_zero="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="147">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="112" name="__module.model.bert.encoder.layer.0.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/scale" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="83936768" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="113" name="__module.model.bert.encoder.layer.0.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="114" name="__module.model.bert.encoder.layer.0.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="83939840" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="115" name="__module.model.bert.encoder.layer.0.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="83939844" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="116" name="__module.model.bert.encoder.layer.0.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="83939840" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="117" name="__module.model.bert.encoder.layer.0.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="83939844" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="118" name="__module.model.bert.encoder.layer.0.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="119" name="Constant_356304" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 768" offset="83939848" size="589824" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="120" name="Convert_356305" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="121" name="Constant_356306" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="84529672" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="122" name="__module.model.bert.encoder.layer.0.attention.output.dense/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="123" name="__module.model.bert.encoder.layer.0.attention.output.dense/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="124" name="Constant_8406" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="84532744" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="125" name="__module.model.bert.encoder.layer.0.attention.output.dense/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="153,input.7">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="126" name="__module.model.bert.encoder.layer.0.attention.output/aten::add/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="155">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="127" name="__module.model.bert.encoder.layer.0.attention.output.LayerNorm/aten::layer_norm/Multiply" type="Const" version="opset1">
+			<data element_type="i32" shape="1" offset="82139512" size="4" />
+			<output>
+				<port id="0" precision="I32">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="128" name="__module.model.bert.encoder.layer.0.attention.output.LayerNorm/aten::layer_norm/MVN" type="MVN" version="opset6">
+			<data eps="9.999999960041972e-13" normalize_variance="true" eps_mode="INSIDE_SQRT" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I32">
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="129" name="Constant_8407" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="84535816" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="130" name="__module.model.bert.encoder.layer.0.attention.output.LayerNorm/aten::layer_norm/Multiply_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="131" name="Constant_8408" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="84538888" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="132" name="__module.model.bert.encoder.layer.0.attention.output.LayerNorm/aten::layer_norm/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="159,input_tensor.3">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="133" name="__module.model.bert.encoder.layer.0.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/scale" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="84541960" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="134" name="__module.model.bert.encoder.layer.0.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="135" name="__module.model.bert.encoder.layer.0.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="84545032" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="136" name="__module.model.bert.encoder.layer.0.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="84545036" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="137" name="__module.model.bert.encoder.layer.0.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="84545032" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="138" name="__module.model.bert.encoder.layer.0.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="84545036" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="139" name="__module.model.bert.encoder.layer.0.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="140" name="Constant_356308" type="Const" version="opset1">
+			<data element_type="i8" shape="3072, 768" offset="84545040" size="2359296" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="141" name="Convert_356309" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="142" name="Constant_356310" type="Const" version="opset1">
+			<data element_type="f32" shape="3072, 1" offset="86904336" size="12288" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>3072</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="143" name="__module.model.bert.encoder.layer.0.intermediate.dense/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>3072</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="144" name="__module.model.bert.encoder.layer.0.intermediate.dense/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="145" name="Constant_8409" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 3072" offset="86916624" size="12288" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="146" name="__module.model.bert.encoder.layer.0.intermediate.dense/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="164,input.9">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="147" name="__module.model.bert.encoder.layer.0.intermediate.intermediate_act_fn/aten::gelu/Gelu" type="Gelu" version="opset7">
+			<data approximation_mode="ERF" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="165">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="148" name="__module.model.bert.encoder.layer.0.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/scale" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 3072" offset="86928912" size="12288" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="149" name="__module.model.bert.encoder.layer.0.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="150" name="__module.model.bert.encoder.layer.0.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="86941200" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="151" name="__module.model.bert.encoder.layer.0.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="86941204" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="152" name="__module.model.bert.encoder.layer.0.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="86941200" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="153" name="__module.model.bert.encoder.layer.0.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="86941204" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="154" name="__module.model.bert.encoder.layer.0.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="155" name="Constant_356312" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 3072" offset="86941208" size="2359296" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="156" name="Convert_356313" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="157" name="Constant_356314" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="89300504" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="158" name="__module.model.bert.encoder.layer.0.output.dense/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="159" name="__module.model.bert.encoder.layer.0.output.dense/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="160" name="Constant_8410" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="89303576" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="161" name="__module.model.bert.encoder.layer.0.output.dense/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="171,input.11">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="162" name="__module.model.bert.encoder.layer.0.output/aten::add/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="173">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="163" name="__module.model.bert.encoder.layer.0.output.LayerNorm/aten::layer_norm/Multiply" type="Const" version="opset1">
+			<data element_type="i32" shape="1" offset="82139512" size="4" />
+			<output>
+				<port id="0" precision="I32">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="164" name="__module.model.bert.encoder.layer.0.output.LayerNorm/aten::layer_norm/MVN" type="MVN" version="opset6">
+			<data eps="9.999999960041972e-13" normalize_variance="true" eps_mode="INSIDE_SQRT" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I32">
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="165" name="Constant_8411" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="89306648" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="166" name="__module.model.bert.encoder.layer.0.output.LayerNorm/aten::layer_norm/Multiply_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="167" name="Constant_8412" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="89309720" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="168" name="__module.model.bert.encoder.layer.0.output.LayerNorm/aten::layer_norm/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="177,input_tensor.5">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="169" name="__module.model.bert.encoder.layer.0.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/scale" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="89312792" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="170" name="__module.model.bert.encoder.layer.0.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="171" name="__module.model.bert.encoder.layer.0.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="89315864" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="172" name="__module.model.bert.encoder.layer.0.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="89315868" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="173" name="__module.model.bert.encoder.layer.0.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="89315864" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="174" name="__module.model.bert.encoder.layer.0.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="89315868" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="175" name="__module.model.bert.encoder.layer.0.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="176" name="Constant_356316" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 768" offset="89315872" size="589824" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="177" name="Convert_356317" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="178" name="Constant_356318" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="89905696" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="179" name="__module.model.bert.encoder.layer.1.attention.self.query/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="180" name="__module.model.bert.encoder.layer.1.attention.self.query/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="181" name="Constant_8413" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="89908768" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="182" name="__module.model.bert.encoder.layer.1.attention.self.query/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="188,x.21">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="183" name="__module.model.bert.encoder.layer.1.attention.self.query/aten::linear/Add/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="89911840" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="184" name="__module.model.bert.encoder.layer.1.attention.self.query/aten::linear/Add/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="89911844" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="185" name="__module.model.bert.encoder.layer.1.attention.self.query/aten::linear/Add/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="89911840" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="186" name="__module.model.bert.encoder.layer.1.attention.self.query/aten::linear/Add/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="89911844" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="187" name="__module.model.bert.encoder.layer.1.attention.self.query/aten::linear/Add/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="188" name="__module.model.bert.encoder.layer.1.attention.self/prim::ListConstruct/Concat" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744716" size="32" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="189" name="__module.model.bert.encoder.layer.1.attention.self/aten::view/Reshape" type="Reshape" version="opset1">
+			<data special_zero="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="210,x.23">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="190" name="Constant_487" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744748" size="32" />
+			<output>
+				<port id="0" precision="I64" names="211">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="191" name="__module.model.bert.encoder.layer.1.attention.self/aten::permute/Transpose" type="Transpose" version="opset1">
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="212">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="192" name="Constant_356320" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 768" offset="89911848" size="589824" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="193" name="Convert_356321" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="194" name="Constant_356322" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="90501672" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="195" name="__module.model.bert.encoder.layer.1.attention.self.key/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="196" name="__module.model.bert.encoder.layer.1.attention.self.key/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="197" name="Constant_8414" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="90504744" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="198" name="__module.model.bert.encoder.layer.1.attention.self.key/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="191,x.13">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="199" name="__module.model.bert.encoder.layer.1.attention.self.key/aten::linear/Add/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="90507816" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="200" name="__module.model.bert.encoder.layer.1.attention.self.key/aten::linear/Add/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="90507820" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="201" name="__module.model.bert.encoder.layer.1.attention.self.key/aten::linear/Add/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="90507816" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="202" name="__module.model.bert.encoder.layer.1.attention.self.key/aten::linear/Add/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="90507820" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="203" name="__module.model.bert.encoder.layer.1.attention.self.key/aten::linear/Add/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="204" name="__module.model.bert.encoder.layer.1.attention.self/prim::ListConstruct/Concat_1" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744716" size="32" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="205" name="__module.model.bert.encoder.layer.1.attention.self/aten::view/Reshape_1" type="Reshape" version="opset1">
+			<data special_zero="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="195,x.15">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="206" name="Constant_447" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744748" size="32" />
+			<output>
+				<port id="0" precision="I64" names="196">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="207" name="__module.model.bert.encoder.layer.1.attention.self/aten::permute/Transpose_1" type="Transpose" version="opset1">
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="197,key_layer.3">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="208" name="__module.model.bert.encoder.layer.1.attention.self/aten::matmul/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="214,attention_scores.5">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="209" name="Constant_8415" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 1, 1" offset="83340756" size="4" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="210" name="__module.model.bert.encoder.layer.1.attention.self/aten::div/Divide" type="Divide" version="opset1">
+			<data auto_broadcast="numpy" m_pythondiv="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="215,attention_scores.7">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="211" name="__module.model.bert.encoder.layer.1.attention.self/aten::add/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="216,input.13">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="212" name="__module.model.bert.encoder.layer.1.attention.self/aten::softmax/Softmax" type="SoftMax" version="opset8">
+			<data axis="-1" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="217,input.15">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="213" name="Constant_356324" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 768" offset="90507824" size="589824" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="214" name="Convert_356325" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="215" name="Constant_356326" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="91097648" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="216" name="__module.model.bert.encoder.layer.1.attention.self.value/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="217" name="__module.model.bert.encoder.layer.1.attention.self.value/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="218" name="Constant_8416" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="91100720" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="219" name="__module.model.bert.encoder.layer.1.attention.self.value/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="200,x.17">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="220" name="__module.model.bert.encoder.layer.1.attention.self/prim::ListConstruct/Concat_2" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744716" size="32" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="221" name="__module.model.bert.encoder.layer.1.attention.self/aten::view/Reshape_2" type="Reshape" version="opset1">
+			<data special_zero="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="204,x.19">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="222" name="Constant_470" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744748" size="32" />
+			<output>
+				<port id="0" precision="I64" names="205">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="223" name="__module.model.bert.encoder.layer.1.attention.self/aten::permute/Transpose_2" type="Transpose" version="opset1">
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="206">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="224" name="__module.model.bert.encoder.layer.1.attention.self/aten::matmul/MatMul_1" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="false" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="219,context_layer.5">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="225" name="Constant_568" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744748" size="32" />
+			<output>
+				<port id="0" precision="I64" names="220">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="226" name="__module.model.bert.encoder.layer.1.attention.self/aten::permute/Transpose_3" type="Transpose" version="opset1">
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="221">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="227" name="__module.model.bert.encoder.layer.1.attention.self/prim::ListConstruct/Concat_3" type="Const" version="opset1">
+			<data element_type="i64" shape="3" offset="83936744" size="24" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="228" name="__module.model.bert.encoder.layer.1.attention.self/aten::view/Reshape_3" type="Reshape" version="opset1">
+			<data special_zero="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="226">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="229" name="__module.model.bert.encoder.layer.1.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/scale" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="91103792" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="230" name="__module.model.bert.encoder.layer.1.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="231" name="__module.model.bert.encoder.layer.1.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="91106864" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="232" name="__module.model.bert.encoder.layer.1.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="91106868" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="233" name="__module.model.bert.encoder.layer.1.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="91106864" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="234" name="__module.model.bert.encoder.layer.1.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="91106868" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="235" name="__module.model.bert.encoder.layer.1.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="236" name="Constant_356328" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 768" offset="91106872" size="589824" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="237" name="Convert_356329" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="238" name="Constant_356330" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="91696696" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="239" name="__module.model.bert.encoder.layer.1.attention.output.dense/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="240" name="__module.model.bert.encoder.layer.1.attention.output.dense/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="241" name="Constant_8417" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="91699768" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="242" name="__module.model.bert.encoder.layer.1.attention.output.dense/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="232,input.17">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="243" name="__module.model.bert.encoder.layer.1.attention.output/aten::add/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="234">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="244" name="__module.model.bert.encoder.layer.1.attention.output.LayerNorm/aten::layer_norm/Multiply" type="Const" version="opset1">
+			<data element_type="i32" shape="1" offset="82139512" size="4" />
+			<output>
+				<port id="0" precision="I32">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="245" name="__module.model.bert.encoder.layer.1.attention.output.LayerNorm/aten::layer_norm/MVN" type="MVN" version="opset6">
+			<data eps="9.999999960041972e-13" normalize_variance="true" eps_mode="INSIDE_SQRT" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I32">
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="246" name="Constant_8418" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="91702840" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="247" name="__module.model.bert.encoder.layer.1.attention.output.LayerNorm/aten::layer_norm/Multiply_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="248" name="Constant_8419" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="91705912" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="249" name="__module.model.bert.encoder.layer.1.attention.output.LayerNorm/aten::layer_norm/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="238,input_tensor.7">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="250" name="__module.model.bert.encoder.layer.1.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/scale" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="91708984" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="251" name="__module.model.bert.encoder.layer.1.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="252" name="__module.model.bert.encoder.layer.1.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="91712056" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="253" name="__module.model.bert.encoder.layer.1.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="91712060" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="254" name="__module.model.bert.encoder.layer.1.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="91712056" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="255" name="__module.model.bert.encoder.layer.1.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="91712060" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="256" name="__module.model.bert.encoder.layer.1.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="257" name="Constant_356332" type="Const" version="opset1">
+			<data element_type="i8" shape="3072, 768" offset="91712064" size="2359296" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="258" name="Convert_356333" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="259" name="Constant_356334" type="Const" version="opset1">
+			<data element_type="f32" shape="3072, 1" offset="94071360" size="12288" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>3072</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="260" name="__module.model.bert.encoder.layer.1.intermediate.dense/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>3072</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="261" name="__module.model.bert.encoder.layer.1.intermediate.dense/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="262" name="Constant_8420" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 3072" offset="94083648" size="12288" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="263" name="__module.model.bert.encoder.layer.1.intermediate.dense/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="243,input.19">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="264" name="__module.model.bert.encoder.layer.1.intermediate.intermediate_act_fn/aten::gelu/Gelu" type="Gelu" version="opset7">
+			<data approximation_mode="ERF" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="244">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="265" name="__module.model.bert.encoder.layer.1.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/scale" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 3072" offset="94095936" size="12288" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="266" name="__module.model.bert.encoder.layer.1.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="267" name="__module.model.bert.encoder.layer.1.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="94108224" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="268" name="__module.model.bert.encoder.layer.1.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="94108228" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="269" name="__module.model.bert.encoder.layer.1.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="94108224" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="270" name="__module.model.bert.encoder.layer.1.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="94108228" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="271" name="__module.model.bert.encoder.layer.1.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="272" name="Constant_356336" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 3072" offset="94108232" size="2359296" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="273" name="Convert_356337" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="274" name="Constant_356338" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="96467528" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="275" name="__module.model.bert.encoder.layer.1.output.dense/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="276" name="__module.model.bert.encoder.layer.1.output.dense/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="277" name="Constant_8421" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="96470600" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="278" name="__module.model.bert.encoder.layer.1.output.dense/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="250,input.21">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="279" name="__module.model.bert.encoder.layer.1.output/aten::add/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="252">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="280" name="__module.model.bert.encoder.layer.1.output.LayerNorm/aten::layer_norm/Multiply" type="Const" version="opset1">
+			<data element_type="i32" shape="1" offset="82139512" size="4" />
+			<output>
+				<port id="0" precision="I32">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="281" name="__module.model.bert.encoder.layer.1.output.LayerNorm/aten::layer_norm/MVN" type="MVN" version="opset6">
+			<data eps="9.999999960041972e-13" normalize_variance="true" eps_mode="INSIDE_SQRT" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I32">
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="282" name="Constant_8422" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="96473672" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="283" name="__module.model.bert.encoder.layer.1.output.LayerNorm/aten::layer_norm/Multiply_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="284" name="Constant_8423" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="96476744" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="285" name="__module.model.bert.encoder.layer.1.output.LayerNorm/aten::layer_norm/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="256,input_tensor.9">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="286" name="__module.model.bert.encoder.layer.1.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/scale" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="96479816" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="287" name="__module.model.bert.encoder.layer.1.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="288" name="__module.model.bert.encoder.layer.1.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="96482888" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="289" name="__module.model.bert.encoder.layer.1.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="96482892" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="290" name="__module.model.bert.encoder.layer.1.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="96482888" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="291" name="__module.model.bert.encoder.layer.1.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="96482892" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="292" name="__module.model.bert.encoder.layer.1.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="293" name="Constant_356340" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 768" offset="96482896" size="589824" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="294" name="Convert_356341" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="295" name="Constant_356342" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="97072720" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="296" name="__module.model.bert.encoder.layer.2.attention.self.query/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="297" name="__module.model.bert.encoder.layer.2.attention.self.query/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="298" name="Constant_8424" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="97075792" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="299" name="__module.model.bert.encoder.layer.2.attention.self.query/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="267,x.33">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="300" name="__module.model.bert.encoder.layer.2.attention.self.query/aten::linear/Add/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="97078864" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="301" name="__module.model.bert.encoder.layer.2.attention.self.query/aten::linear/Add/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="97078868" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="302" name="__module.model.bert.encoder.layer.2.attention.self.query/aten::linear/Add/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="97078864" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="303" name="__module.model.bert.encoder.layer.2.attention.self.query/aten::linear/Add/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="97078868" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="304" name="__module.model.bert.encoder.layer.2.attention.self.query/aten::linear/Add/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="305" name="__module.model.bert.encoder.layer.2.attention.self/prim::ListConstruct/Concat" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744716" size="32" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="306" name="__module.model.bert.encoder.layer.2.attention.self/aten::view/Reshape" type="Reshape" version="opset1">
+			<data special_zero="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="289,x.35">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="307" name="Constant_733" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744748" size="32" />
+			<output>
+				<port id="0" precision="I64" names="290">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="308" name="__module.model.bert.encoder.layer.2.attention.self/aten::permute/Transpose" type="Transpose" version="opset1">
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="291">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="309" name="Constant_356344" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 768" offset="97078872" size="589824" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="310" name="Convert_356345" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="311" name="Constant_356346" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="97668696" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="312" name="__module.model.bert.encoder.layer.2.attention.self.key/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="313" name="__module.model.bert.encoder.layer.2.attention.self.key/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="314" name="Constant_8425" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="97671768" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="315" name="__module.model.bert.encoder.layer.2.attention.self.key/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="270,x.25">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="316" name="__module.model.bert.encoder.layer.2.attention.self.key/aten::linear/Add/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="97674840" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="317" name="__module.model.bert.encoder.layer.2.attention.self.key/aten::linear/Add/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="97674844" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="318" name="__module.model.bert.encoder.layer.2.attention.self.key/aten::linear/Add/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="97674840" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="319" name="__module.model.bert.encoder.layer.2.attention.self.key/aten::linear/Add/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="97674844" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="320" name="__module.model.bert.encoder.layer.2.attention.self.key/aten::linear/Add/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="321" name="__module.model.bert.encoder.layer.2.attention.self/prim::ListConstruct/Concat_1" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744716" size="32" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="322" name="__module.model.bert.encoder.layer.2.attention.self/aten::view/Reshape_1" type="Reshape" version="opset1">
+			<data special_zero="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="274,x.27">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="323" name="Constant_693" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744748" size="32" />
+			<output>
+				<port id="0" precision="I64" names="275">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="324" name="__module.model.bert.encoder.layer.2.attention.self/aten::permute/Transpose_1" type="Transpose" version="opset1">
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="276,key_layer.5">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="325" name="__module.model.bert.encoder.layer.2.attention.self/aten::matmul/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="293,attention_scores.9">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="326" name="Constant_8426" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 1, 1" offset="83340756" size="4" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="327" name="__module.model.bert.encoder.layer.2.attention.self/aten::div/Divide" type="Divide" version="opset1">
+			<data auto_broadcast="numpy" m_pythondiv="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="294,attention_scores.11">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="328" name="__module.model.bert.encoder.layer.2.attention.self/aten::add/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="295,input.23">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="329" name="__module.model.bert.encoder.layer.2.attention.self/aten::softmax/Softmax" type="SoftMax" version="opset8">
+			<data axis="-1" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="296,input.25">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="330" name="Constant_356348" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 768" offset="97674848" size="589824" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="331" name="Convert_356349" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="332" name="Constant_356350" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="98264672" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="333" name="__module.model.bert.encoder.layer.2.attention.self.value/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="334" name="__module.model.bert.encoder.layer.2.attention.self.value/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="335" name="Constant_8427" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="98267744" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="336" name="__module.model.bert.encoder.layer.2.attention.self.value/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="279,x.29">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="337" name="__module.model.bert.encoder.layer.2.attention.self/prim::ListConstruct/Concat_2" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744716" size="32" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="338" name="__module.model.bert.encoder.layer.2.attention.self/aten::view/Reshape_2" type="Reshape" version="opset1">
+			<data special_zero="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="283,x.31">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="339" name="Constant_716" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744748" size="32" />
+			<output>
+				<port id="0" precision="I64" names="284">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="340" name="__module.model.bert.encoder.layer.2.attention.self/aten::permute/Transpose_2" type="Transpose" version="opset1">
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="285">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="341" name="__module.model.bert.encoder.layer.2.attention.self/aten::matmul/MatMul_1" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="false" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="298,context_layer.9">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="342" name="Constant_814" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744748" size="32" />
+			<output>
+				<port id="0" precision="I64" names="299">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="343" name="__module.model.bert.encoder.layer.2.attention.self/aten::permute/Transpose_3" type="Transpose" version="opset1">
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="300">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="344" name="__module.model.bert.encoder.layer.2.attention.self/prim::ListConstruct/Concat_3" type="Const" version="opset1">
+			<data element_type="i64" shape="3" offset="83936744" size="24" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="345" name="__module.model.bert.encoder.layer.2.attention.self/aten::view/Reshape_3" type="Reshape" version="opset1">
+			<data special_zero="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="305">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="346" name="__module.model.bert.encoder.layer.2.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/scale" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="98270816" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="347" name="__module.model.bert.encoder.layer.2.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="348" name="__module.model.bert.encoder.layer.2.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="98273888" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="349" name="__module.model.bert.encoder.layer.2.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="98273892" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="350" name="__module.model.bert.encoder.layer.2.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="98273888" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="351" name="__module.model.bert.encoder.layer.2.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="98273892" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="352" name="__module.model.bert.encoder.layer.2.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="353" name="Constant_356352" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 768" offset="98273896" size="589824" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="354" name="Convert_356353" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="355" name="Constant_356354" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="98863720" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="356" name="__module.model.bert.encoder.layer.2.attention.output.dense/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="357" name="__module.model.bert.encoder.layer.2.attention.output.dense/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="358" name="Constant_8428" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="98866792" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="359" name="__module.model.bert.encoder.layer.2.attention.output.dense/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="311,input.27">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="360" name="__module.model.bert.encoder.layer.2.attention.output/aten::add/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="313">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="361" name="__module.model.bert.encoder.layer.2.attention.output.LayerNorm/aten::layer_norm/Multiply" type="Const" version="opset1">
+			<data element_type="i32" shape="1" offset="82139512" size="4" />
+			<output>
+				<port id="0" precision="I32">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="362" name="__module.model.bert.encoder.layer.2.attention.output.LayerNorm/aten::layer_norm/MVN" type="MVN" version="opset6">
+			<data eps="9.999999960041972e-13" normalize_variance="true" eps_mode="INSIDE_SQRT" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I32">
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="363" name="Constant_8429" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="98869864" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="364" name="__module.model.bert.encoder.layer.2.attention.output.LayerNorm/aten::layer_norm/Multiply_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="365" name="Constant_8430" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="98872936" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="366" name="__module.model.bert.encoder.layer.2.attention.output.LayerNorm/aten::layer_norm/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="317,input_tensor.11">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="367" name="__module.model.bert.encoder.layer.2.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/scale" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="98876008" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="368" name="__module.model.bert.encoder.layer.2.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="369" name="__module.model.bert.encoder.layer.2.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="98879080" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="370" name="__module.model.bert.encoder.layer.2.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="98879084" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="371" name="__module.model.bert.encoder.layer.2.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="98879080" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="372" name="__module.model.bert.encoder.layer.2.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="98879084" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="373" name="__module.model.bert.encoder.layer.2.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="374" name="Constant_356356" type="Const" version="opset1">
+			<data element_type="i8" shape="3072, 768" offset="98879088" size="2359296" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="375" name="Convert_356357" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="376" name="Constant_356358" type="Const" version="opset1">
+			<data element_type="f32" shape="3072, 1" offset="101238384" size="12288" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>3072</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="377" name="__module.model.bert.encoder.layer.2.intermediate.dense/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>3072</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="378" name="__module.model.bert.encoder.layer.2.intermediate.dense/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="379" name="Constant_8431" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 3072" offset="101250672" size="12288" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="380" name="__module.model.bert.encoder.layer.2.intermediate.dense/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="322,input.29">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="381" name="__module.model.bert.encoder.layer.2.intermediate.intermediate_act_fn/aten::gelu/Gelu" type="Gelu" version="opset7">
+			<data approximation_mode="ERF" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="323">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="382" name="__module.model.bert.encoder.layer.2.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/scale" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 3072" offset="101262960" size="12288" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="383" name="__module.model.bert.encoder.layer.2.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="384" name="__module.model.bert.encoder.layer.2.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="101275248" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="385" name="__module.model.bert.encoder.layer.2.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="101275252" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="386" name="__module.model.bert.encoder.layer.2.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="101275248" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="387" name="__module.model.bert.encoder.layer.2.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="101275252" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="388" name="__module.model.bert.encoder.layer.2.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="389" name="Constant_356360" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 3072" offset="101275256" size="2359296" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="390" name="Convert_356361" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="391" name="Constant_356362" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="103634552" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="392" name="__module.model.bert.encoder.layer.2.output.dense/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="393" name="__module.model.bert.encoder.layer.2.output.dense/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="394" name="Constant_8432" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="103637624" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="395" name="__module.model.bert.encoder.layer.2.output.dense/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="329,input.31">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="396" name="__module.model.bert.encoder.layer.2.output/aten::add/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="331">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="397" name="__module.model.bert.encoder.layer.2.output.LayerNorm/aten::layer_norm/Multiply" type="Const" version="opset1">
+			<data element_type="i32" shape="1" offset="82139512" size="4" />
+			<output>
+				<port id="0" precision="I32">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="398" name="__module.model.bert.encoder.layer.2.output.LayerNorm/aten::layer_norm/MVN" type="MVN" version="opset6">
+			<data eps="9.999999960041972e-13" normalize_variance="true" eps_mode="INSIDE_SQRT" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I32">
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="399" name="Constant_8433" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="103640696" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="400" name="__module.model.bert.encoder.layer.2.output.LayerNorm/aten::layer_norm/Multiply_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="401" name="Constant_8434" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="103643768" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="402" name="__module.model.bert.encoder.layer.2.output.LayerNorm/aten::layer_norm/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="335,input_tensor.13">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="403" name="__module.model.bert.encoder.layer.2.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/scale" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="103646840" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="404" name="__module.model.bert.encoder.layer.2.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="405" name="__module.model.bert.encoder.layer.2.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="103649912" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="406" name="__module.model.bert.encoder.layer.2.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="103649916" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="407" name="__module.model.bert.encoder.layer.2.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="103649912" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="408" name="__module.model.bert.encoder.layer.2.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="103649916" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="409" name="__module.model.bert.encoder.layer.2.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="410" name="Constant_356364" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 768" offset="103649920" size="589824" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="411" name="Convert_356365" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="412" name="Constant_356366" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="104239744" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="413" name="__module.model.bert.encoder.layer.3.attention.self.query/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="414" name="__module.model.bert.encoder.layer.3.attention.self.query/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="415" name="Constant_8435" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="104242816" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="416" name="__module.model.bert.encoder.layer.3.attention.self.query/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="346,x.45">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="417" name="__module.model.bert.encoder.layer.3.attention.self.query/aten::linear/Add/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="104245888" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="418" name="__module.model.bert.encoder.layer.3.attention.self.query/aten::linear/Add/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="104245892" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="419" name="__module.model.bert.encoder.layer.3.attention.self.query/aten::linear/Add/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="104245888" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="420" name="__module.model.bert.encoder.layer.3.attention.self.query/aten::linear/Add/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="104245892" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="421" name="__module.model.bert.encoder.layer.3.attention.self.query/aten::linear/Add/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="422" name="__module.model.bert.encoder.layer.3.attention.self/prim::ListConstruct/Concat" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744716" size="32" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="423" name="__module.model.bert.encoder.layer.3.attention.self/aten::view/Reshape" type="Reshape" version="opset1">
+			<data special_zero="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="368,x.47">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="424" name="Constant_979" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744748" size="32" />
+			<output>
+				<port id="0" precision="I64" names="369">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="425" name="__module.model.bert.encoder.layer.3.attention.self/aten::permute/Transpose" type="Transpose" version="opset1">
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="370">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="426" name="Constant_356368" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 768" offset="104245896" size="589824" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="427" name="Convert_356369" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="428" name="Constant_356370" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="104835720" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="429" name="__module.model.bert.encoder.layer.3.attention.self.key/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="430" name="__module.model.bert.encoder.layer.3.attention.self.key/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="431" name="Constant_8436" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="104838792" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="432" name="__module.model.bert.encoder.layer.3.attention.self.key/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="349,x.37">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="433" name="__module.model.bert.encoder.layer.3.attention.self.key/aten::linear/Add/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="104841864" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="434" name="__module.model.bert.encoder.layer.3.attention.self.key/aten::linear/Add/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="104841868" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="435" name="__module.model.bert.encoder.layer.3.attention.self.key/aten::linear/Add/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="104841864" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="436" name="__module.model.bert.encoder.layer.3.attention.self.key/aten::linear/Add/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="104841868" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="437" name="__module.model.bert.encoder.layer.3.attention.self.key/aten::linear/Add/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="438" name="__module.model.bert.encoder.layer.3.attention.self/prim::ListConstruct/Concat_1" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744716" size="32" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="439" name="__module.model.bert.encoder.layer.3.attention.self/aten::view/Reshape_1" type="Reshape" version="opset1">
+			<data special_zero="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="353,x.39">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="440" name="Constant_939" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744748" size="32" />
+			<output>
+				<port id="0" precision="I64" names="354">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="441" name="__module.model.bert.encoder.layer.3.attention.self/aten::permute/Transpose_1" type="Transpose" version="opset1">
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="355,key_layer.7">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="442" name="__module.model.bert.encoder.layer.3.attention.self/aten::matmul/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="372,attention_scores.13">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="443" name="Constant_8437" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 1, 1" offset="83340756" size="4" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="444" name="__module.model.bert.encoder.layer.3.attention.self/aten::div/Divide" type="Divide" version="opset1">
+			<data auto_broadcast="numpy" m_pythondiv="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="373,attention_scores.15">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="445" name="__module.model.bert.encoder.layer.3.attention.self/aten::add/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="374,input.33">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="446" name="__module.model.bert.encoder.layer.3.attention.self/aten::softmax/Softmax" type="SoftMax" version="opset8">
+			<data axis="-1" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="375,input.35">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="447" name="Constant_356372" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 768" offset="104841872" size="589824" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="448" name="Convert_356373" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="449" name="Constant_356374" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="105431696" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="450" name="__module.model.bert.encoder.layer.3.attention.self.value/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="451" name="__module.model.bert.encoder.layer.3.attention.self.value/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="452" name="Constant_8438" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="105434768" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="453" name="__module.model.bert.encoder.layer.3.attention.self.value/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="358,x.41">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="454" name="__module.model.bert.encoder.layer.3.attention.self/prim::ListConstruct/Concat_2" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744716" size="32" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="455" name="__module.model.bert.encoder.layer.3.attention.self/aten::view/Reshape_2" type="Reshape" version="opset1">
+			<data special_zero="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="362,x.43">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="456" name="Constant_962" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744748" size="32" />
+			<output>
+				<port id="0" precision="I64" names="363">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="457" name="__module.model.bert.encoder.layer.3.attention.self/aten::permute/Transpose_2" type="Transpose" version="opset1">
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="364">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="458" name="__module.model.bert.encoder.layer.3.attention.self/aten::matmul/MatMul_1" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="false" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="377,context_layer.13">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="459" name="Constant_1060" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744748" size="32" />
+			<output>
+				<port id="0" precision="I64" names="378">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="460" name="__module.model.bert.encoder.layer.3.attention.self/aten::permute/Transpose_3" type="Transpose" version="opset1">
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="379">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="461" name="__module.model.bert.encoder.layer.3.attention.self/prim::ListConstruct/Concat_3" type="Const" version="opset1">
+			<data element_type="i64" shape="3" offset="83936744" size="24" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="462" name="__module.model.bert.encoder.layer.3.attention.self/aten::view/Reshape_3" type="Reshape" version="opset1">
+			<data special_zero="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="384">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="463" name="__module.model.bert.encoder.layer.3.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/scale" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="105437840" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="464" name="__module.model.bert.encoder.layer.3.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="465" name="__module.model.bert.encoder.layer.3.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="105440912" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="466" name="__module.model.bert.encoder.layer.3.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="105440916" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="467" name="__module.model.bert.encoder.layer.3.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="105440912" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="468" name="__module.model.bert.encoder.layer.3.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="105440916" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="469" name="__module.model.bert.encoder.layer.3.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="470" name="Constant_356376" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 768" offset="105440920" size="589824" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="471" name="Convert_356377" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="472" name="Constant_356378" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="106030744" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="473" name="__module.model.bert.encoder.layer.3.attention.output.dense/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="474" name="__module.model.bert.encoder.layer.3.attention.output.dense/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="475" name="Constant_8439" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="106033816" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="476" name="__module.model.bert.encoder.layer.3.attention.output.dense/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="390,input.37">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="477" name="__module.model.bert.encoder.layer.3.attention.output/aten::add/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="392">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="478" name="__module.model.bert.encoder.layer.3.attention.output.LayerNorm/aten::layer_norm/Multiply" type="Const" version="opset1">
+			<data element_type="i32" shape="1" offset="82139512" size="4" />
+			<output>
+				<port id="0" precision="I32">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="479" name="__module.model.bert.encoder.layer.3.attention.output.LayerNorm/aten::layer_norm/MVN" type="MVN" version="opset6">
+			<data eps="9.999999960041972e-13" normalize_variance="true" eps_mode="INSIDE_SQRT" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I32">
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="480" name="Constant_8440" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="106036888" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="481" name="__module.model.bert.encoder.layer.3.attention.output.LayerNorm/aten::layer_norm/Multiply_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="482" name="Constant_8441" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="106039960" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="483" name="__module.model.bert.encoder.layer.3.attention.output.LayerNorm/aten::layer_norm/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="396,input_tensor.15">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="484" name="__module.model.bert.encoder.layer.3.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/scale" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="106043032" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="485" name="__module.model.bert.encoder.layer.3.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="486" name="__module.model.bert.encoder.layer.3.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="106046104" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="487" name="__module.model.bert.encoder.layer.3.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="106046108" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="488" name="__module.model.bert.encoder.layer.3.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="106046104" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="489" name="__module.model.bert.encoder.layer.3.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="106046108" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="490" name="__module.model.bert.encoder.layer.3.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="491" name="Constant_356380" type="Const" version="opset1">
+			<data element_type="i8" shape="3072, 768" offset="106046112" size="2359296" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="492" name="Convert_356381" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="493" name="Constant_356382" type="Const" version="opset1">
+			<data element_type="f32" shape="3072, 1" offset="108405408" size="12288" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>3072</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="494" name="__module.model.bert.encoder.layer.3.intermediate.dense/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>3072</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="495" name="__module.model.bert.encoder.layer.3.intermediate.dense/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="496" name="Constant_8442" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 3072" offset="108417696" size="12288" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="497" name="__module.model.bert.encoder.layer.3.intermediate.dense/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="401,input.39">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="498" name="__module.model.bert.encoder.layer.3.intermediate.intermediate_act_fn/aten::gelu/Gelu" type="Gelu" version="opset7">
+			<data approximation_mode="ERF" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="402">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="499" name="__module.model.bert.encoder.layer.3.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/scale" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 3072" offset="108429984" size="12288" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="500" name="__module.model.bert.encoder.layer.3.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="501" name="__module.model.bert.encoder.layer.3.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="108442272" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="502" name="__module.model.bert.encoder.layer.3.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="108442276" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="503" name="__module.model.bert.encoder.layer.3.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="108442272" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="504" name="__module.model.bert.encoder.layer.3.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="108442276" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="505" name="__module.model.bert.encoder.layer.3.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="506" name="Constant_356384" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 3072" offset="108442280" size="2359296" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="507" name="Convert_356385" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="508" name="Constant_356386" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="110801576" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="509" name="__module.model.bert.encoder.layer.3.output.dense/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="510" name="__module.model.bert.encoder.layer.3.output.dense/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="511" name="Constant_8443" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="110804648" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="512" name="__module.model.bert.encoder.layer.3.output.dense/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="408,input.41">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="513" name="__module.model.bert.encoder.layer.3.output/aten::add/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="410">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="514" name="__module.model.bert.encoder.layer.3.output.LayerNorm/aten::layer_norm/Multiply" type="Const" version="opset1">
+			<data element_type="i32" shape="1" offset="82139512" size="4" />
+			<output>
+				<port id="0" precision="I32">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="515" name="__module.model.bert.encoder.layer.3.output.LayerNorm/aten::layer_norm/MVN" type="MVN" version="opset6">
+			<data eps="9.999999960041972e-13" normalize_variance="true" eps_mode="INSIDE_SQRT" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I32">
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="516" name="Constant_8444" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="110807720" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="517" name="__module.model.bert.encoder.layer.3.output.LayerNorm/aten::layer_norm/Multiply_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="518" name="Constant_8445" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="110810792" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="519" name="__module.model.bert.encoder.layer.3.output.LayerNorm/aten::layer_norm/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="414,input_tensor.17">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="520" name="__module.model.bert.encoder.layer.3.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/scale" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="110813864" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="521" name="__module.model.bert.encoder.layer.3.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="522" name="__module.model.bert.encoder.layer.3.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="110816936" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="523" name="__module.model.bert.encoder.layer.3.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="110816940" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="524" name="__module.model.bert.encoder.layer.3.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="110816936" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="525" name="__module.model.bert.encoder.layer.3.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="110816940" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="526" name="__module.model.bert.encoder.layer.3.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="527" name="Constant_356388" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 768" offset="110816944" size="589824" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="528" name="Convert_356389" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="529" name="Constant_356390" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="111406768" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="530" name="__module.model.bert.encoder.layer.4.attention.self.query/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="531" name="__module.model.bert.encoder.layer.4.attention.self.query/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="532" name="Constant_8446" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="111409840" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="533" name="__module.model.bert.encoder.layer.4.attention.self.query/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="425,x.57">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="534" name="__module.model.bert.encoder.layer.4.attention.self.query/aten::linear/Add/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="111412912" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="535" name="__module.model.bert.encoder.layer.4.attention.self.query/aten::linear/Add/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="111412916" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="536" name="__module.model.bert.encoder.layer.4.attention.self.query/aten::linear/Add/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="111412912" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="537" name="__module.model.bert.encoder.layer.4.attention.self.query/aten::linear/Add/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="111412916" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="538" name="__module.model.bert.encoder.layer.4.attention.self.query/aten::linear/Add/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="539" name="__module.model.bert.encoder.layer.4.attention.self/prim::ListConstruct/Concat" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744716" size="32" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="540" name="__module.model.bert.encoder.layer.4.attention.self/aten::view/Reshape" type="Reshape" version="opset1">
+			<data special_zero="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="447,x.59">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="541" name="Constant_1225" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744748" size="32" />
+			<output>
+				<port id="0" precision="I64" names="448">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="542" name="__module.model.bert.encoder.layer.4.attention.self/aten::permute/Transpose" type="Transpose" version="opset1">
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="449">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="543" name="Constant_356392" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 768" offset="111412920" size="589824" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="544" name="Convert_356393" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="545" name="Constant_356394" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="112002744" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="546" name="__module.model.bert.encoder.layer.4.attention.self.key/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="547" name="__module.model.bert.encoder.layer.4.attention.self.key/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="548" name="Constant_8447" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="112005816" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="549" name="__module.model.bert.encoder.layer.4.attention.self.key/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="428,x.49">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="550" name="__module.model.bert.encoder.layer.4.attention.self.key/aten::linear/Add/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="112008888" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="551" name="__module.model.bert.encoder.layer.4.attention.self.key/aten::linear/Add/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="112008892" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="552" name="__module.model.bert.encoder.layer.4.attention.self.key/aten::linear/Add/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="112008888" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="553" name="__module.model.bert.encoder.layer.4.attention.self.key/aten::linear/Add/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="112008892" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="554" name="__module.model.bert.encoder.layer.4.attention.self.key/aten::linear/Add/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="555" name="__module.model.bert.encoder.layer.4.attention.self/prim::ListConstruct/Concat_1" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744716" size="32" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="556" name="__module.model.bert.encoder.layer.4.attention.self/aten::view/Reshape_1" type="Reshape" version="opset1">
+			<data special_zero="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="432,x.51">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="557" name="Constant_1185" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744748" size="32" />
+			<output>
+				<port id="0" precision="I64" names="433">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="558" name="__module.model.bert.encoder.layer.4.attention.self/aten::permute/Transpose_1" type="Transpose" version="opset1">
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="434,key_layer.9">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="559" name="__module.model.bert.encoder.layer.4.attention.self/aten::matmul/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="451,attention_scores.17">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="560" name="Constant_8448" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 1, 1" offset="83340756" size="4" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="561" name="__module.model.bert.encoder.layer.4.attention.self/aten::div/Divide" type="Divide" version="opset1">
+			<data auto_broadcast="numpy" m_pythondiv="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="452,attention_scores.19">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="562" name="__module.model.bert.encoder.layer.4.attention.self/aten::add/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="453,input.43">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="563" name="__module.model.bert.encoder.layer.4.attention.self/aten::softmax/Softmax" type="SoftMax" version="opset8">
+			<data axis="-1" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="454,input.45">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="564" name="Constant_356396" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 768" offset="112008896" size="589824" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="565" name="Convert_356397" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="566" name="Constant_356398" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="112598720" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="567" name="__module.model.bert.encoder.layer.4.attention.self.value/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="568" name="__module.model.bert.encoder.layer.4.attention.self.value/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="569" name="Constant_8449" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="112601792" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="570" name="__module.model.bert.encoder.layer.4.attention.self.value/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="437,x.53">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="571" name="__module.model.bert.encoder.layer.4.attention.self/prim::ListConstruct/Concat_2" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744716" size="32" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="572" name="__module.model.bert.encoder.layer.4.attention.self/aten::view/Reshape_2" type="Reshape" version="opset1">
+			<data special_zero="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="441,x.55">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="573" name="Constant_1208" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744748" size="32" />
+			<output>
+				<port id="0" precision="I64" names="442">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="574" name="__module.model.bert.encoder.layer.4.attention.self/aten::permute/Transpose_2" type="Transpose" version="opset1">
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="443">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="575" name="__module.model.bert.encoder.layer.4.attention.self/aten::matmul/MatMul_1" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="false" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="456,context_layer.17">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="576" name="Constant_1306" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744748" size="32" />
+			<output>
+				<port id="0" precision="I64" names="457">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="577" name="__module.model.bert.encoder.layer.4.attention.self/aten::permute/Transpose_3" type="Transpose" version="opset1">
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="458">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="578" name="__module.model.bert.encoder.layer.4.attention.self/prim::ListConstruct/Concat_3" type="Const" version="opset1">
+			<data element_type="i64" shape="3" offset="83936744" size="24" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="579" name="__module.model.bert.encoder.layer.4.attention.self/aten::view/Reshape_3" type="Reshape" version="opset1">
+			<data special_zero="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="463">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="580" name="__module.model.bert.encoder.layer.4.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/scale" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="112604864" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="581" name="__module.model.bert.encoder.layer.4.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="582" name="__module.model.bert.encoder.layer.4.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="112607936" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="583" name="__module.model.bert.encoder.layer.4.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="112607940" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="584" name="__module.model.bert.encoder.layer.4.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="112607936" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="585" name="__module.model.bert.encoder.layer.4.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="112607940" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="586" name="__module.model.bert.encoder.layer.4.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="587" name="Constant_356400" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 768" offset="112607944" size="589824" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="588" name="Convert_356401" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="589" name="Constant_356402" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="113197768" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="590" name="__module.model.bert.encoder.layer.4.attention.output.dense/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="591" name="__module.model.bert.encoder.layer.4.attention.output.dense/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="592" name="Constant_8450" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="113200840" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="593" name="__module.model.bert.encoder.layer.4.attention.output.dense/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="469,input.47">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="594" name="__module.model.bert.encoder.layer.4.attention.output/aten::add/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="471">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="595" name="__module.model.bert.encoder.layer.4.attention.output.LayerNorm/aten::layer_norm/Multiply" type="Const" version="opset1">
+			<data element_type="i32" shape="1" offset="82139512" size="4" />
+			<output>
+				<port id="0" precision="I32">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="596" name="__module.model.bert.encoder.layer.4.attention.output.LayerNorm/aten::layer_norm/MVN" type="MVN" version="opset6">
+			<data eps="9.999999960041972e-13" normalize_variance="true" eps_mode="INSIDE_SQRT" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I32">
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="597" name="Constant_8451" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="113203912" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="598" name="__module.model.bert.encoder.layer.4.attention.output.LayerNorm/aten::layer_norm/Multiply_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="599" name="Constant_8452" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="113206984" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="600" name="__module.model.bert.encoder.layer.4.attention.output.LayerNorm/aten::layer_norm/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="475,input_tensor.19">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="601" name="__module.model.bert.encoder.layer.4.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/scale" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="113210056" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="602" name="__module.model.bert.encoder.layer.4.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="603" name="__module.model.bert.encoder.layer.4.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="113213128" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="604" name="__module.model.bert.encoder.layer.4.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="113213132" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="605" name="__module.model.bert.encoder.layer.4.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="113213128" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="606" name="__module.model.bert.encoder.layer.4.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="113213132" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="607" name="__module.model.bert.encoder.layer.4.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="608" name="Constant_356404" type="Const" version="opset1">
+			<data element_type="i8" shape="3072, 768" offset="113213136" size="2359296" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="609" name="Convert_356405" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="610" name="Constant_356406" type="Const" version="opset1">
+			<data element_type="f32" shape="3072, 1" offset="115572432" size="12288" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>3072</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="611" name="__module.model.bert.encoder.layer.4.intermediate.dense/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>3072</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="612" name="__module.model.bert.encoder.layer.4.intermediate.dense/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="613" name="Constant_8453" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 3072" offset="115584720" size="12288" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="614" name="__module.model.bert.encoder.layer.4.intermediate.dense/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="480,input.49">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="615" name="__module.model.bert.encoder.layer.4.intermediate.intermediate_act_fn/aten::gelu/Gelu" type="Gelu" version="opset7">
+			<data approximation_mode="ERF" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="481">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="616" name="__module.model.bert.encoder.layer.4.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/scale" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 3072" offset="115597008" size="12288" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="617" name="__module.model.bert.encoder.layer.4.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="618" name="__module.model.bert.encoder.layer.4.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="115609296" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="619" name="__module.model.bert.encoder.layer.4.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="115609300" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="620" name="__module.model.bert.encoder.layer.4.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="115609296" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="621" name="__module.model.bert.encoder.layer.4.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="115609300" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="622" name="__module.model.bert.encoder.layer.4.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="623" name="Constant_356408" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 3072" offset="115609304" size="2359296" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="624" name="Convert_356409" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="625" name="Constant_356410" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="117968600" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="626" name="__module.model.bert.encoder.layer.4.output.dense/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="627" name="__module.model.bert.encoder.layer.4.output.dense/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="628" name="Constant_8454" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="117971672" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="629" name="__module.model.bert.encoder.layer.4.output.dense/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="487,input.51">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="630" name="__module.model.bert.encoder.layer.4.output/aten::add/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="489">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="631" name="__module.model.bert.encoder.layer.4.output.LayerNorm/aten::layer_norm/Multiply" type="Const" version="opset1">
+			<data element_type="i32" shape="1" offset="82139512" size="4" />
+			<output>
+				<port id="0" precision="I32">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="632" name="__module.model.bert.encoder.layer.4.output.LayerNorm/aten::layer_norm/MVN" type="MVN" version="opset6">
+			<data eps="9.999999960041972e-13" normalize_variance="true" eps_mode="INSIDE_SQRT" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I32">
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="633" name="Constant_8455" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="117974744" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="634" name="__module.model.bert.encoder.layer.4.output.LayerNorm/aten::layer_norm/Multiply_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="635" name="Constant_8456" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="117977816" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="636" name="__module.model.bert.encoder.layer.4.output.LayerNorm/aten::layer_norm/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="493,input_tensor.21">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="637" name="__module.model.bert.encoder.layer.4.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/scale" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="117980888" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="638" name="__module.model.bert.encoder.layer.4.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="639" name="__module.model.bert.encoder.layer.4.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="117983960" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="640" name="__module.model.bert.encoder.layer.4.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="117983964" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="641" name="__module.model.bert.encoder.layer.4.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="117983960" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="642" name="__module.model.bert.encoder.layer.4.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="117983964" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="643" name="__module.model.bert.encoder.layer.4.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="644" name="Constant_356412" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 768" offset="117983968" size="589824" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="645" name="Convert_356413" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="646" name="Constant_356414" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="118573792" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="647" name="__module.model.bert.encoder.layer.5.attention.self.query/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="648" name="__module.model.bert.encoder.layer.5.attention.self.query/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="649" name="Constant_8457" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="118576864" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="650" name="__module.model.bert.encoder.layer.5.attention.self.query/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="504,x.69">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="651" name="__module.model.bert.encoder.layer.5.attention.self.query/aten::linear/Add/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="118579936" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="652" name="__module.model.bert.encoder.layer.5.attention.self.query/aten::linear/Add/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="118579940" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="653" name="__module.model.bert.encoder.layer.5.attention.self.query/aten::linear/Add/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="118579936" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="654" name="__module.model.bert.encoder.layer.5.attention.self.query/aten::linear/Add/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="118579940" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="655" name="__module.model.bert.encoder.layer.5.attention.self.query/aten::linear/Add/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="656" name="__module.model.bert.encoder.layer.5.attention.self/prim::ListConstruct/Concat" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744716" size="32" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="657" name="__module.model.bert.encoder.layer.5.attention.self/aten::view/Reshape" type="Reshape" version="opset1">
+			<data special_zero="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="526,x.71">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="658" name="Constant_1471" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744748" size="32" />
+			<output>
+				<port id="0" precision="I64" names="527">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="659" name="__module.model.bert.encoder.layer.5.attention.self/aten::permute/Transpose" type="Transpose" version="opset1">
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="528">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="660" name="Constant_356416" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 768" offset="118579944" size="589824" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="661" name="Convert_356417" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="662" name="Constant_356418" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="119169768" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="663" name="__module.model.bert.encoder.layer.5.attention.self.key/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="664" name="__module.model.bert.encoder.layer.5.attention.self.key/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="665" name="Constant_8458" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="119172840" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="666" name="__module.model.bert.encoder.layer.5.attention.self.key/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="507,x.61">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="667" name="__module.model.bert.encoder.layer.5.attention.self.key/aten::linear/Add/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="119175912" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="668" name="__module.model.bert.encoder.layer.5.attention.self.key/aten::linear/Add/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="119175916" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="669" name="__module.model.bert.encoder.layer.5.attention.self.key/aten::linear/Add/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="119175912" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="670" name="__module.model.bert.encoder.layer.5.attention.self.key/aten::linear/Add/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="119175916" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="671" name="__module.model.bert.encoder.layer.5.attention.self.key/aten::linear/Add/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="672" name="__module.model.bert.encoder.layer.5.attention.self/prim::ListConstruct/Concat_1" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744716" size="32" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="673" name="__module.model.bert.encoder.layer.5.attention.self/aten::view/Reshape_1" type="Reshape" version="opset1">
+			<data special_zero="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="511,x.63">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="674" name="Constant_1431" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744748" size="32" />
+			<output>
+				<port id="0" precision="I64" names="512">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="675" name="__module.model.bert.encoder.layer.5.attention.self/aten::permute/Transpose_1" type="Transpose" version="opset1">
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="513,key_layer.11">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="676" name="__module.model.bert.encoder.layer.5.attention.self/aten::matmul/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="530,attention_scores.21">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="677" name="Constant_8459" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 1, 1" offset="83340756" size="4" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="678" name="__module.model.bert.encoder.layer.5.attention.self/aten::div/Divide" type="Divide" version="opset1">
+			<data auto_broadcast="numpy" m_pythondiv="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="531,attention_scores.23">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="679" name="__module.model.bert.encoder.layer.5.attention.self/aten::add/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="532,input.53">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="680" name="__module.model.bert.encoder.layer.5.attention.self/aten::softmax/Softmax" type="SoftMax" version="opset8">
+			<data axis="-1" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="533,input.55">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="681" name="Constant_356420" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 768" offset="119175920" size="589824" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="682" name="Convert_356421" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="683" name="Constant_356422" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="119765744" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="684" name="__module.model.bert.encoder.layer.5.attention.self.value/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="685" name="__module.model.bert.encoder.layer.5.attention.self.value/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="686" name="Constant_8460" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="119768816" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="687" name="__module.model.bert.encoder.layer.5.attention.self.value/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="516,x.65">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="688" name="__module.model.bert.encoder.layer.5.attention.self/prim::ListConstruct/Concat_2" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744716" size="32" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="689" name="__module.model.bert.encoder.layer.5.attention.self/aten::view/Reshape_2" type="Reshape" version="opset1">
+			<data special_zero="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="520,x.67">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="690" name="Constant_1454" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744748" size="32" />
+			<output>
+				<port id="0" precision="I64" names="521">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="691" name="__module.model.bert.encoder.layer.5.attention.self/aten::permute/Transpose_2" type="Transpose" version="opset1">
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="522">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="692" name="__module.model.bert.encoder.layer.5.attention.self/aten::matmul/MatMul_1" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="false" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="535,context_layer.21">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="693" name="Constant_1552" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744748" size="32" />
+			<output>
+				<port id="0" precision="I64" names="536">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="694" name="__module.model.bert.encoder.layer.5.attention.self/aten::permute/Transpose_3" type="Transpose" version="opset1">
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="537">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="695" name="__module.model.bert.encoder.layer.5.attention.self/prim::ListConstruct/Concat_3" type="Const" version="opset1">
+			<data element_type="i64" shape="3" offset="83936744" size="24" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="696" name="__module.model.bert.encoder.layer.5.attention.self/aten::view/Reshape_3" type="Reshape" version="opset1">
+			<data special_zero="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="542">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="697" name="__module.model.bert.encoder.layer.5.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/scale" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="119771888" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="698" name="__module.model.bert.encoder.layer.5.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="699" name="__module.model.bert.encoder.layer.5.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="119774960" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="700" name="__module.model.bert.encoder.layer.5.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="119774964" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="701" name="__module.model.bert.encoder.layer.5.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="119774960" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="702" name="__module.model.bert.encoder.layer.5.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="119774964" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="703" name="__module.model.bert.encoder.layer.5.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="704" name="Constant_356424" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 768" offset="119774968" size="589824" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="705" name="Convert_356425" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="706" name="Constant_356426" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="120364792" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="707" name="__module.model.bert.encoder.layer.5.attention.output.dense/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="708" name="__module.model.bert.encoder.layer.5.attention.output.dense/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="709" name="Constant_8461" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="120367864" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="710" name="__module.model.bert.encoder.layer.5.attention.output.dense/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="548,input.57">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="711" name="__module.model.bert.encoder.layer.5.attention.output/aten::add/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="550">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="712" name="__module.model.bert.encoder.layer.5.attention.output.LayerNorm/aten::layer_norm/Multiply" type="Const" version="opset1">
+			<data element_type="i32" shape="1" offset="82139512" size="4" />
+			<output>
+				<port id="0" precision="I32">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="713" name="__module.model.bert.encoder.layer.5.attention.output.LayerNorm/aten::layer_norm/MVN" type="MVN" version="opset6">
+			<data eps="9.999999960041972e-13" normalize_variance="true" eps_mode="INSIDE_SQRT" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I32">
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="714" name="Constant_8462" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="120370936" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="715" name="__module.model.bert.encoder.layer.5.attention.output.LayerNorm/aten::layer_norm/Multiply_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="716" name="Constant_8463" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="120374008" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="717" name="__module.model.bert.encoder.layer.5.attention.output.LayerNorm/aten::layer_norm/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="554,input_tensor.23">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="718" name="__module.model.bert.encoder.layer.5.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/scale" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="120377080" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="719" name="__module.model.bert.encoder.layer.5.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="720" name="__module.model.bert.encoder.layer.5.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="120380152" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="721" name="__module.model.bert.encoder.layer.5.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="120380156" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="722" name="__module.model.bert.encoder.layer.5.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="120380152" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="723" name="__module.model.bert.encoder.layer.5.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="120380156" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="724" name="__module.model.bert.encoder.layer.5.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="725" name="Constant_356428" type="Const" version="opset1">
+			<data element_type="i8" shape="3072, 768" offset="120380160" size="2359296" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="726" name="Convert_356429" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="727" name="Constant_356430" type="Const" version="opset1">
+			<data element_type="f32" shape="3072, 1" offset="122739456" size="12288" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>3072</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="728" name="__module.model.bert.encoder.layer.5.intermediate.dense/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>3072</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="729" name="__module.model.bert.encoder.layer.5.intermediate.dense/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="730" name="Constant_8464" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 3072" offset="122751744" size="12288" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="731" name="__module.model.bert.encoder.layer.5.intermediate.dense/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="559,input.59">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="732" name="__module.model.bert.encoder.layer.5.intermediate.intermediate_act_fn/aten::gelu/Gelu" type="Gelu" version="opset7">
+			<data approximation_mode="ERF" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="560">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="733" name="__module.model.bert.encoder.layer.5.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/scale" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 3072" offset="122764032" size="12288" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="734" name="__module.model.bert.encoder.layer.5.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="735" name="__module.model.bert.encoder.layer.5.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="122776320" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="736" name="__module.model.bert.encoder.layer.5.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="122776324" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="737" name="__module.model.bert.encoder.layer.5.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="122776320" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="738" name="__module.model.bert.encoder.layer.5.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="122776324" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="739" name="__module.model.bert.encoder.layer.5.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="740" name="Constant_356432" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 3072" offset="122776328" size="2359296" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="741" name="Convert_356433" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="742" name="Constant_356434" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="125135624" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="743" name="__module.model.bert.encoder.layer.5.output.dense/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="744" name="__module.model.bert.encoder.layer.5.output.dense/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="745" name="Constant_8465" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="125138696" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="746" name="__module.model.bert.encoder.layer.5.output.dense/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="566,input.61">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="747" name="__module.model.bert.encoder.layer.5.output/aten::add/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="568">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="748" name="__module.model.bert.encoder.layer.5.output.LayerNorm/aten::layer_norm/Multiply" type="Const" version="opset1">
+			<data element_type="i32" shape="1" offset="82139512" size="4" />
+			<output>
+				<port id="0" precision="I32">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="749" name="__module.model.bert.encoder.layer.5.output.LayerNorm/aten::layer_norm/MVN" type="MVN" version="opset6">
+			<data eps="9.999999960041972e-13" normalize_variance="true" eps_mode="INSIDE_SQRT" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I32">
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="750" name="Constant_8466" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="125141768" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="751" name="__module.model.bert.encoder.layer.5.output.LayerNorm/aten::layer_norm/Multiply_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="752" name="Constant_8467" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="125144840" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="753" name="__module.model.bert.encoder.layer.5.output.LayerNorm/aten::layer_norm/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="572,input_tensor.25">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="754" name="__module.model.bert.encoder.layer.5.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/scale" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="125147912" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="755" name="__module.model.bert.encoder.layer.5.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="756" name="__module.model.bert.encoder.layer.5.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="125150984" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="757" name="__module.model.bert.encoder.layer.5.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="125150988" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="758" name="__module.model.bert.encoder.layer.5.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="125150984" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="759" name="__module.model.bert.encoder.layer.5.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="125150988" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="760" name="__module.model.bert.encoder.layer.5.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="761" name="Constant_356436" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 768" offset="125150992" size="589824" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="762" name="Convert_356437" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="763" name="Constant_356438" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="125740816" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="764" name="__module.model.bert.encoder.layer.6.attention.self.query/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="765" name="__module.model.bert.encoder.layer.6.attention.self.query/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="766" name="Constant_8468" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="125743888" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="767" name="__module.model.bert.encoder.layer.6.attention.self.query/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="583,x.81">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="768" name="__module.model.bert.encoder.layer.6.attention.self.query/aten::linear/Add/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="125746960" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="769" name="__module.model.bert.encoder.layer.6.attention.self.query/aten::linear/Add/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="125746964" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="770" name="__module.model.bert.encoder.layer.6.attention.self.query/aten::linear/Add/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="125746960" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="771" name="__module.model.bert.encoder.layer.6.attention.self.query/aten::linear/Add/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="125746964" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="772" name="__module.model.bert.encoder.layer.6.attention.self.query/aten::linear/Add/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="773" name="__module.model.bert.encoder.layer.6.attention.self/prim::ListConstruct/Concat" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744716" size="32" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="774" name="__module.model.bert.encoder.layer.6.attention.self/aten::view/Reshape" type="Reshape" version="opset1">
+			<data special_zero="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="605,x.83">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="775" name="Constant_1717" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744748" size="32" />
+			<output>
+				<port id="0" precision="I64" names="606">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="776" name="__module.model.bert.encoder.layer.6.attention.self/aten::permute/Transpose" type="Transpose" version="opset1">
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="607">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="777" name="Constant_356440" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 768" offset="125746968" size="589824" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="778" name="Convert_356441" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="779" name="Constant_356442" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="126336792" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="780" name="__module.model.bert.encoder.layer.6.attention.self.key/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="781" name="__module.model.bert.encoder.layer.6.attention.self.key/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="782" name="Constant_8469" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="126339864" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="783" name="__module.model.bert.encoder.layer.6.attention.self.key/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="586,x.73">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="784" name="__module.model.bert.encoder.layer.6.attention.self.key/aten::linear/Add/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="126342936" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="785" name="__module.model.bert.encoder.layer.6.attention.self.key/aten::linear/Add/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="126342940" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="786" name="__module.model.bert.encoder.layer.6.attention.self.key/aten::linear/Add/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="126342936" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="787" name="__module.model.bert.encoder.layer.6.attention.self.key/aten::linear/Add/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="126342940" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="788" name="__module.model.bert.encoder.layer.6.attention.self.key/aten::linear/Add/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="789" name="__module.model.bert.encoder.layer.6.attention.self/prim::ListConstruct/Concat_1" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744716" size="32" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="790" name="__module.model.bert.encoder.layer.6.attention.self/aten::view/Reshape_1" type="Reshape" version="opset1">
+			<data special_zero="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="590,x.75">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="791" name="Constant_1677" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744748" size="32" />
+			<output>
+				<port id="0" precision="I64" names="591">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="792" name="__module.model.bert.encoder.layer.6.attention.self/aten::permute/Transpose_1" type="Transpose" version="opset1">
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="592,key_layer.13">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="793" name="__module.model.bert.encoder.layer.6.attention.self/aten::matmul/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="609,attention_scores.25">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="794" name="Constant_8470" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 1, 1" offset="83340756" size="4" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="795" name="__module.model.bert.encoder.layer.6.attention.self/aten::div/Divide" type="Divide" version="opset1">
+			<data auto_broadcast="numpy" m_pythondiv="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="610,attention_scores.27">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="796" name="__module.model.bert.encoder.layer.6.attention.self/aten::add/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="611,input.63">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="797" name="__module.model.bert.encoder.layer.6.attention.self/aten::softmax/Softmax" type="SoftMax" version="opset8">
+			<data axis="-1" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="612,input.65">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="798" name="Constant_356444" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 768" offset="126342944" size="589824" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="799" name="Convert_356445" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="800" name="Constant_356446" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="126932768" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="801" name="__module.model.bert.encoder.layer.6.attention.self.value/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="802" name="__module.model.bert.encoder.layer.6.attention.self.value/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="803" name="Constant_8471" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="126935840" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="804" name="__module.model.bert.encoder.layer.6.attention.self.value/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="595,x.77">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="805" name="__module.model.bert.encoder.layer.6.attention.self/prim::ListConstruct/Concat_2" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744716" size="32" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="806" name="__module.model.bert.encoder.layer.6.attention.self/aten::view/Reshape_2" type="Reshape" version="opset1">
+			<data special_zero="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="599,x.79">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="807" name="Constant_1700" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744748" size="32" />
+			<output>
+				<port id="0" precision="I64" names="600">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="808" name="__module.model.bert.encoder.layer.6.attention.self/aten::permute/Transpose_2" type="Transpose" version="opset1">
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="601">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="809" name="__module.model.bert.encoder.layer.6.attention.self/aten::matmul/MatMul_1" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="false" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="614,context_layer.25">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="810" name="Constant_1798" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744748" size="32" />
+			<output>
+				<port id="0" precision="I64" names="615">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="811" name="__module.model.bert.encoder.layer.6.attention.self/aten::permute/Transpose_3" type="Transpose" version="opset1">
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="616">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="812" name="__module.model.bert.encoder.layer.6.attention.self/prim::ListConstruct/Concat_3" type="Const" version="opset1">
+			<data element_type="i64" shape="3" offset="83936744" size="24" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="813" name="__module.model.bert.encoder.layer.6.attention.self/aten::view/Reshape_3" type="Reshape" version="opset1">
+			<data special_zero="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="621">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="814" name="__module.model.bert.encoder.layer.6.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/scale" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="126938912" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="815" name="__module.model.bert.encoder.layer.6.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="816" name="__module.model.bert.encoder.layer.6.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="126941984" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="817" name="__module.model.bert.encoder.layer.6.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="126941988" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="818" name="__module.model.bert.encoder.layer.6.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="126941984" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="819" name="__module.model.bert.encoder.layer.6.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="126941988" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="820" name="__module.model.bert.encoder.layer.6.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="821" name="Constant_356448" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 768" offset="126941992" size="589824" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="822" name="Convert_356449" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="823" name="Constant_356450" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="127531816" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="824" name="__module.model.bert.encoder.layer.6.attention.output.dense/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="825" name="__module.model.bert.encoder.layer.6.attention.output.dense/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="826" name="Constant_8472" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="127534888" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="827" name="__module.model.bert.encoder.layer.6.attention.output.dense/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="627,input.67">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="828" name="__module.model.bert.encoder.layer.6.attention.output/aten::add/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="629">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="829" name="__module.model.bert.encoder.layer.6.attention.output.LayerNorm/aten::layer_norm/Multiply" type="Const" version="opset1">
+			<data element_type="i32" shape="1" offset="82139512" size="4" />
+			<output>
+				<port id="0" precision="I32">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="830" name="__module.model.bert.encoder.layer.6.attention.output.LayerNorm/aten::layer_norm/MVN" type="MVN" version="opset6">
+			<data eps="9.999999960041972e-13" normalize_variance="true" eps_mode="INSIDE_SQRT" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I32">
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="831" name="Constant_8473" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="127537960" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="832" name="__module.model.bert.encoder.layer.6.attention.output.LayerNorm/aten::layer_norm/Multiply_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="833" name="Constant_8474" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="127541032" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="834" name="__module.model.bert.encoder.layer.6.attention.output.LayerNorm/aten::layer_norm/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="633,input_tensor.27">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="835" name="__module.model.bert.encoder.layer.6.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/scale" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="127544104" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="836" name="__module.model.bert.encoder.layer.6.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="837" name="__module.model.bert.encoder.layer.6.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="127547176" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="838" name="__module.model.bert.encoder.layer.6.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="127547180" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="839" name="__module.model.bert.encoder.layer.6.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="127547176" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="840" name="__module.model.bert.encoder.layer.6.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="127547180" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="841" name="__module.model.bert.encoder.layer.6.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="842" name="Constant_356452" type="Const" version="opset1">
+			<data element_type="i8" shape="3072, 768" offset="127547184" size="2359296" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="843" name="Convert_356453" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="844" name="Constant_356454" type="Const" version="opset1">
+			<data element_type="f32" shape="3072, 1" offset="129906480" size="12288" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>3072</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="845" name="__module.model.bert.encoder.layer.6.intermediate.dense/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>3072</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="846" name="__module.model.bert.encoder.layer.6.intermediate.dense/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="847" name="Constant_8475" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 3072" offset="129918768" size="12288" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="848" name="__module.model.bert.encoder.layer.6.intermediate.dense/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="638,input.69">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="849" name="__module.model.bert.encoder.layer.6.intermediate.intermediate_act_fn/aten::gelu/Gelu" type="Gelu" version="opset7">
+			<data approximation_mode="ERF" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="639">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="850" name="__module.model.bert.encoder.layer.6.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/scale" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 3072" offset="129931056" size="12288" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="851" name="__module.model.bert.encoder.layer.6.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="852" name="__module.model.bert.encoder.layer.6.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="129943344" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="853" name="__module.model.bert.encoder.layer.6.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="129943348" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="854" name="__module.model.bert.encoder.layer.6.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="129943344" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="855" name="__module.model.bert.encoder.layer.6.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="129943348" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="856" name="__module.model.bert.encoder.layer.6.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="857" name="Constant_356456" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 3072" offset="129943352" size="2359296" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="858" name="Convert_356457" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="859" name="Constant_356458" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="132302648" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="860" name="__module.model.bert.encoder.layer.6.output.dense/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="861" name="__module.model.bert.encoder.layer.6.output.dense/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="862" name="Constant_8476" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="132305720" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="863" name="__module.model.bert.encoder.layer.6.output.dense/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="645,input.71">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="864" name="__module.model.bert.encoder.layer.6.output/aten::add/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="647">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="865" name="__module.model.bert.encoder.layer.6.output.LayerNorm/aten::layer_norm/Multiply" type="Const" version="opset1">
+			<data element_type="i32" shape="1" offset="82139512" size="4" />
+			<output>
+				<port id="0" precision="I32">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="866" name="__module.model.bert.encoder.layer.6.output.LayerNorm/aten::layer_norm/MVN" type="MVN" version="opset6">
+			<data eps="9.999999960041972e-13" normalize_variance="true" eps_mode="INSIDE_SQRT" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I32">
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="867" name="Constant_8477" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="132308792" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="868" name="__module.model.bert.encoder.layer.6.output.LayerNorm/aten::layer_norm/Multiply_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="869" name="Constant_8478" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="132311864" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="870" name="__module.model.bert.encoder.layer.6.output.LayerNorm/aten::layer_norm/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="651,input_tensor.29">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="871" name="__module.model.bert.encoder.layer.6.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/scale" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="132314936" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="872" name="__module.model.bert.encoder.layer.6.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="873" name="__module.model.bert.encoder.layer.6.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="132318008" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="874" name="__module.model.bert.encoder.layer.6.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="132318012" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="875" name="__module.model.bert.encoder.layer.6.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="132318008" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="876" name="__module.model.bert.encoder.layer.6.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="132318012" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="877" name="__module.model.bert.encoder.layer.6.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="878" name="Constant_356460" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 768" offset="132318016" size="589824" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="879" name="Convert_356461" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="880" name="Constant_356462" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="132907840" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="881" name="__module.model.bert.encoder.layer.7.attention.self.query/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="882" name="__module.model.bert.encoder.layer.7.attention.self.query/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="883" name="Constant_8479" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="132910912" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="884" name="__module.model.bert.encoder.layer.7.attention.self.query/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="662,x.93">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="885" name="__module.model.bert.encoder.layer.7.attention.self.query/aten::linear/Add/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="132913984" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="886" name="__module.model.bert.encoder.layer.7.attention.self.query/aten::linear/Add/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="132913988" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="887" name="__module.model.bert.encoder.layer.7.attention.self.query/aten::linear/Add/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="132913984" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="888" name="__module.model.bert.encoder.layer.7.attention.self.query/aten::linear/Add/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="132913988" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="889" name="__module.model.bert.encoder.layer.7.attention.self.query/aten::linear/Add/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="890" name="__module.model.bert.encoder.layer.7.attention.self/prim::ListConstruct/Concat" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744716" size="32" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="891" name="__module.model.bert.encoder.layer.7.attention.self/aten::view/Reshape" type="Reshape" version="opset1">
+			<data special_zero="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="684,x.95">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="892" name="Constant_1963" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744748" size="32" />
+			<output>
+				<port id="0" precision="I64" names="685">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="893" name="__module.model.bert.encoder.layer.7.attention.self/aten::permute/Transpose" type="Transpose" version="opset1">
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="686">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="894" name="Constant_356464" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 768" offset="132913992" size="589824" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="895" name="Convert_356465" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="896" name="Constant_356466" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="133503816" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="897" name="__module.model.bert.encoder.layer.7.attention.self.key/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="898" name="__module.model.bert.encoder.layer.7.attention.self.key/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="899" name="Constant_8480" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="133506888" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="900" name="__module.model.bert.encoder.layer.7.attention.self.key/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="665,x.85">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="901" name="__module.model.bert.encoder.layer.7.attention.self.key/aten::linear/Add/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="133509960" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="902" name="__module.model.bert.encoder.layer.7.attention.self.key/aten::linear/Add/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="133509964" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="903" name="__module.model.bert.encoder.layer.7.attention.self.key/aten::linear/Add/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="133509960" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="904" name="__module.model.bert.encoder.layer.7.attention.self.key/aten::linear/Add/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="133509964" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="905" name="__module.model.bert.encoder.layer.7.attention.self.key/aten::linear/Add/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="906" name="__module.model.bert.encoder.layer.7.attention.self/prim::ListConstruct/Concat_1" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744716" size="32" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="907" name="__module.model.bert.encoder.layer.7.attention.self/aten::view/Reshape_1" type="Reshape" version="opset1">
+			<data special_zero="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="669,x.87">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="908" name="Constant_1923" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744748" size="32" />
+			<output>
+				<port id="0" precision="I64" names="670">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="909" name="__module.model.bert.encoder.layer.7.attention.self/aten::permute/Transpose_1" type="Transpose" version="opset1">
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="671,key_layer.15">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="910" name="__module.model.bert.encoder.layer.7.attention.self/aten::matmul/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="688,attention_scores.29">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="911" name="Constant_8481" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 1, 1" offset="83340756" size="4" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="912" name="__module.model.bert.encoder.layer.7.attention.self/aten::div/Divide" type="Divide" version="opset1">
+			<data auto_broadcast="numpy" m_pythondiv="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="689,attention_scores.31">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="913" name="__module.model.bert.encoder.layer.7.attention.self/aten::add/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="690,input.73">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="914" name="__module.model.bert.encoder.layer.7.attention.self/aten::softmax/Softmax" type="SoftMax" version="opset8">
+			<data axis="-1" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="691,input.75">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="915" name="Constant_356468" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 768" offset="133509968" size="589824" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="916" name="Convert_356469" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="917" name="Constant_356470" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="134099792" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="918" name="__module.model.bert.encoder.layer.7.attention.self.value/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="919" name="__module.model.bert.encoder.layer.7.attention.self.value/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="920" name="Constant_8482" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="134102864" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="921" name="__module.model.bert.encoder.layer.7.attention.self.value/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="674,x.89">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="922" name="__module.model.bert.encoder.layer.7.attention.self/prim::ListConstruct/Concat_2" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744716" size="32" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="923" name="__module.model.bert.encoder.layer.7.attention.self/aten::view/Reshape_2" type="Reshape" version="opset1">
+			<data special_zero="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="678,x.91">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="924" name="Constant_1946" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744748" size="32" />
+			<output>
+				<port id="0" precision="I64" names="679">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="925" name="__module.model.bert.encoder.layer.7.attention.self/aten::permute/Transpose_2" type="Transpose" version="opset1">
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="680">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="926" name="__module.model.bert.encoder.layer.7.attention.self/aten::matmul/MatMul_1" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="false" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="693,context_layer.29">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="927" name="Constant_2044" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744748" size="32" />
+			<output>
+				<port id="0" precision="I64" names="694">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="928" name="__module.model.bert.encoder.layer.7.attention.self/aten::permute/Transpose_3" type="Transpose" version="opset1">
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="695">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="929" name="__module.model.bert.encoder.layer.7.attention.self/prim::ListConstruct/Concat_3" type="Const" version="opset1">
+			<data element_type="i64" shape="3" offset="83936744" size="24" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="930" name="__module.model.bert.encoder.layer.7.attention.self/aten::view/Reshape_3" type="Reshape" version="opset1">
+			<data special_zero="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="700">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="931" name="__module.model.bert.encoder.layer.7.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/scale" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="134105936" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="932" name="__module.model.bert.encoder.layer.7.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="933" name="__module.model.bert.encoder.layer.7.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="134109008" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="934" name="__module.model.bert.encoder.layer.7.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="134109012" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="935" name="__module.model.bert.encoder.layer.7.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="134109008" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="936" name="__module.model.bert.encoder.layer.7.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="134109012" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="937" name="__module.model.bert.encoder.layer.7.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="938" name="Constant_356472" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 768" offset="134109016" size="589824" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="939" name="Convert_356473" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="940" name="Constant_356474" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="134698840" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="941" name="__module.model.bert.encoder.layer.7.attention.output.dense/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="942" name="__module.model.bert.encoder.layer.7.attention.output.dense/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="943" name="Constant_8483" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="134701912" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="944" name="__module.model.bert.encoder.layer.7.attention.output.dense/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="706,input.77">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="945" name="__module.model.bert.encoder.layer.7.attention.output/aten::add/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="708">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="946" name="__module.model.bert.encoder.layer.7.attention.output.LayerNorm/aten::layer_norm/Multiply" type="Const" version="opset1">
+			<data element_type="i32" shape="1" offset="82139512" size="4" />
+			<output>
+				<port id="0" precision="I32">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="947" name="__module.model.bert.encoder.layer.7.attention.output.LayerNorm/aten::layer_norm/MVN" type="MVN" version="opset6">
+			<data eps="9.999999960041972e-13" normalize_variance="true" eps_mode="INSIDE_SQRT" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I32">
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="948" name="Constant_8484" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="134704984" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="949" name="__module.model.bert.encoder.layer.7.attention.output.LayerNorm/aten::layer_norm/Multiply_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="950" name="Constant_8485" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="134708056" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="951" name="__module.model.bert.encoder.layer.7.attention.output.LayerNorm/aten::layer_norm/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="712,input_tensor.31">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="952" name="__module.model.bert.encoder.layer.7.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/scale" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="134711128" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="953" name="__module.model.bert.encoder.layer.7.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="954" name="__module.model.bert.encoder.layer.7.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="134714200" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="955" name="__module.model.bert.encoder.layer.7.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="134714204" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="956" name="__module.model.bert.encoder.layer.7.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="134714200" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="957" name="__module.model.bert.encoder.layer.7.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="134714204" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="958" name="__module.model.bert.encoder.layer.7.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="959" name="Constant_356476" type="Const" version="opset1">
+			<data element_type="i8" shape="3072, 768" offset="134714208" size="2359296" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="960" name="Convert_356477" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="961" name="Constant_356478" type="Const" version="opset1">
+			<data element_type="f32" shape="3072, 1" offset="137073504" size="12288" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>3072</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="962" name="__module.model.bert.encoder.layer.7.intermediate.dense/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>3072</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="963" name="__module.model.bert.encoder.layer.7.intermediate.dense/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="964" name="Constant_8486" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 3072" offset="137085792" size="12288" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="965" name="__module.model.bert.encoder.layer.7.intermediate.dense/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="717,input.79">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="966" name="__module.model.bert.encoder.layer.7.intermediate.intermediate_act_fn/aten::gelu/Gelu" type="Gelu" version="opset7">
+			<data approximation_mode="ERF" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="718">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="967" name="__module.model.bert.encoder.layer.7.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/scale" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 3072" offset="137098080" size="12288" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="968" name="__module.model.bert.encoder.layer.7.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="969" name="__module.model.bert.encoder.layer.7.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="137110368" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="970" name="__module.model.bert.encoder.layer.7.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="137110372" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="971" name="__module.model.bert.encoder.layer.7.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="137110368" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="972" name="__module.model.bert.encoder.layer.7.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="137110372" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="973" name="__module.model.bert.encoder.layer.7.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="974" name="Constant_356480" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 3072" offset="137110376" size="2359296" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="975" name="Convert_356481" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="976" name="Constant_356482" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="139469672" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="977" name="__module.model.bert.encoder.layer.7.output.dense/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="978" name="__module.model.bert.encoder.layer.7.output.dense/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="979" name="Constant_8487" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="139472744" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="980" name="__module.model.bert.encoder.layer.7.output.dense/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="724,input.81">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="981" name="__module.model.bert.encoder.layer.7.output/aten::add/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="726">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="982" name="__module.model.bert.encoder.layer.7.output.LayerNorm/aten::layer_norm/Multiply" type="Const" version="opset1">
+			<data element_type="i32" shape="1" offset="82139512" size="4" />
+			<output>
+				<port id="0" precision="I32">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="983" name="__module.model.bert.encoder.layer.7.output.LayerNorm/aten::layer_norm/MVN" type="MVN" version="opset6">
+			<data eps="9.999999960041972e-13" normalize_variance="true" eps_mode="INSIDE_SQRT" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I32">
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="984" name="Constant_8488" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="139475816" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="985" name="__module.model.bert.encoder.layer.7.output.LayerNorm/aten::layer_norm/Multiply_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="986" name="Constant_8489" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="139478888" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="987" name="__module.model.bert.encoder.layer.7.output.LayerNorm/aten::layer_norm/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="730,input_tensor.33">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="988" name="__module.model.bert.encoder.layer.7.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/scale" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="139481960" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="989" name="__module.model.bert.encoder.layer.7.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="990" name="__module.model.bert.encoder.layer.7.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="139485032" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="991" name="__module.model.bert.encoder.layer.7.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="139485036" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="992" name="__module.model.bert.encoder.layer.7.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="139485032" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="993" name="__module.model.bert.encoder.layer.7.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="139485036" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="994" name="__module.model.bert.encoder.layer.7.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="995" name="Constant_356484" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 768" offset="139485040" size="589824" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="996" name="Convert_356485" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="997" name="Constant_356486" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="140074864" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="998" name="__module.model.bert.encoder.layer.8.attention.self.query/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="999" name="__module.model.bert.encoder.layer.8.attention.self.query/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1000" name="Constant_8490" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="140077936" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1001" name="__module.model.bert.encoder.layer.8.attention.self.query/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="741,x.105">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1002" name="__module.model.bert.encoder.layer.8.attention.self.query/aten::linear/Add/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="140081008" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="1003" name="__module.model.bert.encoder.layer.8.attention.self.query/aten::linear/Add/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="140081012" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="1004" name="__module.model.bert.encoder.layer.8.attention.self.query/aten::linear/Add/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="140081008" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="1005" name="__module.model.bert.encoder.layer.8.attention.self.query/aten::linear/Add/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="140081012" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="1006" name="__module.model.bert.encoder.layer.8.attention.self.query/aten::linear/Add/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1007" name="__module.model.bert.encoder.layer.8.attention.self/prim::ListConstruct/Concat" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744716" size="32" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1008" name="__module.model.bert.encoder.layer.8.attention.self/aten::view/Reshape" type="Reshape" version="opset1">
+			<data special_zero="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="763,x.107">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1009" name="Constant_2209" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744748" size="32" />
+			<output>
+				<port id="0" precision="I64" names="764">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1010" name="__module.model.bert.encoder.layer.8.attention.self/aten::permute/Transpose" type="Transpose" version="opset1">
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="765">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1011" name="Constant_356488" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 768" offset="140081016" size="589824" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1012" name="Convert_356489" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1013" name="Constant_356490" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="140670840" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1014" name="__module.model.bert.encoder.layer.8.attention.self.key/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1015" name="__module.model.bert.encoder.layer.8.attention.self.key/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1016" name="Constant_8491" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="140673912" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1017" name="__module.model.bert.encoder.layer.8.attention.self.key/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="744,x.97">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1018" name="__module.model.bert.encoder.layer.8.attention.self.key/aten::linear/Add/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="140676984" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="1019" name="__module.model.bert.encoder.layer.8.attention.self.key/aten::linear/Add/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="140676988" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="1020" name="__module.model.bert.encoder.layer.8.attention.self.key/aten::linear/Add/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="140676984" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="1021" name="__module.model.bert.encoder.layer.8.attention.self.key/aten::linear/Add/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="140676988" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="1022" name="__module.model.bert.encoder.layer.8.attention.self.key/aten::linear/Add/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1023" name="__module.model.bert.encoder.layer.8.attention.self/prim::ListConstruct/Concat_1" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744716" size="32" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1024" name="__module.model.bert.encoder.layer.8.attention.self/aten::view/Reshape_1" type="Reshape" version="opset1">
+			<data special_zero="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="748,x.99">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1025" name="Constant_2169" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744748" size="32" />
+			<output>
+				<port id="0" precision="I64" names="749">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1026" name="__module.model.bert.encoder.layer.8.attention.self/aten::permute/Transpose_1" type="Transpose" version="opset1">
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="750,key_layer.17">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1027" name="__module.model.bert.encoder.layer.8.attention.self/aten::matmul/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="767,attention_scores.33">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1028" name="Constant_8492" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 1, 1" offset="83340756" size="4" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1029" name="__module.model.bert.encoder.layer.8.attention.self/aten::div/Divide" type="Divide" version="opset1">
+			<data auto_broadcast="numpy" m_pythondiv="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="768,attention_scores.35">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1030" name="__module.model.bert.encoder.layer.8.attention.self/aten::add/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="769,input.83">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1031" name="__module.model.bert.encoder.layer.8.attention.self/aten::softmax/Softmax" type="SoftMax" version="opset8">
+			<data axis="-1" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="770,input.85">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1032" name="Constant_356492" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 768" offset="140676992" size="589824" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1033" name="Convert_356493" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1034" name="Constant_356494" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="141266816" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1035" name="__module.model.bert.encoder.layer.8.attention.self.value/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1036" name="__module.model.bert.encoder.layer.8.attention.self.value/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1037" name="Constant_8493" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="141269888" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1038" name="__module.model.bert.encoder.layer.8.attention.self.value/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="753,x.101">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1039" name="__module.model.bert.encoder.layer.8.attention.self/prim::ListConstruct/Concat_2" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744716" size="32" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1040" name="__module.model.bert.encoder.layer.8.attention.self/aten::view/Reshape_2" type="Reshape" version="opset1">
+			<data special_zero="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="757,x.103">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1041" name="Constant_2192" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744748" size="32" />
+			<output>
+				<port id="0" precision="I64" names="758">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1042" name="__module.model.bert.encoder.layer.8.attention.self/aten::permute/Transpose_2" type="Transpose" version="opset1">
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="759">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1043" name="__module.model.bert.encoder.layer.8.attention.self/aten::matmul/MatMul_1" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="false" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="772,context_layer.33">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1044" name="Constant_2290" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744748" size="32" />
+			<output>
+				<port id="0" precision="I64" names="773">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1045" name="__module.model.bert.encoder.layer.8.attention.self/aten::permute/Transpose_3" type="Transpose" version="opset1">
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="774">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1046" name="__module.model.bert.encoder.layer.8.attention.self/prim::ListConstruct/Concat_3" type="Const" version="opset1">
+			<data element_type="i64" shape="3" offset="83936744" size="24" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1047" name="__module.model.bert.encoder.layer.8.attention.self/aten::view/Reshape_3" type="Reshape" version="opset1">
+			<data special_zero="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="779">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1048" name="__module.model.bert.encoder.layer.8.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/scale" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="141272960" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1049" name="__module.model.bert.encoder.layer.8.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1050" name="__module.model.bert.encoder.layer.8.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="141276032" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="1051" name="__module.model.bert.encoder.layer.8.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="141276036" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="1052" name="__module.model.bert.encoder.layer.8.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="141276032" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="1053" name="__module.model.bert.encoder.layer.8.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="141276036" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="1054" name="__module.model.bert.encoder.layer.8.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1055" name="Constant_356496" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 768" offset="141276040" size="589824" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1056" name="Convert_356497" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1057" name="Constant_356498" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="141865864" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1058" name="__module.model.bert.encoder.layer.8.attention.output.dense/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1059" name="__module.model.bert.encoder.layer.8.attention.output.dense/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1060" name="Constant_8494" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="141868936" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1061" name="__module.model.bert.encoder.layer.8.attention.output.dense/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="785,input.87">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1062" name="__module.model.bert.encoder.layer.8.attention.output/aten::add/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="787">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1063" name="__module.model.bert.encoder.layer.8.attention.output.LayerNorm/aten::layer_norm/Multiply" type="Const" version="opset1">
+			<data element_type="i32" shape="1" offset="82139512" size="4" />
+			<output>
+				<port id="0" precision="I32">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1064" name="__module.model.bert.encoder.layer.8.attention.output.LayerNorm/aten::layer_norm/MVN" type="MVN" version="opset6">
+			<data eps="9.999999960041972e-13" normalize_variance="true" eps_mode="INSIDE_SQRT" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I32">
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1065" name="Constant_8495" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="141872008" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1066" name="__module.model.bert.encoder.layer.8.attention.output.LayerNorm/aten::layer_norm/Multiply_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1067" name="Constant_8496" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="141875080" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1068" name="__module.model.bert.encoder.layer.8.attention.output.LayerNorm/aten::layer_norm/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="791,input_tensor.35">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1069" name="__module.model.bert.encoder.layer.8.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/scale" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="141878152" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1070" name="__module.model.bert.encoder.layer.8.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1071" name="__module.model.bert.encoder.layer.8.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="141881224" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="1072" name="__module.model.bert.encoder.layer.8.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="141881228" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="1073" name="__module.model.bert.encoder.layer.8.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="141881224" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="1074" name="__module.model.bert.encoder.layer.8.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="141881228" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="1075" name="__module.model.bert.encoder.layer.8.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1076" name="Constant_356500" type="Const" version="opset1">
+			<data element_type="i8" shape="3072, 768" offset="141881232" size="2359296" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1077" name="Convert_356501" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1078" name="Constant_356502" type="Const" version="opset1">
+			<data element_type="f32" shape="3072, 1" offset="144240528" size="12288" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>3072</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1079" name="__module.model.bert.encoder.layer.8.intermediate.dense/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>3072</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1080" name="__module.model.bert.encoder.layer.8.intermediate.dense/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1081" name="Constant_8497" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 3072" offset="144252816" size="12288" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1082" name="__module.model.bert.encoder.layer.8.intermediate.dense/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="796,input.89">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1083" name="__module.model.bert.encoder.layer.8.intermediate.intermediate_act_fn/aten::gelu/Gelu" type="Gelu" version="opset7">
+			<data approximation_mode="ERF" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="797">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1084" name="__module.model.bert.encoder.layer.8.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/scale" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 3072" offset="144265104" size="12288" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1085" name="__module.model.bert.encoder.layer.8.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1086" name="__module.model.bert.encoder.layer.8.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="144277392" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="1087" name="__module.model.bert.encoder.layer.8.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="144277396" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="1088" name="__module.model.bert.encoder.layer.8.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="144277392" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="1089" name="__module.model.bert.encoder.layer.8.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="144277396" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="1090" name="__module.model.bert.encoder.layer.8.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1091" name="Constant_356504" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 3072" offset="144277400" size="2359296" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1092" name="Convert_356505" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1093" name="Constant_356506" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="146636696" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1094" name="__module.model.bert.encoder.layer.8.output.dense/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1095" name="__module.model.bert.encoder.layer.8.output.dense/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1096" name="Constant_8498" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="146639768" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1097" name="__module.model.bert.encoder.layer.8.output.dense/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="803,input.91">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1098" name="__module.model.bert.encoder.layer.8.output/aten::add/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="805">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1099" name="__module.model.bert.encoder.layer.8.output.LayerNorm/aten::layer_norm/Multiply" type="Const" version="opset1">
+			<data element_type="i32" shape="1" offset="82139512" size="4" />
+			<output>
+				<port id="0" precision="I32">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1100" name="__module.model.bert.encoder.layer.8.output.LayerNorm/aten::layer_norm/MVN" type="MVN" version="opset6">
+			<data eps="9.999999960041972e-13" normalize_variance="true" eps_mode="INSIDE_SQRT" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I32">
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1101" name="Constant_8499" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="146642840" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1102" name="__module.model.bert.encoder.layer.8.output.LayerNorm/aten::layer_norm/Multiply_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1103" name="Constant_8500" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="146645912" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1104" name="__module.model.bert.encoder.layer.8.output.LayerNorm/aten::layer_norm/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="809,input_tensor.37">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1105" name="__module.model.bert.encoder.layer.8.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/scale" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="146648984" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1106" name="__module.model.bert.encoder.layer.8.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1107" name="__module.model.bert.encoder.layer.8.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="146652056" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="1108" name="__module.model.bert.encoder.layer.8.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="146652060" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="1109" name="__module.model.bert.encoder.layer.8.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="146652056" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="1110" name="__module.model.bert.encoder.layer.8.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="146652060" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="1111" name="__module.model.bert.encoder.layer.8.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1112" name="Constant_356508" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 768" offset="146652064" size="589824" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1113" name="Convert_356509" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1114" name="Constant_356510" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="147241888" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1115" name="__module.model.bert.encoder.layer.9.attention.self.query/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1116" name="__module.model.bert.encoder.layer.9.attention.self.query/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1117" name="Constant_8501" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="147244960" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1118" name="__module.model.bert.encoder.layer.9.attention.self.query/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="820,x.117">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1119" name="__module.model.bert.encoder.layer.9.attention.self.query/aten::linear/Add/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="147248032" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="1120" name="__module.model.bert.encoder.layer.9.attention.self.query/aten::linear/Add/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="147248036" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="1121" name="__module.model.bert.encoder.layer.9.attention.self.query/aten::linear/Add/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="147248032" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="1122" name="__module.model.bert.encoder.layer.9.attention.self.query/aten::linear/Add/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="147248036" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="1123" name="__module.model.bert.encoder.layer.9.attention.self.query/aten::linear/Add/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1124" name="__module.model.bert.encoder.layer.9.attention.self/prim::ListConstruct/Concat" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744716" size="32" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1125" name="__module.model.bert.encoder.layer.9.attention.self/aten::view/Reshape" type="Reshape" version="opset1">
+			<data special_zero="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="842,x.119">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1126" name="Constant_2455" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744748" size="32" />
+			<output>
+				<port id="0" precision="I64" names="843">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1127" name="__module.model.bert.encoder.layer.9.attention.self/aten::permute/Transpose" type="Transpose" version="opset1">
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="844">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1128" name="Constant_356512" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 768" offset="147248040" size="589824" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1129" name="Convert_356513" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1130" name="Constant_356514" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="147837864" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1131" name="__module.model.bert.encoder.layer.9.attention.self.key/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1132" name="__module.model.bert.encoder.layer.9.attention.self.key/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1133" name="Constant_8502" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="147840936" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1134" name="__module.model.bert.encoder.layer.9.attention.self.key/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="823,x.109">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1135" name="__module.model.bert.encoder.layer.9.attention.self.key/aten::linear/Add/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="147844008" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="1136" name="__module.model.bert.encoder.layer.9.attention.self.key/aten::linear/Add/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="147844012" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="1137" name="__module.model.bert.encoder.layer.9.attention.self.key/aten::linear/Add/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="147844008" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="1138" name="__module.model.bert.encoder.layer.9.attention.self.key/aten::linear/Add/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="147844012" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="1139" name="__module.model.bert.encoder.layer.9.attention.self.key/aten::linear/Add/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1140" name="__module.model.bert.encoder.layer.9.attention.self/prim::ListConstruct/Concat_1" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744716" size="32" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1141" name="__module.model.bert.encoder.layer.9.attention.self/aten::view/Reshape_1" type="Reshape" version="opset1">
+			<data special_zero="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="827,x.111">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1142" name="Constant_2415" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744748" size="32" />
+			<output>
+				<port id="0" precision="I64" names="828">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1143" name="__module.model.bert.encoder.layer.9.attention.self/aten::permute/Transpose_1" type="Transpose" version="opset1">
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="829,key_layer.19">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1144" name="__module.model.bert.encoder.layer.9.attention.self/aten::matmul/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="846,attention_scores.37">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1145" name="Constant_8503" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 1, 1" offset="83340756" size="4" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1146" name="__module.model.bert.encoder.layer.9.attention.self/aten::div/Divide" type="Divide" version="opset1">
+			<data auto_broadcast="numpy" m_pythondiv="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="847,attention_scores.39">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1147" name="__module.model.bert.encoder.layer.9.attention.self/aten::add/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="848,input.93">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1148" name="__module.model.bert.encoder.layer.9.attention.self/aten::softmax/Softmax" type="SoftMax" version="opset8">
+			<data axis="-1" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="849,input.95">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1149" name="Constant_356516" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 768" offset="147844016" size="589824" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1150" name="Convert_356517" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1151" name="Constant_356518" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="148433840" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1152" name="__module.model.bert.encoder.layer.9.attention.self.value/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1153" name="__module.model.bert.encoder.layer.9.attention.self.value/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1154" name="Constant_8504" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="148436912" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1155" name="__module.model.bert.encoder.layer.9.attention.self.value/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="832,x.113">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1156" name="__module.model.bert.encoder.layer.9.attention.self/prim::ListConstruct/Concat_2" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744716" size="32" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1157" name="__module.model.bert.encoder.layer.9.attention.self/aten::view/Reshape_2" type="Reshape" version="opset1">
+			<data special_zero="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="836,x.115">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1158" name="Constant_2438" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744748" size="32" />
+			<output>
+				<port id="0" precision="I64" names="837">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1159" name="__module.model.bert.encoder.layer.9.attention.self/aten::permute/Transpose_2" type="Transpose" version="opset1">
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="838">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1160" name="__module.model.bert.encoder.layer.9.attention.self/aten::matmul/MatMul_1" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="false" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="851,context_layer.37">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1161" name="Constant_2536" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="82744748" size="32" />
+			<output>
+				<port id="0" precision="I64" names="852">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1162" name="__module.model.bert.encoder.layer.9.attention.self/aten::permute/Transpose_3" type="Transpose" version="opset1">
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="853">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1163" name="__module.model.bert.encoder.layer.9.attention.self/prim::ListConstruct/Concat_3" type="Const" version="opset1">
+			<data element_type="i64" shape="3" offset="83936744" size="24" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1164" name="__module.model.bert.encoder.layer.9.attention.self/aten::view/Reshape_3" type="Reshape" version="opset1">
+			<data special_zero="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>12</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="858">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1165" name="__module.model.bert.encoder.layer.9.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/scale" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="148439984" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1166" name="__module.model.bert.encoder.layer.9.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1167" name="__module.model.bert.encoder.layer.9.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="148443056" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="1168" name="__module.model.bert.encoder.layer.9.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="148443060" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="1169" name="__module.model.bert.encoder.layer.9.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="148443056" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="1170" name="__module.model.bert.encoder.layer.9.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="148443060" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="1171" name="__module.model.bert.encoder.layer.9.attention.self/aten::view/Reshape_3_0_0/nncf_smooth_quant/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1172" name="Constant_356520" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 768" offset="148443064" size="589824" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1173" name="Convert_356521" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1174" name="Constant_356522" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="149032888" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1175" name="__module.model.bert.encoder.layer.9.attention.output.dense/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1176" name="__module.model.bert.encoder.layer.9.attention.output.dense/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1177" name="Constant_8505" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="149035960" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1178" name="__module.model.bert.encoder.layer.9.attention.output.dense/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="864,input.97">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1179" name="__module.model.bert.encoder.layer.9.attention.output/aten::add/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="866">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1180" name="__module.model.bert.encoder.layer.9.attention.output.LayerNorm/aten::layer_norm/Multiply" type="Const" version="opset1">
+			<data element_type="i32" shape="1" offset="82139512" size="4" />
+			<output>
+				<port id="0" precision="I32">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1181" name="__module.model.bert.encoder.layer.9.attention.output.LayerNorm/aten::layer_norm/MVN" type="MVN" version="opset6">
+			<data eps="9.999999960041972e-13" normalize_variance="true" eps_mode="INSIDE_SQRT" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I32">
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1182" name="Constant_8506" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="149039032" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1183" name="__module.model.bert.encoder.layer.9.attention.output.LayerNorm/aten::layer_norm/Multiply_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1184" name="Constant_8507" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="149042104" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1185" name="__module.model.bert.encoder.layer.9.attention.output.LayerNorm/aten::layer_norm/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="870,input_tensor.39">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1186" name="__module.model.bert.encoder.layer.9.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/scale" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="149045176" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1187" name="__module.model.bert.encoder.layer.9.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1188" name="__module.model.bert.encoder.layer.9.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="149048248" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="1189" name="__module.model.bert.encoder.layer.9.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="149048252" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="1190" name="__module.model.bert.encoder.layer.9.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="149048248" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="1191" name="__module.model.bert.encoder.layer.9.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="149048252" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="1192" name="__module.model.bert.encoder.layer.9.attention.output.LayerNorm/aten::layer_norm/Add_0_0/nncf_smooth_quant/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1193" name="Constant_356524" type="Const" version="opset1">
+			<data element_type="i8" shape="3072, 768" offset="149048256" size="2359296" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1194" name="Convert_356525" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1195" name="Constant_356526" type="Const" version="opset1">
+			<data element_type="f32" shape="3072, 1" offset="151407552" size="12288" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>3072</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1196" name="__module.model.bert.encoder.layer.9.intermediate.dense/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>3072</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1197" name="__module.model.bert.encoder.layer.9.intermediate.dense/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>3072</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1198" name="Constant_8508" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 3072" offset="151419840" size="12288" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1199" name="__module.model.bert.encoder.layer.9.intermediate.dense/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="875,input.99">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1200" name="__module.model.bert.encoder.layer.9.intermediate.intermediate_act_fn/aten::gelu/Gelu" type="Gelu" version="opset7">
+			<data approximation_mode="ERF" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="876">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1201" name="__module.model.bert.encoder.layer.9.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/scale" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 3072" offset="151432128" size="12288" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1202" name="__module.model.bert.encoder.layer.9.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1203" name="__module.model.bert.encoder.layer.9.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0/input_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="151444416" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="1204" name="__module.model.bert.encoder.layer.9.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0/input_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="151444420" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="1205" name="__module.model.bert.encoder.layer.9.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0/output_low" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="151444416" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="1206" name="__module.model.bert.encoder.layer.9.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0/output_high" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="151444420" size="4" />
+			<output>
+				<port id="0" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="1207" name="__module.model.bert.encoder.layer.9.intermediate.intermediate_act_fn/aten::gelu/Gelu_0_0/nncf_smooth_quant/fq_output_0" type="FakeQuantize" version="opset1">
+			<data levels="256" auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32" />
+				<port id="2" precision="FP32" />
+				<port id="3" precision="FP32" />
+				<port id="4" precision="FP32" />
+			</input>
+			<output>
+				<port id="5" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1208" name="Constant_356528" type="Const" version="opset1">
+			<data element_type="i8" shape="768, 3072" offset="151444424" size="2359296" />
+			<output>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1209" name="Convert_356529" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I8">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1210" name="Constant_356530" type="Const" version="opset1">
+			<data element_type="f32" shape="768, 1" offset="153803720" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1211" name="__module.model.bert.encoder.layer.9.output.dense/aten::linear/MatMul/fq_weights_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1212" name="__module.model.bert.encoder.layer.9.output.dense/aten::linear/MatMul" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>3072</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>768</dim>
+					<dim>3072</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1213" name="Constant_8509" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="153806792" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1214" name="__module.model.bert.encoder.layer.9.output.dense/aten::linear/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="882,input.101">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1215" name="__module.model.bert.encoder.layer.9.output/aten::add/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="884">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1216" name="__module.model.bert.encoder.layer.9.output.LayerNorm/aten::layer_norm/Multiply" type="Const" version="opset1">
+			<data element_type="i32" shape="1" offset="82139512" size="4" />
+			<output>
+				<port id="0" precision="I32">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1217" name="__module.model.bert.encoder.layer.9.output.LayerNorm/aten::layer_norm/MVN" type="MVN" version="opset6">
+			<data eps="9.999999960041972e-13" normalize_variance="true" eps_mode="INSIDE_SQRT" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I32">
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1218" name="Constant_8510" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="153809864" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1219" name="__module.model.bert.encoder.layer.9.output.LayerNorm/aten::layer_norm/Multiply_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1220" name="Constant_8511" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 768" offset="153812936" size="3072" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1221" name="__module.model.bert.encoder.layer.9.output.LayerNorm/aten::layer_norm/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="1049,1052,8,888,input_tensor.41">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1222" name="10" type="Const" version="opset1">
+			<data element_type="i64" shape="" offset="82139496" size="8" />
+			<output>
+				<port id="0" precision="I64" names="10" />
+			</output>
+		</layer>
+		<layer id="1223" name="9" type="Const" version="opset1">
+			<data element_type="i64" shape="" offset="82139496" size="8" />
+			<output>
+				<port id="0" precision="I64" names="9" />
+			</output>
+		</layer>
+		<layer id="1224" name="aten::select/Gather" type="Gather" version="opset8">
+			<data batch_dims="0" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+				<port id="1" precision="I64" />
+				<port id="2" precision="I64" />
+			</input>
+			<output>
+				<port id="3" precision="FP32" names="hidden_states">
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1225" name="Result_4814" type="Result" version="opset1">
+			<input>
+				<port id="0" precision="FP32">
+					<dim>64</dim>
+					<dim>768</dim>
+				</port>
+			</input>
+		</layer>
+	</layers>
+	<edges>
+		<edge from-layer="0" from-port="0" to-layer="14" to-port="0" />
+		<edge from-layer="1" from-port="0" to-layer="85" to-port="0" />
+		<edge from-layer="2" from-port="0" to-layer="7" to-port="0" />
+		<edge from-layer="2" from-port="0" to-layer="24" to-port="0" />
+		<edge from-layer="3" from-port="0" to-layer="4" to-port="0" />
+		<edge from-layer="4" from-port="1" to-layer="6" to-port="0" />
+		<edge from-layer="5" from-port="0" to-layer="6" to-port="1" />
+		<edge from-layer="6" from-port="2" to-layer="9" to-port="0" />
+		<edge from-layer="7" from-port="1" to-layer="9" to-port="1" />
+		<edge from-layer="8" from-port="0" to-layer="9" to-port="2" />
+		<edge from-layer="9" from-port="3" to-layer="17" to-port="0" />
+		<edge from-layer="10" from-port="0" to-layer="11" to-port="0" />
+		<edge from-layer="11" from-port="1" to-layer="13" to-port="0" />
+		<edge from-layer="12" from-port="0" to-layer="13" to-port="1" />
+		<edge from-layer="13" from-port="2" to-layer="16" to-port="0" />
+		<edge from-layer="14" from-port="1" to-layer="16" to-port="1" />
+		<edge from-layer="15" from-port="0" to-layer="16" to-port="2" />
+		<edge from-layer="16" from-port="3" to-layer="17" to-port="1" />
+		<edge from-layer="17" from-port="2" to-layer="34" to-port="0" />
+		<edge from-layer="18" from-port="0" to-layer="19" to-port="0" />
+		<edge from-layer="19" from-port="1" to-layer="21" to-port="0" />
+		<edge from-layer="20" from-port="0" to-layer="21" to-port="1" />
+		<edge from-layer="21" from-port="2" to-layer="33" to-port="0" />
+		<edge from-layer="22" from-port="0" to-layer="30" to-port="0" />
+		<edge from-layer="23" from-port="0" to-layer="30" to-port="1" />
+		<edge from-layer="24" from-port="1" to-layer="27" to-port="0" />
+		<edge from-layer="25" from-port="0" to-layer="27" to-port="1" />
+		<edge from-layer="26" from-port="0" to-layer="27" to-port="2" />
+		<edge from-layer="27" from-port="3" to-layer="30" to-port="2" />
+		<edge from-layer="28" from-port="0" to-layer="30" to-port="3" />
+		<edge from-layer="29" from-port="0" to-layer="30" to-port="4" />
+		<edge from-layer="30" from-port="5" to-layer="31" to-port="0" />
+		<edge from-layer="31" from-port="1" to-layer="33" to-port="1" />
+		<edge from-layer="32" from-port="0" to-layer="33" to-port="2" />
+		<edge from-layer="33" from-port="3" to-layer="34" to-port="1" />
+		<edge from-layer="34" from-port="2" to-layer="36" to-port="0" />
+		<edge from-layer="35" from-port="0" to-layer="36" to-port="1" />
+		<edge from-layer="36" from-port="2" to-layer="38" to-port="0" />
+		<edge from-layer="37" from-port="0" to-layer="38" to-port="1" />
+		<edge from-layer="38" from-port="2" to-layer="40" to-port="0" />
+		<edge from-layer="39" from-port="0" to-layer="40" to-port="1" />
+		<edge from-layer="40" from-port="2" to-layer="42" to-port="0" />
+		<edge from-layer="40" from-port="2" to-layer="126" to-port="1" />
+		<edge from-layer="41" from-port="0" to-layer="42" to-port="1" />
+		<edge from-layer="42" from-port="2" to-layer="47" to-port="0" />
+		<edge from-layer="43" from-port="0" to-layer="47" to-port="1" />
+		<edge from-layer="44" from-port="0" to-layer="47" to-port="2" />
+		<edge from-layer="45" from-port="0" to-layer="47" to-port="3" />
+		<edge from-layer="46" from-port="0" to-layer="47" to-port="4" />
+		<edge from-layer="47" from-port="5" to-layer="52" to-port="0" />
+		<edge from-layer="47" from-port="5" to-layer="68" to-port="0" />
+		<edge from-layer="47" from-port="5" to-layer="100" to-port="0" />
+		<edge from-layer="48" from-port="0" to-layer="49" to-port="0" />
+		<edge from-layer="49" from-port="1" to-layer="51" to-port="0" />
+		<edge from-layer="50" from-port="0" to-layer="51" to-port="1" />
+		<edge from-layer="51" from-port="2" to-layer="52" to-port="1" />
+		<edge from-layer="52" from-port="2" to-layer="54" to-port="0" />
+		<edge from-layer="53" from-port="0" to-layer="54" to-port="1" />
+		<edge from-layer="54" from-port="2" to-layer="59" to-port="0" />
+		<edge from-layer="55" from-port="0" to-layer="59" to-port="1" />
+		<edge from-layer="56" from-port="0" to-layer="59" to-port="2" />
+		<edge from-layer="57" from-port="0" to-layer="59" to-port="3" />
+		<edge from-layer="58" from-port="0" to-layer="59" to-port="4" />
+		<edge from-layer="59" from-port="5" to-layer="61" to-port="0" />
+		<edge from-layer="60" from-port="0" to-layer="61" to-port="1" />
+		<edge from-layer="61" from-port="2" to-layer="63" to-port="0" />
+		<edge from-layer="62" from-port="0" to-layer="63" to-port="1" />
+		<edge from-layer="63" from-port="2" to-layer="80" to-port="0" />
+		<edge from-layer="64" from-port="0" to-layer="65" to-port="0" />
+		<edge from-layer="65" from-port="1" to-layer="67" to-port="0" />
+		<edge from-layer="66" from-port="0" to-layer="67" to-port="1" />
+		<edge from-layer="67" from-port="2" to-layer="68" to-port="1" />
+		<edge from-layer="68" from-port="2" to-layer="70" to-port="0" />
+		<edge from-layer="69" from-port="0" to-layer="70" to-port="1" />
+		<edge from-layer="70" from-port="2" to-layer="75" to-port="0" />
+		<edge from-layer="71" from-port="0" to-layer="75" to-port="1" />
+		<edge from-layer="72" from-port="0" to-layer="75" to-port="2" />
+		<edge from-layer="73" from-port="0" to-layer="75" to-port="3" />
+		<edge from-layer="74" from-port="0" to-layer="75" to-port="4" />
+		<edge from-layer="75" from-port="5" to-layer="77" to-port="0" />
+		<edge from-layer="76" from-port="0" to-layer="77" to-port="1" />
+		<edge from-layer="77" from-port="2" to-layer="79" to-port="0" />
+		<edge from-layer="78" from-port="0" to-layer="79" to-port="1" />
+		<edge from-layer="79" from-port="2" to-layer="80" to-port="1" />
+		<edge from-layer="80" from-port="2" to-layer="82" to-port="0" />
+		<edge from-layer="81" from-port="0" to-layer="82" to-port="1" />
+		<edge from-layer="82" from-port="2" to-layer="94" to-port="0" />
+		<edge from-layer="83" from-port="0" to-layer="91" to-port="0" />
+		<edge from-layer="84" from-port="0" to-layer="85" to-port="1" />
+		<edge from-layer="85" from-port="2" to-layer="87" to-port="0" />
+		<edge from-layer="86" from-port="0" to-layer="87" to-port="1" />
+		<edge from-layer="87" from-port="2" to-layer="88" to-port="0" />
+		<edge from-layer="88" from-port="1" to-layer="90" to-port="0" />
+		<edge from-layer="89" from-port="0" to-layer="90" to-port="1" />
+		<edge from-layer="90" from-port="2" to-layer="91" to-port="1" />
+		<edge from-layer="91" from-port="2" to-layer="93" to-port="0" />
+		<edge from-layer="92" from-port="0" to-layer="93" to-port="1" />
+		<edge from-layer="93" from-port="2" to-layer="94" to-port="1" />
+		<edge from-layer="93" from-port="2" to-layer="796" to-port="1" />
+		<edge from-layer="93" from-port="2" to-layer="679" to-port="1" />
+		<edge from-layer="93" from-port="2" to-layer="562" to-port="1" />
+		<edge from-layer="93" from-port="2" to-layer="1147" to-port="1" />
+		<edge from-layer="93" from-port="2" to-layer="328" to-port="1" />
+		<edge from-layer="93" from-port="2" to-layer="445" to-port="1" />
+		<edge from-layer="93" from-port="2" to-layer="211" to-port="1" />
+		<edge from-layer="93" from-port="2" to-layer="1030" to-port="1" />
+		<edge from-layer="93" from-port="2" to-layer="913" to-port="1" />
+		<edge from-layer="94" from-port="2" to-layer="95" to-port="0" />
+		<edge from-layer="95" from-port="1" to-layer="107" to-port="0" />
+		<edge from-layer="96" from-port="0" to-layer="97" to-port="0" />
+		<edge from-layer="97" from-port="1" to-layer="99" to-port="0" />
+		<edge from-layer="98" from-port="0" to-layer="99" to-port="1" />
+		<edge from-layer="99" from-port="2" to-layer="100" to-port="1" />
+		<edge from-layer="100" from-port="2" to-layer="102" to-port="0" />
+		<edge from-layer="101" from-port="0" to-layer="102" to-port="1" />
+		<edge from-layer="102" from-port="2" to-layer="104" to-port="0" />
+		<edge from-layer="103" from-port="0" to-layer="104" to-port="1" />
+		<edge from-layer="104" from-port="2" to-layer="106" to-port="0" />
+		<edge from-layer="105" from-port="0" to-layer="106" to-port="1" />
+		<edge from-layer="106" from-port="2" to-layer="107" to-port="1" />
+		<edge from-layer="107" from-port="2" to-layer="109" to-port="0" />
+		<edge from-layer="108" from-port="0" to-layer="109" to-port="1" />
+		<edge from-layer="109" from-port="2" to-layer="111" to-port="0" />
+		<edge from-layer="110" from-port="0" to-layer="111" to-port="1" />
+		<edge from-layer="111" from-port="2" to-layer="113" to-port="0" />
+		<edge from-layer="112" from-port="0" to-layer="113" to-port="1" />
+		<edge from-layer="113" from-port="2" to-layer="118" to-port="0" />
+		<edge from-layer="114" from-port="0" to-layer="118" to-port="1" />
+		<edge from-layer="115" from-port="0" to-layer="118" to-port="2" />
+		<edge from-layer="116" from-port="0" to-layer="118" to-port="3" />
+		<edge from-layer="117" from-port="0" to-layer="118" to-port="4" />
+		<edge from-layer="118" from-port="5" to-layer="123" to-port="0" />
+		<edge from-layer="119" from-port="0" to-layer="120" to-port="0" />
+		<edge from-layer="120" from-port="1" to-layer="122" to-port="0" />
+		<edge from-layer="121" from-port="0" to-layer="122" to-port="1" />
+		<edge from-layer="122" from-port="2" to-layer="123" to-port="1" />
+		<edge from-layer="123" from-port="2" to-layer="125" to-port="0" />
+		<edge from-layer="124" from-port="0" to-layer="125" to-port="1" />
+		<edge from-layer="125" from-port="2" to-layer="126" to-port="0" />
+		<edge from-layer="126" from-port="2" to-layer="128" to-port="0" />
+		<edge from-layer="127" from-port="0" to-layer="128" to-port="1" />
+		<edge from-layer="128" from-port="2" to-layer="130" to-port="0" />
+		<edge from-layer="129" from-port="0" to-layer="130" to-port="1" />
+		<edge from-layer="130" from-port="2" to-layer="132" to-port="0" />
+		<edge from-layer="131" from-port="0" to-layer="132" to-port="1" />
+		<edge from-layer="132" from-port="2" to-layer="134" to-port="0" />
+		<edge from-layer="132" from-port="2" to-layer="162" to-port="1" />
+		<edge from-layer="133" from-port="0" to-layer="134" to-port="1" />
+		<edge from-layer="134" from-port="2" to-layer="139" to-port="0" />
+		<edge from-layer="135" from-port="0" to-layer="139" to-port="1" />
+		<edge from-layer="136" from-port="0" to-layer="139" to-port="2" />
+		<edge from-layer="137" from-port="0" to-layer="139" to-port="3" />
+		<edge from-layer="138" from-port="0" to-layer="139" to-port="4" />
+		<edge from-layer="139" from-port="5" to-layer="144" to-port="0" />
+		<edge from-layer="140" from-port="0" to-layer="141" to-port="0" />
+		<edge from-layer="141" from-port="1" to-layer="143" to-port="0" />
+		<edge from-layer="142" from-port="0" to-layer="143" to-port="1" />
+		<edge from-layer="143" from-port="2" to-layer="144" to-port="1" />
+		<edge from-layer="144" from-port="2" to-layer="146" to-port="0" />
+		<edge from-layer="145" from-port="0" to-layer="146" to-port="1" />
+		<edge from-layer="146" from-port="2" to-layer="147" to-port="0" />
+		<edge from-layer="147" from-port="1" to-layer="149" to-port="0" />
+		<edge from-layer="148" from-port="0" to-layer="149" to-port="1" />
+		<edge from-layer="149" from-port="2" to-layer="154" to-port="0" />
+		<edge from-layer="150" from-port="0" to-layer="154" to-port="1" />
+		<edge from-layer="151" from-port="0" to-layer="154" to-port="2" />
+		<edge from-layer="152" from-port="0" to-layer="154" to-port="3" />
+		<edge from-layer="153" from-port="0" to-layer="154" to-port="4" />
+		<edge from-layer="154" from-port="5" to-layer="159" to-port="0" />
+		<edge from-layer="155" from-port="0" to-layer="156" to-port="0" />
+		<edge from-layer="156" from-port="1" to-layer="158" to-port="0" />
+		<edge from-layer="157" from-port="0" to-layer="158" to-port="1" />
+		<edge from-layer="158" from-port="2" to-layer="159" to-port="1" />
+		<edge from-layer="159" from-port="2" to-layer="161" to-port="0" />
+		<edge from-layer="160" from-port="0" to-layer="161" to-port="1" />
+		<edge from-layer="161" from-port="2" to-layer="162" to-port="0" />
+		<edge from-layer="162" from-port="2" to-layer="164" to-port="0" />
+		<edge from-layer="163" from-port="0" to-layer="164" to-port="1" />
+		<edge from-layer="164" from-port="2" to-layer="166" to-port="0" />
+		<edge from-layer="165" from-port="0" to-layer="166" to-port="1" />
+		<edge from-layer="166" from-port="2" to-layer="168" to-port="0" />
+		<edge from-layer="167" from-port="0" to-layer="168" to-port="1" />
+		<edge from-layer="168" from-port="2" to-layer="170" to-port="0" />
+		<edge from-layer="168" from-port="2" to-layer="243" to-port="1" />
+		<edge from-layer="169" from-port="0" to-layer="170" to-port="1" />
+		<edge from-layer="170" from-port="2" to-layer="175" to-port="0" />
+		<edge from-layer="171" from-port="0" to-layer="175" to-port="1" />
+		<edge from-layer="172" from-port="0" to-layer="175" to-port="2" />
+		<edge from-layer="173" from-port="0" to-layer="175" to-port="3" />
+		<edge from-layer="174" from-port="0" to-layer="175" to-port="4" />
+		<edge from-layer="175" from-port="5" to-layer="180" to-port="0" />
+		<edge from-layer="175" from-port="5" to-layer="196" to-port="0" />
+		<edge from-layer="175" from-port="5" to-layer="217" to-port="0" />
+		<edge from-layer="176" from-port="0" to-layer="177" to-port="0" />
+		<edge from-layer="177" from-port="1" to-layer="179" to-port="0" />
+		<edge from-layer="178" from-port="0" to-layer="179" to-port="1" />
+		<edge from-layer="179" from-port="2" to-layer="180" to-port="1" />
+		<edge from-layer="180" from-port="2" to-layer="182" to-port="0" />
+		<edge from-layer="181" from-port="0" to-layer="182" to-port="1" />
+		<edge from-layer="182" from-port="2" to-layer="187" to-port="0" />
+		<edge from-layer="183" from-port="0" to-layer="187" to-port="1" />
+		<edge from-layer="184" from-port="0" to-layer="187" to-port="2" />
+		<edge from-layer="185" from-port="0" to-layer="187" to-port="3" />
+		<edge from-layer="186" from-port="0" to-layer="187" to-port="4" />
+		<edge from-layer="187" from-port="5" to-layer="189" to-port="0" />
+		<edge from-layer="188" from-port="0" to-layer="189" to-port="1" />
+		<edge from-layer="189" from-port="2" to-layer="191" to-port="0" />
+		<edge from-layer="190" from-port="0" to-layer="191" to-port="1" />
+		<edge from-layer="191" from-port="2" to-layer="208" to-port="0" />
+		<edge from-layer="192" from-port="0" to-layer="193" to-port="0" />
+		<edge from-layer="193" from-port="1" to-layer="195" to-port="0" />
+		<edge from-layer="194" from-port="0" to-layer="195" to-port="1" />
+		<edge from-layer="195" from-port="2" to-layer="196" to-port="1" />
+		<edge from-layer="196" from-port="2" to-layer="198" to-port="0" />
+		<edge from-layer="197" from-port="0" to-layer="198" to-port="1" />
+		<edge from-layer="198" from-port="2" to-layer="203" to-port="0" />
+		<edge from-layer="199" from-port="0" to-layer="203" to-port="1" />
+		<edge from-layer="200" from-port="0" to-layer="203" to-port="2" />
+		<edge from-layer="201" from-port="0" to-layer="203" to-port="3" />
+		<edge from-layer="202" from-port="0" to-layer="203" to-port="4" />
+		<edge from-layer="203" from-port="5" to-layer="205" to-port="0" />
+		<edge from-layer="204" from-port="0" to-layer="205" to-port="1" />
+		<edge from-layer="205" from-port="2" to-layer="207" to-port="0" />
+		<edge from-layer="206" from-port="0" to-layer="207" to-port="1" />
+		<edge from-layer="207" from-port="2" to-layer="208" to-port="1" />
+		<edge from-layer="208" from-port="2" to-layer="210" to-port="0" />
+		<edge from-layer="209" from-port="0" to-layer="210" to-port="1" />
+		<edge from-layer="210" from-port="2" to-layer="211" to-port="0" />
+		<edge from-layer="211" from-port="2" to-layer="212" to-port="0" />
+		<edge from-layer="212" from-port="1" to-layer="224" to-port="0" />
+		<edge from-layer="213" from-port="0" to-layer="214" to-port="0" />
+		<edge from-layer="214" from-port="1" to-layer="216" to-port="0" />
+		<edge from-layer="215" from-port="0" to-layer="216" to-port="1" />
+		<edge from-layer="216" from-port="2" to-layer="217" to-port="1" />
+		<edge from-layer="217" from-port="2" to-layer="219" to-port="0" />
+		<edge from-layer="218" from-port="0" to-layer="219" to-port="1" />
+		<edge from-layer="219" from-port="2" to-layer="221" to-port="0" />
+		<edge from-layer="220" from-port="0" to-layer="221" to-port="1" />
+		<edge from-layer="221" from-port="2" to-layer="223" to-port="0" />
+		<edge from-layer="222" from-port="0" to-layer="223" to-port="1" />
+		<edge from-layer="223" from-port="2" to-layer="224" to-port="1" />
+		<edge from-layer="224" from-port="2" to-layer="226" to-port="0" />
+		<edge from-layer="225" from-port="0" to-layer="226" to-port="1" />
+		<edge from-layer="226" from-port="2" to-layer="228" to-port="0" />
+		<edge from-layer="227" from-port="0" to-layer="228" to-port="1" />
+		<edge from-layer="228" from-port="2" to-layer="230" to-port="0" />
+		<edge from-layer="229" from-port="0" to-layer="230" to-port="1" />
+		<edge from-layer="230" from-port="2" to-layer="235" to-port="0" />
+		<edge from-layer="231" from-port="0" to-layer="235" to-port="1" />
+		<edge from-layer="232" from-port="0" to-layer="235" to-port="2" />
+		<edge from-layer="233" from-port="0" to-layer="235" to-port="3" />
+		<edge from-layer="234" from-port="0" to-layer="235" to-port="4" />
+		<edge from-layer="235" from-port="5" to-layer="240" to-port="0" />
+		<edge from-layer="236" from-port="0" to-layer="237" to-port="0" />
+		<edge from-layer="237" from-port="1" to-layer="239" to-port="0" />
+		<edge from-layer="238" from-port="0" to-layer="239" to-port="1" />
+		<edge from-layer="239" from-port="2" to-layer="240" to-port="1" />
+		<edge from-layer="240" from-port="2" to-layer="242" to-port="0" />
+		<edge from-layer="241" from-port="0" to-layer="242" to-port="1" />
+		<edge from-layer="242" from-port="2" to-layer="243" to-port="0" />
+		<edge from-layer="243" from-port="2" to-layer="245" to-port="0" />
+		<edge from-layer="244" from-port="0" to-layer="245" to-port="1" />
+		<edge from-layer="245" from-port="2" to-layer="247" to-port="0" />
+		<edge from-layer="246" from-port="0" to-layer="247" to-port="1" />
+		<edge from-layer="247" from-port="2" to-layer="249" to-port="0" />
+		<edge from-layer="248" from-port="0" to-layer="249" to-port="1" />
+		<edge from-layer="249" from-port="2" to-layer="251" to-port="0" />
+		<edge from-layer="249" from-port="2" to-layer="279" to-port="1" />
+		<edge from-layer="250" from-port="0" to-layer="251" to-port="1" />
+		<edge from-layer="251" from-port="2" to-layer="256" to-port="0" />
+		<edge from-layer="252" from-port="0" to-layer="256" to-port="1" />
+		<edge from-layer="253" from-port="0" to-layer="256" to-port="2" />
+		<edge from-layer="254" from-port="0" to-layer="256" to-port="3" />
+		<edge from-layer="255" from-port="0" to-layer="256" to-port="4" />
+		<edge from-layer="256" from-port="5" to-layer="261" to-port="0" />
+		<edge from-layer="257" from-port="0" to-layer="258" to-port="0" />
+		<edge from-layer="258" from-port="1" to-layer="260" to-port="0" />
+		<edge from-layer="259" from-port="0" to-layer="260" to-port="1" />
+		<edge from-layer="260" from-port="2" to-layer="261" to-port="1" />
+		<edge from-layer="261" from-port="2" to-layer="263" to-port="0" />
+		<edge from-layer="262" from-port="0" to-layer="263" to-port="1" />
+		<edge from-layer="263" from-port="2" to-layer="264" to-port="0" />
+		<edge from-layer="264" from-port="1" to-layer="266" to-port="0" />
+		<edge from-layer="265" from-port="0" to-layer="266" to-port="1" />
+		<edge from-layer="266" from-port="2" to-layer="271" to-port="0" />
+		<edge from-layer="267" from-port="0" to-layer="271" to-port="1" />
+		<edge from-layer="268" from-port="0" to-layer="271" to-port="2" />
+		<edge from-layer="269" from-port="0" to-layer="271" to-port="3" />
+		<edge from-layer="270" from-port="0" to-layer="271" to-port="4" />
+		<edge from-layer="271" from-port="5" to-layer="276" to-port="0" />
+		<edge from-layer="272" from-port="0" to-layer="273" to-port="0" />
+		<edge from-layer="273" from-port="1" to-layer="275" to-port="0" />
+		<edge from-layer="274" from-port="0" to-layer="275" to-port="1" />
+		<edge from-layer="275" from-port="2" to-layer="276" to-port="1" />
+		<edge from-layer="276" from-port="2" to-layer="278" to-port="0" />
+		<edge from-layer="277" from-port="0" to-layer="278" to-port="1" />
+		<edge from-layer="278" from-port="2" to-layer="279" to-port="0" />
+		<edge from-layer="279" from-port="2" to-layer="281" to-port="0" />
+		<edge from-layer="280" from-port="0" to-layer="281" to-port="1" />
+		<edge from-layer="281" from-port="2" to-layer="283" to-port="0" />
+		<edge from-layer="282" from-port="0" to-layer="283" to-port="1" />
+		<edge from-layer="283" from-port="2" to-layer="285" to-port="0" />
+		<edge from-layer="284" from-port="0" to-layer="285" to-port="1" />
+		<edge from-layer="285" from-port="2" to-layer="287" to-port="0" />
+		<edge from-layer="285" from-port="2" to-layer="360" to-port="1" />
+		<edge from-layer="286" from-port="0" to-layer="287" to-port="1" />
+		<edge from-layer="287" from-port="2" to-layer="292" to-port="0" />
+		<edge from-layer="288" from-port="0" to-layer="292" to-port="1" />
+		<edge from-layer="289" from-port="0" to-layer="292" to-port="2" />
+		<edge from-layer="290" from-port="0" to-layer="292" to-port="3" />
+		<edge from-layer="291" from-port="0" to-layer="292" to-port="4" />
+		<edge from-layer="292" from-port="5" to-layer="297" to-port="0" />
+		<edge from-layer="292" from-port="5" to-layer="313" to-port="0" />
+		<edge from-layer="292" from-port="5" to-layer="334" to-port="0" />
+		<edge from-layer="293" from-port="0" to-layer="294" to-port="0" />
+		<edge from-layer="294" from-port="1" to-layer="296" to-port="0" />
+		<edge from-layer="295" from-port="0" to-layer="296" to-port="1" />
+		<edge from-layer="296" from-port="2" to-layer="297" to-port="1" />
+		<edge from-layer="297" from-port="2" to-layer="299" to-port="0" />
+		<edge from-layer="298" from-port="0" to-layer="299" to-port="1" />
+		<edge from-layer="299" from-port="2" to-layer="304" to-port="0" />
+		<edge from-layer="300" from-port="0" to-layer="304" to-port="1" />
+		<edge from-layer="301" from-port="0" to-layer="304" to-port="2" />
+		<edge from-layer="302" from-port="0" to-layer="304" to-port="3" />
+		<edge from-layer="303" from-port="0" to-layer="304" to-port="4" />
+		<edge from-layer="304" from-port="5" to-layer="306" to-port="0" />
+		<edge from-layer="305" from-port="0" to-layer="306" to-port="1" />
+		<edge from-layer="306" from-port="2" to-layer="308" to-port="0" />
+		<edge from-layer="307" from-port="0" to-layer="308" to-port="1" />
+		<edge from-layer="308" from-port="2" to-layer="325" to-port="0" />
+		<edge from-layer="309" from-port="0" to-layer="310" to-port="0" />
+		<edge from-layer="310" from-port="1" to-layer="312" to-port="0" />
+		<edge from-layer="311" from-port="0" to-layer="312" to-port="1" />
+		<edge from-layer="312" from-port="2" to-layer="313" to-port="1" />
+		<edge from-layer="313" from-port="2" to-layer="315" to-port="0" />
+		<edge from-layer="314" from-port="0" to-layer="315" to-port="1" />
+		<edge from-layer="315" from-port="2" to-layer="320" to-port="0" />
+		<edge from-layer="316" from-port="0" to-layer="320" to-port="1" />
+		<edge from-layer="317" from-port="0" to-layer="320" to-port="2" />
+		<edge from-layer="318" from-port="0" to-layer="320" to-port="3" />
+		<edge from-layer="319" from-port="0" to-layer="320" to-port="4" />
+		<edge from-layer="320" from-port="5" to-layer="322" to-port="0" />
+		<edge from-layer="321" from-port="0" to-layer="322" to-port="1" />
+		<edge from-layer="322" from-port="2" to-layer="324" to-port="0" />
+		<edge from-layer="323" from-port="0" to-layer="324" to-port="1" />
+		<edge from-layer="324" from-port="2" to-layer="325" to-port="1" />
+		<edge from-layer="325" from-port="2" to-layer="327" to-port="0" />
+		<edge from-layer="326" from-port="0" to-layer="327" to-port="1" />
+		<edge from-layer="327" from-port="2" to-layer="328" to-port="0" />
+		<edge from-layer="328" from-port="2" to-layer="329" to-port="0" />
+		<edge from-layer="329" from-port="1" to-layer="341" to-port="0" />
+		<edge from-layer="330" from-port="0" to-layer="331" to-port="0" />
+		<edge from-layer="331" from-port="1" to-layer="333" to-port="0" />
+		<edge from-layer="332" from-port="0" to-layer="333" to-port="1" />
+		<edge from-layer="333" from-port="2" to-layer="334" to-port="1" />
+		<edge from-layer="334" from-port="2" to-layer="336" to-port="0" />
+		<edge from-layer="335" from-port="0" to-layer="336" to-port="1" />
+		<edge from-layer="336" from-port="2" to-layer="338" to-port="0" />
+		<edge from-layer="337" from-port="0" to-layer="338" to-port="1" />
+		<edge from-layer="338" from-port="2" to-layer="340" to-port="0" />
+		<edge from-layer="339" from-port="0" to-layer="340" to-port="1" />
+		<edge from-layer="340" from-port="2" to-layer="341" to-port="1" />
+		<edge from-layer="341" from-port="2" to-layer="343" to-port="0" />
+		<edge from-layer="342" from-port="0" to-layer="343" to-port="1" />
+		<edge from-layer="343" from-port="2" to-layer="345" to-port="0" />
+		<edge from-layer="344" from-port="0" to-layer="345" to-port="1" />
+		<edge from-layer="345" from-port="2" to-layer="347" to-port="0" />
+		<edge from-layer="346" from-port="0" to-layer="347" to-port="1" />
+		<edge from-layer="347" from-port="2" to-layer="352" to-port="0" />
+		<edge from-layer="348" from-port="0" to-layer="352" to-port="1" />
+		<edge from-layer="349" from-port="0" to-layer="352" to-port="2" />
+		<edge from-layer="350" from-port="0" to-layer="352" to-port="3" />
+		<edge from-layer="351" from-port="0" to-layer="352" to-port="4" />
+		<edge from-layer="352" from-port="5" to-layer="357" to-port="0" />
+		<edge from-layer="353" from-port="0" to-layer="354" to-port="0" />
+		<edge from-layer="354" from-port="1" to-layer="356" to-port="0" />
+		<edge from-layer="355" from-port="0" to-layer="356" to-port="1" />
+		<edge from-layer="356" from-port="2" to-layer="357" to-port="1" />
+		<edge from-layer="357" from-port="2" to-layer="359" to-port="0" />
+		<edge from-layer="358" from-port="0" to-layer="359" to-port="1" />
+		<edge from-layer="359" from-port="2" to-layer="360" to-port="0" />
+		<edge from-layer="360" from-port="2" to-layer="362" to-port="0" />
+		<edge from-layer="361" from-port="0" to-layer="362" to-port="1" />
+		<edge from-layer="362" from-port="2" to-layer="364" to-port="0" />
+		<edge from-layer="363" from-port="0" to-layer="364" to-port="1" />
+		<edge from-layer="364" from-port="2" to-layer="366" to-port="0" />
+		<edge from-layer="365" from-port="0" to-layer="366" to-port="1" />
+		<edge from-layer="366" from-port="2" to-layer="368" to-port="0" />
+		<edge from-layer="366" from-port="2" to-layer="396" to-port="1" />
+		<edge from-layer="367" from-port="0" to-layer="368" to-port="1" />
+		<edge from-layer="368" from-port="2" to-layer="373" to-port="0" />
+		<edge from-layer="369" from-port="0" to-layer="373" to-port="1" />
+		<edge from-layer="370" from-port="0" to-layer="373" to-port="2" />
+		<edge from-layer="371" from-port="0" to-layer="373" to-port="3" />
+		<edge from-layer="372" from-port="0" to-layer="373" to-port="4" />
+		<edge from-layer="373" from-port="5" to-layer="378" to-port="0" />
+		<edge from-layer="374" from-port="0" to-layer="375" to-port="0" />
+		<edge from-layer="375" from-port="1" to-layer="377" to-port="0" />
+		<edge from-layer="376" from-port="0" to-layer="377" to-port="1" />
+		<edge from-layer="377" from-port="2" to-layer="378" to-port="1" />
+		<edge from-layer="378" from-port="2" to-layer="380" to-port="0" />
+		<edge from-layer="379" from-port="0" to-layer="380" to-port="1" />
+		<edge from-layer="380" from-port="2" to-layer="381" to-port="0" />
+		<edge from-layer="381" from-port="1" to-layer="383" to-port="0" />
+		<edge from-layer="382" from-port="0" to-layer="383" to-port="1" />
+		<edge from-layer="383" from-port="2" to-layer="388" to-port="0" />
+		<edge from-layer="384" from-port="0" to-layer="388" to-port="1" />
+		<edge from-layer="385" from-port="0" to-layer="388" to-port="2" />
+		<edge from-layer="386" from-port="0" to-layer="388" to-port="3" />
+		<edge from-layer="387" from-port="0" to-layer="388" to-port="4" />
+		<edge from-layer="388" from-port="5" to-layer="393" to-port="0" />
+		<edge from-layer="389" from-port="0" to-layer="390" to-port="0" />
+		<edge from-layer="390" from-port="1" to-layer="392" to-port="0" />
+		<edge from-layer="391" from-port="0" to-layer="392" to-port="1" />
+		<edge from-layer="392" from-port="2" to-layer="393" to-port="1" />
+		<edge from-layer="393" from-port="2" to-layer="395" to-port="0" />
+		<edge from-layer="394" from-port="0" to-layer="395" to-port="1" />
+		<edge from-layer="395" from-port="2" to-layer="396" to-port="0" />
+		<edge from-layer="396" from-port="2" to-layer="398" to-port="0" />
+		<edge from-layer="397" from-port="0" to-layer="398" to-port="1" />
+		<edge from-layer="398" from-port="2" to-layer="400" to-port="0" />
+		<edge from-layer="399" from-port="0" to-layer="400" to-port="1" />
+		<edge from-layer="400" from-port="2" to-layer="402" to-port="0" />
+		<edge from-layer="401" from-port="0" to-layer="402" to-port="1" />
+		<edge from-layer="402" from-port="2" to-layer="404" to-port="0" />
+		<edge from-layer="402" from-port="2" to-layer="477" to-port="1" />
+		<edge from-layer="403" from-port="0" to-layer="404" to-port="1" />
+		<edge from-layer="404" from-port="2" to-layer="409" to-port="0" />
+		<edge from-layer="405" from-port="0" to-layer="409" to-port="1" />
+		<edge from-layer="406" from-port="0" to-layer="409" to-port="2" />
+		<edge from-layer="407" from-port="0" to-layer="409" to-port="3" />
+		<edge from-layer="408" from-port="0" to-layer="409" to-port="4" />
+		<edge from-layer="409" from-port="5" to-layer="430" to-port="0" />
+		<edge from-layer="409" from-port="5" to-layer="414" to-port="0" />
+		<edge from-layer="409" from-port="5" to-layer="451" to-port="0" />
+		<edge from-layer="410" from-port="0" to-layer="411" to-port="0" />
+		<edge from-layer="411" from-port="1" to-layer="413" to-port="0" />
+		<edge from-layer="412" from-port="0" to-layer="413" to-port="1" />
+		<edge from-layer="413" from-port="2" to-layer="414" to-port="1" />
+		<edge from-layer="414" from-port="2" to-layer="416" to-port="0" />
+		<edge from-layer="415" from-port="0" to-layer="416" to-port="1" />
+		<edge from-layer="416" from-port="2" to-layer="421" to-port="0" />
+		<edge from-layer="417" from-port="0" to-layer="421" to-port="1" />
+		<edge from-layer="418" from-port="0" to-layer="421" to-port="2" />
+		<edge from-layer="419" from-port="0" to-layer="421" to-port="3" />
+		<edge from-layer="420" from-port="0" to-layer="421" to-port="4" />
+		<edge from-layer="421" from-port="5" to-layer="423" to-port="0" />
+		<edge from-layer="422" from-port="0" to-layer="423" to-port="1" />
+		<edge from-layer="423" from-port="2" to-layer="425" to-port="0" />
+		<edge from-layer="424" from-port="0" to-layer="425" to-port="1" />
+		<edge from-layer="425" from-port="2" to-layer="442" to-port="0" />
+		<edge from-layer="426" from-port="0" to-layer="427" to-port="0" />
+		<edge from-layer="427" from-port="1" to-layer="429" to-port="0" />
+		<edge from-layer="428" from-port="0" to-layer="429" to-port="1" />
+		<edge from-layer="429" from-port="2" to-layer="430" to-port="1" />
+		<edge from-layer="430" from-port="2" to-layer="432" to-port="0" />
+		<edge from-layer="431" from-port="0" to-layer="432" to-port="1" />
+		<edge from-layer="432" from-port="2" to-layer="437" to-port="0" />
+		<edge from-layer="433" from-port="0" to-layer="437" to-port="1" />
+		<edge from-layer="434" from-port="0" to-layer="437" to-port="2" />
+		<edge from-layer="435" from-port="0" to-layer="437" to-port="3" />
+		<edge from-layer="436" from-port="0" to-layer="437" to-port="4" />
+		<edge from-layer="437" from-port="5" to-layer="439" to-port="0" />
+		<edge from-layer="438" from-port="0" to-layer="439" to-port="1" />
+		<edge from-layer="439" from-port="2" to-layer="441" to-port="0" />
+		<edge from-layer="440" from-port="0" to-layer="441" to-port="1" />
+		<edge from-layer="441" from-port="2" to-layer="442" to-port="1" />
+		<edge from-layer="442" from-port="2" to-layer="444" to-port="0" />
+		<edge from-layer="443" from-port="0" to-layer="444" to-port="1" />
+		<edge from-layer="444" from-port="2" to-layer="445" to-port="0" />
+		<edge from-layer="445" from-port="2" to-layer="446" to-port="0" />
+		<edge from-layer="446" from-port="1" to-layer="458" to-port="0" />
+		<edge from-layer="447" from-port="0" to-layer="448" to-port="0" />
+		<edge from-layer="448" from-port="1" to-layer="450" to-port="0" />
+		<edge from-layer="449" from-port="0" to-layer="450" to-port="1" />
+		<edge from-layer="450" from-port="2" to-layer="451" to-port="1" />
+		<edge from-layer="451" from-port="2" to-layer="453" to-port="0" />
+		<edge from-layer="452" from-port="0" to-layer="453" to-port="1" />
+		<edge from-layer="453" from-port="2" to-layer="455" to-port="0" />
+		<edge from-layer="454" from-port="0" to-layer="455" to-port="1" />
+		<edge from-layer="455" from-port="2" to-layer="457" to-port="0" />
+		<edge from-layer="456" from-port="0" to-layer="457" to-port="1" />
+		<edge from-layer="457" from-port="2" to-layer="458" to-port="1" />
+		<edge from-layer="458" from-port="2" to-layer="460" to-port="0" />
+		<edge from-layer="459" from-port="0" to-layer="460" to-port="1" />
+		<edge from-layer="460" from-port="2" to-layer="462" to-port="0" />
+		<edge from-layer="461" from-port="0" to-layer="462" to-port="1" />
+		<edge from-layer="462" from-port="2" to-layer="464" to-port="0" />
+		<edge from-layer="463" from-port="0" to-layer="464" to-port="1" />
+		<edge from-layer="464" from-port="2" to-layer="469" to-port="0" />
+		<edge from-layer="465" from-port="0" to-layer="469" to-port="1" />
+		<edge from-layer="466" from-port="0" to-layer="469" to-port="2" />
+		<edge from-layer="467" from-port="0" to-layer="469" to-port="3" />
+		<edge from-layer="468" from-port="0" to-layer="469" to-port="4" />
+		<edge from-layer="469" from-port="5" to-layer="474" to-port="0" />
+		<edge from-layer="470" from-port="0" to-layer="471" to-port="0" />
+		<edge from-layer="471" from-port="1" to-layer="473" to-port="0" />
+		<edge from-layer="472" from-port="0" to-layer="473" to-port="1" />
+		<edge from-layer="473" from-port="2" to-layer="474" to-port="1" />
+		<edge from-layer="474" from-port="2" to-layer="476" to-port="0" />
+		<edge from-layer="475" from-port="0" to-layer="476" to-port="1" />
+		<edge from-layer="476" from-port="2" to-layer="477" to-port="0" />
+		<edge from-layer="477" from-port="2" to-layer="479" to-port="0" />
+		<edge from-layer="478" from-port="0" to-layer="479" to-port="1" />
+		<edge from-layer="479" from-port="2" to-layer="481" to-port="0" />
+		<edge from-layer="480" from-port="0" to-layer="481" to-port="1" />
+		<edge from-layer="481" from-port="2" to-layer="483" to-port="0" />
+		<edge from-layer="482" from-port="0" to-layer="483" to-port="1" />
+		<edge from-layer="483" from-port="2" to-layer="513" to-port="1" />
+		<edge from-layer="483" from-port="2" to-layer="485" to-port="0" />
+		<edge from-layer="484" from-port="0" to-layer="485" to-port="1" />
+		<edge from-layer="485" from-port="2" to-layer="490" to-port="0" />
+		<edge from-layer="486" from-port="0" to-layer="490" to-port="1" />
+		<edge from-layer="487" from-port="0" to-layer="490" to-port="2" />
+		<edge from-layer="488" from-port="0" to-layer="490" to-port="3" />
+		<edge from-layer="489" from-port="0" to-layer="490" to-port="4" />
+		<edge from-layer="490" from-port="5" to-layer="495" to-port="0" />
+		<edge from-layer="491" from-port="0" to-layer="492" to-port="0" />
+		<edge from-layer="492" from-port="1" to-layer="494" to-port="0" />
+		<edge from-layer="493" from-port="0" to-layer="494" to-port="1" />
+		<edge from-layer="494" from-port="2" to-layer="495" to-port="1" />
+		<edge from-layer="495" from-port="2" to-layer="497" to-port="0" />
+		<edge from-layer="496" from-port="0" to-layer="497" to-port="1" />
+		<edge from-layer="497" from-port="2" to-layer="498" to-port="0" />
+		<edge from-layer="498" from-port="1" to-layer="500" to-port="0" />
+		<edge from-layer="499" from-port="0" to-layer="500" to-port="1" />
+		<edge from-layer="500" from-port="2" to-layer="505" to-port="0" />
+		<edge from-layer="501" from-port="0" to-layer="505" to-port="1" />
+		<edge from-layer="502" from-port="0" to-layer="505" to-port="2" />
+		<edge from-layer="503" from-port="0" to-layer="505" to-port="3" />
+		<edge from-layer="504" from-port="0" to-layer="505" to-port="4" />
+		<edge from-layer="505" from-port="5" to-layer="510" to-port="0" />
+		<edge from-layer="506" from-port="0" to-layer="507" to-port="0" />
+		<edge from-layer="507" from-port="1" to-layer="509" to-port="0" />
+		<edge from-layer="508" from-port="0" to-layer="509" to-port="1" />
+		<edge from-layer="509" from-port="2" to-layer="510" to-port="1" />
+		<edge from-layer="510" from-port="2" to-layer="512" to-port="0" />
+		<edge from-layer="511" from-port="0" to-layer="512" to-port="1" />
+		<edge from-layer="512" from-port="2" to-layer="513" to-port="0" />
+		<edge from-layer="513" from-port="2" to-layer="515" to-port="0" />
+		<edge from-layer="514" from-port="0" to-layer="515" to-port="1" />
+		<edge from-layer="515" from-port="2" to-layer="517" to-port="0" />
+		<edge from-layer="516" from-port="0" to-layer="517" to-port="1" />
+		<edge from-layer="517" from-port="2" to-layer="519" to-port="0" />
+		<edge from-layer="518" from-port="0" to-layer="519" to-port="1" />
+		<edge from-layer="519" from-port="2" to-layer="521" to-port="0" />
+		<edge from-layer="519" from-port="2" to-layer="594" to-port="1" />
+		<edge from-layer="520" from-port="0" to-layer="521" to-port="1" />
+		<edge from-layer="521" from-port="2" to-layer="526" to-port="0" />
+		<edge from-layer="522" from-port="0" to-layer="526" to-port="1" />
+		<edge from-layer="523" from-port="0" to-layer="526" to-port="2" />
+		<edge from-layer="524" from-port="0" to-layer="526" to-port="3" />
+		<edge from-layer="525" from-port="0" to-layer="526" to-port="4" />
+		<edge from-layer="526" from-port="5" to-layer="547" to-port="0" />
+		<edge from-layer="526" from-port="5" to-layer="531" to-port="0" />
+		<edge from-layer="526" from-port="5" to-layer="568" to-port="0" />
+		<edge from-layer="527" from-port="0" to-layer="528" to-port="0" />
+		<edge from-layer="528" from-port="1" to-layer="530" to-port="0" />
+		<edge from-layer="529" from-port="0" to-layer="530" to-port="1" />
+		<edge from-layer="530" from-port="2" to-layer="531" to-port="1" />
+		<edge from-layer="531" from-port="2" to-layer="533" to-port="0" />
+		<edge from-layer="532" from-port="0" to-layer="533" to-port="1" />
+		<edge from-layer="533" from-port="2" to-layer="538" to-port="0" />
+		<edge from-layer="534" from-port="0" to-layer="538" to-port="1" />
+		<edge from-layer="535" from-port="0" to-layer="538" to-port="2" />
+		<edge from-layer="536" from-port="0" to-layer="538" to-port="3" />
+		<edge from-layer="537" from-port="0" to-layer="538" to-port="4" />
+		<edge from-layer="538" from-port="5" to-layer="540" to-port="0" />
+		<edge from-layer="539" from-port="0" to-layer="540" to-port="1" />
+		<edge from-layer="540" from-port="2" to-layer="542" to-port="0" />
+		<edge from-layer="541" from-port="0" to-layer="542" to-port="1" />
+		<edge from-layer="542" from-port="2" to-layer="559" to-port="0" />
+		<edge from-layer="543" from-port="0" to-layer="544" to-port="0" />
+		<edge from-layer="544" from-port="1" to-layer="546" to-port="0" />
+		<edge from-layer="545" from-port="0" to-layer="546" to-port="1" />
+		<edge from-layer="546" from-port="2" to-layer="547" to-port="1" />
+		<edge from-layer="547" from-port="2" to-layer="549" to-port="0" />
+		<edge from-layer="548" from-port="0" to-layer="549" to-port="1" />
+		<edge from-layer="549" from-port="2" to-layer="554" to-port="0" />
+		<edge from-layer="550" from-port="0" to-layer="554" to-port="1" />
+		<edge from-layer="551" from-port="0" to-layer="554" to-port="2" />
+		<edge from-layer="552" from-port="0" to-layer="554" to-port="3" />
+		<edge from-layer="553" from-port="0" to-layer="554" to-port="4" />
+		<edge from-layer="554" from-port="5" to-layer="556" to-port="0" />
+		<edge from-layer="555" from-port="0" to-layer="556" to-port="1" />
+		<edge from-layer="556" from-port="2" to-layer="558" to-port="0" />
+		<edge from-layer="557" from-port="0" to-layer="558" to-port="1" />
+		<edge from-layer="558" from-port="2" to-layer="559" to-port="1" />
+		<edge from-layer="559" from-port="2" to-layer="561" to-port="0" />
+		<edge from-layer="560" from-port="0" to-layer="561" to-port="1" />
+		<edge from-layer="561" from-port="2" to-layer="562" to-port="0" />
+		<edge from-layer="562" from-port="2" to-layer="563" to-port="0" />
+		<edge from-layer="563" from-port="1" to-layer="575" to-port="0" />
+		<edge from-layer="564" from-port="0" to-layer="565" to-port="0" />
+		<edge from-layer="565" from-port="1" to-layer="567" to-port="0" />
+		<edge from-layer="566" from-port="0" to-layer="567" to-port="1" />
+		<edge from-layer="567" from-port="2" to-layer="568" to-port="1" />
+		<edge from-layer="568" from-port="2" to-layer="570" to-port="0" />
+		<edge from-layer="569" from-port="0" to-layer="570" to-port="1" />
+		<edge from-layer="570" from-port="2" to-layer="572" to-port="0" />
+		<edge from-layer="571" from-port="0" to-layer="572" to-port="1" />
+		<edge from-layer="572" from-port="2" to-layer="574" to-port="0" />
+		<edge from-layer="573" from-port="0" to-layer="574" to-port="1" />
+		<edge from-layer="574" from-port="2" to-layer="575" to-port="1" />
+		<edge from-layer="575" from-port="2" to-layer="577" to-port="0" />
+		<edge from-layer="576" from-port="0" to-layer="577" to-port="1" />
+		<edge from-layer="577" from-port="2" to-layer="579" to-port="0" />
+		<edge from-layer="578" from-port="0" to-layer="579" to-port="1" />
+		<edge from-layer="579" from-port="2" to-layer="581" to-port="0" />
+		<edge from-layer="580" from-port="0" to-layer="581" to-port="1" />
+		<edge from-layer="581" from-port="2" to-layer="586" to-port="0" />
+		<edge from-layer="582" from-port="0" to-layer="586" to-port="1" />
+		<edge from-layer="583" from-port="0" to-layer="586" to-port="2" />
+		<edge from-layer="584" from-port="0" to-layer="586" to-port="3" />
+		<edge from-layer="585" from-port="0" to-layer="586" to-port="4" />
+		<edge from-layer="586" from-port="5" to-layer="591" to-port="0" />
+		<edge from-layer="587" from-port="0" to-layer="588" to-port="0" />
+		<edge from-layer="588" from-port="1" to-layer="590" to-port="0" />
+		<edge from-layer="589" from-port="0" to-layer="590" to-port="1" />
+		<edge from-layer="590" from-port="2" to-layer="591" to-port="1" />
+		<edge from-layer="591" from-port="2" to-layer="593" to-port="0" />
+		<edge from-layer="592" from-port="0" to-layer="593" to-port="1" />
+		<edge from-layer="593" from-port="2" to-layer="594" to-port="0" />
+		<edge from-layer="594" from-port="2" to-layer="596" to-port="0" />
+		<edge from-layer="595" from-port="0" to-layer="596" to-port="1" />
+		<edge from-layer="596" from-port="2" to-layer="598" to-port="0" />
+		<edge from-layer="597" from-port="0" to-layer="598" to-port="1" />
+		<edge from-layer="598" from-port="2" to-layer="600" to-port="0" />
+		<edge from-layer="599" from-port="0" to-layer="600" to-port="1" />
+		<edge from-layer="600" from-port="2" to-layer="602" to-port="0" />
+		<edge from-layer="600" from-port="2" to-layer="630" to-port="1" />
+		<edge from-layer="601" from-port="0" to-layer="602" to-port="1" />
+		<edge from-layer="602" from-port="2" to-layer="607" to-port="0" />
+		<edge from-layer="603" from-port="0" to-layer="607" to-port="1" />
+		<edge from-layer="604" from-port="0" to-layer="607" to-port="2" />
+		<edge from-layer="605" from-port="0" to-layer="607" to-port="3" />
+		<edge from-layer="606" from-port="0" to-layer="607" to-port="4" />
+		<edge from-layer="607" from-port="5" to-layer="612" to-port="0" />
+		<edge from-layer="608" from-port="0" to-layer="609" to-port="0" />
+		<edge from-layer="609" from-port="1" to-layer="611" to-port="0" />
+		<edge from-layer="610" from-port="0" to-layer="611" to-port="1" />
+		<edge from-layer="611" from-port="2" to-layer="612" to-port="1" />
+		<edge from-layer="612" from-port="2" to-layer="614" to-port="0" />
+		<edge from-layer="613" from-port="0" to-layer="614" to-port="1" />
+		<edge from-layer="614" from-port="2" to-layer="615" to-port="0" />
+		<edge from-layer="615" from-port="1" to-layer="617" to-port="0" />
+		<edge from-layer="616" from-port="0" to-layer="617" to-port="1" />
+		<edge from-layer="617" from-port="2" to-layer="622" to-port="0" />
+		<edge from-layer="618" from-port="0" to-layer="622" to-port="1" />
+		<edge from-layer="619" from-port="0" to-layer="622" to-port="2" />
+		<edge from-layer="620" from-port="0" to-layer="622" to-port="3" />
+		<edge from-layer="621" from-port="0" to-layer="622" to-port="4" />
+		<edge from-layer="622" from-port="5" to-layer="627" to-port="0" />
+		<edge from-layer="623" from-port="0" to-layer="624" to-port="0" />
+		<edge from-layer="624" from-port="1" to-layer="626" to-port="0" />
+		<edge from-layer="625" from-port="0" to-layer="626" to-port="1" />
+		<edge from-layer="626" from-port="2" to-layer="627" to-port="1" />
+		<edge from-layer="627" from-port="2" to-layer="629" to-port="0" />
+		<edge from-layer="628" from-port="0" to-layer="629" to-port="1" />
+		<edge from-layer="629" from-port="2" to-layer="630" to-port="0" />
+		<edge from-layer="630" from-port="2" to-layer="632" to-port="0" />
+		<edge from-layer="631" from-port="0" to-layer="632" to-port="1" />
+		<edge from-layer="632" from-port="2" to-layer="634" to-port="0" />
+		<edge from-layer="633" from-port="0" to-layer="634" to-port="1" />
+		<edge from-layer="634" from-port="2" to-layer="636" to-port="0" />
+		<edge from-layer="635" from-port="0" to-layer="636" to-port="1" />
+		<edge from-layer="636" from-port="2" to-layer="638" to-port="0" />
+		<edge from-layer="636" from-port="2" to-layer="711" to-port="1" />
+		<edge from-layer="637" from-port="0" to-layer="638" to-port="1" />
+		<edge from-layer="638" from-port="2" to-layer="643" to-port="0" />
+		<edge from-layer="639" from-port="0" to-layer="643" to-port="1" />
+		<edge from-layer="640" from-port="0" to-layer="643" to-port="2" />
+		<edge from-layer="641" from-port="0" to-layer="643" to-port="3" />
+		<edge from-layer="642" from-port="0" to-layer="643" to-port="4" />
+		<edge from-layer="643" from-port="5" to-layer="648" to-port="0" />
+		<edge from-layer="643" from-port="5" to-layer="664" to-port="0" />
+		<edge from-layer="643" from-port="5" to-layer="685" to-port="0" />
+		<edge from-layer="644" from-port="0" to-layer="645" to-port="0" />
+		<edge from-layer="645" from-port="1" to-layer="647" to-port="0" />
+		<edge from-layer="646" from-port="0" to-layer="647" to-port="1" />
+		<edge from-layer="647" from-port="2" to-layer="648" to-port="1" />
+		<edge from-layer="648" from-port="2" to-layer="650" to-port="0" />
+		<edge from-layer="649" from-port="0" to-layer="650" to-port="1" />
+		<edge from-layer="650" from-port="2" to-layer="655" to-port="0" />
+		<edge from-layer="651" from-port="0" to-layer="655" to-port="1" />
+		<edge from-layer="652" from-port="0" to-layer="655" to-port="2" />
+		<edge from-layer="653" from-port="0" to-layer="655" to-port="3" />
+		<edge from-layer="654" from-port="0" to-layer="655" to-port="4" />
+		<edge from-layer="655" from-port="5" to-layer="657" to-port="0" />
+		<edge from-layer="656" from-port="0" to-layer="657" to-port="1" />
+		<edge from-layer="657" from-port="2" to-layer="659" to-port="0" />
+		<edge from-layer="658" from-port="0" to-layer="659" to-port="1" />
+		<edge from-layer="659" from-port="2" to-layer="676" to-port="0" />
+		<edge from-layer="660" from-port="0" to-layer="661" to-port="0" />
+		<edge from-layer="661" from-port="1" to-layer="663" to-port="0" />
+		<edge from-layer="662" from-port="0" to-layer="663" to-port="1" />
+		<edge from-layer="663" from-port="2" to-layer="664" to-port="1" />
+		<edge from-layer="664" from-port="2" to-layer="666" to-port="0" />
+		<edge from-layer="665" from-port="0" to-layer="666" to-port="1" />
+		<edge from-layer="666" from-port="2" to-layer="671" to-port="0" />
+		<edge from-layer="667" from-port="0" to-layer="671" to-port="1" />
+		<edge from-layer="668" from-port="0" to-layer="671" to-port="2" />
+		<edge from-layer="669" from-port="0" to-layer="671" to-port="3" />
+		<edge from-layer="670" from-port="0" to-layer="671" to-port="4" />
+		<edge from-layer="671" from-port="5" to-layer="673" to-port="0" />
+		<edge from-layer="672" from-port="0" to-layer="673" to-port="1" />
+		<edge from-layer="673" from-port="2" to-layer="675" to-port="0" />
+		<edge from-layer="674" from-port="0" to-layer="675" to-port="1" />
+		<edge from-layer="675" from-port="2" to-layer="676" to-port="1" />
+		<edge from-layer="676" from-port="2" to-layer="678" to-port="0" />
+		<edge from-layer="677" from-port="0" to-layer="678" to-port="1" />
+		<edge from-layer="678" from-port="2" to-layer="679" to-port="0" />
+		<edge from-layer="679" from-port="2" to-layer="680" to-port="0" />
+		<edge from-layer="680" from-port="1" to-layer="692" to-port="0" />
+		<edge from-layer="681" from-port="0" to-layer="682" to-port="0" />
+		<edge from-layer="682" from-port="1" to-layer="684" to-port="0" />
+		<edge from-layer="683" from-port="0" to-layer="684" to-port="1" />
+		<edge from-layer="684" from-port="2" to-layer="685" to-port="1" />
+		<edge from-layer="685" from-port="2" to-layer="687" to-port="0" />
+		<edge from-layer="686" from-port="0" to-layer="687" to-port="1" />
+		<edge from-layer="687" from-port="2" to-layer="689" to-port="0" />
+		<edge from-layer="688" from-port="0" to-layer="689" to-port="1" />
+		<edge from-layer="689" from-port="2" to-layer="691" to-port="0" />
+		<edge from-layer="690" from-port="0" to-layer="691" to-port="1" />
+		<edge from-layer="691" from-port="2" to-layer="692" to-port="1" />
+		<edge from-layer="692" from-port="2" to-layer="694" to-port="0" />
+		<edge from-layer="693" from-port="0" to-layer="694" to-port="1" />
+		<edge from-layer="694" from-port="2" to-layer="696" to-port="0" />
+		<edge from-layer="695" from-port="0" to-layer="696" to-port="1" />
+		<edge from-layer="696" from-port="2" to-layer="698" to-port="0" />
+		<edge from-layer="697" from-port="0" to-layer="698" to-port="1" />
+		<edge from-layer="698" from-port="2" to-layer="703" to-port="0" />
+		<edge from-layer="699" from-port="0" to-layer="703" to-port="1" />
+		<edge from-layer="700" from-port="0" to-layer="703" to-port="2" />
+		<edge from-layer="701" from-port="0" to-layer="703" to-port="3" />
+		<edge from-layer="702" from-port="0" to-layer="703" to-port="4" />
+		<edge from-layer="703" from-port="5" to-layer="708" to-port="0" />
+		<edge from-layer="704" from-port="0" to-layer="705" to-port="0" />
+		<edge from-layer="705" from-port="1" to-layer="707" to-port="0" />
+		<edge from-layer="706" from-port="0" to-layer="707" to-port="1" />
+		<edge from-layer="707" from-port="2" to-layer="708" to-port="1" />
+		<edge from-layer="708" from-port="2" to-layer="710" to-port="0" />
+		<edge from-layer="709" from-port="0" to-layer="710" to-port="1" />
+		<edge from-layer="710" from-port="2" to-layer="711" to-port="0" />
+		<edge from-layer="711" from-port="2" to-layer="713" to-port="0" />
+		<edge from-layer="712" from-port="0" to-layer="713" to-port="1" />
+		<edge from-layer="713" from-port="2" to-layer="715" to-port="0" />
+		<edge from-layer="714" from-port="0" to-layer="715" to-port="1" />
+		<edge from-layer="715" from-port="2" to-layer="717" to-port="0" />
+		<edge from-layer="716" from-port="0" to-layer="717" to-port="1" />
+		<edge from-layer="717" from-port="2" to-layer="719" to-port="0" />
+		<edge from-layer="717" from-port="2" to-layer="747" to-port="1" />
+		<edge from-layer="718" from-port="0" to-layer="719" to-port="1" />
+		<edge from-layer="719" from-port="2" to-layer="724" to-port="0" />
+		<edge from-layer="720" from-port="0" to-layer="724" to-port="1" />
+		<edge from-layer="721" from-port="0" to-layer="724" to-port="2" />
+		<edge from-layer="722" from-port="0" to-layer="724" to-port="3" />
+		<edge from-layer="723" from-port="0" to-layer="724" to-port="4" />
+		<edge from-layer="724" from-port="5" to-layer="729" to-port="0" />
+		<edge from-layer="725" from-port="0" to-layer="726" to-port="0" />
+		<edge from-layer="726" from-port="1" to-layer="728" to-port="0" />
+		<edge from-layer="727" from-port="0" to-layer="728" to-port="1" />
+		<edge from-layer="728" from-port="2" to-layer="729" to-port="1" />
+		<edge from-layer="729" from-port="2" to-layer="731" to-port="0" />
+		<edge from-layer="730" from-port="0" to-layer="731" to-port="1" />
+		<edge from-layer="731" from-port="2" to-layer="732" to-port="0" />
+		<edge from-layer="732" from-port="1" to-layer="734" to-port="0" />
+		<edge from-layer="733" from-port="0" to-layer="734" to-port="1" />
+		<edge from-layer="734" from-port="2" to-layer="739" to-port="0" />
+		<edge from-layer="735" from-port="0" to-layer="739" to-port="1" />
+		<edge from-layer="736" from-port="0" to-layer="739" to-port="2" />
+		<edge from-layer="737" from-port="0" to-layer="739" to-port="3" />
+		<edge from-layer="738" from-port="0" to-layer="739" to-port="4" />
+		<edge from-layer="739" from-port="5" to-layer="744" to-port="0" />
+		<edge from-layer="740" from-port="0" to-layer="741" to-port="0" />
+		<edge from-layer="741" from-port="1" to-layer="743" to-port="0" />
+		<edge from-layer="742" from-port="0" to-layer="743" to-port="1" />
+		<edge from-layer="743" from-port="2" to-layer="744" to-port="1" />
+		<edge from-layer="744" from-port="2" to-layer="746" to-port="0" />
+		<edge from-layer="745" from-port="0" to-layer="746" to-port="1" />
+		<edge from-layer="746" from-port="2" to-layer="747" to-port="0" />
+		<edge from-layer="747" from-port="2" to-layer="749" to-port="0" />
+		<edge from-layer="748" from-port="0" to-layer="749" to-port="1" />
+		<edge from-layer="749" from-port="2" to-layer="751" to-port="0" />
+		<edge from-layer="750" from-port="0" to-layer="751" to-port="1" />
+		<edge from-layer="751" from-port="2" to-layer="753" to-port="0" />
+		<edge from-layer="752" from-port="0" to-layer="753" to-port="1" />
+		<edge from-layer="753" from-port="2" to-layer="755" to-port="0" />
+		<edge from-layer="753" from-port="2" to-layer="828" to-port="1" />
+		<edge from-layer="754" from-port="0" to-layer="755" to-port="1" />
+		<edge from-layer="755" from-port="2" to-layer="760" to-port="0" />
+		<edge from-layer="756" from-port="0" to-layer="760" to-port="1" />
+		<edge from-layer="757" from-port="0" to-layer="760" to-port="2" />
+		<edge from-layer="758" from-port="0" to-layer="760" to-port="3" />
+		<edge from-layer="759" from-port="0" to-layer="760" to-port="4" />
+		<edge from-layer="760" from-port="5" to-layer="765" to-port="0" />
+		<edge from-layer="760" from-port="5" to-layer="781" to-port="0" />
+		<edge from-layer="760" from-port="5" to-layer="802" to-port="0" />
+		<edge from-layer="761" from-port="0" to-layer="762" to-port="0" />
+		<edge from-layer="762" from-port="1" to-layer="764" to-port="0" />
+		<edge from-layer="763" from-port="0" to-layer="764" to-port="1" />
+		<edge from-layer="764" from-port="2" to-layer="765" to-port="1" />
+		<edge from-layer="765" from-port="2" to-layer="767" to-port="0" />
+		<edge from-layer="766" from-port="0" to-layer="767" to-port="1" />
+		<edge from-layer="767" from-port="2" to-layer="772" to-port="0" />
+		<edge from-layer="768" from-port="0" to-layer="772" to-port="1" />
+		<edge from-layer="769" from-port="0" to-layer="772" to-port="2" />
+		<edge from-layer="770" from-port="0" to-layer="772" to-port="3" />
+		<edge from-layer="771" from-port="0" to-layer="772" to-port="4" />
+		<edge from-layer="772" from-port="5" to-layer="774" to-port="0" />
+		<edge from-layer="773" from-port="0" to-layer="774" to-port="1" />
+		<edge from-layer="774" from-port="2" to-layer="776" to-port="0" />
+		<edge from-layer="775" from-port="0" to-layer="776" to-port="1" />
+		<edge from-layer="776" from-port="2" to-layer="793" to-port="0" />
+		<edge from-layer="777" from-port="0" to-layer="778" to-port="0" />
+		<edge from-layer="778" from-port="1" to-layer="780" to-port="0" />
+		<edge from-layer="779" from-port="0" to-layer="780" to-port="1" />
+		<edge from-layer="780" from-port="2" to-layer="781" to-port="1" />
+		<edge from-layer="781" from-port="2" to-layer="783" to-port="0" />
+		<edge from-layer="782" from-port="0" to-layer="783" to-port="1" />
+		<edge from-layer="783" from-port="2" to-layer="788" to-port="0" />
+		<edge from-layer="784" from-port="0" to-layer="788" to-port="1" />
+		<edge from-layer="785" from-port="0" to-layer="788" to-port="2" />
+		<edge from-layer="786" from-port="0" to-layer="788" to-port="3" />
+		<edge from-layer="787" from-port="0" to-layer="788" to-port="4" />
+		<edge from-layer="788" from-port="5" to-layer="790" to-port="0" />
+		<edge from-layer="789" from-port="0" to-layer="790" to-port="1" />
+		<edge from-layer="790" from-port="2" to-layer="792" to-port="0" />
+		<edge from-layer="791" from-port="0" to-layer="792" to-port="1" />
+		<edge from-layer="792" from-port="2" to-layer="793" to-port="1" />
+		<edge from-layer="793" from-port="2" to-layer="795" to-port="0" />
+		<edge from-layer="794" from-port="0" to-layer="795" to-port="1" />
+		<edge from-layer="795" from-port="2" to-layer="796" to-port="0" />
+		<edge from-layer="796" from-port="2" to-layer="797" to-port="0" />
+		<edge from-layer="797" from-port="1" to-layer="809" to-port="0" />
+		<edge from-layer="798" from-port="0" to-layer="799" to-port="0" />
+		<edge from-layer="799" from-port="1" to-layer="801" to-port="0" />
+		<edge from-layer="800" from-port="0" to-layer="801" to-port="1" />
+		<edge from-layer="801" from-port="2" to-layer="802" to-port="1" />
+		<edge from-layer="802" from-port="2" to-layer="804" to-port="0" />
+		<edge from-layer="803" from-port="0" to-layer="804" to-port="1" />
+		<edge from-layer="804" from-port="2" to-layer="806" to-port="0" />
+		<edge from-layer="805" from-port="0" to-layer="806" to-port="1" />
+		<edge from-layer="806" from-port="2" to-layer="808" to-port="0" />
+		<edge from-layer="807" from-port="0" to-layer="808" to-port="1" />
+		<edge from-layer="808" from-port="2" to-layer="809" to-port="1" />
+		<edge from-layer="809" from-port="2" to-layer="811" to-port="0" />
+		<edge from-layer="810" from-port="0" to-layer="811" to-port="1" />
+		<edge from-layer="811" from-port="2" to-layer="813" to-port="0" />
+		<edge from-layer="812" from-port="0" to-layer="813" to-port="1" />
+		<edge from-layer="813" from-port="2" to-layer="815" to-port="0" />
+		<edge from-layer="814" from-port="0" to-layer="815" to-port="1" />
+		<edge from-layer="815" from-port="2" to-layer="820" to-port="0" />
+		<edge from-layer="816" from-port="0" to-layer="820" to-port="1" />
+		<edge from-layer="817" from-port="0" to-layer="820" to-port="2" />
+		<edge from-layer="818" from-port="0" to-layer="820" to-port="3" />
+		<edge from-layer="819" from-port="0" to-layer="820" to-port="4" />
+		<edge from-layer="820" from-port="5" to-layer="825" to-port="0" />
+		<edge from-layer="821" from-port="0" to-layer="822" to-port="0" />
+		<edge from-layer="822" from-port="1" to-layer="824" to-port="0" />
+		<edge from-layer="823" from-port="0" to-layer="824" to-port="1" />
+		<edge from-layer="824" from-port="2" to-layer="825" to-port="1" />
+		<edge from-layer="825" from-port="2" to-layer="827" to-port="0" />
+		<edge from-layer="826" from-port="0" to-layer="827" to-port="1" />
+		<edge from-layer="827" from-port="2" to-layer="828" to-port="0" />
+		<edge from-layer="828" from-port="2" to-layer="830" to-port="0" />
+		<edge from-layer="829" from-port="0" to-layer="830" to-port="1" />
+		<edge from-layer="830" from-port="2" to-layer="832" to-port="0" />
+		<edge from-layer="831" from-port="0" to-layer="832" to-port="1" />
+		<edge from-layer="832" from-port="2" to-layer="834" to-port="0" />
+		<edge from-layer="833" from-port="0" to-layer="834" to-port="1" />
+		<edge from-layer="834" from-port="2" to-layer="864" to-port="1" />
+		<edge from-layer="834" from-port="2" to-layer="836" to-port="0" />
+		<edge from-layer="835" from-port="0" to-layer="836" to-port="1" />
+		<edge from-layer="836" from-port="2" to-layer="841" to-port="0" />
+		<edge from-layer="837" from-port="0" to-layer="841" to-port="1" />
+		<edge from-layer="838" from-port="0" to-layer="841" to-port="2" />
+		<edge from-layer="839" from-port="0" to-layer="841" to-port="3" />
+		<edge from-layer="840" from-port="0" to-layer="841" to-port="4" />
+		<edge from-layer="841" from-port="5" to-layer="846" to-port="0" />
+		<edge from-layer="842" from-port="0" to-layer="843" to-port="0" />
+		<edge from-layer="843" from-port="1" to-layer="845" to-port="0" />
+		<edge from-layer="844" from-port="0" to-layer="845" to-port="1" />
+		<edge from-layer="845" from-port="2" to-layer="846" to-port="1" />
+		<edge from-layer="846" from-port="2" to-layer="848" to-port="0" />
+		<edge from-layer="847" from-port="0" to-layer="848" to-port="1" />
+		<edge from-layer="848" from-port="2" to-layer="849" to-port="0" />
+		<edge from-layer="849" from-port="1" to-layer="851" to-port="0" />
+		<edge from-layer="850" from-port="0" to-layer="851" to-port="1" />
+		<edge from-layer="851" from-port="2" to-layer="856" to-port="0" />
+		<edge from-layer="852" from-port="0" to-layer="856" to-port="1" />
+		<edge from-layer="853" from-port="0" to-layer="856" to-port="2" />
+		<edge from-layer="854" from-port="0" to-layer="856" to-port="3" />
+		<edge from-layer="855" from-port="0" to-layer="856" to-port="4" />
+		<edge from-layer="856" from-port="5" to-layer="861" to-port="0" />
+		<edge from-layer="857" from-port="0" to-layer="858" to-port="0" />
+		<edge from-layer="858" from-port="1" to-layer="860" to-port="0" />
+		<edge from-layer="859" from-port="0" to-layer="860" to-port="1" />
+		<edge from-layer="860" from-port="2" to-layer="861" to-port="1" />
+		<edge from-layer="861" from-port="2" to-layer="863" to-port="0" />
+		<edge from-layer="862" from-port="0" to-layer="863" to-port="1" />
+		<edge from-layer="863" from-port="2" to-layer="864" to-port="0" />
+		<edge from-layer="864" from-port="2" to-layer="866" to-port="0" />
+		<edge from-layer="865" from-port="0" to-layer="866" to-port="1" />
+		<edge from-layer="866" from-port="2" to-layer="868" to-port="0" />
+		<edge from-layer="867" from-port="0" to-layer="868" to-port="1" />
+		<edge from-layer="868" from-port="2" to-layer="870" to-port="0" />
+		<edge from-layer="869" from-port="0" to-layer="870" to-port="1" />
+		<edge from-layer="870" from-port="2" to-layer="872" to-port="0" />
+		<edge from-layer="870" from-port="2" to-layer="945" to-port="1" />
+		<edge from-layer="871" from-port="0" to-layer="872" to-port="1" />
+		<edge from-layer="872" from-port="2" to-layer="877" to-port="0" />
+		<edge from-layer="873" from-port="0" to-layer="877" to-port="1" />
+		<edge from-layer="874" from-port="0" to-layer="877" to-port="2" />
+		<edge from-layer="875" from-port="0" to-layer="877" to-port="3" />
+		<edge from-layer="876" from-port="0" to-layer="877" to-port="4" />
+		<edge from-layer="877" from-port="5" to-layer="898" to-port="0" />
+		<edge from-layer="877" from-port="5" to-layer="919" to-port="0" />
+		<edge from-layer="877" from-port="5" to-layer="882" to-port="0" />
+		<edge from-layer="878" from-port="0" to-layer="879" to-port="0" />
+		<edge from-layer="879" from-port="1" to-layer="881" to-port="0" />
+		<edge from-layer="880" from-port="0" to-layer="881" to-port="1" />
+		<edge from-layer="881" from-port="2" to-layer="882" to-port="1" />
+		<edge from-layer="882" from-port="2" to-layer="884" to-port="0" />
+		<edge from-layer="883" from-port="0" to-layer="884" to-port="1" />
+		<edge from-layer="884" from-port="2" to-layer="889" to-port="0" />
+		<edge from-layer="885" from-port="0" to-layer="889" to-port="1" />
+		<edge from-layer="886" from-port="0" to-layer="889" to-port="2" />
+		<edge from-layer="887" from-port="0" to-layer="889" to-port="3" />
+		<edge from-layer="888" from-port="0" to-layer="889" to-port="4" />
+		<edge from-layer="889" from-port="5" to-layer="891" to-port="0" />
+		<edge from-layer="890" from-port="0" to-layer="891" to-port="1" />
+		<edge from-layer="891" from-port="2" to-layer="893" to-port="0" />
+		<edge from-layer="892" from-port="0" to-layer="893" to-port="1" />
+		<edge from-layer="893" from-port="2" to-layer="910" to-port="0" />
+		<edge from-layer="894" from-port="0" to-layer="895" to-port="0" />
+		<edge from-layer="895" from-port="1" to-layer="897" to-port="0" />
+		<edge from-layer="896" from-port="0" to-layer="897" to-port="1" />
+		<edge from-layer="897" from-port="2" to-layer="898" to-port="1" />
+		<edge from-layer="898" from-port="2" to-layer="900" to-port="0" />
+		<edge from-layer="899" from-port="0" to-layer="900" to-port="1" />
+		<edge from-layer="900" from-port="2" to-layer="905" to-port="0" />
+		<edge from-layer="901" from-port="0" to-layer="905" to-port="1" />
+		<edge from-layer="902" from-port="0" to-layer="905" to-port="2" />
+		<edge from-layer="903" from-port="0" to-layer="905" to-port="3" />
+		<edge from-layer="904" from-port="0" to-layer="905" to-port="4" />
+		<edge from-layer="905" from-port="5" to-layer="907" to-port="0" />
+		<edge from-layer="906" from-port="0" to-layer="907" to-port="1" />
+		<edge from-layer="907" from-port="2" to-layer="909" to-port="0" />
+		<edge from-layer="908" from-port="0" to-layer="909" to-port="1" />
+		<edge from-layer="909" from-port="2" to-layer="910" to-port="1" />
+		<edge from-layer="910" from-port="2" to-layer="912" to-port="0" />
+		<edge from-layer="911" from-port="0" to-layer="912" to-port="1" />
+		<edge from-layer="912" from-port="2" to-layer="913" to-port="0" />
+		<edge from-layer="913" from-port="2" to-layer="914" to-port="0" />
+		<edge from-layer="914" from-port="1" to-layer="926" to-port="0" />
+		<edge from-layer="915" from-port="0" to-layer="916" to-port="0" />
+		<edge from-layer="916" from-port="1" to-layer="918" to-port="0" />
+		<edge from-layer="917" from-port="0" to-layer="918" to-port="1" />
+		<edge from-layer="918" from-port="2" to-layer="919" to-port="1" />
+		<edge from-layer="919" from-port="2" to-layer="921" to-port="0" />
+		<edge from-layer="920" from-port="0" to-layer="921" to-port="1" />
+		<edge from-layer="921" from-port="2" to-layer="923" to-port="0" />
+		<edge from-layer="922" from-port="0" to-layer="923" to-port="1" />
+		<edge from-layer="923" from-port="2" to-layer="925" to-port="0" />
+		<edge from-layer="924" from-port="0" to-layer="925" to-port="1" />
+		<edge from-layer="925" from-port="2" to-layer="926" to-port="1" />
+		<edge from-layer="926" from-port="2" to-layer="928" to-port="0" />
+		<edge from-layer="927" from-port="0" to-layer="928" to-port="1" />
+		<edge from-layer="928" from-port="2" to-layer="930" to-port="0" />
+		<edge from-layer="929" from-port="0" to-layer="930" to-port="1" />
+		<edge from-layer="930" from-port="2" to-layer="932" to-port="0" />
+		<edge from-layer="931" from-port="0" to-layer="932" to-port="1" />
+		<edge from-layer="932" from-port="2" to-layer="937" to-port="0" />
+		<edge from-layer="933" from-port="0" to-layer="937" to-port="1" />
+		<edge from-layer="934" from-port="0" to-layer="937" to-port="2" />
+		<edge from-layer="935" from-port="0" to-layer="937" to-port="3" />
+		<edge from-layer="936" from-port="0" to-layer="937" to-port="4" />
+		<edge from-layer="937" from-port="5" to-layer="942" to-port="0" />
+		<edge from-layer="938" from-port="0" to-layer="939" to-port="0" />
+		<edge from-layer="939" from-port="1" to-layer="941" to-port="0" />
+		<edge from-layer="940" from-port="0" to-layer="941" to-port="1" />
+		<edge from-layer="941" from-port="2" to-layer="942" to-port="1" />
+		<edge from-layer="942" from-port="2" to-layer="944" to-port="0" />
+		<edge from-layer="943" from-port="0" to-layer="944" to-port="1" />
+		<edge from-layer="944" from-port="2" to-layer="945" to-port="0" />
+		<edge from-layer="945" from-port="2" to-layer="947" to-port="0" />
+		<edge from-layer="946" from-port="0" to-layer="947" to-port="1" />
+		<edge from-layer="947" from-port="2" to-layer="949" to-port="0" />
+		<edge from-layer="948" from-port="0" to-layer="949" to-port="1" />
+		<edge from-layer="949" from-port="2" to-layer="951" to-port="0" />
+		<edge from-layer="950" from-port="0" to-layer="951" to-port="1" />
+		<edge from-layer="951" from-port="2" to-layer="953" to-port="0" />
+		<edge from-layer="951" from-port="2" to-layer="981" to-port="1" />
+		<edge from-layer="952" from-port="0" to-layer="953" to-port="1" />
+		<edge from-layer="953" from-port="2" to-layer="958" to-port="0" />
+		<edge from-layer="954" from-port="0" to-layer="958" to-port="1" />
+		<edge from-layer="955" from-port="0" to-layer="958" to-port="2" />
+		<edge from-layer="956" from-port="0" to-layer="958" to-port="3" />
+		<edge from-layer="957" from-port="0" to-layer="958" to-port="4" />
+		<edge from-layer="958" from-port="5" to-layer="963" to-port="0" />
+		<edge from-layer="959" from-port="0" to-layer="960" to-port="0" />
+		<edge from-layer="960" from-port="1" to-layer="962" to-port="0" />
+		<edge from-layer="961" from-port="0" to-layer="962" to-port="1" />
+		<edge from-layer="962" from-port="2" to-layer="963" to-port="1" />
+		<edge from-layer="963" from-port="2" to-layer="965" to-port="0" />
+		<edge from-layer="964" from-port="0" to-layer="965" to-port="1" />
+		<edge from-layer="965" from-port="2" to-layer="966" to-port="0" />
+		<edge from-layer="966" from-port="1" to-layer="968" to-port="0" />
+		<edge from-layer="967" from-port="0" to-layer="968" to-port="1" />
+		<edge from-layer="968" from-port="2" to-layer="973" to-port="0" />
+		<edge from-layer="969" from-port="0" to-layer="973" to-port="1" />
+		<edge from-layer="970" from-port="0" to-layer="973" to-port="2" />
+		<edge from-layer="971" from-port="0" to-layer="973" to-port="3" />
+		<edge from-layer="972" from-port="0" to-layer="973" to-port="4" />
+		<edge from-layer="973" from-port="5" to-layer="978" to-port="0" />
+		<edge from-layer="974" from-port="0" to-layer="975" to-port="0" />
+		<edge from-layer="975" from-port="1" to-layer="977" to-port="0" />
+		<edge from-layer="976" from-port="0" to-layer="977" to-port="1" />
+		<edge from-layer="977" from-port="2" to-layer="978" to-port="1" />
+		<edge from-layer="978" from-port="2" to-layer="980" to-port="0" />
+		<edge from-layer="979" from-port="0" to-layer="980" to-port="1" />
+		<edge from-layer="980" from-port="2" to-layer="981" to-port="0" />
+		<edge from-layer="981" from-port="2" to-layer="983" to-port="0" />
+		<edge from-layer="982" from-port="0" to-layer="983" to-port="1" />
+		<edge from-layer="983" from-port="2" to-layer="985" to-port="0" />
+		<edge from-layer="984" from-port="0" to-layer="985" to-port="1" />
+		<edge from-layer="985" from-port="2" to-layer="987" to-port="0" />
+		<edge from-layer="986" from-port="0" to-layer="987" to-port="1" />
+		<edge from-layer="987" from-port="2" to-layer="989" to-port="0" />
+		<edge from-layer="987" from-port="2" to-layer="1062" to-port="1" />
+		<edge from-layer="988" from-port="0" to-layer="989" to-port="1" />
+		<edge from-layer="989" from-port="2" to-layer="994" to-port="0" />
+		<edge from-layer="990" from-port="0" to-layer="994" to-port="1" />
+		<edge from-layer="991" from-port="0" to-layer="994" to-port="2" />
+		<edge from-layer="992" from-port="0" to-layer="994" to-port="3" />
+		<edge from-layer="993" from-port="0" to-layer="994" to-port="4" />
+		<edge from-layer="994" from-port="5" to-layer="1015" to-port="0" />
+		<edge from-layer="994" from-port="5" to-layer="1036" to-port="0" />
+		<edge from-layer="994" from-port="5" to-layer="999" to-port="0" />
+		<edge from-layer="995" from-port="0" to-layer="996" to-port="0" />
+		<edge from-layer="996" from-port="1" to-layer="998" to-port="0" />
+		<edge from-layer="997" from-port="0" to-layer="998" to-port="1" />
+		<edge from-layer="998" from-port="2" to-layer="999" to-port="1" />
+		<edge from-layer="999" from-port="2" to-layer="1001" to-port="0" />
+		<edge from-layer="1000" from-port="0" to-layer="1001" to-port="1" />
+		<edge from-layer="1001" from-port="2" to-layer="1006" to-port="0" />
+		<edge from-layer="1002" from-port="0" to-layer="1006" to-port="1" />
+		<edge from-layer="1003" from-port="0" to-layer="1006" to-port="2" />
+		<edge from-layer="1004" from-port="0" to-layer="1006" to-port="3" />
+		<edge from-layer="1005" from-port="0" to-layer="1006" to-port="4" />
+		<edge from-layer="1006" from-port="5" to-layer="1008" to-port="0" />
+		<edge from-layer="1007" from-port="0" to-layer="1008" to-port="1" />
+		<edge from-layer="1008" from-port="2" to-layer="1010" to-port="0" />
+		<edge from-layer="1009" from-port="0" to-layer="1010" to-port="1" />
+		<edge from-layer="1010" from-port="2" to-layer="1027" to-port="0" />
+		<edge from-layer="1011" from-port="0" to-layer="1012" to-port="0" />
+		<edge from-layer="1012" from-port="1" to-layer="1014" to-port="0" />
+		<edge from-layer="1013" from-port="0" to-layer="1014" to-port="1" />
+		<edge from-layer="1014" from-port="2" to-layer="1015" to-port="1" />
+		<edge from-layer="1015" from-port="2" to-layer="1017" to-port="0" />
+		<edge from-layer="1016" from-port="0" to-layer="1017" to-port="1" />
+		<edge from-layer="1017" from-port="2" to-layer="1022" to-port="0" />
+		<edge from-layer="1018" from-port="0" to-layer="1022" to-port="1" />
+		<edge from-layer="1019" from-port="0" to-layer="1022" to-port="2" />
+		<edge from-layer="1020" from-port="0" to-layer="1022" to-port="3" />
+		<edge from-layer="1021" from-port="0" to-layer="1022" to-port="4" />
+		<edge from-layer="1022" from-port="5" to-layer="1024" to-port="0" />
+		<edge from-layer="1023" from-port="0" to-layer="1024" to-port="1" />
+		<edge from-layer="1024" from-port="2" to-layer="1026" to-port="0" />
+		<edge from-layer="1025" from-port="0" to-layer="1026" to-port="1" />
+		<edge from-layer="1026" from-port="2" to-layer="1027" to-port="1" />
+		<edge from-layer="1027" from-port="2" to-layer="1029" to-port="0" />
+		<edge from-layer="1028" from-port="0" to-layer="1029" to-port="1" />
+		<edge from-layer="1029" from-port="2" to-layer="1030" to-port="0" />
+		<edge from-layer="1030" from-port="2" to-layer="1031" to-port="0" />
+		<edge from-layer="1031" from-port="1" to-layer="1043" to-port="0" />
+		<edge from-layer="1032" from-port="0" to-layer="1033" to-port="0" />
+		<edge from-layer="1033" from-port="1" to-layer="1035" to-port="0" />
+		<edge from-layer="1034" from-port="0" to-layer="1035" to-port="1" />
+		<edge from-layer="1035" from-port="2" to-layer="1036" to-port="1" />
+		<edge from-layer="1036" from-port="2" to-layer="1038" to-port="0" />
+		<edge from-layer="1037" from-port="0" to-layer="1038" to-port="1" />
+		<edge from-layer="1038" from-port="2" to-layer="1040" to-port="0" />
+		<edge from-layer="1039" from-port="0" to-layer="1040" to-port="1" />
+		<edge from-layer="1040" from-port="2" to-layer="1042" to-port="0" />
+		<edge from-layer="1041" from-port="0" to-layer="1042" to-port="1" />
+		<edge from-layer="1042" from-port="2" to-layer="1043" to-port="1" />
+		<edge from-layer="1043" from-port="2" to-layer="1045" to-port="0" />
+		<edge from-layer="1044" from-port="0" to-layer="1045" to-port="1" />
+		<edge from-layer="1045" from-port="2" to-layer="1047" to-port="0" />
+		<edge from-layer="1046" from-port="0" to-layer="1047" to-port="1" />
+		<edge from-layer="1047" from-port="2" to-layer="1049" to-port="0" />
+		<edge from-layer="1048" from-port="0" to-layer="1049" to-port="1" />
+		<edge from-layer="1049" from-port="2" to-layer="1054" to-port="0" />
+		<edge from-layer="1050" from-port="0" to-layer="1054" to-port="1" />
+		<edge from-layer="1051" from-port="0" to-layer="1054" to-port="2" />
+		<edge from-layer="1052" from-port="0" to-layer="1054" to-port="3" />
+		<edge from-layer="1053" from-port="0" to-layer="1054" to-port="4" />
+		<edge from-layer="1054" from-port="5" to-layer="1059" to-port="0" />
+		<edge from-layer="1055" from-port="0" to-layer="1056" to-port="0" />
+		<edge from-layer="1056" from-port="1" to-layer="1058" to-port="0" />
+		<edge from-layer="1057" from-port="0" to-layer="1058" to-port="1" />
+		<edge from-layer="1058" from-port="2" to-layer="1059" to-port="1" />
+		<edge from-layer="1059" from-port="2" to-layer="1061" to-port="0" />
+		<edge from-layer="1060" from-port="0" to-layer="1061" to-port="1" />
+		<edge from-layer="1061" from-port="2" to-layer="1062" to-port="0" />
+		<edge from-layer="1062" from-port="2" to-layer="1064" to-port="0" />
+		<edge from-layer="1063" from-port="0" to-layer="1064" to-port="1" />
+		<edge from-layer="1064" from-port="2" to-layer="1066" to-port="0" />
+		<edge from-layer="1065" from-port="0" to-layer="1066" to-port="1" />
+		<edge from-layer="1066" from-port="2" to-layer="1068" to-port="0" />
+		<edge from-layer="1067" from-port="0" to-layer="1068" to-port="1" />
+		<edge from-layer="1068" from-port="2" to-layer="1098" to-port="1" />
+		<edge from-layer="1068" from-port="2" to-layer="1070" to-port="0" />
+		<edge from-layer="1069" from-port="0" to-layer="1070" to-port="1" />
+		<edge from-layer="1070" from-port="2" to-layer="1075" to-port="0" />
+		<edge from-layer="1071" from-port="0" to-layer="1075" to-port="1" />
+		<edge from-layer="1072" from-port="0" to-layer="1075" to-port="2" />
+		<edge from-layer="1073" from-port="0" to-layer="1075" to-port="3" />
+		<edge from-layer="1074" from-port="0" to-layer="1075" to-port="4" />
+		<edge from-layer="1075" from-port="5" to-layer="1080" to-port="0" />
+		<edge from-layer="1076" from-port="0" to-layer="1077" to-port="0" />
+		<edge from-layer="1077" from-port="1" to-layer="1079" to-port="0" />
+		<edge from-layer="1078" from-port="0" to-layer="1079" to-port="1" />
+		<edge from-layer="1079" from-port="2" to-layer="1080" to-port="1" />
+		<edge from-layer="1080" from-port="2" to-layer="1082" to-port="0" />
+		<edge from-layer="1081" from-port="0" to-layer="1082" to-port="1" />
+		<edge from-layer="1082" from-port="2" to-layer="1083" to-port="0" />
+		<edge from-layer="1083" from-port="1" to-layer="1085" to-port="0" />
+		<edge from-layer="1084" from-port="0" to-layer="1085" to-port="1" />
+		<edge from-layer="1085" from-port="2" to-layer="1090" to-port="0" />
+		<edge from-layer="1086" from-port="0" to-layer="1090" to-port="1" />
+		<edge from-layer="1087" from-port="0" to-layer="1090" to-port="2" />
+		<edge from-layer="1088" from-port="0" to-layer="1090" to-port="3" />
+		<edge from-layer="1089" from-port="0" to-layer="1090" to-port="4" />
+		<edge from-layer="1090" from-port="5" to-layer="1095" to-port="0" />
+		<edge from-layer="1091" from-port="0" to-layer="1092" to-port="0" />
+		<edge from-layer="1092" from-port="1" to-layer="1094" to-port="0" />
+		<edge from-layer="1093" from-port="0" to-layer="1094" to-port="1" />
+		<edge from-layer="1094" from-port="2" to-layer="1095" to-port="1" />
+		<edge from-layer="1095" from-port="2" to-layer="1097" to-port="0" />
+		<edge from-layer="1096" from-port="0" to-layer="1097" to-port="1" />
+		<edge from-layer="1097" from-port="2" to-layer="1098" to-port="0" />
+		<edge from-layer="1098" from-port="2" to-layer="1100" to-port="0" />
+		<edge from-layer="1099" from-port="0" to-layer="1100" to-port="1" />
+		<edge from-layer="1100" from-port="2" to-layer="1102" to-port="0" />
+		<edge from-layer="1101" from-port="0" to-layer="1102" to-port="1" />
+		<edge from-layer="1102" from-port="2" to-layer="1104" to-port="0" />
+		<edge from-layer="1103" from-port="0" to-layer="1104" to-port="1" />
+		<edge from-layer="1104" from-port="2" to-layer="1106" to-port="0" />
+		<edge from-layer="1104" from-port="2" to-layer="1179" to-port="1" />
+		<edge from-layer="1105" from-port="0" to-layer="1106" to-port="1" />
+		<edge from-layer="1106" from-port="2" to-layer="1111" to-port="0" />
+		<edge from-layer="1107" from-port="0" to-layer="1111" to-port="1" />
+		<edge from-layer="1108" from-port="0" to-layer="1111" to-port="2" />
+		<edge from-layer="1109" from-port="0" to-layer="1111" to-port="3" />
+		<edge from-layer="1110" from-port="0" to-layer="1111" to-port="4" />
+		<edge from-layer="1111" from-port="5" to-layer="1116" to-port="0" />
+		<edge from-layer="1111" from-port="5" to-layer="1153" to-port="0" />
+		<edge from-layer="1111" from-port="5" to-layer="1132" to-port="0" />
+		<edge from-layer="1112" from-port="0" to-layer="1113" to-port="0" />
+		<edge from-layer="1113" from-port="1" to-layer="1115" to-port="0" />
+		<edge from-layer="1114" from-port="0" to-layer="1115" to-port="1" />
+		<edge from-layer="1115" from-port="2" to-layer="1116" to-port="1" />
+		<edge from-layer="1116" from-port="2" to-layer="1118" to-port="0" />
+		<edge from-layer="1117" from-port="0" to-layer="1118" to-port="1" />
+		<edge from-layer="1118" from-port="2" to-layer="1123" to-port="0" />
+		<edge from-layer="1119" from-port="0" to-layer="1123" to-port="1" />
+		<edge from-layer="1120" from-port="0" to-layer="1123" to-port="2" />
+		<edge from-layer="1121" from-port="0" to-layer="1123" to-port="3" />
+		<edge from-layer="1122" from-port="0" to-layer="1123" to-port="4" />
+		<edge from-layer="1123" from-port="5" to-layer="1125" to-port="0" />
+		<edge from-layer="1124" from-port="0" to-layer="1125" to-port="1" />
+		<edge from-layer="1125" from-port="2" to-layer="1127" to-port="0" />
+		<edge from-layer="1126" from-port="0" to-layer="1127" to-port="1" />
+		<edge from-layer="1127" from-port="2" to-layer="1144" to-port="0" />
+		<edge from-layer="1128" from-port="0" to-layer="1129" to-port="0" />
+		<edge from-layer="1129" from-port="1" to-layer="1131" to-port="0" />
+		<edge from-layer="1130" from-port="0" to-layer="1131" to-port="1" />
+		<edge from-layer="1131" from-port="2" to-layer="1132" to-port="1" />
+		<edge from-layer="1132" from-port="2" to-layer="1134" to-port="0" />
+		<edge from-layer="1133" from-port="0" to-layer="1134" to-port="1" />
+		<edge from-layer="1134" from-port="2" to-layer="1139" to-port="0" />
+		<edge from-layer="1135" from-port="0" to-layer="1139" to-port="1" />
+		<edge from-layer="1136" from-port="0" to-layer="1139" to-port="2" />
+		<edge from-layer="1137" from-port="0" to-layer="1139" to-port="3" />
+		<edge from-layer="1138" from-port="0" to-layer="1139" to-port="4" />
+		<edge from-layer="1139" from-port="5" to-layer="1141" to-port="0" />
+		<edge from-layer="1140" from-port="0" to-layer="1141" to-port="1" />
+		<edge from-layer="1141" from-port="2" to-layer="1143" to-port="0" />
+		<edge from-layer="1142" from-port="0" to-layer="1143" to-port="1" />
+		<edge from-layer="1143" from-port="2" to-layer="1144" to-port="1" />
+		<edge from-layer="1144" from-port="2" to-layer="1146" to-port="0" />
+		<edge from-layer="1145" from-port="0" to-layer="1146" to-port="1" />
+		<edge from-layer="1146" from-port="2" to-layer="1147" to-port="0" />
+		<edge from-layer="1147" from-port="2" to-layer="1148" to-port="0" />
+		<edge from-layer="1148" from-port="1" to-layer="1160" to-port="0" />
+		<edge from-layer="1149" from-port="0" to-layer="1150" to-port="0" />
+		<edge from-layer="1150" from-port="1" to-layer="1152" to-port="0" />
+		<edge from-layer="1151" from-port="0" to-layer="1152" to-port="1" />
+		<edge from-layer="1152" from-port="2" to-layer="1153" to-port="1" />
+		<edge from-layer="1153" from-port="2" to-layer="1155" to-port="0" />
+		<edge from-layer="1154" from-port="0" to-layer="1155" to-port="1" />
+		<edge from-layer="1155" from-port="2" to-layer="1157" to-port="0" />
+		<edge from-layer="1156" from-port="0" to-layer="1157" to-port="1" />
+		<edge from-layer="1157" from-port="2" to-layer="1159" to-port="0" />
+		<edge from-layer="1158" from-port="0" to-layer="1159" to-port="1" />
+		<edge from-layer="1159" from-port="2" to-layer="1160" to-port="1" />
+		<edge from-layer="1160" from-port="2" to-layer="1162" to-port="0" />
+		<edge from-layer="1161" from-port="0" to-layer="1162" to-port="1" />
+		<edge from-layer="1162" from-port="2" to-layer="1164" to-port="0" />
+		<edge from-layer="1163" from-port="0" to-layer="1164" to-port="1" />
+		<edge from-layer="1164" from-port="2" to-layer="1166" to-port="0" />
+		<edge from-layer="1165" from-port="0" to-layer="1166" to-port="1" />
+		<edge from-layer="1166" from-port="2" to-layer="1171" to-port="0" />
+		<edge from-layer="1167" from-port="0" to-layer="1171" to-port="1" />
+		<edge from-layer="1168" from-port="0" to-layer="1171" to-port="2" />
+		<edge from-layer="1169" from-port="0" to-layer="1171" to-port="3" />
+		<edge from-layer="1170" from-port="0" to-layer="1171" to-port="4" />
+		<edge from-layer="1171" from-port="5" to-layer="1176" to-port="0" />
+		<edge from-layer="1172" from-port="0" to-layer="1173" to-port="0" />
+		<edge from-layer="1173" from-port="1" to-layer="1175" to-port="0" />
+		<edge from-layer="1174" from-port="0" to-layer="1175" to-port="1" />
+		<edge from-layer="1175" from-port="2" to-layer="1176" to-port="1" />
+		<edge from-layer="1176" from-port="2" to-layer="1178" to-port="0" />
+		<edge from-layer="1177" from-port="0" to-layer="1178" to-port="1" />
+		<edge from-layer="1178" from-port="2" to-layer="1179" to-port="0" />
+		<edge from-layer="1179" from-port="2" to-layer="1181" to-port="0" />
+		<edge from-layer="1180" from-port="0" to-layer="1181" to-port="1" />
+		<edge from-layer="1181" from-port="2" to-layer="1183" to-port="0" />
+		<edge from-layer="1182" from-port="0" to-layer="1183" to-port="1" />
+		<edge from-layer="1183" from-port="2" to-layer="1185" to-port="0" />
+		<edge from-layer="1184" from-port="0" to-layer="1185" to-port="1" />
+		<edge from-layer="1185" from-port="2" to-layer="1187" to-port="0" />
+		<edge from-layer="1185" from-port="2" to-layer="1215" to-port="1" />
+		<edge from-layer="1186" from-port="0" to-layer="1187" to-port="1" />
+		<edge from-layer="1187" from-port="2" to-layer="1192" to-port="0" />
+		<edge from-layer="1188" from-port="0" to-layer="1192" to-port="1" />
+		<edge from-layer="1189" from-port="0" to-layer="1192" to-port="2" />
+		<edge from-layer="1190" from-port="0" to-layer="1192" to-port="3" />
+		<edge from-layer="1191" from-port="0" to-layer="1192" to-port="4" />
+		<edge from-layer="1192" from-port="5" to-layer="1197" to-port="0" />
+		<edge from-layer="1193" from-port="0" to-layer="1194" to-port="0" />
+		<edge from-layer="1194" from-port="1" to-layer="1196" to-port="0" />
+		<edge from-layer="1195" from-port="0" to-layer="1196" to-port="1" />
+		<edge from-layer="1196" from-port="2" to-layer="1197" to-port="1" />
+		<edge from-layer="1197" from-port="2" to-layer="1199" to-port="0" />
+		<edge from-layer="1198" from-port="0" to-layer="1199" to-port="1" />
+		<edge from-layer="1199" from-port="2" to-layer="1200" to-port="0" />
+		<edge from-layer="1200" from-port="1" to-layer="1202" to-port="0" />
+		<edge from-layer="1201" from-port="0" to-layer="1202" to-port="1" />
+		<edge from-layer="1202" from-port="2" to-layer="1207" to-port="0" />
+		<edge from-layer="1203" from-port="0" to-layer="1207" to-port="1" />
+		<edge from-layer="1204" from-port="0" to-layer="1207" to-port="2" />
+		<edge from-layer="1205" from-port="0" to-layer="1207" to-port="3" />
+		<edge from-layer="1206" from-port="0" to-layer="1207" to-port="4" />
+		<edge from-layer="1207" from-port="5" to-layer="1212" to-port="0" />
+		<edge from-layer="1208" from-port="0" to-layer="1209" to-port="0" />
+		<edge from-layer="1209" from-port="1" to-layer="1211" to-port="0" />
+		<edge from-layer="1210" from-port="0" to-layer="1211" to-port="1" />
+		<edge from-layer="1211" from-port="2" to-layer="1212" to-port="1" />
+		<edge from-layer="1212" from-port="2" to-layer="1214" to-port="0" />
+		<edge from-layer="1213" from-port="0" to-layer="1214" to-port="1" />
+		<edge from-layer="1214" from-port="2" to-layer="1215" to-port="0" />
+		<edge from-layer="1215" from-port="2" to-layer="1217" to-port="0" />
+		<edge from-layer="1216" from-port="0" to-layer="1217" to-port="1" />
+		<edge from-layer="1217" from-port="2" to-layer="1219" to-port="0" />
+		<edge from-layer="1218" from-port="0" to-layer="1219" to-port="1" />
+		<edge from-layer="1219" from-port="2" to-layer="1221" to-port="0" />
+		<edge from-layer="1220" from-port="0" to-layer="1221" to-port="1" />
+		<edge from-layer="1221" from-port="2" to-layer="1224" to-port="0" />
+		<edge from-layer="1222" from-port="0" to-layer="1224" to-port="1" />
+		<edge from-layer="1223" from-port="0" to-layer="1224" to-port="2" />
+		<edge from-layer="1224" from-port="3" to-layer="1225" to-port="0" />
+	</edges>
+	<rt_info>
+		<Runtime_version value="2024.5.0-16853-050966f82a1" />
+		<conversion_parameters>
+			<framework value="pytorch" />
+			<is_python_object value="True" />
+		</conversion_parameters>
+		<nncf>
+			<friendly_names_were_updated value="True" />
+			<quantization>
+				<advanced_parameters value="{'overflow_fix': None, 'quantize_outputs': False, 'inplace_statistics': True, 'disable_channel_alignment': True, 'disable_bias_correction': False, 'batchwise_statistics': None, 'activations_quantization_params': None, 'weights_quantization_params': None, 'activations_range_estimator_params': {'min': {'statistics_type': None, 'aggregator_type': None, 'clipping_value': None, 'quantile_outlier_prob': 0.0001}, 'max': {'statistics_type': None, 'aggregator_type': None, 'clipping_value': None, 'quantile_outlier_prob': 0.0001}}, 'weights_range_estimator_params': {'min': {'statistics_type': None, 'aggregator_type': None, 'clipping_value': None, 'quantile_outlier_prob': 0.0001}, 'max': {'statistics_type': None, 'aggregator_type': None, 'clipping_value': None, 'quantile_outlier_prob': 0.0001}}, 'bias_correction_params': {'apply_for_all_nodes': False, 'threshold': None}, 'smooth_quant_alphas': {'convolution': -1, 'matmul': 0.6}, 'smooth_quant_alpha': 0.6, 'backend_params': {}}" />
+				<fast_bias_correction value="True" />
+				<ignored_scope value="None" />
+				<model_type value="transformer" />
+				<preset value="None" />
+				<subset_size value="1" />
+				<target_device value="ANY" />
+			</quantization>
+		</nncf>
+	</rt_info>
+</net>