diff --git "a/vae_encoder.xml" "b/vae_encoder.xml"
new file mode 100644--- /dev/null
+++ "b/vae_encoder.xml"
@@ -0,0 +1,8732 @@
+<?xml version="1.0" ?>
+<net name="torch_jit" version="11">
+	<layers>
+		<layer id="0" name="init_image" type="Parameter" version="opset1">
+			<data shape="1,3,512,512" element_type="f32"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="init_image"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="FP32" names="init_image">
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>512</dim>
+					<dim>512</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1" name="Constant_13488" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 512" offset="0" size="2048"/>
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>512</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="2" name="Constant_13483" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 512" offset="2048" size="2048"/>
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>512</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="3" name="m.encoder.conv_in.weight" type="Const" version="opset1">
+			<data element_type="f32" shape="128, 3, 3, 3" offset="4096" size="13824"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="m.encoder.conv_in.weight"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="FP32" names="m.encoder.conv_in.weight">
+					<dim>128</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="4" name="Convolution_114" type="Convolution" version="opset1">
+			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="Convolution_114"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>512</dim>
+					<dim>512</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>128</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>512</dim>
+					<dim>512</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="5" name="Reshape_134" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 128, 1, 1" offset="17920" size="512"/>
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="6" name="onnx::Cast_249" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="Concat_133, Reshape_134, input, onnx::Cast_249"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>512</dim>
+					<dim>512</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="input,onnx::Cast_249">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>512</dim>
+					<dim>512</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="7" name="onnx::Reshape_251" type="Const" version="opset1">
+			<data element_type="i64" shape="3" offset="18432" size="24"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::Reshape_251"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="I64" names="onnx::Reshape_251">
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="8" name="onnx::InstanceNormalization_252" type="Reshape" version="opset1">
+			<data special_zero="true"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::InstanceNormalization_252"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>512</dim>
+					<dim>512</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="onnx::InstanceNormalization_252">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>1048576</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="9" name="Constant_172" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="18456" size="8"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="Constant_172"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="I64">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="10" name="MVN_173" type="MVN" version="opset6">
+			<data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="Concat_192, Concat_237, MVN_173, Multiply_220, Reshape_193, Reshape_238, onnx::Reshape_255"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>1048576</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="onnx::Reshape_255">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>1048576</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="11" name="onnx::Reshape_256" type="ShapeOf" version="opset3">
+			<data output_type="i64"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::Reshape_256"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>512</dim>
+					<dim>512</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="I64" names="onnx::Reshape_256">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="12" name="onnx::Mul_257" type="Reshape" version="opset1">
+			<data special_zero="true"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::Mul_257"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>1048576</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="onnx::Mul_257">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>512</dim>
+					<dim>512</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="13" name="Constant_13445" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 128, 1, 1" offset="18464" size="512"/>
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="14" name="onnx::Add_260" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::Add_260"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>512</dim>
+					<dim>512</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="onnx::Add_260">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>512</dim>
+					<dim>512</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="15" name="Constant_13446" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 128, 1, 1" offset="18976" size="512"/>
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="16" name="onnx::Cast_263" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="input.4, onnx::Cast_263"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>512</dim>
+					<dim>512</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="input.4,onnx::Cast_263">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>512</dim>
+					<dim>512</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="17" name="input.8" type="Swish" version="opset4">
+			<rt_info>
+				<attribute name="fused_names" version="0" value="input.8, onnx::Mul_265"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>512</dim>
+					<dim>512</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="input.8">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>512</dim>
+					<dim>512</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="18" name="m.encoder.down_blocks.0.resnets.0.conv1.weight" type="Const" version="opset1">
+			<data element_type="f32" shape="128, 128, 3, 3" offset="19488" size="589824"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="m.encoder.down_blocks.0.resnets.0.conv1.weight"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="FP32" names="m.encoder.down_blocks.0.resnets.0.conv1.weight">
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="19" name="Convolution_278" type="Convolution" version="opset1">
+			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="Convolution_278"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>512</dim>
+					<dim>512</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>512</dim>
+					<dim>512</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="20" name="Reshape_298" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 128, 1, 1" offset="609312" size="512"/>
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="21" name="onnx::Cast_267" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="Concat_297, Reshape_298, input.12, onnx::Cast_267"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>512</dim>
+					<dim>512</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="input.12,onnx::Cast_267">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>512</dim>
+					<dim>512</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="22" name="onnx::Reshape_269" type="Const" version="opset1">
+			<data element_type="i64" shape="3" offset="18432" size="24"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::Reshape_269"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="I64" names="onnx::Reshape_269">
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="23" name="onnx::InstanceNormalization_270" type="Reshape" version="opset1">
+			<data special_zero="true"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::InstanceNormalization_270"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>512</dim>
+					<dim>512</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="onnx::InstanceNormalization_270">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>1048576</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="24" name="Constant_336" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="18456" size="8"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="Constant_336"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="I64">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="25" name="MVN_337" type="MVN" version="opset6">
+			<data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="Concat_356, Concat_401, MVN_337, Multiply_384, Reshape_357, Reshape_402, onnx::Reshape_273"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>1048576</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="onnx::Reshape_273">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>1048576</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="26" name="onnx::Reshape_274" type="ShapeOf" version="opset3">
+			<data output_type="i64"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::Reshape_274"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>512</dim>
+					<dim>512</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="I64" names="onnx::Reshape_274">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="27" name="onnx::Mul_275" type="Reshape" version="opset1">
+			<data special_zero="true"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::Mul_275"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>1048576</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="onnx::Mul_275">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>512</dim>
+					<dim>512</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="28" name="Constant_13447" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 128, 1, 1" offset="609824" size="512"/>
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="29" name="onnx::Add_278" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::Add_278"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>512</dim>
+					<dim>512</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="onnx::Add_278">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>512</dim>
+					<dim>512</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="30" name="Constant_13448" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 128, 1, 1" offset="610336" size="512"/>
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="31" name="onnx::Cast_281" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="input.16, onnx::Cast_281"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>512</dim>
+					<dim>512</dim>
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+			</output>
+		</layer>
+		<layer id="32" name="input.20" type="Swish" version="opset4">
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+					<dim>1</dim>
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+					<dim>512</dim>
+					<dim>512</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="33" name="m.encoder.down_blocks.0.resnets.0.conv2.weight" type="Const" version="opset1">
+			<data element_type="f32" shape="128, 128, 3, 3" offset="610848" size="589824"/>
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+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="34" name="Convolution_442" type="Convolution" version="opset1">
+			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="Convolution_442"/>
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+				<port id="1" precision="FP32">
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+					<dim>512</dim>
+					<dim>512</dim>
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+					<dim>1</dim>
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+			</output>
+		</layer>
+		<layer id="36" name="onnx::Add_285" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="Concat_461, Reshape_462, onnx::Add_285"/>
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+					<dim>512</dim>
+					<dim>512</dim>
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+			</output>
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+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="input.24, onnx::Cast_288, onnx::Div_286"/>
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+					<dim>512</dim>
+					<dim>512</dim>
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+			<data element_type="i64" shape="3" offset="18432" size="24"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::Reshape_290"/>
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+			<output>
+				<port id="0" precision="I64" names="onnx::Reshape_290">
+					<dim>3</dim>
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+			</output>
+		</layer>
+		<layer id="39" name="onnx::InstanceNormalization_291" type="Reshape" version="opset1">
+			<data special_zero="true"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::InstanceNormalization_291"/>
+			</rt_info>
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+				<port id="0" precision="FP32">
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+					<dim>512</dim>
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+				<port id="1" precision="I64">
+					<dim>3</dim>
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+			</input>
+			<output>
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+			</output>
+		</layer>
+		<layer id="40" name="Constant_503" type="Const" version="opset1">
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+			<rt_info>
+				<attribute name="fused_names" version="0" value="Constant_503"/>
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+					<dim>1</dim>
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+			</output>
+		</layer>
+		<layer id="41" name="MVN_504" type="MVN" version="opset6">
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+			<rt_info>
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+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::Reshape_295"/>
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+					<dim>4</dim>
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+			</output>
+		</layer>
+		<layer id="43" name="onnx::Mul_296" type="Reshape" version="opset1">
+			<data special_zero="true"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::Mul_296"/>
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+				<port id="1" precision="I64">
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+			<output>
+				<port id="2" precision="FP32" names="onnx::Mul_296">
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+					<dim>512</dim>
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+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::Add_299"/>
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+					<dim>512</dim>
+					<dim>512</dim>
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+					<dim>3</dim>
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+			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
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+			<data auto_broadcast="numpy"/>
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+		</layer>
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+			<data auto_broadcast="numpy"/>
+			<rt_info>
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+			</output>
+		</layer>
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+			<data special_zero="true"/>
+			<rt_info>
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+		</layer>
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+			</output>
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+			<data auto_broadcast="numpy"/>
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+				<attribute name="fused_names" version="0" value="onnx::Add_381"/>
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+			<data auto_broadcast="numpy"/>
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+			</output>
+		</layer>
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+			</output>
+		</layer>
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+		<layer id="181" name="MVN_2219" type="MVN" version="opset6">
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+			<data auto_broadcast="numpy"/>
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+				<attribute name="fused_names" version="0" value="onnx::Add_507"/>
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+			<data auto_broadcast="numpy"/>
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+			</output>
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+		</layer>
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+			<data auto_broadcast="numpy"/>
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+		<layer id="216" name="MVN_2696" type="MVN" version="opset6">
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+					<dim>1</dim>
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+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="239" name="m.encoder.down_blocks.3.resnets.0.conv2.weight" type="Const" version="opset1">
+			<data element_type="f32" shape="512, 512, 3, 3" offset="66201120" size="9437184"/>
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+					<dim>512</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="240" name="Convolution_2965" type="Convolution" version="opset1">
+			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="Convolution_2965"/>
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+					<dim>64</dim>
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+			</output>
+		</layer>
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+					<dim>1</dim>
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+		</layer>
+		<layer id="242" name="onnx::Add_596" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="Concat_2984, Reshape_2985, onnx::Add_596"/>
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+					<dim>64</dim>
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+		</layer>
+		<layer id="243" name="onnx::Div_597" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="input.180, onnx::Cast_599, onnx::Div_597"/>
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+		</layer>
+		<layer id="244" name="onnx::Reshape_601" type="Const" version="opset1">
+			<data element_type="i64" shape="3" offset="18432" size="24"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::Reshape_601"/>
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+				<port id="0" precision="I64" names="onnx::Reshape_601">
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="245" name="onnx::InstanceNormalization_602" type="Reshape" version="opset1">
+			<data special_zero="true"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::InstanceNormalization_602"/>
+			</rt_info>
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+				<port id="1" precision="I64">
+					<dim>3</dim>
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+			<output>
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+					<dim>1</dim>
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+			</output>
+		</layer>
+		<layer id="246" name="Constant_3026" type="Const" version="opset1">
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+			<rt_info>
+				<attribute name="fused_names" version="0" value="Constant_3026"/>
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+			<output>
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+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="247" name="MVN_3027" type="MVN" version="opset6">
+			<data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT"/>
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+		</layer>
+		<layer id="248" name="onnx::Reshape_606" type="ShapeOf" version="opset3">
+			<data output_type="i64"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::Reshape_606"/>
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+			</output>
+		</layer>
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+			<data special_zero="true"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::Mul_607"/>
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+			<data auto_broadcast="numpy"/>
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+				<attribute name="fused_names" version="0" value="onnx::Add_610"/>
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+				<port id="1" precision="FP32">
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+					<dim>1</dim>
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+			</input>
+			<output>
+				<port id="2" precision="FP32" names="onnx::Add_667">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="298" name="Constant_13480" type="Const" version="opset1">
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+					<dim>1</dim>
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+			</output>
+		</layer>
+		<layer id="299" name="onnx::Cast_670" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
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+				<attribute name="fused_names" version="0" value="input.220, onnx::Cast_670"/>
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+					<dim>1</dim>
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+			</input>
+			<output>
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+					<dim>64</dim>
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+			</output>
+		</layer>
+		<layer id="300" name="input.224" type="Swish" version="opset4">
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+					<dim>64</dim>
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+			</output>
+		</layer>
+		<layer id="301" name="m.encoder.mid_block.resnets.0.conv2.weight" type="Const" version="opset1">
+			<data element_type="f32" shape="512, 512, 3, 3" offset="103974432" size="9437184"/>
+			<rt_info>
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+					<dim>512</dim>
+					<dim>3</dim>
+					<dim>3</dim>
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+			</output>
+		</layer>
+		<layer id="302" name="Convolution_3627" type="Convolution" version="opset1">
+			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
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+				<attribute name="fused_names" version="0" value="Convolution_3627"/>
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+				<port id="1" precision="FP32">
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+					<dim>3</dim>
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+					<dim>64</dim>
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+		<layer id="303" name="Reshape_3647" type="Const" version="opset1">
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+					<dim>1</dim>
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+		</layer>
+		<layer id="304" name="onnx::Add_674" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="Concat_3646, Reshape_3647, onnx::Add_674"/>
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+					<dim>1</dim>
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+					<dim>64</dim>
+					<dim>64</dim>
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+		</layer>
+		<layer id="305" name="onnx::Div_675" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="input.228, onnx::Div_675"/>
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+				<attribute name="fused_names" version="0" value="onnx::Reshape_690"/>
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+			<output>
+				<port id="0" precision="I64" names="onnx::Reshape_690">
+					<dim>3</dim>
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+			</output>
+		</layer>
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+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::InstanceNormalization_691"/>
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+					<dim>64</dim>
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+				<port id="1" precision="I64">
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+			<output>
+				<port id="2" precision="FP32" names="onnx::InstanceNormalization_691">
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+		<layer id="309" name="MVN_3704" type="MVN" version="opset6">
+			<data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT"/>
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+			<data output_type="i64"/>
+			<rt_info>
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+			<data auto_broadcast="numpy"/>
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+				<attribute name="fused_names" version="0" value="onnx::Add_699"/>
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+			<rt_info>
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+			<rt_info>
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+		</layer>
+		<layer id="331" name="onnx::MatMul_712" type="Transpose" version="opset1">
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::MatMul_712"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>4096</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="onnx::MatMul_712">
+					<dim>1</dim>
+					<dim>4096</dim>
+					<dim>512</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="332" name="Constant_13329" type="Const" version="opset1">
+			<data element_type="f32" shape="512, 512" offset="113417816" size="1048576"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::Add_714, onnx::MatMul_930"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="FP32">
+					<dim>512</dim>
+					<dim>512</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="333" name="onnx::Add_714" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::Add_714, onnx::MatMul_930"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>4096</dim>
+					<dim>512</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>512</dim>
+					<dim>512</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="onnx::Add_714">
+					<dim>1</dim>
+					<dim>4096</dim>
+					<dim>512</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="334" name="query_proj" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="query_proj"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>512</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>4096</dim>
+					<dim>512</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="query_proj">
+					<dim>1</dim>
+					<dim>4096</dim>
+					<dim>512</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="335" name="onnx::Reshape_738" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="114466392" size="32"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::Concat_935, onnx::Concat_936, onnx::Reshape_738"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="I64">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="336" name="onnx::Transpose_739" type="Reshape" version="opset1">
+			<data special_zero="true"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::Transpose_739"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>4096</dim>
+					<dim>512</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="onnx::Transpose_739">
+					<dim>1</dim>
+					<dim>4096</dim>
+					<dim>1</dim>
+					<dim>512</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="337" name="Constant_13331" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="114466424" size="32"/>
+			<output>
+				<port id="0" precision="I64">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="338" name="onnx::Mul_740" type="Reshape" version="opset1">
+			<data special_zero="true"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::Mul_740"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>4096</dim>
+					<dim>1</dim>
+					<dim>512</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="onnx::Mul_740">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>4096</dim>
+					<dim>512</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="339" name="Constant_13484" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 1, 1" offset="114466456" 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="340" name="onnx::MatMul_779" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::MatMul_779"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>4096</dim>
+					<dim>512</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="onnx::MatMul_779">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>4096</dim>
+					<dim>512</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="341" name="Constant_13485" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 512" offset="114466460" size="2048"/>
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>512</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="342" name="Constant_13343" type="Const" version="opset1">
+			<data element_type="f32" shape="512, 512" offset="114468508" size="1048576"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::Add_717, onnx::MatMul_931"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="FP32">
+					<dim>512</dim>
+					<dim>512</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="343" name="onnx::Add_717" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::Add_717, onnx::MatMul_931"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>4096</dim>
+					<dim>512</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>512</dim>
+					<dim>512</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="onnx::Add_717">
+					<dim>1</dim>
+					<dim>4096</dim>
+					<dim>512</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="344" name="key_proj" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="key_proj"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>512</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>4096</dim>
+					<dim>512</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="key_proj">
+					<dim>1</dim>
+					<dim>4096</dim>
+					<dim>512</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="345" name="onnx::Reshape_757" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="114466392" size="32"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::Concat_935, onnx::Concat_936, onnx::Reshape_757"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="I64">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="346" name="onnx::Transpose_758" type="Reshape" version="opset1">
+			<data special_zero="true"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::Transpose_758"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>4096</dim>
+					<dim>512</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="onnx::Transpose_758">
+					<dim>1</dim>
+					<dim>4096</dim>
+					<dim>1</dim>
+					<dim>512</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="347" name="Constant_4086" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="115517084" size="32"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="Constant_4086"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="I64">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="348" name="onnx::Mul_780" type="Transpose" version="opset1">
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::Mul_780"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>4096</dim>
+					<dim>1</dim>
+					<dim>512</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="onnx::Mul_780">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>4096</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="349" name="Constant_13486" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 1, 1" offset="114466456" 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="350" name="onnx::MatMul_782" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::MatMul_782"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>4096</dim>
+				</port>
+				<port id="1" precision="FP32">
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+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="onnx::MatMul_782">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>4096</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="351" name="onnx::Cast_783" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="false"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::Cast_783, onnx::Softmax_784"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>4096</dim>
+					<dim>512</dim>
+				</port>
+				<port id="1" precision="FP32">
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+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>4096</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="onnx::Cast_783,onnx::Softmax_784">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>4096</dim>
+					<dim>4096</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="352" name="onnx::Cast_785" type="SoftMax" version="opset8">
+			<data axis="-1"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::Cast_785, onnx::MatMul_786"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>4096</dim>
+					<dim>4096</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="onnx::Cast_785,onnx::MatMul_786">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>4096</dim>
+					<dim>4096</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="353" name="Constant_13487" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 1, 512" offset="115517116" size="2048"/>
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>512</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="354" name="Constant_13350" type="Const" version="opset1">
+			<data element_type="f32" shape="512, 512" offset="115519164" size="1048576"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::Add_720, onnx::MatMul_932"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="FP32">
+					<dim>512</dim>
+					<dim>512</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="355" name="onnx::Add_720" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::Add_720, onnx::MatMul_932"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>4096</dim>
+					<dim>512</dim>
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+				<port id="1" precision="FP32">
+					<dim>512</dim>
+					<dim>512</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="onnx::Add_720">
+					<dim>1</dim>
+					<dim>4096</dim>
+					<dim>512</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="356" name="value_proj" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="value_proj"/>
+			</rt_info>
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+					<dim>512</dim>
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+					<dim>4096</dim>
+					<dim>512</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="value_proj">
+					<dim>1</dim>
+					<dim>4096</dim>
+					<dim>512</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="357" name="onnx::Reshape_775" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="114466392" size="32"/>
+			<rt_info>
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+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="358" name="onnx::Transpose_776" type="Reshape" version="opset1">
+			<data special_zero="true"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::Transpose_776"/>
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+					<dim>512</dim>
+				</port>
+				<port id="1" precision="I64">
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+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="onnx::Transpose_776">
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+					<dim>512</dim>
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+			</output>
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+		<layer id="359" name="Constant_13352" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="114466424" size="32"/>
+			<output>
+				<port id="0" precision="I64">
+					<dim>4</dim>
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+			</output>
+		</layer>
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+			<data special_zero="true"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::MatMul_777"/>
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+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="onnx::MatMul_777">
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+					<dim>1</dim>
+					<dim>4096</dim>
+					<dim>512</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="361" name="onnx::Transpose_787" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="false"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::Transpose_787"/>
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+					<dim>4096</dim>
+					<dim>512</dim>
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+			<output>
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+					<dim>1</dim>
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+					<dim>512</dim>
+				</port>
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+			<output>
+				<port id="0" precision="I64">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="363" name="onnx::Shape_788" type="Reshape" version="opset1">
+			<data special_zero="true"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::Shape_788"/>
+			</rt_info>
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+					<dim>4096</dim>
+					<dim>512</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="onnx::Shape_788">
+					<dim>1</dim>
+					<dim>4096</dim>
+					<dim>1</dim>
+					<dim>512</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="364" name="onnx::Reshape_802" type="Const" version="opset1">
+			<data element_type="i64" shape="3" offset="116567772" size="24"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::Concat_939, onnx::Reshape_802"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="I64">
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="365" name="onnx::MatMul_803" type="Reshape" version="opset1">
+			<data special_zero="true"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::MatMul_803"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>4096</dim>
+					<dim>1</dim>
+					<dim>512</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="onnx::MatMul_803">
+					<dim>1</dim>
+					<dim>4096</dim>
+					<dim>512</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="366" name="Constant_13371" type="Const" version="opset1">
+			<data element_type="f32" shape="512, 512" offset="116567796" size="1048576"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::Add_805, onnx::MatMul_940"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="FP32">
+					<dim>512</dim>
+					<dim>512</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="367" name="onnx::Add_805" type="MatMul" version="opset1">
+			<data transpose_a="false" transpose_b="true"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::Add_805, onnx::MatMul_940"/>
+			</rt_info>
+			<input>
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+				<port id="1" precision="FP32">
+					<dim>512</dim>
+					<dim>512</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="onnx::Add_805">
+					<dim>1</dim>
+					<dim>4096</dim>
+					<dim>512</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="368" name="onnx::Transpose_806" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::Transpose_806"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>512</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>4096</dim>
+					<dim>512</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="onnx::Transpose_806">
+					<dim>1</dim>
+					<dim>4096</dim>
+					<dim>512</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="369" name="Constant_4157" type="Const" version="opset1">
+			<data element_type="i64" shape="3" offset="113417792" size="24"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="Constant_4157"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="I64">
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="370" name="onnx::Reshape_807" type="Transpose" version="opset1">
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::Reshape_807"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>4096</dim>
+					<dim>512</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="onnx::Reshape_807">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>4096</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="371" name="onnx::Add_817" type="Reshape" version="opset1">
+			<data special_zero="true"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::Add_817"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
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+					<dim>512</dim>
+					<dim>4096</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="onnx::Add_817">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="372" name="onnx::Div_818" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="input.232, onnx::Cast_820, onnx::Div_818"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
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+					<dim>512</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="input.232,onnx::Cast_820,onnx::Div_818">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="373" name="onnx::Reshape_822" type="Const" version="opset1">
+			<data element_type="i64" shape="3" offset="18432" size="24"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::Reshape_822"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="I64" names="onnx::Reshape_822">
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="374" name="onnx::InstanceNormalization_823" type="Reshape" version="opset1">
+			<data special_zero="true"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::InstanceNormalization_823"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
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+					<dim>512</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="onnx::InstanceNormalization_823">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>65536</dim>
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+			</output>
+		</layer>
+		<layer id="375" name="Constant_4259" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="18456" size="8"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="Constant_4259"/>
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+			<output>
+				<port id="0" precision="I64">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="376" name="MVN_4260" type="MVN" version="opset6">
+			<data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="Concat_4279, Concat_4324, MVN_4260, Multiply_4307, Reshape_4280, Reshape_4325, onnx::Reshape_826"/>
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+					<dim>32</dim>
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+				<port id="1" precision="I64">
+					<dim>1</dim>
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+			<output>
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+					<dim>1</dim>
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+			</output>
+		</layer>
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+			<data output_type="i64"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::Reshape_827"/>
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+			<output>
+				<port id="1" precision="I64" names="onnx::Reshape_827">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="378" name="onnx::Mul_828" type="Reshape" version="opset1">
+			<data special_zero="true"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::Mul_828"/>
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+			<input>
+				<port id="0" precision="FP32">
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+					<dim>65536</dim>
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+				<port id="1" precision="I64">
+					<dim>4</dim>
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+			</input>
+			<output>
+				<port id="2" precision="FP32" names="onnx::Mul_828">
+					<dim>1</dim>
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+					<dim>64</dim>
+					<dim>64</dim>
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+			</output>
+		</layer>
+		<layer id="379" name="Constant_13489" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 512, 1, 1" offset="117616372" size="2048"/>
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+					<dim>1</dim>
+					<dim>1</dim>
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+			</output>
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+		<layer id="380" name="onnx::Add_831" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="onnx::Add_831"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
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+					<dim>64</dim>
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+				<port id="1" precision="FP32">
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+					<dim>512</dim>
+					<dim>1</dim>
+					<dim>1</dim>
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+			</input>
+			<output>
+				<port id="2" precision="FP32" names="onnx::Add_831">
+					<dim>1</dim>
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+					<dim>64</dim>
+					<dim>64</dim>
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+			</output>
+		</layer>
+		<layer id="381" name="Constant_13490" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 512, 1, 1" offset="117618420" size="2048"/>
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+					<dim>1</dim>
+					<dim>1</dim>
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+			</output>
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+		<layer id="382" name="onnx::Cast_834" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="input.236, onnx::Cast_834"/>
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+				<port id="1" precision="FP32">
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+					<dim>1</dim>
+					<dim>1</dim>
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+			<output>
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+					<dim>64</dim>
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+			</output>
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+		<layer id="383" name="input.240" type="Swish" version="opset4">
+			<rt_info>
+				<attribute name="fused_names" version="0" value="input.240, onnx::Mul_836"/>
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+			<input>
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+			<output>
+				<port id="1" precision="FP32" names="input.240">
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+					<dim>64</dim>
+					<dim>64</dim>
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+			</output>
+		</layer>
+		<layer id="384" name="m.encoder.mid_block.resnets.1.conv1.weight" type="Const" version="opset1">
+			<data element_type="f32" shape="512, 512, 3, 3" offset="117620468" size="9437184"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="m.encoder.mid_block.resnets.1.conv1.weight"/>
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+			<output>
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+					<dim>512</dim>
+					<dim>3</dim>
+					<dim>3</dim>
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+			</output>
+		</layer>
+		<layer id="385" name="Convolution_4365" type="Convolution" version="opset1">
+			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="Convolution_4365"/>
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+				<port id="1" precision="FP32">
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+					<dim>512</dim>
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+					<dim>3</dim>
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+					<dim>64</dim>
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+					<dim>1</dim>
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+			<data auto_broadcast="numpy"/>
+			<rt_info>
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+			<data special_zero="true"/>
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+		<MO_version value="2022.1.0-7019-cdb9bec7210-releases/2022/1"/>
+		<Runtime_version value="2022.1.0-7019-cdb9bec7210-releases/2022/1"/>
+		<legacy_path value="False"/>
+		<cli_parameters>
+			<caffe_parser_path value="DIR"/>
+			<compress_fp16 value="False"/>
+			<data_type value="float"/>
+			<disable_nhwc_to_nchw value="False"/>
+			<disable_omitting_optional value="False"/>
+			<disable_resnet_optimization value="False"/>
+			<disable_weights_compression value="False"/>
+			<enable_concat_optimization value="False"/>
+			<enable_flattening_nested_params value="False"/>
+			<enable_ssd_gluoncv value="False"/>
+			<extensions value="DIR"/>
+			<framework value="onnx"/>
+			<freeze_placeholder_with_value value="{}"/>
+			<input_model value="DIR/vae_encoder.onnx"/>
+			<input_model_is_text value="False"/>
+			<k value="DIR/CustomLayersMapping.xml"/>
+			<layout value="()"/>
+			<layout_values value="{}"/>
+			<legacy_mxnet_model value="False"/>
+			<log_level value="ERROR"/>
+			<mean_scale_values value="{}"/>
+			<mean_values value="()"/>
+			<model_name value="vae_encoder"/>
+			<output_dir value="DIR"/>
+			<placeholder_data_types value="{}"/>
+			<progress value="False"/>
+			<remove_memory value="False"/>
+			<remove_output_softmax value="False"/>
+			<reverse_input_channels value="False"/>
+			<save_params_from_nd value="False"/>
+			<scale_values value="()"/>
+			<silent value="False"/>
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+			<static_shape value="False"/>
+			<stream_output value="False"/>
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+			<use_legacy_frontend value="False"/>
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+	</meta_data>
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