vae_encoder/openvino_model.xml

<?xml version="1.0"?>
<net name="Model314" version="11">
	<layers>
		<layer id="0" name="sample" type="Parameter" version="opset1">
			<data shape="?,3,?,?" element_type="f32" />
			<output>
				<port id="0" precision="FP32" names="sample">
					<dim>-1</dim>
					<dim>3</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="1" name="self.encoder.conv_in.weight" type="Const" version="opset1">
			<data element_type="f32" shape="128, 3, 3, 3" offset="0" size="13824" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.conv_in.weight">
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="2" name="__module.encoder.conv_in/aten::_convolution/Convolution" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>3</dim>
					<dim>-1</dim>
					<dim>-1</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>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="3" name="__module.encoder.conv_in/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 128, 1, 1" offset="13824" 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="4" name="__module.encoder.conv_in/aten::_convolution/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</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="47,input.1">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="5" name="self.encoder.down_blocks.0.resnets.0.norm1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="128" offset="14336" size="512" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.0.resnets.0.norm1.weight">
					<dim>128</dim>
				</port>
			</output>
		</layer>
		<layer id="6" name="self.encoder.down_blocks.0.resnets.0.norm1.bias" type="Const" version="opset1">
			<data element_type="f32" shape="128" offset="14848" size="512" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.0.resnets.0.norm1.bias">
					<dim>128</dim>
				</port>
			</output>
		</layer>
		<layer id="7" name="__module.encoder.down_blocks.0.resnets.0.norm1/aten::group_norm/GroupNormalization" type="GroupNormalization" version="opset12">
			<data num_groups="32" epsilon="9.9999999747524271e-07" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>128</dim>
				</port>
				<port id="2" precision="FP32">
					<dim>128</dim>
				</port>
			</input>
			<output>
				<port id="3" precision="FP32" names="61,input.3">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="8" name="__module.decoder.mid_block.resnets.1.nonlinearity/aten::silu/Swish" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="62">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="9" name="self.encoder.down_blocks.0.resnets.0.conv1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="128, 128, 3, 3" offset="15360" size="589824" />
			<output>
				<port id="0" precision="FP32" names="self.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="10" name="__module.encoder.down_blocks.0.resnets.0.conv1/aten::_convolution/Convolution" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</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>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="11" name="__module.encoder.down_blocks.0.resnets.0.conv1/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 128, 1, 1" offset="605184" 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="12" name="__module.encoder.down_blocks.0.resnets.0.conv1/aten::_convolution/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</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="69,input.5">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="13" name="self.encoder.down_blocks.0.resnets.0.norm2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="128" offset="605696" size="512" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.0.resnets.0.norm2.weight">
					<dim>128</dim>
				</port>
			</output>
		</layer>
		<layer id="14" name="self.encoder.down_blocks.0.resnets.0.norm2.bias" type="Const" version="opset1">
			<data element_type="f32" shape="128" offset="606208" size="512" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.0.resnets.0.norm2.bias">
					<dim>128</dim>
				</port>
			</output>
		</layer>
		<layer id="15" name="__module.encoder.down_blocks.0.resnets.0.norm2/aten::group_norm/GroupNormalization" type="GroupNormalization" version="opset12">
			<data num_groups="32" epsilon="9.9999999747524271e-07" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>128</dim>
				</port>
				<port id="2" precision="FP32">
					<dim>128</dim>
				</port>
			</input>
			<output>
				<port id="3" precision="FP32" names="72,input.7">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="16" name="__module.decoder.mid_block.resnets.1.nonlinearity/aten::silu/Swish_1" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="73,input.9">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="17" name="self.encoder.down_blocks.0.resnets.0.conv2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="128, 128, 3, 3" offset="606720" size="589824" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.0.resnets.0.conv2.weight">
					<dim>128</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="18" name="__module.encoder.down_blocks.0.resnets.0.conv2/aten::_convolution/Convolution" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</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>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="19" name="__module.encoder.down_blocks.0.resnets.0.conv2/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 128, 1, 1" offset="1196544" 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="20" name="__module.encoder.down_blocks.0.resnets.0.conv2/aten::_convolution/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</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="81,hidden_states.1">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="21" name="__module.encoder.down_blocks.0.resnets.0/aten::add/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</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="82,83,input.11">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="22" name="self.encoder.down_blocks.0.resnets.1.norm1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="128" offset="1197056" size="512" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.0.resnets.1.norm1.weight">
					<dim>128</dim>
				</port>
			</output>
		</layer>
		<layer id="23" name="self.encoder.down_blocks.0.resnets.1.norm1.bias" type="Const" version="opset1">
			<data element_type="f32" shape="128" offset="1197568" size="512" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.0.resnets.1.norm1.bias">
					<dim>128</dim>
				</port>
			</output>
		</layer>
		<layer id="24" name="__module.encoder.down_blocks.0.resnets.1.norm1/aten::group_norm/GroupNormalization" type="GroupNormalization" version="opset12">
			<data num_groups="32" epsilon="9.9999999747524271e-07" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>128</dim>
				</port>
				<port id="2" precision="FP32">
					<dim>128</dim>
				</port>
			</input>
			<output>
				<port id="3" precision="FP32" names="91,input.13">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="25" name="__module.decoder.mid_block.resnets.1.nonlinearity/aten::silu/Swish_2" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="92">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="26" name="self.encoder.down_blocks.0.resnets.1.conv1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="128, 128, 3, 3" offset="1198080" size="589824" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.0.resnets.1.conv1.weight">
					<dim>128</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="27" name="__module.encoder.down_blocks.0.resnets.1.conv1/aten::_convolution/Convolution" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</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>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="28" name="__module.encoder.down_blocks.0.resnets.1.conv1/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 128, 1, 1" offset="1787904" 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="__module.encoder.down_blocks.0.resnets.1.conv1/aten::_convolution/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</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="99,input.15">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="30" name="self.encoder.down_blocks.0.resnets.1.norm2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="128" offset="1788416" size="512" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.0.resnets.1.norm2.weight">
					<dim>128</dim>
				</port>
			</output>
		</layer>
		<layer id="31" name="self.encoder.down_blocks.0.resnets.1.norm2.bias" type="Const" version="opset1">
			<data element_type="f32" shape="128" offset="1788928" size="512" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.0.resnets.1.norm2.bias">
					<dim>128</dim>
				</port>
			</output>
		</layer>
		<layer id="32" name="__module.encoder.down_blocks.0.resnets.1.norm2/aten::group_norm/GroupNormalization" type="GroupNormalization" version="opset12">
			<data num_groups="32" epsilon="9.9999999747524271e-07" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>128</dim>
				</port>
				<port id="2" precision="FP32">
					<dim>128</dim>
				</port>
			</input>
			<output>
				<port id="3" precision="FP32" names="102,input.17">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="33" name="__module.decoder.mid_block.resnets.1.nonlinearity/aten::silu/Swish_3" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="103,input.19">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="34" name="self.encoder.down_blocks.0.resnets.1.conv2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="128, 128, 3, 3" offset="1789440" size="589824" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.0.resnets.1.conv2.weight">
					<dim>128</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="35" name="__module.encoder.down_blocks.0.resnets.1.conv2/aten::_convolution/Convolution" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</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>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="36" name="__module.encoder.down_blocks.0.resnets.1.conv2/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 128, 1, 1" offset="2379264" 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="37" name="__module.encoder.down_blocks.0.resnets.1.conv2/aten::_convolution/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</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="111,hidden_states.3">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="38" name="__module.encoder.down_blocks.0.resnets.1/aten::add/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</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="112,113,hidden_states.5">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="39" name="self.encoder.down_blocks.0.downsamplers.0.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="128, 128, 3, 3" offset="2379776" size="589824" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.0.downsamplers.0.conv.weight">
					<dim>128</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="40" name="__module.encoder.down_blocks.0.downsamplers.0.conv/aten::_convolution/Convolution" type="Convolution" version="opset1">
			<data strides="2, 2" dilations="1, 1" pads_begin="0, 0" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</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>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="41" name="__module.encoder.down_blocks.0.downsamplers.0.conv/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 128, 1, 1" offset="2969600" 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="42" name="__module.encoder.down_blocks.0.downsamplers.0.conv/aten::_convolution/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</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="123,input.21">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="43" name="self.encoder.down_blocks.1.resnets.0.conv_shortcut.weight" type="Const" version="opset1">
			<data element_type="f32" shape="256, 128, 1, 1" offset="2970112" size="131072" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.1.resnets.0.conv_shortcut.weight">
					<dim>256</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="44" name="__module.encoder.down_blocks.1.resnets.0.conv_shortcut/aten::_convolution/Convolution" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="0, 0" pads_end="0, 0" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>256</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="45" name="__module.encoder.down_blocks.1.resnets.0.conv_shortcut/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 256, 1, 1" offset="3101184" size="1024" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="46" name="__module.encoder.down_blocks.1.resnets.0.conv_shortcut/aten::_convolution/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="165,input_tensor.1">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="47" name="self.encoder.down_blocks.1.resnets.0.norm1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="128" offset="3102208" size="512" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.1.resnets.0.norm1.weight">
					<dim>128</dim>
				</port>
			</output>
		</layer>
		<layer id="48" name="self.encoder.down_blocks.1.resnets.0.norm1.bias" type="Const" version="opset1">
			<data element_type="f32" shape="128" offset="3102720" size="512" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.1.resnets.0.norm1.bias">
					<dim>128</dim>
				</port>
			</output>
		</layer>
		<layer id="49" name="__module.encoder.down_blocks.1.resnets.0.norm1/aten::group_norm/GroupNormalization" type="GroupNormalization" version="opset12">
			<data num_groups="32" epsilon="9.9999999747524271e-07" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>128</dim>
				</port>
				<port id="2" precision="FP32">
					<dim>128</dim>
				</port>
			</input>
			<output>
				<port id="3" precision="FP32" names="138,input.23">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="50" name="__module.decoder.mid_block.resnets.1.nonlinearity/aten::silu/Swish_4" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="139">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="51" name="self.encoder.down_blocks.1.resnets.0.conv1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="256, 128, 3, 3" offset="3103232" size="1179648" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.1.resnets.0.conv1.weight">
					<dim>256</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="52" name="__module.encoder.down_blocks.1.resnets.0.conv1/aten::_convolution/Convolution" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>256</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="53" name="__module.encoder.down_blocks.1.resnets.0.conv1/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 256, 1, 1" offset="4282880" size="1024" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="54" name="__module.encoder.down_blocks.1.resnets.0.conv1/aten::_convolution/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="146,input.25">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="55" name="self.encoder.down_blocks.1.resnets.0.norm2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="256" offset="4283904" size="1024" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.1.resnets.0.norm2.weight">
					<dim>256</dim>
				</port>
			</output>
		</layer>
		<layer id="56" name="self.encoder.down_blocks.1.resnets.0.norm2.bias" type="Const" version="opset1">
			<data element_type="f32" shape="256" offset="4284928" size="1024" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.1.resnets.0.norm2.bias">
					<dim>256</dim>
				</port>
			</output>
		</layer>
		<layer id="57" name="__module.encoder.down_blocks.1.resnets.0.norm2/aten::group_norm/GroupNormalization" type="GroupNormalization" version="opset12">
			<data num_groups="32" epsilon="9.9999999747524271e-07" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>256</dim>
				</port>
				<port id="2" precision="FP32">
					<dim>256</dim>
				</port>
			</input>
			<output>
				<port id="3" precision="FP32" names="149,input.27">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="58" name="__module.decoder.mid_block.resnets.1.nonlinearity/aten::silu/Swish_5" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="150,input.29">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="59" name="self.encoder.down_blocks.1.resnets.0.conv2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="256, 256, 3, 3" offset="4285952" size="2359296" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.1.resnets.0.conv2.weight">
					<dim>256</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="60" name="__module.encoder.down_blocks.1.resnets.0.conv2/aten::_convolution/Convolution" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>256</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="61" name="__module.encoder.down_blocks.1.resnets.0.conv2/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 256, 1, 1" offset="6645248" size="1024" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="62" name="__module.encoder.down_blocks.1.resnets.0.conv2/aten::_convolution/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="158,hidden_states.9">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="63" name="__module.encoder.down_blocks.1.resnets.0/aten::add/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="166,167,input.31">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="64" name="self.encoder.down_blocks.1.resnets.1.norm1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="256" offset="6646272" size="1024" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.1.resnets.1.norm1.weight">
					<dim>256</dim>
				</port>
			</output>
		</layer>
		<layer id="65" name="self.encoder.down_blocks.1.resnets.1.norm1.bias" type="Const" version="opset1">
			<data element_type="f32" shape="256" offset="6647296" size="1024" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.1.resnets.1.norm1.bias">
					<dim>256</dim>
				</port>
			</output>
		</layer>
		<layer id="66" name="__module.encoder.down_blocks.1.resnets.1.norm1/aten::group_norm/GroupNormalization" type="GroupNormalization" version="opset12">
			<data num_groups="32" epsilon="9.9999999747524271e-07" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>256</dim>
				</port>
				<port id="2" precision="FP32">
					<dim>256</dim>
				</port>
			</input>
			<output>
				<port id="3" precision="FP32" names="175,input.33">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="67" name="__module.decoder.mid_block.resnets.1.nonlinearity/aten::silu/Swish_6" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="176">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="68" name="self.encoder.down_blocks.1.resnets.1.conv1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="256, 256, 3, 3" offset="6648320" size="2359296" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.1.resnets.1.conv1.weight">
					<dim>256</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="69" name="__module.encoder.down_blocks.1.resnets.1.conv1/aten::_convolution/Convolution" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>256</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="70" name="__module.encoder.down_blocks.1.resnets.1.conv1/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 256, 1, 1" offset="9007616" size="1024" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="71" name="__module.encoder.down_blocks.1.resnets.1.conv1/aten::_convolution/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="183,input.35">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="72" name="self.encoder.down_blocks.1.resnets.1.norm2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="256" offset="9008640" size="1024" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.1.resnets.1.norm2.weight">
					<dim>256</dim>
				</port>
			</output>
		</layer>
		<layer id="73" name="self.encoder.down_blocks.1.resnets.1.norm2.bias" type="Const" version="opset1">
			<data element_type="f32" shape="256" offset="9009664" size="1024" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.1.resnets.1.norm2.bias">
					<dim>256</dim>
				</port>
			</output>
		</layer>
		<layer id="74" name="__module.encoder.down_blocks.1.resnets.1.norm2/aten::group_norm/GroupNormalization" type="GroupNormalization" version="opset12">
			<data num_groups="32" epsilon="9.9999999747524271e-07" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>256</dim>
				</port>
				<port id="2" precision="FP32">
					<dim>256</dim>
				</port>
			</input>
			<output>
				<port id="3" precision="FP32" names="186,input.37">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="75" name="__module.decoder.mid_block.resnets.1.nonlinearity/aten::silu/Swish_7" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="187,input.39">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="76" name="self.encoder.down_blocks.1.resnets.1.conv2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="256, 256, 3, 3" offset="9010688" size="2359296" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.1.resnets.1.conv2.weight">
					<dim>256</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="77" name="__module.encoder.down_blocks.1.resnets.1.conv2/aten::_convolution/Convolution" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>256</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="78" name="__module.encoder.down_blocks.1.resnets.1.conv2/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 256, 1, 1" offset="11369984" size="1024" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="79" name="__module.encoder.down_blocks.1.resnets.1.conv2/aten::_convolution/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="195,hidden_states.11">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="80" name="__module.encoder.down_blocks.1.resnets.1/aten::add/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="196,197,hidden_states.13">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="81" name="self.encoder.down_blocks.1.downsamplers.0.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="256, 256, 3, 3" offset="11371008" size="2359296" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.1.downsamplers.0.conv.weight">
					<dim>256</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="82" name="__module.encoder.down_blocks.1.downsamplers.0.conv/aten::_convolution/Convolution" type="Convolution" version="opset1">
			<data strides="2, 2" dilations="1, 1" pads_begin="0, 0" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>256</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="83" name="__module.encoder.down_blocks.1.downsamplers.0.conv/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 256, 1, 1" offset="13730304" size="1024" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="84" name="__module.encoder.down_blocks.1.downsamplers.0.conv/aten::_convolution/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="207,input.41">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="85" name="self.encoder.down_blocks.2.resnets.0.conv_shortcut.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512, 256, 1, 1" offset="13731328" size="524288" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.2.resnets.0.conv_shortcut.weight">
					<dim>512</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="86" name="__module.encoder.down_blocks.2.resnets.0.conv_shortcut/aten::_convolution/Convolution" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="0, 0" pads_end="0, 0" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>512</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="87" name="__module.encoder.down_blocks.2.resnets.0.conv_shortcut/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 512, 1, 1" offset="14255616" size="2048" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="88" name="__module.encoder.down_blocks.2.resnets.0.conv_shortcut/aten::_convolution/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="249,input_tensor">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="89" name="self.encoder.down_blocks.2.resnets.0.norm1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="256" offset="14257664" size="1024" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.2.resnets.0.norm1.weight">
					<dim>256</dim>
				</port>
			</output>
		</layer>
		<layer id="90" name="self.encoder.down_blocks.2.resnets.0.norm1.bias" type="Const" version="opset1">
			<data element_type="f32" shape="256" offset="14258688" size="1024" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.2.resnets.0.norm1.bias">
					<dim>256</dim>
				</port>
			</output>
		</layer>
		<layer id="91" name="__module.encoder.down_blocks.2.resnets.0.norm1/aten::group_norm/GroupNormalization" type="GroupNormalization" version="opset12">
			<data num_groups="32" epsilon="9.9999999747524271e-07" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>256</dim>
				</port>
				<port id="2" precision="FP32">
					<dim>256</dim>
				</port>
			</input>
			<output>
				<port id="3" precision="FP32" names="222,input.43">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="92" name="__module.decoder.mid_block.resnets.1.nonlinearity/aten::silu/Swish_8" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="223">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="93" name="self.encoder.down_blocks.2.resnets.0.conv1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512, 256, 3, 3" offset="14259712" size="4718592" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.2.resnets.0.conv1.weight">
					<dim>512</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="94" name="__module.encoder.down_blocks.2.resnets.0.conv1/aten::_convolution/Convolution" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>512</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="95" name="__module.encoder.down_blocks.2.resnets.0.conv1/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 512, 1, 1" offset="18978304" size="2048" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="96" name="__module.encoder.down_blocks.2.resnets.0.conv1/aten::_convolution/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="230,input.45">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="97" name="self.encoder.down_blocks.2.resnets.0.norm2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="18980352" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.2.resnets.0.norm2.weight">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="98" name="self.encoder.down_blocks.2.resnets.0.norm2.bias" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="18982400" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.2.resnets.0.norm2.bias">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="99" name="__module.encoder.down_blocks.2.resnets.0.norm2/aten::group_norm/GroupNormalization" type="GroupNormalization" version="opset12">
			<data num_groups="32" epsilon="9.9999999747524271e-07" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>512</dim>
				</port>
				<port id="2" precision="FP32">
					<dim>512</dim>
				</port>
			</input>
			<output>
				<port id="3" precision="FP32" names="233,input.47">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="100" name="__module.decoder.mid_block.resnets.1.nonlinearity/aten::silu/Swish_9" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="234,input.49">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="101" name="self.encoder.down_blocks.2.resnets.0.conv2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512, 512, 3, 3" offset="18984448" size="9437184" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.2.resnets.0.conv2.weight">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="102" name="__module.encoder.down_blocks.2.resnets.0.conv2/aten::_convolution/Convolution" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="103" name="__module.encoder.down_blocks.2.resnets.0.conv2/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 512, 1, 1" offset="28421632" size="2048" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="104" name="__module.encoder.down_blocks.2.resnets.0.conv2/aten::_convolution/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="242,hidden_states.17">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="105" name="__module.encoder.down_blocks.2.resnets.0/aten::add/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="250,251,input.51">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="106" name="self.encoder.down_blocks.2.resnets.1.norm1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="28423680" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.2.resnets.1.norm1.weight">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="107" name="self.encoder.down_blocks.2.resnets.1.norm1.bias" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="28425728" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.2.resnets.1.norm1.bias">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="108" name="__module.encoder.down_blocks.2.resnets.1.norm1/aten::group_norm/GroupNormalization" type="GroupNormalization" version="opset12">
			<data num_groups="32" epsilon="9.9999999747524271e-07" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>512</dim>
				</port>
				<port id="2" precision="FP32">
					<dim>512</dim>
				</port>
			</input>
			<output>
				<port id="3" precision="FP32" names="259,input.53">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="109" name="__module.decoder.mid_block.resnets.1.nonlinearity/aten::silu/Swish_10" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="260">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="110" name="self.encoder.down_blocks.2.resnets.1.conv1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512, 512, 3, 3" offset="28427776" size="9437184" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.2.resnets.1.conv1.weight">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="111" name="__module.encoder.down_blocks.2.resnets.1.conv1/aten::_convolution/Convolution" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="112" name="__module.encoder.down_blocks.2.resnets.1.conv1/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 512, 1, 1" offset="37864960" size="2048" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="113" name="__module.encoder.down_blocks.2.resnets.1.conv1/aten::_convolution/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="267,input.55">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="114" name="self.encoder.down_blocks.2.resnets.1.norm2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="37867008" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.2.resnets.1.norm2.weight">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="115" name="self.encoder.down_blocks.2.resnets.1.norm2.bias" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="37869056" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.2.resnets.1.norm2.bias">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="116" name="__module.encoder.down_blocks.2.resnets.1.norm2/aten::group_norm/GroupNormalization" type="GroupNormalization" version="opset12">
			<data num_groups="32" epsilon="9.9999999747524271e-07" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>512</dim>
				</port>
				<port id="2" precision="FP32">
					<dim>512</dim>
				</port>
			</input>
			<output>
				<port id="3" precision="FP32" names="270,input.57">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="117" name="__module.decoder.mid_block.resnets.1.nonlinearity/aten::silu/Swish_11" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="271,input.59">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="118" name="self.encoder.down_blocks.2.resnets.1.conv2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512, 512, 3, 3" offset="37871104" size="9437184" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.2.resnets.1.conv2.weight">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="119" name="__module.encoder.down_blocks.2.resnets.1.conv2/aten::_convolution/Convolution" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="120" name="__module.encoder.down_blocks.2.resnets.1.conv2/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 512, 1, 1" offset="47308288" size="2048" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="121" name="__module.encoder.down_blocks.2.resnets.1.conv2/aten::_convolution/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="279,hidden_states.19">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="122" name="__module.encoder.down_blocks.2.resnets.1/aten::add/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="280,281,hidden_states.21">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="123" name="self.encoder.down_blocks.2.downsamplers.0.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512, 512, 3, 3" offset="47310336" size="9437184" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.2.downsamplers.0.conv.weight">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="124" name="__module.encoder.down_blocks.2.downsamplers.0.conv/aten::_convolution/Convolution" type="Convolution" version="opset1">
			<data strides="2, 2" dilations="1, 1" pads_begin="0, 0" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="125" name="__module.encoder.down_blocks.2.downsamplers.0.conv/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 512, 1, 1" offset="56747520" size="2048" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="126" name="__module.encoder.down_blocks.2.downsamplers.0.conv/aten::_convolution/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="291,input.61">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="127" name="self.encoder.down_blocks.3.resnets.0.norm1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="56749568" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.3.resnets.0.norm1.weight">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="128" name="self.encoder.down_blocks.3.resnets.0.norm1.bias" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="56751616" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.3.resnets.0.norm1.bias">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="129" name="__module.encoder.down_blocks.3.resnets.0.norm1/aten::group_norm/GroupNormalization" type="GroupNormalization" version="opset12">
			<data num_groups="32" epsilon="9.9999999747524271e-07" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>512</dim>
				</port>
				<port id="2" precision="FP32">
					<dim>512</dim>
				</port>
			</input>
			<output>
				<port id="3" precision="FP32" names="303,input.63">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="130" name="__module.decoder.mid_block.resnets.1.nonlinearity/aten::silu/Swish_12" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="304">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="131" name="self.encoder.down_blocks.3.resnets.0.conv1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512, 512, 3, 3" offset="56753664" size="9437184" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.3.resnets.0.conv1.weight">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="132" name="__module.encoder.down_blocks.3.resnets.0.conv1/aten::_convolution/Convolution" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="133" name="__module.encoder.down_blocks.3.resnets.0.conv1/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 512, 1, 1" offset="66190848" size="2048" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="134" name="__module.encoder.down_blocks.3.resnets.0.conv1/aten::_convolution/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="311,input.65">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="135" name="self.encoder.down_blocks.3.resnets.0.norm2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="66192896" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.3.resnets.0.norm2.weight">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="136" name="self.encoder.down_blocks.3.resnets.0.norm2.bias" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="66194944" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.3.resnets.0.norm2.bias">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="137" name="__module.encoder.down_blocks.3.resnets.0.norm2/aten::group_norm/GroupNormalization" type="GroupNormalization" version="opset12">
			<data num_groups="32" epsilon="9.9999999747524271e-07" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>512</dim>
				</port>
				<port id="2" precision="FP32">
					<dim>512</dim>
				</port>
			</input>
			<output>
				<port id="3" precision="FP32" names="314,input.67">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="138" name="__module.decoder.mid_block.resnets.1.nonlinearity/aten::silu/Swish_13" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="315,input.69">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="139" name="self.encoder.down_blocks.3.resnets.0.conv2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512, 512, 3, 3" offset="66196992" size="9437184" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.3.resnets.0.conv2.weight">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="140" name="__module.encoder.down_blocks.3.resnets.0.conv2/aten::_convolution/Convolution" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="141" name="__module.encoder.down_blocks.3.resnets.0.conv2/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 512, 1, 1" offset="75634176" size="2048" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="142" name="__module.encoder.down_blocks.3.resnets.0.conv2/aten::_convolution/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="323,hidden_states.25">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="143" name="__module.encoder.down_blocks.3.resnets.0/aten::add/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="324,325,input.71">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="144" name="self.encoder.down_blocks.3.resnets.1.norm1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="75636224" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.3.resnets.1.norm1.weight">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="145" name="self.encoder.down_blocks.3.resnets.1.norm1.bias" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="75638272" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.3.resnets.1.norm1.bias">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="146" name="__module.encoder.down_blocks.3.resnets.1.norm1/aten::group_norm/GroupNormalization" type="GroupNormalization" version="opset12">
			<data num_groups="32" epsilon="9.9999999747524271e-07" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>512</dim>
				</port>
				<port id="2" precision="FP32">
					<dim>512</dim>
				</port>
			</input>
			<output>
				<port id="3" precision="FP32" names="333,input.73">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="147" name="__module.decoder.mid_block.resnets.1.nonlinearity/aten::silu/Swish_14" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="334">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="148" name="self.encoder.down_blocks.3.resnets.1.conv1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512, 512, 3, 3" offset="75640320" size="9437184" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.3.resnets.1.conv1.weight">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="149" name="__module.encoder.down_blocks.3.resnets.1.conv1/aten::_convolution/Convolution" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="150" name="__module.encoder.down_blocks.3.resnets.1.conv1/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 512, 1, 1" offset="85077504" size="2048" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="151" name="__module.encoder.down_blocks.3.resnets.1.conv1/aten::_convolution/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="341,input.75">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="152" name="self.encoder.down_blocks.3.resnets.1.norm2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="85079552" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.3.resnets.1.norm2.weight">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="153" name="self.encoder.down_blocks.3.resnets.1.norm2.bias" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="85081600" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.3.resnets.1.norm2.bias">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="154" name="__module.encoder.down_blocks.3.resnets.1.norm2/aten::group_norm/GroupNormalization" type="GroupNormalization" version="opset12">
			<data num_groups="32" epsilon="9.9999999747524271e-07" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>512</dim>
				</port>
				<port id="2" precision="FP32">
					<dim>512</dim>
				</port>
			</input>
			<output>
				<port id="3" precision="FP32" names="344,input.77">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="155" name="__module.decoder.mid_block.resnets.1.nonlinearity/aten::silu/Swish_15" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="345,input.79">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="156" name="self.encoder.down_blocks.3.resnets.1.conv2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512, 512, 3, 3" offset="85083648" size="9437184" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.down_blocks.3.resnets.1.conv2.weight">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="157" name="__module.encoder.down_blocks.3.resnets.1.conv2/aten::_convolution/Convolution" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="158" name="__module.encoder.down_blocks.3.resnets.1.conv2/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 512, 1, 1" offset="94520832" size="2048" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="159" name="__module.encoder.down_blocks.3.resnets.1.conv2/aten::_convolution/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="353,hidden_states.27">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="160" name="__module.encoder.down_blocks.3.resnets.1/aten::add/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="354,355,input.81">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="161" name="self.encoder.mid_block.resnets.0.norm1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="94522880" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.mid_block.resnets.0.norm1.weight">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="162" name="self.encoder.mid_block.resnets.0.norm1.bias" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="94524928" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.mid_block.resnets.0.norm1.bias">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="163" name="__module.encoder.mid_block.resnets.0.norm1/aten::group_norm/GroupNormalization" type="GroupNormalization" version="opset12">
			<data num_groups="32" epsilon="9.9999999747524271e-07" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>512</dim>
				</port>
				<port id="2" precision="FP32">
					<dim>512</dim>
				</port>
			</input>
			<output>
				<port id="3" precision="FP32" names="369,input.83">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="164" name="__module.decoder.mid_block.resnets.1.nonlinearity/aten::silu/Swish_16" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="370">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="165" name="self.encoder.mid_block.resnets.0.conv1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512, 512, 3, 3" offset="94526976" size="9437184" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.mid_block.resnets.0.conv1.weight">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="166" name="__module.encoder.mid_block.resnets.0.conv1/aten::_convolution/Convolution" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="167" name="__module.encoder.mid_block.resnets.0.conv1/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 512, 1, 1" offset="103964160" size="2048" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="168" name="__module.encoder.mid_block.resnets.0.conv1/aten::_convolution/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="377,input.85">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="169" name="self.encoder.mid_block.resnets.0.norm2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="103966208" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.mid_block.resnets.0.norm2.weight">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="170" name="self.encoder.mid_block.resnets.0.norm2.bias" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="103968256" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.mid_block.resnets.0.norm2.bias">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="171" name="__module.encoder.mid_block.resnets.0.norm2/aten::group_norm/GroupNormalization" type="GroupNormalization" version="opset12">
			<data num_groups="32" epsilon="9.9999999747524271e-07" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>512</dim>
				</port>
				<port id="2" precision="FP32">
					<dim>512</dim>
				</port>
			</input>
			<output>
				<port id="3" precision="FP32" names="380,input.87">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="172" name="__module.decoder.mid_block.resnets.1.nonlinearity/aten::silu/Swish_17" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="381,input.89">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="173" name="self.encoder.mid_block.resnets.0.conv2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512, 512, 3, 3" offset="103970304" size="9437184" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.mid_block.resnets.0.conv2.weight">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="174" name="__module.encoder.mid_block.resnets.0.conv2/aten::_convolution/Convolution" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="175" name="__module.encoder.mid_block.resnets.0.conv2/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 512, 1, 1" offset="113407488" size="2048" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="176" name="__module.encoder.mid_block.resnets.0.conv2/aten::_convolution/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="389,hidden_states.29">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="177" name="__module.encoder.mid_block.resnets.0/aten::add/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="390,391,hidden_states.31">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="178" name="Constant_625525" type="Const" version="opset1">
			<data element_type="i64" shape="3" offset="113409536" size="24" />
			<output>
				<port id="0" precision="I64">
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="179" name="__module.encoder.mid_block.attentions.0/aten::view/Reshape" type="Reshape" version="opset1">
			<data special_zero="true" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="I64">
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="407">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="180" name="__module.encoder.mid_block.attentions.0/aten::transpose/ScatterElementsUpdate" type="Const" version="opset1">
			<data element_type="i32" shape="3" offset="113409560" size="12" />
			<output>
				<port id="0" precision="I32">
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="181" name="__module.encoder.mid_block.attentions.0/aten::transpose/Transpose" type="Transpose" version="opset1">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="I32">
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="408,hidden_states.33">
					<dim>-1</dim>
					<dim>-1</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="182" name="__module.encoder.mid_block.attentions.0/aten::transpose/ScatterElementsUpdate_1" type="Const" version="opset1">
			<data element_type="i32" shape="3" offset="113409560" size="12" />
			<output>
				<port id="0" precision="I32">
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="183" name="__module.encoder.mid_block.attentions.0/aten::transpose/Transpose_1" type="Transpose" version="opset1">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>-1</dim>
					<dim>512</dim>
				</port>
				<port id="1" precision="I32">
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="410,input.91">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="184" name="self.encoder.mid_block.attentions.0.group_norm.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="113409572" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.mid_block.attentions.0.group_norm.weight">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="185" name="self.encoder.mid_block.attentions.0.group_norm.bias" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="113411620" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.mid_block.attentions.0.group_norm.bias">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="186" name="__module.encoder.mid_block.attentions.0.group_norm/aten::group_norm/GroupNormalization" type="GroupNormalization" version="opset12">
			<data num_groups="32" epsilon="9.9999999747524271e-07" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>512</dim>
				</port>
				<port id="2" precision="FP32">
					<dim>512</dim>
				</port>
			</input>
			<output>
				<port id="3" precision="FP32" names="413">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="187" name="self.encoder.mid_block.attentions.0.to_q.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512, 512" offset="113413668" size="1048576" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.mid_block.attentions.0.to_q.weight">
					<dim>512</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="188" name="__module.encoder.mid_block.attentions.0.to_q/aten::linear/MatMul" type="MatMul" version="opset1">
			<data transpose_a="true" transpose_b="true" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>512</dim>
					<dim>512</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>-1</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="189" name="Constant_625406" type="Const" version="opset1">
			<data element_type="f32" shape="1, 1, 512" offset="114462244" size="2048" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>1</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="190" name="__module.encoder.mid_block.attentions.0.to_q/aten::linear/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<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>1</dim>
					<dim>512</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="417,query">
					<dim>-1</dim>
					<dim>-1</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="191" name="Constant_625526" type="Const" version="opset1">
			<data element_type="i64" shape="4" offset="114464292" size="32" />
			<output>
				<port id="0" precision="I64">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="192" name="__module.encoder.mid_block.attentions.0/aten::view/Reshape_1" type="Reshape" version="opset1">
			<data special_zero="true" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</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="431">
					<dim>-1</dim>
					<dim>-1</dim>
					<dim>1</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="193" name="Constant_625352" type="Const" version="opset1">
			<data element_type="i64" shape="4" offset="114464324" size="32" />
			<output>
				<port id="0" precision="I64">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="194" name="__module.encoder.mid_block.attentions.0/aten::transpose/Transpose_3" type="Reshape" version="opset1">
			<data special_zero="true" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>-1</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="432">
					<dim>-1</dim>
					<dim>1</dim>
					<dim>-1</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="195" name="self.encoder.mid_block.attentions.0.to_k.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512, 512" offset="114464356" size="1048576" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.mid_block.attentions.0.to_k.weight">
					<dim>512</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="196" name="__module.encoder.mid_block.attentions.0.to_k/aten::linear/MatMul" type="MatMul" version="opset1">
			<data transpose_a="true" transpose_b="true" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>512</dim>
					<dim>512</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>-1</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="197" name="Constant_625407" type="Const" version="opset1">
			<data element_type="f32" shape="1, 1, 512" offset="115512932" size="2048" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>1</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="198" name="__module.encoder.mid_block.attentions.0.to_k/aten::linear/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<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>1</dim>
					<dim>512</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="420,key">
					<dim>-1</dim>
					<dim>-1</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="199" name="Constant_625527" type="Const" version="opset1">
			<data element_type="i64" shape="4" offset="114464292" size="32" />
			<output>
				<port id="0" precision="I64">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="200" name="__module.encoder.mid_block.attentions.0/aten::view/Reshape_2" type="Reshape" version="opset1">
			<data special_zero="true" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</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="434">
					<dim>-1</dim>
					<dim>-1</dim>
					<dim>1</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="201" name="Constant_625354" type="Const" version="opset1">
			<data element_type="i64" shape="4" offset="114464324" size="32" />
			<output>
				<port id="0" precision="I64">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="202" name="__module.encoder.mid_block.attentions.0/aten::transpose/Transpose_4" type="Reshape" version="opset1">
			<data special_zero="true" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>-1</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="435">
					<dim>-1</dim>
					<dim>1</dim>
					<dim>-1</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="203" name="self.encoder.mid_block.attentions.0.to_v.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512, 512" offset="115514980" size="1048576" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.mid_block.attentions.0.to_v.weight">
					<dim>512</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="204" name="__module.encoder.mid_block.attentions.0.to_v/aten::linear/MatMul" type="MatMul" version="opset1">
			<data transpose_a="true" transpose_b="true" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>512</dim>
					<dim>512</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>-1</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="205" name="Constant_625408" type="Const" version="opset1">
			<data element_type="f32" shape="1, 1, 512" offset="116563556" size="2048" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>1</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="206" name="__module.encoder.mid_block.attentions.0.to_v/aten::linear/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<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>1</dim>
					<dim>512</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="423,value">
					<dim>-1</dim>
					<dim>-1</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="207" name="Constant_625528" type="Const" version="opset1">
			<data element_type="i64" shape="4" offset="114464292" size="32" />
			<output>
				<port id="0" precision="I64">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="208" name="__module.encoder.mid_block.attentions.0/aten::view/Reshape_3" type="Reshape" version="opset1">
			<data special_zero="true" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</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="437">
					<dim>-1</dim>
					<dim>-1</dim>
					<dim>1</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="209" name="Constant_625358" type="Const" version="opset1">
			<data element_type="i64" shape="4" offset="114464324" size="32" />
			<output>
				<port id="0" precision="I64">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="210" name="__module.encoder.mid_block.attentions.0/aten::transpose/Transpose_5" type="Reshape" version="opset1">
			<data special_zero="true" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>-1</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="438">
					<dim>-1</dim>
					<dim>1</dim>
					<dim>-1</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="211" name="__module.encoder.mid_block.attentions.0/aten::scaled_dot_product_attention/ScaledDotProductAttention" type="ScaledDotProductAttention" version="opset13">
			<data causal="false" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>1</dim>
					<dim>-1</dim>
					<dim>512</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>-1</dim>
					<dim>1</dim>
					<dim>-1</dim>
					<dim>512</dim>
				</port>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>1</dim>
					<dim>-1</dim>
					<dim>512</dim>
				</port>
			</input>
			<output>
				<port id="3" precision="FP32" names="439,hidden_states.35">
					<dim>-1</dim>
					<dim>1</dim>
					<dim>-1</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="212" name="Constant_625360" type="Const" version="opset1">
			<data element_type="i64" shape="4" offset="116565604" size="32" />
			<output>
				<port id="0" precision="I64">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="213" name="__module.encoder.mid_block.attentions.0/aten::transpose/Transpose_6" type="Reshape" version="opset1">
			<data special_zero="true" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>1</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="440">
					<dim>-1</dim>
					<dim>-1</dim>
					<dim>1</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="214" name="Constant_625529" type="Const" version="opset1">
			<data element_type="i64" shape="3" offset="116565636" size="24" />
			<output>
				<port id="0" precision="I64">
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="215" name="__module.encoder.mid_block.attentions.0/aten::reshape/Reshape" type="Reshape" version="opset1">
			<data special_zero="true" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>-1</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="444,445,hidden_states.37">
					<dim>-1</dim>
					<dim>-1</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="216" name="self.encoder.mid_block.attentions.0.to_out.0.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512, 512" offset="116565660" size="1048576" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.mid_block.attentions.0.to_out.0.weight">
					<dim>512</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="217" name="__module.encoder.mid_block.attentions.0.to_out.0/aten::linear/MatMul" type="MatMul" version="opset1">
			<data transpose_a="false" transpose_b="true" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>-1</dim>
					<dim>512</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>512</dim>
					<dim>512</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>-1</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="218" name="Constant_625409" type="Const" version="opset1">
			<data element_type="f32" shape="1, 1, 512" offset="117614236" size="2048" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>1</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="219" name="__module.encoder.mid_block.attentions.0.to_out.0/aten::linear/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<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>1</dim>
					<dim>512</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="448,input.93">
					<dim>-1</dim>
					<dim>-1</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="220" name="__module.encoder.mid_block.attentions.0/aten::transpose/ScatterElementsUpdate_7" type="Const" version="opset1">
			<data element_type="i32" shape="3" offset="113409560" size="12" />
			<output>
				<port id="0" precision="I32">
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="221" name="__module.encoder.mid_block.attentions.0/aten::transpose/Transpose_7" type="Transpose" version="opset1">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>-1</dim>
					<dim>512</dim>
				</port>
				<port id="1" precision="I32">
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="450">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="222" name="ShapeOf_625504" type="ShapeOf" version="opset3">
			<data output_type="i64" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="I64">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="223" name="Constant_625505" type="Const" version="opset1">
			<data element_type="i64" shape="1" offset="117616284" size="8" />
			<output>
				<port id="0" precision="I64">
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="224" name="Constant_625506" type="Const" version="opset1">
			<data element_type="i64" shape="" offset="117616284" size="8" />
			<output>
				<port id="0" precision="I64" />
			</output>
		</layer>
		<layer id="225" name="Gather_625507" type="Gather" version="opset8">
			<data batch_dims="0" />
			<input>
				<port id="0" precision="I64">
					<dim>4</dim>
				</port>
				<port id="1" precision="I64">
					<dim>1</dim>
				</port>
				<port id="2" precision="I64" />
			</input>
			<output>
				<port id="3" precision="I64" names="398,409">
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="226" name="__module.encoder.mid_block.attentions.0/prim::ListConstruct/Reshape_0" type="Const" version="opset1">
			<data element_type="i64" shape="1" offset="117616292" size="8" />
			<output>
				<port id="0" precision="I64">
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="227" name="Constant_625632" type="Const" version="opset1">
			<data element_type="i64" shape="2" offset="117616300" size="16" />
			<output>
				<port id="0" precision="I64">
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="228" name="Constant_625633" type="Const" version="opset1">
			<data element_type="i64" shape="" offset="117616284" size="8" />
			<output>
				<port id="0" precision="I64" />
			</output>
		</layer>
		<layer id="229" name="Gather_625634" type="Gather" version="opset8">
			<data batch_dims="0" />
			<input>
				<port id="0" precision="I64">
					<dim>4</dim>
				</port>
				<port id="1" precision="I64">
					<dim>2</dim>
				</port>
				<port id="2" precision="I64" />
			</input>
			<output>
				<port id="3" precision="I64">
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="230" name="__module.encoder.mid_block.attentions.0/prim::ListConstruct/Concat_5" type="Concat" version="opset1">
			<data axis="0" />
			<input>
				<port id="0" precision="I64">
					<dim>1</dim>
				</port>
				<port id="1" precision="I64">
					<dim>1</dim>
				</port>
				<port id="2" precision="I64">
					<dim>2</dim>
				</port>
			</input>
			<output>
				<port id="3" precision="I64" names="451">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="231" name="__module.encoder.mid_block.attentions.0/aten::reshape/Reshape_1" type="Reshape" version="opset1">
			<data special_zero="false" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="I64">
					<dim>4</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="452,hidden_states.41">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="232" name="__module.encoder.mid_block.attentions.0/aten::add/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="453,454,hidden_states.43,input.95">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="233" name="self.encoder.mid_block.resnets.1.norm1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="117616316" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.mid_block.resnets.1.norm1.weight">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="234" name="self.encoder.mid_block.resnets.1.norm1.bias" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="117618364" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.mid_block.resnets.1.norm1.bias">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="235" name="__module.encoder.mid_block.resnets.1.norm1/aten::group_norm/GroupNormalization" type="GroupNormalization" version="opset12">
			<data num_groups="32" epsilon="9.9999999747524271e-07" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>512</dim>
				</port>
				<port id="2" precision="FP32">
					<dim>512</dim>
				</port>
			</input>
			<output>
				<port id="3" precision="FP32" names="462,input.97">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="236" name="__module.decoder.mid_block.resnets.1.nonlinearity/aten::silu/Swish_18" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="463">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="237" name="self.encoder.mid_block.resnets.1.conv1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512, 512, 3, 3" offset="117620412" size="9437184" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.mid_block.resnets.1.conv1.weight">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="238" name="__module.encoder.mid_block.resnets.1.conv1/aten::_convolution/Convolution" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="239" name="__module.encoder.mid_block.resnets.1.conv1/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 512, 1, 1" offset="127057596" size="2048" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="240" name="__module.encoder.mid_block.resnets.1.conv1/aten::_convolution/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="470,input.99">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="241" name="self.encoder.mid_block.resnets.1.norm2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="127059644" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.mid_block.resnets.1.norm2.weight">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="242" name="self.encoder.mid_block.resnets.1.norm2.bias" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="127061692" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.mid_block.resnets.1.norm2.bias">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="243" name="__module.encoder.mid_block.resnets.1.norm2/aten::group_norm/GroupNormalization" type="GroupNormalization" version="opset12">
			<data num_groups="32" epsilon="9.9999999747524271e-07" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>512</dim>
				</port>
				<port id="2" precision="FP32">
					<dim>512</dim>
				</port>
			</input>
			<output>
				<port id="3" precision="FP32" names="473,input.101">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="244" name="__module.decoder.mid_block.resnets.1.nonlinearity/aten::silu/Swish_19" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="474,input.103">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="245" name="self.encoder.mid_block.resnets.1.conv2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512, 512, 3, 3" offset="127063740" size="9437184" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.mid_block.resnets.1.conv2.weight">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="246" name="__module.encoder.mid_block.resnets.1.conv2/aten::_convolution/Convolution" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="247" name="__module.encoder.mid_block.resnets.1.conv2/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 512, 1, 1" offset="136500924" size="2048" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="248" name="__module.encoder.mid_block.resnets.1.conv2/aten::_convolution/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="482,hidden_states">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="249" name="__module.encoder.mid_block.resnets.1/aten::add/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="483,484,input.105">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="250" name="self.encoder.conv_norm_out.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="136502972" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.conv_norm_out.weight">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="251" name="self.encoder.conv_norm_out.bias" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="136505020" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.conv_norm_out.bias">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="252" name="__module.encoder.conv_norm_out/aten::group_norm/GroupNormalization" type="GroupNormalization" version="opset12">
			<data num_groups="32" epsilon="9.9999999747524271e-07" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>512</dim>
				</port>
				<port id="2" precision="FP32">
					<dim>512</dim>
				</port>
			</input>
			<output>
				<port id="3" precision="FP32" names="487,input">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="253" name="__module.encoder.conv_act/aten::silu/Swish" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="488">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="254" name="self.encoder.conv_out.weight" type="Const" version="opset1">
			<data element_type="f32" shape="8, 512, 3, 3" offset="136507068" size="147456" />
			<output>
				<port id="0" precision="FP32" names="self.encoder.conv_out.weight">
					<dim>8</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="255" name="__module.encoder.conv_out/aten::_convolution/Convolution" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>8</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>8</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="256" name="__module.encoder.conv_out/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 8, 1, 1" offset="136654524" size="32" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>8</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="257" name="__module.encoder.conv_out/aten::_convolution/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>8</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>8</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="495">
					<dim>-1</dim>
					<dim>8</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="258" name="self.quant_conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="8, 8, 1, 1" offset="136654556" size="256" />
			<output>
				<port id="0" precision="FP32" names="self.quant_conv.weight">
					<dim>8</dim>
					<dim>8</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="259" name="__module.quant_conv/aten::_convolution/Convolution" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="0, 0" pads_end="0, 0" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>8</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>8</dim>
					<dim>8</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>8</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="260" name="__module.quant_conv/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 8, 1, 1" offset="136654812" size="32" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>8</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="261" name="__module.quant_conv/aten::_convolution/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>8</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>8</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="latent_parameters">
					<dim>-1</dim>
					<dim>8</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="262" name="Result_619871" type="Result" version="opset1">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>8</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
		</layer>
	</layers>
	<edges>
		<edge from-layer="0" from-port="0" to-layer="2" to-port="0" />
		<edge from-layer="1" from-port="0" to-layer="2" to-port="1" />
		<edge from-layer="2" from-port="2" to-layer="4" to-port="0" />
		<edge from-layer="3" from-port="0" to-layer="4" to-port="1" />
		<edge from-layer="4" from-port="2" to-layer="21" to-port="0" />
		<edge from-layer="4" from-port="2" to-layer="7" to-port="0" />
		<edge from-layer="5" from-port="0" to-layer="7" to-port="1" />
		<edge from-layer="6" from-port="0" to-layer="7" to-port="2" />
		<edge from-layer="7" from-port="3" to-layer="8" to-port="0" />
		<edge from-layer="8" from-port="1" to-layer="10" to-port="0" />
		<edge from-layer="9" from-port="0" to-layer="10" to-port="1" />
		<edge from-layer="10" from-port="2" to-layer="12" to-port="0" />
		<edge from-layer="11" from-port="0" to-layer="12" to-port="1" />
		<edge from-layer="12" from-port="2" to-layer="15" to-port="0" />
		<edge from-layer="13" from-port="0" to-layer="15" to-port="1" />
		<edge from-layer="14" from-port="0" to-layer="15" to-port="2" />
		<edge from-layer="15" from-port="3" to-layer="16" to-port="0" />
		<edge from-layer="16" from-port="1" to-layer="18" to-port="0" />
		<edge from-layer="17" from-port="0" to-layer="18" to-port="1" />
		<edge from-layer="18" from-port="2" to-layer="20" to-port="0" />
		<edge from-layer="19" from-port="0" to-layer="20" to-port="1" />
		<edge from-layer="20" from-port="2" to-layer="21" to-port="1" />
		<edge from-layer="21" from-port="2" to-layer="24" to-port="0" />
		<edge from-layer="21" from-port="2" to-layer="38" to-port="0" />
		<edge from-layer="22" from-port="0" to-layer="24" to-port="1" />
		<edge from-layer="23" from-port="0" to-layer="24" to-port="2" />
		<edge from-layer="24" from-port="3" to-layer="25" to-port="0" />
		<edge from-layer="25" from-port="1" to-layer="27" to-port="0" />
		<edge from-layer="26" from-port="0" to-layer="27" to-port="1" />
		<edge from-layer="27" from-port="2" to-layer="29" to-port="0" />
		<edge from-layer="28" from-port="0" to-layer="29" to-port="1" />
		<edge from-layer="29" from-port="2" to-layer="32" to-port="0" />
		<edge from-layer="30" from-port="0" to-layer="32" to-port="1" />
		<edge from-layer="31" from-port="0" to-layer="32" to-port="2" />
		<edge from-layer="32" from-port="3" to-layer="33" to-port="0" />
		<edge from-layer="33" from-port="1" to-layer="35" to-port="0" />
		<edge from-layer="34" from-port="0" to-layer="35" to-port="1" />
		<edge from-layer="35" from-port="2" to-layer="37" to-port="0" />
		<edge from-layer="36" from-port="0" to-layer="37" to-port="1" />
		<edge from-layer="37" from-port="2" 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="41" from-port="0" to-layer="42" to-port="1" />
		<edge from-layer="42" from-port="2" to-layer="44" to-port="0" />
		<edge from-layer="42" from-port="2" to-layer="49" to-port="0" />
		<edge from-layer="43" from-port="0" to-layer="44" to-port="1" />
		<edge from-layer="44" from-port="2" to-layer="46" to-port="0" />
		<edge from-layer="45" from-port="0" to-layer="46" to-port="1" />
		<edge from-layer="46" from-port="2" to-layer="63" to-port="0" />
		<edge from-layer="47" from-port="0" to-layer="49" to-port="1" />
		<edge from-layer="48" from-port="0" to-layer="49" to-port="2" />
		<edge from-layer="49" from-port="3" to-layer="50" to-port="0" />
		<edge from-layer="50" from-port="1" to-layer="52" to-port="0" />
		<edge from-layer="51" from-port="0" 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="57" to-port="0" />
		<edge from-layer="55" from-port="0" to-layer="57" to-port="1" />
		<edge from-layer="56" from-port="0" to-layer="57" to-port="2" />
		<edge from-layer="57" from-port="3" to-layer="58" to-port="0" />
		<edge from-layer="58" from-port="1" to-layer="60" to-port="0" />
		<edge from-layer="59" from-port="0" to-layer="60" to-port="1" />
		<edge from-layer="60" from-port="2" to-layer="62" to-port="0" />
		<edge from-layer="61" from-port="0" to-layer="62" to-port="1" />
		<edge from-layer="62" from-port="2" to-layer="63" to-port="1" />
		<edge from-layer="63" from-port="2" to-layer="66" to-port="0" />
		<edge from-layer="63" from-port="2" to-layer="80" to-port="0" />
		<edge from-layer="64" from-port="0" to-layer="66" to-port="1" />
		<edge from-layer="65" from-port="0" to-layer="66" to-port="2" />
		<edge from-layer="66" from-port="3" to-layer="67" to-port="0" />
		<edge from-layer="67" from-port="1" to-layer="69" to-port="0" />
		<edge from-layer="68" from-port="0" to-layer="69" to-port="1" />
		<edge from-layer="69" from-port="2" to-layer="71" to-port="0" />
		<edge from-layer="70" from-port="0" to-layer="71" to-port="1" />
		<edge from-layer="71" from-port="2" to-layer="74" to-port="0" />
		<edge from-layer="72" from-port="0" to-layer="74" to-port="1" />
		<edge from-layer="73" from-port="0" to-layer="74" to-port="2" />
		<edge from-layer="74" from-port="3" to-layer="75" to-port="0" />
		<edge from-layer="75" from-port="1" 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="84" to-port="0" />
		<edge from-layer="83" from-port="0" to-layer="84" to-port="1" />
		<edge from-layer="84" from-port="2" to-layer="86" to-port="0" />
		<edge from-layer="84" from-port="2" to-layer="91" to-port="0" />
		<edge from-layer="85" from-port="0" to-layer="86" to-port="1" />
		<edge from-layer="86" from-port="2" to-layer="88" to-port="0" />
		<edge from-layer="87" from-port="0" to-layer="88" to-port="1" />
		<edge from-layer="88" from-port="2" to-layer="105" to-port="0" />
		<edge from-layer="89" from-port="0" to-layer="91" to-port="1" />
		<edge from-layer="90" from-port="0" to-layer="91" to-port="2" />
		<edge from-layer="91" from-port="3" to-layer="92" to-port="0" />
		<edge from-layer="92" from-port="1" to-layer="94" to-port="0" />
		<edge from-layer="93" from-port="0" to-layer="94" to-port="1" />
		<edge from-layer="94" from-port="2" to-layer="96" to-port="0" />
		<edge from-layer="95" from-port="0" to-layer="96" to-port="1" />
		<edge from-layer="96" from-port="2" to-layer="99" to-port="0" />
		<edge from-layer="97" from-port="0" to-layer="99" to-port="1" />
		<edge from-layer="98" from-port="0" to-layer="99" to-port="2" />
		<edge from-layer="99" from-port="3" to-layer="100" to-port="0" />
		<edge from-layer="100" from-port="1" 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="105" to-port="1" />
		<edge from-layer="105" from-port="2" to-layer="122" to-port="0" />
		<edge from-layer="105" from-port="2" to-layer="108" to-port="0" />
		<edge from-layer="106" from-port="0" to-layer="108" to-port="1" />
		<edge from-layer="107" from-port="0" to-layer="108" to-port="2" />
		<edge from-layer="108" from-port="3" to-layer="109" to-port="0" />
		<edge from-layer="109" from-port="1" 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="116" to-port="0" />
		<edge from-layer="114" from-port="0" to-layer="116" to-port="1" />
		<edge from-layer="115" from-port="0" to-layer="116" to-port="2" />
		<edge from-layer="116" from-port="3" to-layer="117" to-port="0" />
		<edge from-layer="117" from-port="1" to-layer="119" to-port="0" />
		<edge from-layer="118" from-port="0" to-layer="119" to-port="1" />
		<edge from-layer="119" from-port="2" to-layer="121" to-port="0" />
		<edge from-layer="120" from-port="0" to-layer="121" to-port="1" />
		<edge from-layer="121" from-port="2" to-layer="122" to-port="1" />
		<edge from-layer="122" from-port="2" to-layer="124" to-port="0" />
		<edge from-layer="123" from-port="0" to-layer="124" to-port="1" />
		<edge from-layer="124" from-port="2" to-layer="126" to-port="0" />
		<edge from-layer="125" from-port="0" to-layer="126" to-port="1" />
		<edge from-layer="126" from-port="2" to-layer="129" to-port="0" />
		<edge from-layer="126" from-port="2" to-layer="143" to-port="0" />
		<edge from-layer="127" from-port="0" to-layer="129" to-port="1" />
		<edge from-layer="128" from-port="0" to-layer="129" to-port="2" />
		<edge from-layer="129" from-port="3" to-layer="130" to-port="0" />
		<edge from-layer="130" from-port="1" 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="133" from-port="0" to-layer="134" to-port="1" />
		<edge from-layer="134" from-port="2" to-layer="137" to-port="0" />
		<edge from-layer="135" from-port="0" to-layer="137" to-port="1" />
		<edge from-layer="136" from-port="0" to-layer="137" to-port="2" />
		<edge from-layer="137" from-port="3" to-layer="138" to-port="0" />
		<edge from-layer="138" from-port="1" to-layer="140" to-port="0" />
		<edge from-layer="139" from-port="0" to-layer="140" to-port="1" />
		<edge from-layer="140" from-port="2" to-layer="142" to-port="0" />
		<edge from-layer="141" from-port="0" to-layer="142" to-port="1" />
		<edge from-layer="142" from-port="2" to-layer="143" to-port="1" />
		<edge from-layer="143" from-port="2" to-layer="160" to-port="0" />
		<edge from-layer="143" from-port="2" to-layer="146" to-port="0" />
		<edge from-layer="144" from-port="0" to-layer="146" to-port="1" />
		<edge from-layer="145" from-port="0" to-layer="146" to-port="2" />
		<edge from-layer="146" from-port="3" 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="151" to-port="0" />
		<edge from-layer="150" from-port="0" to-layer="151" to-port="1" />
		<edge from-layer="151" from-port="2" to-layer="154" to-port="0" />
		<edge from-layer="152" from-port="0" to-layer="154" to-port="1" />
		<edge from-layer="153" from-port="0" to-layer="154" to-port="2" />
		<edge from-layer="154" from-port="3" to-layer="155" to-port="0" />
		<edge from-layer="155" from-port="1" to-layer="157" to-port="0" />
		<edge from-layer="156" from-port="0" to-layer="157" to-port="1" />
		<edge from-layer="157" from-port="2" to-layer="159" to-port="0" />
		<edge from-layer="158" from-port="0" to-layer="159" to-port="1" />
		<edge from-layer="159" from-port="2" to-layer="160" to-port="1" />
		<edge from-layer="160" from-port="2" to-layer="177" to-port="0" />
		<edge from-layer="160" from-port="2" to-layer="163" to-port="0" />
		<edge from-layer="161" from-port="0" to-layer="163" to-port="1" />
		<edge from-layer="162" from-port="0" to-layer="163" to-port="2" />
		<edge from-layer="163" from-port="3" to-layer="164" to-port="0" />
		<edge from-layer="164" from-port="1" 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="171" to-port="0" />
		<edge from-layer="169" from-port="0" to-layer="171" to-port="1" />
		<edge from-layer="170" from-port="0" to-layer="171" to-port="2" />
		<edge from-layer="171" from-port="3" to-layer="172" to-port="0" />
		<edge from-layer="172" from-port="1" to-layer="174" to-port="0" />
		<edge from-layer="173" from-port="0" to-layer="174" to-port="1" />
		<edge from-layer="174" from-port="2" to-layer="176" to-port="0" />
		<edge from-layer="175" from-port="0" to-layer="176" to-port="1" />
		<edge from-layer="176" from-port="2" to-layer="177" to-port="1" />
		<edge from-layer="177" from-port="2" to-layer="179" to-port="0" />
		<edge from-layer="177" from-port="2" to-layer="232" to-port="1" />
		<edge from-layer="177" from-port="2" to-layer="222" 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="181" to-port="0" />
		<edge from-layer="180" from-port="0" to-layer="181" to-port="1" />
		<edge from-layer="181" from-port="2" to-layer="183" to-port="0" />
		<edge from-layer="182" from-port="0" to-layer="183" to-port="1" />
		<edge from-layer="183" from-port="2" to-layer="186" to-port="0" />
		<edge from-layer="184" from-port="0" to-layer="186" to-port="1" />
		<edge from-layer="185" from-port="0" to-layer="186" to-port="2" />
		<edge from-layer="186" from-port="3" to-layer="204" to-port="0" />
		<edge from-layer="186" from-port="3" to-layer="188" to-port="0" />
		<edge from-layer="186" from-port="3" to-layer="196" to-port="0" />
		<edge from-layer="187" from-port="0" to-layer="188" to-port="1" />
		<edge from-layer="188" from-port="2" to-layer="190" to-port="0" />
		<edge from-layer="189" from-port="0" to-layer="190" to-port="1" />
		<edge from-layer="190" from-port="2" to-layer="192" to-port="0" />
		<edge from-layer="191" from-port="0" to-layer="192" to-port="1" />
		<edge from-layer="192" from-port="2" to-layer="194" to-port="0" />
		<edge from-layer="193" from-port="0" to-layer="194" to-port="1" />
		<edge from-layer="194" from-port="2" to-layer="211" to-port="0" />
		<edge from-layer="195" from-port="0" 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="200" to-port="0" />
		<edge from-layer="199" from-port="0" to-layer="200" to-port="1" />
		<edge from-layer="200" from-port="2" to-layer="202" to-port="0" />
		<edge from-layer="201" from-port="0" to-layer="202" to-port="1" />
		<edge from-layer="202" from-port="2" to-layer="211" to-port="1" />
		<edge from-layer="203" from-port="0" to-layer="204" to-port="1" />
		<edge from-layer="204" from-port="2" to-layer="206" to-port="0" />
		<edge from-layer="205" from-port="0" to-layer="206" to-port="1" />
		<edge from-layer="206" from-port="2" to-layer="208" to-port="0" />
		<edge from-layer="207" from-port="0" 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="2" />
		<edge from-layer="211" from-port="3" to-layer="213" to-port="0" />
		<edge from-layer="212" from-port="0" to-layer="213" to-port="1" />
		<edge from-layer="213" from-port="2" to-layer="215" to-port="0" />
		<edge from-layer="214" from-port="0" to-layer="215" to-port="1" />
		<edge from-layer="215" from-port="2" to-layer="217" to-port="0" />
		<edge from-layer="216" from-port="0" 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="231" to-port="0" />
		<edge from-layer="222" from-port="1" to-layer="225" to-port="0" />
		<edge from-layer="222" from-port="1" to-layer="229" to-port="0" />
		<edge from-layer="223" from-port="0" to-layer="225" to-port="1" />
		<edge from-layer="224" from-port="0" to-layer="225" to-port="2" />
		<edge from-layer="225" from-port="3" to-layer="230" to-port="0" />
		<edge from-layer="226" from-port="0" to-layer="230" to-port="1" />
		<edge from-layer="227" from-port="0" to-layer="229" to-port="1" />
		<edge from-layer="228" from-port="0" to-layer="229" to-port="2" />
		<edge from-layer="229" from-port="3" to-layer="230" to-port="2" />
		<edge from-layer="230" from-port="3" to-layer="231" to-port="1" />
		<edge from-layer="231" from-port="2" to-layer="232" to-port="0" />
		<edge from-layer="232" from-port="2" to-layer="235" to-port="0" />
		<edge from-layer="232" from-port="2" to-layer="249" to-port="0" />
		<edge from-layer="233" from-port="0" to-layer="235" to-port="1" />
		<edge from-layer="234" from-port="0" to-layer="235" to-port="2" />
		<edge from-layer="235" from-port="3" to-layer="236" to-port="0" />
		<edge from-layer="236" from-port="1" to-layer="238" to-port="0" />
		<edge from-layer="237" from-port="0" to-layer="238" to-port="1" />
		<edge from-layer="238" from-port="2" to-layer="240" to-port="0" />
		<edge from-layer="239" from-port="0" to-layer="240" to-port="1" />
		<edge from-layer="240" from-port="2" to-layer="243" to-port="0" />
		<edge from-layer="241" from-port="0" to-layer="243" to-port="1" />
		<edge from-layer="242" from-port="0" to-layer="243" to-port="2" />
		<edge from-layer="243" from-port="3" to-layer="244" to-port="0" />
		<edge from-layer="244" from-port="1" to-layer="246" to-port="0" />
		<edge from-layer="245" from-port="0" to-layer="246" to-port="1" />
		<edge from-layer="246" from-port="2" to-layer="248" to-port="0" />
		<edge from-layer="247" from-port="0" to-layer="248" to-port="1" />
		<edge from-layer="248" from-port="2" to-layer="249" to-port="1" />
		<edge from-layer="249" from-port="2" to-layer="252" to-port="0" />
		<edge from-layer="250" from-port="0" to-layer="252" to-port="1" />
		<edge from-layer="251" from-port="0" to-layer="252" to-port="2" />
		<edge from-layer="252" from-port="3" to-layer="253" to-port="0" />
		<edge from-layer="253" from-port="1" to-layer="255" to-port="0" />
		<edge from-layer="254" from-port="0" to-layer="255" to-port="1" />
		<edge from-layer="255" from-port="2" to-layer="257" to-port="0" />
		<edge from-layer="256" from-port="0" to-layer="257" to-port="1" />
		<edge from-layer="257" from-port="2" to-layer="259" to-port="0" />
		<edge from-layer="258" from-port="0" to-layer="259" to-port="1" />
		<edge from-layer="259" from-port="2" to-layer="261" to-port="0" />
		<edge from-layer="260" from-port="0" to-layer="261" to-port="1" />
		<edge from-layer="261" from-port="2" to-layer="262" to-port="0" />
	</edges>
	<rt_info>
		<Runtime_version value="2024.4.0-16579-c3152d32c9c-releases/2024/4" />
		<conversion_parameters>
			<framework value="pytorch" />
			<is_python_object value="True" />
		</conversion_parameters>
		<optimum>
			<diffusers_version value="1.23.1" />
			<optimum_intel_version value="1.20.0.dev0+f7b5b54" />
			<optimum_version value="1.23.1" />
			<pytorch_version value="2.5.0" />
			<transformers_version value="4.42.4" />
		</optimum>
	</rt_info>
</net>