vae_decoder/openvino_model.xml

<?xml version="1.0"?>
<net name="Model9" version="11">
	<layers>
		<layer id="0" name="latent_sample" type="Parameter" version="opset1">
			<data shape="?,4,?,?" element_type="f32" />
			<output>
				<port id="0" precision="FP32" names="latent_sample">
					<dim>-1</dim>
					<dim>4</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="1" name="self.post_quant_conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="4, 4, 1, 1" offset="0" size="64" />
			<output>
				<port id="0" precision="FP32" names="self.post_quant_conv.weight">
					<dim>4</dim>
					<dim>4</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="2" name="__module.post_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>4</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>4</dim>
					<dim>4</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>4</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="3" name="__module.post_quant_conv/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 4, 1, 1" offset="64" size="16" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>4</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="4" name="__module.post_quant_conv/aten::_convolution/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>4</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>4</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="17">
					<dim>-1</dim>
					<dim>4</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="5" name="self.decoder.conv_in.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512, 4, 3, 3" offset="80" size="73728" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.conv_in.weight">
					<dim>512</dim>
					<dim>4</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="6" name="__module.decoder.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>4</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>512</dim>
					<dim>4</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="7" name="__module.decoder.conv_in/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 512, 1, 1" offset="73808" 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="8" name="__module.decoder.conv_in/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="57,input.1">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="9" name="self.decoder.mid_block.resnets.0.norm1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="75856" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.mid_block.resnets.0.norm1.weight">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="10" name="self.decoder.mid_block.resnets.0.norm1.bias" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="77904" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.mid_block.resnets.0.norm1.bias">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="11" name="__module.decoder.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="74,input.3">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="12" 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>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="75">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="13" name="self.decoder.mid_block.resnets.0.conv1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512, 512, 3, 3" offset="79952" size="9437184" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.mid_block.resnets.0.conv1.weight">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="14" name="__module.decoder.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="15" name="__module.decoder.mid_block.resnets.0.conv1/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 512, 1, 1" offset="9517136" 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="16" name="__module.decoder.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="82,input.5">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="17" name="self.decoder.mid_block.resnets.0.norm2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="9519184" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.mid_block.resnets.0.norm2.weight">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="18" name="self.decoder.mid_block.resnets.0.norm2.bias" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="9521232" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.mid_block.resnets.0.norm2.bias">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="19" name="__module.decoder.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="85,input.7">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="20" 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>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="86,input.9">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="21" name="self.decoder.mid_block.resnets.0.conv2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512, 512, 3, 3" offset="9523280" size="9437184" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.mid_block.resnets.0.conv2.weight">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="22" name="__module.decoder.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="23" name="__module.decoder.mid_block.resnets.0.conv2/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 512, 1, 1" offset="18960464" 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="24" name="__module.decoder.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="94,hidden_states.1">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="25" name="__module.decoder.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="95,96,hidden_states.3">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="26" name="Constant_239741" type="Const" version="opset1">
			<data element_type="i64" shape="3" offset="18962512" size="24" />
			<output>
				<port id="0" precision="I64">
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="27" name="__module.decoder.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="112">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="28" name="__module.decoder.mid_block.attentions.0/aten::transpose/ScatterElementsUpdate" type="Const" version="opset1">
			<data element_type="i32" shape="3" offset="18962536" size="12" />
			<output>
				<port id="0" precision="I32">
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="29" name="__module.decoder.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="113,hidden_states.5">
					<dim>-1</dim>
					<dim>-1</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="30" name="__module.decoder.mid_block.attentions.0/aten::transpose/ScatterElementsUpdate_1" type="Const" version="opset1">
			<data element_type="i32" shape="3" offset="18962536" size="12" />
			<output>
				<port id="0" precision="I32">
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="31" name="__module.decoder.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="115,input.11">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="32" name="self.decoder.mid_block.attentions.0.group_norm.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="18962548" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.mid_block.attentions.0.group_norm.weight">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="33" name="self.decoder.mid_block.attentions.0.group_norm.bias" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="18964596" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.mid_block.attentions.0.group_norm.bias">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="34" name="__module.decoder.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="118">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="35" name="self.decoder.mid_block.attentions.0.to_q.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512, 512" offset="18966644" size="1048576" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.mid_block.attentions.0.to_q.weight">
					<dim>512</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="36" name="__module.decoder.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="37" name="Constant_239622" type="Const" version="opset1">
			<data element_type="f32" shape="1, 1, 512" offset="20015220" size="2048" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>1</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="38" name="__module.decoder.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="122,query">
					<dim>-1</dim>
					<dim>-1</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="39" name="Constant_239742" type="Const" version="opset1">
			<data element_type="i64" shape="4" offset="20017268" size="32" />
			<output>
				<port id="0" precision="I64">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="40" name="__module.decoder.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="136">
					<dim>-1</dim>
					<dim>-1</dim>
					<dim>1</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="41" name="Constant_239488" type="Const" version="opset1">
			<data element_type="i64" shape="4" offset="20017300" size="32" />
			<output>
				<port id="0" precision="I64">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="42" name="__module.decoder.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="137">
					<dim>-1</dim>
					<dim>1</dim>
					<dim>-1</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="43" name="self.decoder.mid_block.attentions.0.to_k.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512, 512" offset="20017332" size="1048576" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.mid_block.attentions.0.to_k.weight">
					<dim>512</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="44" name="__module.decoder.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="45" name="Constant_239623" type="Const" version="opset1">
			<data element_type="f32" shape="1, 1, 512" offset="21065908" size="2048" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>1</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="46" name="__module.decoder.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="125,key">
					<dim>-1</dim>
					<dim>-1</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="47" name="Constant_239743" type="Const" version="opset1">
			<data element_type="i64" shape="4" offset="20017268" size="32" />
			<output>
				<port id="0" precision="I64">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="48" name="__module.decoder.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="139">
					<dim>-1</dim>
					<dim>-1</dim>
					<dim>1</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="49" name="Constant_239490" type="Const" version="opset1">
			<data element_type="i64" shape="4" offset="20017300" size="32" />
			<output>
				<port id="0" precision="I64">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="50" name="__module.decoder.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="140">
					<dim>-1</dim>
					<dim>1</dim>
					<dim>-1</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="51" name="self.decoder.mid_block.attentions.0.to_v.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512, 512" offset="21067956" size="1048576" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.mid_block.attentions.0.to_v.weight">
					<dim>512</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="52" name="__module.decoder.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="53" name="Constant_239624" type="Const" version="opset1">
			<data element_type="f32" shape="1, 1, 512" offset="22116532" size="2048" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>1</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="54" name="__module.decoder.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="128,value">
					<dim>-1</dim>
					<dim>-1</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="55" name="Constant_239744" type="Const" version="opset1">
			<data element_type="i64" shape="4" offset="20017268" size="32" />
			<output>
				<port id="0" precision="I64">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="56" name="__module.decoder.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="142">
					<dim>-1</dim>
					<dim>-1</dim>
					<dim>1</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="57" name="Constant_239494" type="Const" version="opset1">
			<data element_type="i64" shape="4" offset="20017300" size="32" />
			<output>
				<port id="0" precision="I64">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="58" name="__module.decoder.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="143">
					<dim>-1</dim>
					<dim>1</dim>
					<dim>-1</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="59" name="__module.decoder.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="144,hidden_states.7">
					<dim>-1</dim>
					<dim>1</dim>
					<dim>-1</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="60" name="Constant_239496" type="Const" version="opset1">
			<data element_type="i64" shape="4" offset="22118580" size="32" />
			<output>
				<port id="0" precision="I64">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="61" name="__module.decoder.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="145">
					<dim>-1</dim>
					<dim>-1</dim>
					<dim>1</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="62" name="Constant_239745" type="Const" version="opset1">
			<data element_type="i64" shape="3" offset="22118612" size="24" />
			<output>
				<port id="0" precision="I64">
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="63" name="__module.decoder.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="149,150,hidden_states.9">
					<dim>-1</dim>
					<dim>-1</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="64" name="self.decoder.mid_block.attentions.0.to_out.0.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512, 512" offset="22118636" size="1048576" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.mid_block.attentions.0.to_out.0.weight">
					<dim>512</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="65" name="__module.decoder.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="66" name="Constant_239625" type="Const" version="opset1">
			<data element_type="f32" shape="1, 1, 512" offset="23167212" size="2048" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>1</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="67" name="__module.decoder.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="153,input.13">
					<dim>-1</dim>
					<dim>-1</dim>
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="68" name="__module.decoder.mid_block.attentions.0/aten::transpose/ScatterElementsUpdate_7" type="Const" version="opset1">
			<data element_type="i32" shape="3" offset="18962536" size="12" />
			<output>
				<port id="0" precision="I32">
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="69" name="__module.decoder.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="155">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="70" name="ShapeOf_239720" 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="71" name="Constant_239721" type="Const" version="opset1">
			<data element_type="i64" shape="1" offset="23169260" size="8" />
			<output>
				<port id="0" precision="I64">
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="72" name="Constant_239722" type="Const" version="opset1">
			<data element_type="i64" shape="" offset="23169260" size="8" />
			<output>
				<port id="0" precision="I64" />
			</output>
		</layer>
		<layer id="73" name="Gather_239723" 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="103,114">
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="74" name="__module.decoder.mid_block.attentions.0/prim::ListConstruct/Reshape_0" type="Const" version="opset1">
			<data element_type="i64" shape="1" offset="23169268" size="8" />
			<output>
				<port id="0" precision="I64">
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="75" name="Constant_239848" type="Const" version="opset1">
			<data element_type="i64" shape="2" offset="23169276" size="16" />
			<output>
				<port id="0" precision="I64">
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="76" name="Constant_239849" type="Const" version="opset1">
			<data element_type="i64" shape="" offset="23169260" size="8" />
			<output>
				<port id="0" precision="I64" />
			</output>
		</layer>
		<layer id="77" name="Gather_239850" 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="78" name="__module.decoder.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="156">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="79" name="__module.decoder.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="157,hidden_states.13">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="80" name="__module.decoder.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="158,159,hidden_states.15,input.15">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="81" name="self.decoder.mid_block.resnets.1.norm1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="23169292" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.mid_block.resnets.1.norm1.weight">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="82" name="self.decoder.mid_block.resnets.1.norm1.bias" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="23171340" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.mid_block.resnets.1.norm1.bias">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="83" name="__module.decoder.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="168,input.17">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="84" 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>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="169">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="85" name="self.decoder.mid_block.resnets.1.conv1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512, 512, 3, 3" offset="23173388" size="9437184" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.mid_block.resnets.1.conv1.weight">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="86" name="__module.decoder.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="87" name="__module.decoder.mid_block.resnets.1.conv1/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 512, 1, 1" offset="32610572" 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.decoder.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="176,input.19">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="89" name="self.decoder.mid_block.resnets.1.norm2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="32612620" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.mid_block.resnets.1.norm2.weight">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="90" name="self.decoder.mid_block.resnets.1.norm2.bias" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="32614668" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.mid_block.resnets.1.norm2.bias">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="91" name="__module.decoder.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="179,input.21">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="92" 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>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="180,input.23">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="93" name="self.decoder.mid_block.resnets.1.conv2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512, 512, 3, 3" offset="32616716" size="9437184" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.mid_block.resnets.1.conv2.weight">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="94" name="__module.decoder.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="95" name="__module.decoder.mid_block.resnets.1.conv2/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 512, 1, 1" offset="42053900" 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.decoder.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="188,hidden_states.17">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="97" name="__module.decoder.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="189,190,191,input.25,sample">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="98" name="self.decoder.up_blocks.0.resnets.0.norm1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="42055948" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.0.resnets.0.norm1.weight">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="99" name="self.decoder.up_blocks.0.resnets.0.norm1.bias" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="42057996" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.0.resnets.0.norm1.bias">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="100" name="__module.decoder.up_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>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="207,input.27">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="101" 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>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="208">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="102" name="self.decoder.up_blocks.0.resnets.0.conv1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512, 512, 3, 3" offset="42060044" size="9437184" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.0.resnets.0.conv1.weight">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="103" name="__module.decoder.up_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>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="104" name="__module.decoder.up_blocks.0.resnets.0.conv1/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 512, 1, 1" offset="51497228" 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="105" name="__module.decoder.up_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>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="215,input.29">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="106" name="self.decoder.up_blocks.0.resnets.0.norm2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="51499276" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.0.resnets.0.norm2.weight">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="107" name="self.decoder.up_blocks.0.resnets.0.norm2.bias" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="51501324" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.0.resnets.0.norm2.bias">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="108" name="__module.decoder.up_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>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="218,input.31">
					<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_5" 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="219,input.33">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="110" name="self.decoder.up_blocks.0.resnets.0.conv2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512, 512, 3, 3" offset="51503372" size="9437184" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.0.resnets.0.conv2.weight">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="111" name="__module.decoder.up_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>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.decoder.up_blocks.0.resnets.0.conv2/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 512, 1, 1" offset="60940556" 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.decoder.up_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>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="227,hidden_states.19">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="114" name="__module.decoder.up_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>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="228,229,input.35">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="115" name="self.decoder.up_blocks.0.resnets.1.norm1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="60942604" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.0.resnets.1.norm1.weight">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="116" name="self.decoder.up_blocks.0.resnets.1.norm1.bias" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="60944652" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.0.resnets.1.norm1.bias">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="117" name="__module.decoder.up_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>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="237,input.37">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="118" 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>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="238">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="119" name="self.decoder.up_blocks.0.resnets.1.conv1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512, 512, 3, 3" offset="60946700" size="9437184" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.0.resnets.1.conv1.weight">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="120" name="__module.decoder.up_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>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="121" name="__module.decoder.up_blocks.0.resnets.1.conv1/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 512, 1, 1" offset="70383884" 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="122" name="__module.decoder.up_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>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="245,input.39">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="123" name="self.decoder.up_blocks.0.resnets.1.norm2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="70385932" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.0.resnets.1.norm2.weight">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="124" name="self.decoder.up_blocks.0.resnets.1.norm2.bias" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="70387980" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.0.resnets.1.norm2.bias">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="125" name="__module.decoder.up_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>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="248,input.41">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="126" 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>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="249,input.43">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="127" name="self.decoder.up_blocks.0.resnets.1.conv2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512, 512, 3, 3" offset="70390028" size="9437184" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.0.resnets.1.conv2.weight">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="128" name="__module.decoder.up_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>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="129" name="__module.decoder.up_blocks.0.resnets.1.conv2/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 512, 1, 1" offset="79827212" 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="130" name="__module.decoder.up_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>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="257,hidden_states.21">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="131" name="__module.decoder.up_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>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="258,259,input.45">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="132" name="self.decoder.up_blocks.0.resnets.2.norm1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="79829260" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.0.resnets.2.norm1.weight">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="133" name="self.decoder.up_blocks.0.resnets.2.norm1.bias" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="79831308" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.0.resnets.2.norm1.bias">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="134" name="__module.decoder.up_blocks.0.resnets.2.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="267,input.47">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="135" 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>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="268">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="136" name="self.decoder.up_blocks.0.resnets.2.conv1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512, 512, 3, 3" offset="79833356" size="9437184" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.0.resnets.2.conv1.weight">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="137" name="__module.decoder.up_blocks.0.resnets.2.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="138" name="__module.decoder.up_blocks.0.resnets.2.conv1/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 512, 1, 1" offset="89270540" 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="139" name="__module.decoder.up_blocks.0.resnets.2.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="275,input.49">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="140" name="self.decoder.up_blocks.0.resnets.2.norm2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="89272588" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.0.resnets.2.norm2.weight">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="141" name="self.decoder.up_blocks.0.resnets.2.norm2.bias" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="89274636" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.0.resnets.2.norm2.bias">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="142" name="__module.decoder.up_blocks.0.resnets.2.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="278,input.51">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="143" 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="279,input.53">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="144" name="self.decoder.up_blocks.0.resnets.2.conv2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512, 512, 3, 3" offset="89276684" size="9437184" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.0.resnets.2.conv2.weight">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="145" name="__module.decoder.up_blocks.0.resnets.2.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="146" name="__module.decoder.up_blocks.0.resnets.2.conv2/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 512, 1, 1" offset="98713868" 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="147" name="__module.decoder.up_blocks.0.resnets.2.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="287,hidden_states.23">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="148" name="__module.decoder.up_blocks.0.resnets.2/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="288,289,hidden_states.25">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="149" name="__module.decoder.up_blocks.0.upsamplers.0/aten::upsample_nearest2d/Multiply" type="Const" version="opset1">
			<data element_type="f32" shape="2" offset="98715916" size="8" />
			<output>
				<port id="0" precision="FP32">
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="150" name="Constant_231203" type="Const" version="opset1">
			<data element_type="i32" shape="2" offset="98715924" size="8" />
			<output>
				<port id="0" precision="I32">
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="151" name="__module.decoder.up_blocks.0.upsamplers.0/aten::upsample_nearest2d/Interpolate" type="Interpolate" version="opset11">
			<data mode="nearest" shape_calculation_mode="scales" coordinate_transformation_mode="asymmetric" nearest_mode="floor" antialias="false" pads_begin="0, 0, 0, 0" pads_end="0, 0, 0, 0" cube_coeff="-0.75" />
			<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>2</dim>
				</port>
				<port id="2" precision="I32">
					<dim>2</dim>
				</port>
			</input>
			<output>
				<port id="3" precision="FP32" names="292">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="152" name="self.decoder.up_blocks.0.upsamplers.0.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512, 512, 3, 3" offset="98715932" size="9437184" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.0.upsamplers.0.conv.weight">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="153" name="__module.decoder.up_blocks.0.upsamplers.0.conv/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="154" name="__module.decoder.up_blocks.0.upsamplers.0.conv/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 512, 1, 1" offset="108153116" 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="155" name="__module.decoder.up_blocks.0.upsamplers.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="299,input.55">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="156" name="self.decoder.up_blocks.1.resnets.0.norm1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="108155164" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.1.resnets.0.norm1.weight">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="157" name="self.decoder.up_blocks.1.resnets.0.norm1.bias" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="108157212" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.1.resnets.0.norm1.bias">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="158" name="__module.decoder.up_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>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="315,input.57">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="159" 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="316">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="160" name="self.decoder.up_blocks.1.resnets.0.conv1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512, 512, 3, 3" offset="108159260" size="9437184" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.1.resnets.0.conv1.weight">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="161" name="__module.decoder.up_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>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="162" name="__module.decoder.up_blocks.1.resnets.0.conv1/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 512, 1, 1" offset="117596444" 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="163" name="__module.decoder.up_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>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,input.59">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="164" name="self.decoder.up_blocks.1.resnets.0.norm2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="117598492" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.1.resnets.0.norm2.weight">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="165" name="self.decoder.up_blocks.1.resnets.0.norm2.bias" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="117600540" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.1.resnets.0.norm2.bias">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="166" name="__module.decoder.up_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>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="326,input.61">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="167" 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="327,input.63">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="168" name="self.decoder.up_blocks.1.resnets.0.conv2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512, 512, 3, 3" offset="117602588" size="9437184" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.1.resnets.0.conv2.weight">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="169" name="__module.decoder.up_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>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="170" name="__module.decoder.up_blocks.1.resnets.0.conv2/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 512, 1, 1" offset="127039772" 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="171" name="__module.decoder.up_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>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="335,hidden_states.27">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="172" name="__module.decoder.up_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>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="336,337,input.65">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="173" name="self.decoder.up_blocks.1.resnets.1.norm1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="127041820" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.1.resnets.1.norm1.weight">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="174" name="self.decoder.up_blocks.1.resnets.1.norm1.bias" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="127043868" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.1.resnets.1.norm1.bias">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="175" name="__module.decoder.up_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>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="345,input.67">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="176" 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="346">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="177" name="self.decoder.up_blocks.1.resnets.1.conv1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512, 512, 3, 3" offset="127045916" size="9437184" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.1.resnets.1.conv1.weight">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="178" name="__module.decoder.up_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>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="179" name="__module.decoder.up_blocks.1.resnets.1.conv1/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 512, 1, 1" offset="136483100" 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="180" name="__module.decoder.up_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>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,input.69">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="181" name="self.decoder.up_blocks.1.resnets.1.norm2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="136485148" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.1.resnets.1.norm2.weight">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="182" name="self.decoder.up_blocks.1.resnets.1.norm2.bias" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="136487196" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.1.resnets.1.norm2.bias">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="183" name="__module.decoder.up_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>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="356,input.71">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="184" 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="357,input.73">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="185" name="self.decoder.up_blocks.1.resnets.1.conv2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512, 512, 3, 3" offset="136489244" size="9437184" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.1.resnets.1.conv2.weight">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="186" name="__module.decoder.up_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>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="187" name="__module.decoder.up_blocks.1.resnets.1.conv2/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 512, 1, 1" offset="145926428" 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="188" name="__module.decoder.up_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>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="365,hidden_states.29">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="189" name="__module.decoder.up_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>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="366,367,input.75">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="190" name="self.decoder.up_blocks.1.resnets.2.norm1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="145928476" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.1.resnets.2.norm1.weight">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="191" name="self.decoder.up_blocks.1.resnets.2.norm1.bias" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="145930524" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.1.resnets.2.norm1.bias">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="192" name="__module.decoder.up_blocks.1.resnets.2.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="375,input.77">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="193" 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="376">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="194" name="self.decoder.up_blocks.1.resnets.2.conv1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512, 512, 3, 3" offset="145932572" size="9437184" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.1.resnets.2.conv1.weight">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="195" name="__module.decoder.up_blocks.1.resnets.2.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="196" name="__module.decoder.up_blocks.1.resnets.2.conv1/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 512, 1, 1" offset="155369756" 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="197" name="__module.decoder.up_blocks.1.resnets.2.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="383,input.79">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="198" name="self.decoder.up_blocks.1.resnets.2.norm2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="155371804" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.1.resnets.2.norm2.weight">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="199" name="self.decoder.up_blocks.1.resnets.2.norm2.bias" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="155373852" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.1.resnets.2.norm2.bias">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="200" name="__module.decoder.up_blocks.1.resnets.2.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="386,input.81">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="201" 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="387,input.83">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="202" name="self.decoder.up_blocks.1.resnets.2.conv2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512, 512, 3, 3" offset="155375900" size="9437184" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.1.resnets.2.conv2.weight">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="203" name="__module.decoder.up_blocks.1.resnets.2.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="204" name="__module.decoder.up_blocks.1.resnets.2.conv2/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 512, 1, 1" offset="164813084" 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="205" name="__module.decoder.up_blocks.1.resnets.2.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="395,hidden_states.31">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="206" name="__module.decoder.up_blocks.1.resnets.2/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="396,397,hidden_states.33">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="207" name="__module.decoder.up_blocks.1.upsamplers.0/aten::upsample_nearest2d/Multiply" type="Const" version="opset1">
			<data element_type="f32" shape="2" offset="98715916" size="8" />
			<output>
				<port id="0" precision="FP32">
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="208" name="Constant_231635" type="Const" version="opset1">
			<data element_type="i32" shape="2" offset="98715924" size="8" />
			<output>
				<port id="0" precision="I32">
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="209" name="__module.decoder.up_blocks.1.upsamplers.0/aten::upsample_nearest2d/Interpolate" type="Interpolate" version="opset11">
			<data mode="nearest" shape_calculation_mode="scales" coordinate_transformation_mode="asymmetric" nearest_mode="floor" antialias="false" pads_begin="0, 0, 0, 0" pads_end="0, 0, 0, 0" cube_coeff="-0.75" />
			<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>2</dim>
				</port>
				<port id="2" precision="I32">
					<dim>2</dim>
				</port>
			</input>
			<output>
				<port id="3" precision="FP32" names="400">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="210" name="self.decoder.up_blocks.1.upsamplers.0.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512, 512, 3, 3" offset="164815132" size="9437184" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.1.upsamplers.0.conv.weight">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="211" name="__module.decoder.up_blocks.1.upsamplers.0.conv/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="212" name="__module.decoder.up_blocks.1.upsamplers.0.conv/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 512, 1, 1" offset="174252316" 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="213" name="__module.decoder.up_blocks.1.upsamplers.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="407,input.85">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="214" name="self.decoder.up_blocks.2.resnets.0.conv_shortcut.weight" type="Const" version="opset1">
			<data element_type="f32" shape="256, 512, 1, 1" offset="174254364" size="524288" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.2.resnets.0.conv_shortcut.weight">
					<dim>256</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="215" name="__module.decoder.up_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>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>256</dim>
					<dim>512</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="216" name="__module.decoder.up_blocks.2.resnets.0.conv_shortcut/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 256, 1, 1" offset="174778652" 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="217" name="__module.decoder.up_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>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="451,input_tensor.1">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="218" name="self.decoder.up_blocks.2.resnets.0.norm1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="174779676" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.2.resnets.0.norm1.weight">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="219" name="self.decoder.up_blocks.2.resnets.0.norm1.bias" type="Const" version="opset1">
			<data element_type="f32" shape="512" offset="174781724" size="2048" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.2.resnets.0.norm1.bias">
					<dim>512</dim>
				</port>
			</output>
		</layer>
		<layer id="220" name="__module.decoder.up_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>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="424,input.87">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="221" 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="425">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="222" name="self.decoder.up_blocks.2.resnets.0.conv1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="256, 512, 3, 3" offset="174783772" size="4718592" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.2.resnets.0.conv1.weight">
					<dim>256</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="223" name="__module.decoder.up_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>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>256</dim>
					<dim>512</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="224" name="__module.decoder.up_blocks.2.resnets.0.conv1/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 256, 1, 1" offset="179502364" 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="225" name="__module.decoder.up_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>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="432,input.89">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="226" name="self.decoder.up_blocks.2.resnets.0.norm2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="256" offset="179503388" size="1024" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.2.resnets.0.norm2.weight">
					<dim>256</dim>
				</port>
			</output>
		</layer>
		<layer id="227" name="self.decoder.up_blocks.2.resnets.0.norm2.bias" type="Const" version="opset1">
			<data element_type="f32" shape="256" offset="179504412" size="1024" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.2.resnets.0.norm2.bias">
					<dim>256</dim>
				</port>
			</output>
		</layer>
		<layer id="228" name="__module.decoder.up_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>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="435,input.91">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="229" 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>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="436,input.93">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="230" name="self.decoder.up_blocks.2.resnets.0.conv2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="256, 256, 3, 3" offset="179505436" size="2359296" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.2.resnets.0.conv2.weight">
					<dim>256</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="231" name="__module.decoder.up_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>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="232" name="__module.decoder.up_blocks.2.resnets.0.conv2/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 256, 1, 1" offset="181864732" 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="233" name="__module.decoder.up_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>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="444,hidden_states.35">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="234" name="__module.decoder.up_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>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="452,453,input.95">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="235" name="self.decoder.up_blocks.2.resnets.1.norm1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="256" offset="181865756" size="1024" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.2.resnets.1.norm1.weight">
					<dim>256</dim>
				</port>
			</output>
		</layer>
		<layer id="236" name="self.decoder.up_blocks.2.resnets.1.norm1.bias" type="Const" version="opset1">
			<data element_type="f32" shape="256" offset="181866780" size="1024" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.2.resnets.1.norm1.bias">
					<dim>256</dim>
				</port>
			</output>
		</layer>
		<layer id="237" name="__module.decoder.up_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>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="461,input.97">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="238" 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>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="462">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="239" name="self.decoder.up_blocks.2.resnets.1.conv1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="256, 256, 3, 3" offset="181867804" size="2359296" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.2.resnets.1.conv1.weight">
					<dim>256</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="240" name="__module.decoder.up_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>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="241" name="__module.decoder.up_blocks.2.resnets.1.conv1/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 256, 1, 1" offset="184227100" 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="242" name="__module.decoder.up_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>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="469,input.99">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="243" name="self.decoder.up_blocks.2.resnets.1.norm2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="256" offset="184228124" size="1024" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.2.resnets.1.norm2.weight">
					<dim>256</dim>
				</port>
			</output>
		</layer>
		<layer id="244" name="self.decoder.up_blocks.2.resnets.1.norm2.bias" type="Const" version="opset1">
			<data element_type="f32" shape="256" offset="184229148" size="1024" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.2.resnets.1.norm2.bias">
					<dim>256</dim>
				</port>
			</output>
		</layer>
		<layer id="245" name="__module.decoder.up_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>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="472,input.101">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="246" 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>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="473,input.103">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="247" name="self.decoder.up_blocks.2.resnets.1.conv2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="256, 256, 3, 3" offset="184230172" size="2359296" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.2.resnets.1.conv2.weight">
					<dim>256</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="248" name="__module.decoder.up_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>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="249" name="__module.decoder.up_blocks.2.resnets.1.conv2/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 256, 1, 1" offset="186589468" 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="250" name="__module.decoder.up_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>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="481,hidden_states.37">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="251" name="__module.decoder.up_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>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="482,483,input.105">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="252" name="self.decoder.up_blocks.2.resnets.2.norm1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="256" offset="186590492" size="1024" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.2.resnets.2.norm1.weight">
					<dim>256</dim>
				</port>
			</output>
		</layer>
		<layer id="253" name="self.decoder.up_blocks.2.resnets.2.norm1.bias" type="Const" version="opset1">
			<data element_type="f32" shape="256" offset="186591516" size="1024" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.2.resnets.2.norm1.bias">
					<dim>256</dim>
				</port>
			</output>
		</layer>
		<layer id="254" name="__module.decoder.up_blocks.2.resnets.2.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="491,input.107">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="255" name="__module.decoder.mid_block.resnets.1.nonlinearity/aten::silu/Swish_20" 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="492">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="256" name="self.decoder.up_blocks.2.resnets.2.conv1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="256, 256, 3, 3" offset="186592540" size="2359296" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.2.resnets.2.conv1.weight">
					<dim>256</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="257" name="__module.decoder.up_blocks.2.resnets.2.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="258" name="__module.decoder.up_blocks.2.resnets.2.conv1/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 256, 1, 1" offset="188951836" 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="259" name="__module.decoder.up_blocks.2.resnets.2.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="499,input.109">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="260" name="self.decoder.up_blocks.2.resnets.2.norm2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="256" offset="188952860" size="1024" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.2.resnets.2.norm2.weight">
					<dim>256</dim>
				</port>
			</output>
		</layer>
		<layer id="261" name="self.decoder.up_blocks.2.resnets.2.norm2.bias" type="Const" version="opset1">
			<data element_type="f32" shape="256" offset="188953884" size="1024" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.2.resnets.2.norm2.bias">
					<dim>256</dim>
				</port>
			</output>
		</layer>
		<layer id="262" name="__module.decoder.up_blocks.2.resnets.2.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="502,input.111">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="263" name="__module.decoder.mid_block.resnets.1.nonlinearity/aten::silu/Swish_21" 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="503,input.113">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="264" name="self.decoder.up_blocks.2.resnets.2.conv2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="256, 256, 3, 3" offset="188954908" size="2359296" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.2.resnets.2.conv2.weight">
					<dim>256</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="265" name="__module.decoder.up_blocks.2.resnets.2.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="266" name="__module.decoder.up_blocks.2.resnets.2.conv2/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 256, 1, 1" offset="191314204" 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="267" name="__module.decoder.up_blocks.2.resnets.2.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="511,hidden_states.39">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="268" name="__module.decoder.up_blocks.2.resnets.2/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="512,513,hidden_states.41">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="269" name="__module.decoder.up_blocks.2.upsamplers.0/aten::upsample_nearest2d/Multiply" type="Const" version="opset1">
			<data element_type="f32" shape="2" offset="98715916" size="8" />
			<output>
				<port id="0" precision="FP32">
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="270" name="Constant_232116" type="Const" version="opset1">
			<data element_type="i32" shape="2" offset="98715924" size="8" />
			<output>
				<port id="0" precision="I32">
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="271" name="__module.decoder.up_blocks.2.upsamplers.0/aten::upsample_nearest2d/Interpolate" type="Interpolate" version="opset11">
			<data mode="nearest" shape_calculation_mode="scales" coordinate_transformation_mode="asymmetric" nearest_mode="floor" antialias="false" pads_begin="0, 0, 0, 0" pads_end="0, 0, 0, 0" cube_coeff="-0.75" />
			<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>2</dim>
				</port>
				<port id="2" precision="I32">
					<dim>2</dim>
				</port>
			</input>
			<output>
				<port id="3" precision="FP32" names="516">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="272" name="self.decoder.up_blocks.2.upsamplers.0.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="256, 256, 3, 3" offset="191315228" size="2359296" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.2.upsamplers.0.conv.weight">
					<dim>256</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="273" name="__module.decoder.up_blocks.2.upsamplers.0.conv/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="274" name="__module.decoder.up_blocks.2.upsamplers.0.conv/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 256, 1, 1" offset="193674524" 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="275" name="__module.decoder.up_blocks.2.upsamplers.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="523,input.115">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="276" name="self.decoder.up_blocks.3.resnets.0.conv_shortcut.weight" type="Const" version="opset1">
			<data element_type="f32" shape="128, 256, 1, 1" offset="193675548" size="131072" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.3.resnets.0.conv_shortcut.weight">
					<dim>128</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="277" name="__module.decoder.up_blocks.3.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>128</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</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="278" name="__module.decoder.up_blocks.3.resnets.0.conv_shortcut/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 128, 1, 1" offset="193806620" 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="279" name="__module.decoder.up_blocks.3.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>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="565,input_tensor">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="280" name="self.decoder.up_blocks.3.resnets.0.norm1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="256" offset="193807132" size="1024" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.3.resnets.0.norm1.weight">
					<dim>256</dim>
				</port>
			</output>
		</layer>
		<layer id="281" name="self.decoder.up_blocks.3.resnets.0.norm1.bias" type="Const" version="opset1">
			<data element_type="f32" shape="256" offset="193808156" size="1024" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.3.resnets.0.norm1.bias">
					<dim>256</dim>
				</port>
			</output>
		</layer>
		<layer id="282" name="__module.decoder.up_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>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="538,input.117">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="283" name="__module.decoder.mid_block.resnets.1.nonlinearity/aten::silu/Swish_22" 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="539">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="284" name="self.decoder.up_blocks.3.resnets.0.conv1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="128, 256, 3, 3" offset="193809180" size="1179648" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.3.resnets.0.conv1.weight">
					<dim>128</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="285" name="__module.decoder.up_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>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>128</dim>
					<dim>256</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="286" name="__module.decoder.up_blocks.3.resnets.0.conv1/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 128, 1, 1" offset="194988828" 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="287" name="__module.decoder.up_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>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="546,input.119">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="288" name="self.decoder.up_blocks.3.resnets.0.norm2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="128" offset="194989340" size="512" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.3.resnets.0.norm2.weight">
					<dim>128</dim>
				</port>
			</output>
		</layer>
		<layer id="289" name="self.decoder.up_blocks.3.resnets.0.norm2.bias" type="Const" version="opset1">
			<data element_type="f32" shape="128" offset="194989852" size="512" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.3.resnets.0.norm2.bias">
					<dim>128</dim>
				</port>
			</output>
		</layer>
		<layer id="290" name="__module.decoder.up_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>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="549,input.121">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="291" name="__module.decoder.mid_block.resnets.1.nonlinearity/aten::silu/Swish_23" 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="550,input.123">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="292" name="self.decoder.up_blocks.3.resnets.0.conv2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="128, 128, 3, 3" offset="194990364" size="589824" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.3.resnets.0.conv2.weight">
					<dim>128</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="293" name="__module.decoder.up_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>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="294" name="__module.decoder.up_blocks.3.resnets.0.conv2/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 128, 1, 1" offset="195580188" 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="295" name="__module.decoder.up_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>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="558,hidden_states.43">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="296" name="__module.decoder.up_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>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="566,567,input.125">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="297" name="self.decoder.up_blocks.3.resnets.1.norm1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="128" offset="195580700" size="512" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.3.resnets.1.norm1.weight">
					<dim>128</dim>
				</port>
			</output>
		</layer>
		<layer id="298" name="self.decoder.up_blocks.3.resnets.1.norm1.bias" type="Const" version="opset1">
			<data element_type="f32" shape="128" offset="195581212" size="512" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.3.resnets.1.norm1.bias">
					<dim>128</dim>
				</port>
			</output>
		</layer>
		<layer id="299" name="__module.decoder.up_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>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="575,input.127">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="300" name="__module.decoder.mid_block.resnets.1.nonlinearity/aten::silu/Swish_24" 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="576">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="301" name="self.decoder.up_blocks.3.resnets.1.conv1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="128, 128, 3, 3" offset="195581724" size="589824" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.3.resnets.1.conv1.weight">
					<dim>128</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="302" name="__module.decoder.up_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>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="303" name="__module.decoder.up_blocks.3.resnets.1.conv1/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 128, 1, 1" offset="196171548" 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="304" name="__module.decoder.up_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>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="583,input.129">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="305" name="self.decoder.up_blocks.3.resnets.1.norm2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="128" offset="196172060" size="512" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.3.resnets.1.norm2.weight">
					<dim>128</dim>
				</port>
			</output>
		</layer>
		<layer id="306" name="self.decoder.up_blocks.3.resnets.1.norm2.bias" type="Const" version="opset1">
			<data element_type="f32" shape="128" offset="196172572" size="512" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.3.resnets.1.norm2.bias">
					<dim>128</dim>
				</port>
			</output>
		</layer>
		<layer id="307" name="__module.decoder.up_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>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="586,input.131">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="308" name="__module.decoder.mid_block.resnets.1.nonlinearity/aten::silu/Swish_25" 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="587,input.133">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="309" name="self.decoder.up_blocks.3.resnets.1.conv2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="128, 128, 3, 3" offset="196173084" size="589824" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.3.resnets.1.conv2.weight">
					<dim>128</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="310" name="__module.decoder.up_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>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="311" name="__module.decoder.up_blocks.3.resnets.1.conv2/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 128, 1, 1" offset="196762908" 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="312" name="__module.decoder.up_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>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="595,hidden_states.45">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="313" name="__module.decoder.up_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>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="596,597,input.135">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="314" name="self.decoder.up_blocks.3.resnets.2.norm1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="128" offset="196763420" size="512" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.3.resnets.2.norm1.weight">
					<dim>128</dim>
				</port>
			</output>
		</layer>
		<layer id="315" name="self.decoder.up_blocks.3.resnets.2.norm1.bias" type="Const" version="opset1">
			<data element_type="f32" shape="128" offset="196763932" size="512" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.3.resnets.2.norm1.bias">
					<dim>128</dim>
				</port>
			</output>
		</layer>
		<layer id="316" name="__module.decoder.up_blocks.3.resnets.2.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="605,input.137">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="317" name="__module.decoder.mid_block.resnets.1.nonlinearity/aten::silu/Swish_26" 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="606">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="318" name="self.decoder.up_blocks.3.resnets.2.conv1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="128, 128, 3, 3" offset="196764444" size="589824" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.3.resnets.2.conv1.weight">
					<dim>128</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="319" name="__module.decoder.up_blocks.3.resnets.2.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="320" name="__module.decoder.up_blocks.3.resnets.2.conv1/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 128, 1, 1" offset="197354268" 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="321" name="__module.decoder.up_blocks.3.resnets.2.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="613,input.139">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="322" name="self.decoder.up_blocks.3.resnets.2.norm2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="128" offset="197354780" size="512" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.3.resnets.2.norm2.weight">
					<dim>128</dim>
				</port>
			</output>
		</layer>
		<layer id="323" name="self.decoder.up_blocks.3.resnets.2.norm2.bias" type="Const" version="opset1">
			<data element_type="f32" shape="128" offset="197355292" size="512" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.3.resnets.2.norm2.bias">
					<dim>128</dim>
				</port>
			</output>
		</layer>
		<layer id="324" name="__module.decoder.up_blocks.3.resnets.2.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="616,input.141">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="325" name="__module.decoder.mid_block.resnets.1.nonlinearity/aten::silu/Swish_27" 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="617,input.143">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="326" name="self.decoder.up_blocks.3.resnets.2.conv2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="128, 128, 3, 3" offset="197355804" size="589824" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.up_blocks.3.resnets.2.conv2.weight">
					<dim>128</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="327" name="__module.decoder.up_blocks.3.resnets.2.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="328" name="__module.decoder.up_blocks.3.resnets.2.conv2/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 128, 1, 1" offset="197945628" 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="329" name="__module.decoder.up_blocks.3.resnets.2.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="625,hidden_states">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="330" name="__module.decoder.up_blocks.3.resnets.2/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="626,627,input.145">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="331" name="self.decoder.conv_norm_out.weight" type="Const" version="opset1">
			<data element_type="f32" shape="128" offset="197946140" size="512" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.conv_norm_out.weight">
					<dim>128</dim>
				</port>
			</output>
		</layer>
		<layer id="332" name="self.decoder.conv_norm_out.bias" type="Const" version="opset1">
			<data element_type="f32" shape="128" offset="197946652" size="512" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.conv_norm_out.bias">
					<dim>128</dim>
				</port>
			</output>
		</layer>
		<layer id="333" name="__module.decoder.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>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="630,input">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="334" name="__module.decoder.conv_act/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="631">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="335" name="self.decoder.conv_out.weight" type="Const" version="opset1">
			<data element_type="f32" shape="3, 128, 3, 3" offset="197947164" size="13824" />
			<output>
				<port id="0" precision="FP32" names="self.decoder.conv_out.weight">
					<dim>3</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="336" name="__module.decoder.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>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>3</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>3</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="337" name="__module.decoder.conv_out/aten::_convolution/Reshape" type="Const" version="opset1">
			<data element_type="f32" shape="1, 3, 1, 1" offset="197960988" size="12" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="338" name="__module.decoder.conv_out/aten::_convolution/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<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>1</dim>
					<dim>3</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="sample">
					<dim>-1</dim>
					<dim>3</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="339" name="Result_234078" type="Result" version="opset1">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>3</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="6" to-port="0" />
		<edge from-layer="5" from-port="0" to-layer="6" to-port="1" />
		<edge from-layer="6" from-port="2" to-layer="8" to-port="0" />
		<edge from-layer="7" from-port="0" to-layer="8" to-port="1" />
		<edge from-layer="8" from-port="2" to-layer="11" to-port="0" />
		<edge from-layer="8" from-port="2" to-layer="25" to-port="0" />
		<edge from-layer="9" from-port="0" to-layer="11" to-port="1" />
		<edge from-layer="10" from-port="0" to-layer="11" to-port="2" />
		<edge from-layer="11" from-port="3" to-layer="12" to-port="0" />
		<edge from-layer="12" from-port="1" to-layer="14" to-port="0" />
		<edge from-layer="13" from-port="0" to-layer="14" to-port="1" />
		<edge from-layer="14" from-port="2" to-layer="16" to-port="0" />
		<edge from-layer="15" from-port="0" to-layer="16" to-port="1" />
		<edge from-layer="16" from-port="2" to-layer="19" to-port="0" />
		<edge from-layer="17" from-port="0" to-layer="19" to-port="1" />
		<edge from-layer="18" from-port="0" to-layer="19" to-port="2" />
		<edge from-layer="19" from-port="3" to-layer="20" to-port="0" />
		<edge from-layer="20" from-port="1" to-layer="22" to-port="0" />
		<edge from-layer="21" from-port="0" to-layer="22" to-port="1" />
		<edge from-layer="22" from-port="2" to-layer="24" to-port="0" />
		<edge from-layer="23" from-port="0" to-layer="24" to-port="1" />
		<edge from-layer="24" from-port="2" to-layer="25" to-port="1" />
		<edge from-layer="25" from-port="2" to-layer="27" to-port="0" />
		<edge from-layer="25" from-port="2" to-layer="70" to-port="0" />
		<edge from-layer="25" from-port="2" to-layer="80" to-port="1" />
		<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="31" to-port="0" />
		<edge from-layer="30" from-port="0" to-layer="31" to-port="1" />
		<edge from-layer="31" from-port="2" to-layer="34" to-port="0" />
		<edge from-layer="32" from-port="0" to-layer="34" to-port="1" />
		<edge from-layer="33" from-port="0" to-layer="34" to-port="2" />
		<edge from-layer="34" from-port="3" to-layer="52" to-port="0" />
		<edge from-layer="34" from-port="3" to-layer="44" to-port="0" />
		<edge from-layer="34" from-port="3" to-layer="36" to-port="0" />
		<edge from-layer="35" from-port="0" to-layer="36" to-port="1" />
		<edge from-layer="36" from-port="2" to-layer="38" to-port="0" />
		<edge from-layer="37" from-port="0" to-layer="38" to-port="1" />
		<edge from-layer="38" from-port="2" to-layer="40" to-port="0" />
		<edge from-layer="39" from-port="0" to-layer="40" to-port="1" />
		<edge from-layer="40" from-port="2" to-layer="42" to-port="0" />
		<edge from-layer="41" from-port="0" to-layer="42" to-port="1" />
		<edge from-layer="42" from-port="2" to-layer="59" 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="48" to-port="0" />
		<edge from-layer="47" from-port="0" to-layer="48" to-port="1" />
		<edge from-layer="48" from-port="2" to-layer="50" to-port="0" />
		<edge from-layer="49" from-port="0" to-layer="50" to-port="1" />
		<edge from-layer="50" from-port="2" to-layer="59" to-port="1" />
		<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="56" to-port="0" />
		<edge from-layer="55" from-port="0" to-layer="56" to-port="1" />
		<edge from-layer="56" from-port="2" to-layer="58" to-port="0" />
		<edge from-layer="57" from-port="0" to-layer="58" to-port="1" />
		<edge from-layer="58" from-port="2" to-layer="59" to-port="2" />
		<edge from-layer="59" from-port="3" to-layer="61" to-port="0" />
		<edge from-layer="60" from-port="0" to-layer="61" to-port="1" />
		<edge from-layer="61" from-port="2" to-layer="63" to-port="0" />
		<edge from-layer="62" from-port="0" to-layer="63" to-port="1" />
		<edge from-layer="63" from-port="2" to-layer="65" to-port="0" />
		<edge from-layer="64" from-port="0" to-layer="65" to-port="1" />
		<edge from-layer="65" from-port="2" to-layer="67" to-port="0" />
		<edge from-layer="66" from-port="0" to-layer="67" to-port="1" />
		<edge from-layer="67" from-port="2" to-layer="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="79" to-port="0" />
		<edge from-layer="70" from-port="1" to-layer="77" to-port="0" />
		<edge from-layer="70" from-port="1" to-layer="73" to-port="0" />
		<edge from-layer="71" from-port="0" to-layer="73" to-port="1" />
		<edge from-layer="72" from-port="0" to-layer="73" to-port="2" />
		<edge from-layer="73" from-port="3" to-layer="78" to-port="0" />
		<edge from-layer="74" from-port="0" to-layer="78" to-port="1" />
		<edge from-layer="75" from-port="0" to-layer="77" to-port="1" />
		<edge from-layer="76" from-port="0" to-layer="77" to-port="2" />
		<edge from-layer="77" from-port="3" to-layer="78" to-port="2" />
		<edge from-layer="78" from-port="3" to-layer="79" to-port="1" />
		<edge from-layer="79" from-port="2" to-layer="80" to-port="0" />
		<edge from-layer="80" from-port="2" to-layer="83" to-port="0" />
		<edge from-layer="80" from-port="2" to-layer="97" to-port="0" />
		<edge from-layer="81" from-port="0" to-layer="83" to-port="1" />
		<edge from-layer="82" from-port="0" to-layer="83" to-port="2" />
		<edge from-layer="83" from-port="3" to-layer="84" to-port="0" />
		<edge from-layer="84" from-port="1" to-layer="86" 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="91" 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="97" to-port="1" />
		<edge from-layer="97" from-port="2" to-layer="114" to-port="0" />
		<edge from-layer="97" from-port="2" to-layer="100" to-port="0" />
		<edge from-layer="98" from-port="0" to-layer="100" to-port="1" />
		<edge from-layer="99" from-port="0" to-layer="100" to-port="2" />
		<edge from-layer="100" from-port="3" to-layer="101" to-port="0" />
		<edge from-layer="101" from-port="1" to-layer="103" to-port="0" />
		<edge from-layer="102" from-port="0" to-layer="103" to-port="1" />
		<edge from-layer="103" from-port="2" to-layer="105" to-port="0" />
		<edge from-layer="104" from-port="0" to-layer="105" to-port="1" />
		<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="114" to-port="1" />
		<edge from-layer="114" from-port="2" to-layer="131" to-port="0" />
		<edge from-layer="114" from-port="2" to-layer="117" to-port="0" />
		<edge from-layer="115" from-port="0" to-layer="117" to-port="1" />
		<edge from-layer="116" from-port="0" to-layer="117" to-port="2" />
		<edge from-layer="117" from-port="3" to-layer="118" to-port="0" />
		<edge from-layer="118" from-port="1" to-layer="120" to-port="0" />
		<edge from-layer="119" from-port="0" to-layer="120" to-port="1" />
		<edge from-layer="120" from-port="2" to-layer="122" to-port="0" />
		<edge from-layer="121" from-port="0" to-layer="122" to-port="1" />
		<edge from-layer="122" from-port="2" to-layer="125" to-port="0" />
		<edge from-layer="123" from-port="0" to-layer="125" to-port="1" />
		<edge from-layer="124" from-port="0" to-layer="125" to-port="2" />
		<edge from-layer="125" from-port="3" to-layer="126" to-port="0" />
		<edge from-layer="126" from-port="1" to-layer="128" to-port="0" />
		<edge from-layer="127" from-port="0" to-layer="128" to-port="1" />
		<edge from-layer="128" from-port="2" to-layer="130" to-port="0" />
		<edge from-layer="129" from-port="0" to-layer="130" to-port="1" />
		<edge from-layer="130" from-port="2" to-layer="131" to-port="1" />
		<edge from-layer="131" from-port="2" to-layer="134" to-port="0" />
		<edge from-layer="131" from-port="2" to-layer="148" to-port="0" />
		<edge from-layer="132" from-port="0" to-layer="134" to-port="1" />
		<edge from-layer="133" from-port="0" to-layer="134" to-port="2" />
		<edge from-layer="134" from-port="3" to-layer="135" to-port="0" />
		<edge from-layer="135" from-port="1" to-layer="137" to-port="0" />
		<edge from-layer="136" from-port="0" to-layer="137" to-port="1" />
		<edge from-layer="137" from-port="2" to-layer="139" to-port="0" />
		<edge from-layer="138" from-port="0" to-layer="139" to-port="1" />
		<edge from-layer="139" from-port="2" to-layer="142" to-port="0" />
		<edge from-layer="140" from-port="0" to-layer="142" to-port="1" />
		<edge from-layer="141" from-port="0" to-layer="142" to-port="2" />
		<edge from-layer="142" from-port="3" to-layer="143" to-port="0" />
		<edge from-layer="143" from-port="1" to-layer="145" to-port="0" />
		<edge from-layer="144" from-port="0" to-layer="145" to-port="1" />
		<edge from-layer="145" from-port="2" to-layer="147" to-port="0" />
		<edge from-layer="146" from-port="0" to-layer="147" to-port="1" />
		<edge from-layer="147" from-port="2" to-layer="148" to-port="1" />
		<edge from-layer="148" from-port="2" to-layer="151" to-port="0" />
		<edge from-layer="149" from-port="0" to-layer="151" to-port="1" />
		<edge from-layer="150" from-port="0" to-layer="151" to-port="2" />
		<edge from-layer="151" from-port="3" to-layer="153" to-port="0" />
		<edge from-layer="152" from-port="0" to-layer="153" to-port="1" />
		<edge from-layer="153" from-port="2" to-layer="155" to-port="0" />
		<edge from-layer="154" from-port="0" to-layer="155" to-port="1" />
		<edge from-layer="155" from-port="2" to-layer="172" to-port="0" />
		<edge from-layer="155" from-port="2" to-layer="158" to-port="0" />
		<edge from-layer="156" from-port="0" to-layer="158" to-port="1" />
		<edge from-layer="157" from-port="0" to-layer="158" to-port="2" />
		<edge from-layer="158" from-port="3" to-layer="159" to-port="0" />
		<edge from-layer="159" from-port="1" to-layer="161" to-port="0" />
		<edge from-layer="160" from-port="0" to-layer="161" to-port="1" />
		<edge from-layer="161" from-port="2" to-layer="163" to-port="0" />
		<edge from-layer="162" from-port="0" to-layer="163" to-port="1" />
		<edge from-layer="163" from-port="2" to-layer="166" to-port="0" />
		<edge from-layer="164" from-port="0" to-layer="166" to-port="1" />
		<edge from-layer="165" from-port="0" to-layer="166" to-port="2" />
		<edge from-layer="166" from-port="3" to-layer="167" to-port="0" />
		<edge from-layer="167" from-port="1" to-layer="169" to-port="0" />
		<edge from-layer="168" from-port="0" to-layer="169" to-port="1" />
		<edge from-layer="169" from-port="2" to-layer="171" to-port="0" />
		<edge from-layer="170" from-port="0" to-layer="171" to-port="1" />
		<edge from-layer="171" from-port="2" to-layer="172" to-port="1" />
		<edge from-layer="172" from-port="2" to-layer="175" to-port="0" />
		<edge from-layer="172" from-port="2" to-layer="189" to-port="0" />
		<edge from-layer="173" from-port="0" to-layer="175" to-port="1" />
		<edge from-layer="174" from-port="0" to-layer="175" to-port="2" />
		<edge from-layer="175" from-port="3" to-layer="176" to-port="0" />
		<edge from-layer="176" from-port="1" to-layer="178" to-port="0" />
		<edge from-layer="177" from-port="0" to-layer="178" to-port="1" />
		<edge from-layer="178" from-port="2" to-layer="180" to-port="0" />
		<edge from-layer="179" from-port="0" to-layer="180" to-port="1" />
		<edge from-layer="180" from-port="2" to-layer="183" to-port="0" />
		<edge from-layer="181" from-port="0" to-layer="183" to-port="1" />
		<edge from-layer="182" from-port="0" to-layer="183" to-port="2" />
		<edge from-layer="183" from-port="3" to-layer="184" to-port="0" />
		<edge from-layer="184" from-port="1" to-layer="186" to-port="0" />
		<edge from-layer="185" from-port="0" to-layer="186" to-port="1" />
		<edge from-layer="186" from-port="2" to-layer="188" 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="189" to-port="1" />
		<edge from-layer="189" from-port="2" to-layer="192" to-port="0" />
		<edge from-layer="189" from-port="2" to-layer="206" to-port="0" />
		<edge from-layer="190" from-port="0" to-layer="192" to-port="1" />
		<edge from-layer="191" from-port="0" to-layer="192" to-port="2" />
		<edge from-layer="192" from-port="3" to-layer="193" to-port="0" />
		<edge from-layer="193" from-port="1" to-layer="195" to-port="0" />
		<edge from-layer="194" from-port="0" to-layer="195" to-port="1" />
		<edge from-layer="195" from-port="2" to-layer="197" to-port="0" />
		<edge from-layer="196" from-port="0" to-layer="197" to-port="1" />
		<edge from-layer="197" from-port="2" to-layer="200" to-port="0" />
		<edge from-layer="198" from-port="0" to-layer="200" to-port="1" />
		<edge from-layer="199" from-port="0" to-layer="200" to-port="2" />
		<edge from-layer="200" from-port="3" to-layer="201" to-port="0" />
		<edge from-layer="201" from-port="1" to-layer="203" to-port="0" />
		<edge from-layer="202" from-port="0" to-layer="203" to-port="1" />
		<edge from-layer="203" from-port="2" to-layer="205" to-port="0" />
		<edge from-layer="204" from-port="0" to-layer="205" to-port="1" />
		<edge from-layer="205" from-port="2" to-layer="206" to-port="1" />
		<edge from-layer="206" from-port="2" to-layer="209" to-port="0" />
		<edge from-layer="207" from-port="0" to-layer="209" to-port="1" />
		<edge from-layer="208" from-port="0" to-layer="209" to-port="2" />
		<edge from-layer="209" from-port="3" to-layer="211" to-port="0" />
		<edge from-layer="210" from-port="0" to-layer="211" to-port="1" />
		<edge from-layer="211" from-port="2" 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="213" from-port="2" to-layer="220" 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="234" to-port="0" />
		<edge from-layer="218" from-port="0" to-layer="220" to-port="1" />
		<edge from-layer="219" from-port="0" to-layer="220" to-port="2" />
		<edge from-layer="220" from-port="3" to-layer="221" to-port="0" />
		<edge from-layer="221" from-port="1" to-layer="223" to-port="0" />
		<edge from-layer="222" from-port="0" to-layer="223" to-port="1" />
		<edge from-layer="223" from-port="2" to-layer="225" to-port="0" />
		<edge from-layer="224" from-port="0" to-layer="225" to-port="1" />
		<edge from-layer="225" from-port="2" to-layer="228" to-port="0" />
		<edge from-layer="226" from-port="0" to-layer="228" to-port="1" />
		<edge from-layer="227" from-port="0" to-layer="228" to-port="2" />
		<edge from-layer="228" from-port="3" to-layer="229" to-port="0" />
		<edge from-layer="229" from-port="1" to-layer="231" to-port="0" />
		<edge from-layer="230" from-port="0" to-layer="231" to-port="1" />
		<edge from-layer="231" from-port="2" to-layer="233" to-port="0" />
		<edge from-layer="232" from-port="0" to-layer="233" to-port="1" />
		<edge from-layer="233" from-port="2" to-layer="234" to-port="1" />
		<edge from-layer="234" from-port="2" to-layer="237" to-port="0" />
		<edge from-layer="234" from-port="2" to-layer="251" to-port="0" />
		<edge from-layer="235" from-port="0" to-layer="237" to-port="1" />
		<edge from-layer="236" from-port="0" to-layer="237" to-port="2" />
		<edge from-layer="237" from-port="3" to-layer="238" to-port="0" />
		<edge from-layer="238" from-port="1" 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="242" to-port="0" />
		<edge from-layer="241" from-port="0" to-layer="242" to-port="1" />
		<edge from-layer="242" from-port="2" to-layer="245" to-port="0" />
		<edge from-layer="243" from-port="0" to-layer="245" to-port="1" />
		<edge from-layer="244" from-port="0" to-layer="245" to-port="2" />
		<edge from-layer="245" from-port="3" to-layer="246" to-port="0" />
		<edge from-layer="246" from-port="1" 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="250" to-port="0" />
		<edge from-layer="249" from-port="0" to-layer="250" to-port="1" />
		<edge from-layer="250" from-port="2" to-layer="251" to-port="1" />
		<edge from-layer="251" from-port="2" to-layer="254" to-port="0" />
		<edge from-layer="251" from-port="2" to-layer="268" to-port="0" />
		<edge from-layer="252" from-port="0" to-layer="254" to-port="1" />
		<edge from-layer="253" from-port="0" to-layer="254" to-port="2" />
		<edge from-layer="254" from-port="3" to-layer="255" to-port="0" />
		<edge from-layer="255" from-port="1" 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="262" to-port="0" />
		<edge from-layer="260" from-port="0" to-layer="262" to-port="1" />
		<edge from-layer="261" from-port="0" to-layer="262" to-port="2" />
		<edge from-layer="262" from-port="3" to-layer="263" to-port="0" />
		<edge from-layer="263" from-port="1" to-layer="265" to-port="0" />
		<edge from-layer="264" from-port="0" to-layer="265" to-port="1" />
		<edge from-layer="265" from-port="2" to-layer="267" to-port="0" />
		<edge from-layer="266" from-port="0" to-layer="267" to-port="1" />
		<edge from-layer="267" from-port="2" to-layer="268" to-port="1" />
		<edge from-layer="268" from-port="2" to-layer="271" to-port="0" />
		<edge from-layer="269" from-port="0" to-layer="271" to-port="1" />
		<edge from-layer="270" from-port="0" to-layer="271" to-port="2" />
		<edge from-layer="271" from-port="3" to-layer="273" to-port="0" />
		<edge from-layer="272" from-port="0" to-layer="273" to-port="1" />
		<edge from-layer="273" from-port="2" to-layer="275" to-port="0" />
		<edge from-layer="274" from-port="0" to-layer="275" to-port="1" />
		<edge from-layer="275" from-port="2" to-layer="277" to-port="0" />
		<edge from-layer="275" from-port="2" to-layer="282" to-port="0" />
		<edge from-layer="276" from-port="0" to-layer="277" to-port="1" />
		<edge from-layer="277" from-port="2" to-layer="279" to-port="0" />
		<edge from-layer="278" from-port="0" to-layer="279" to-port="1" />
		<edge from-layer="279" from-port="2" to-layer="296" to-port="0" />
		<edge from-layer="280" from-port="0" to-layer="282" to-port="1" />
		<edge from-layer="281" from-port="0" to-layer="282" to-port="2" />
		<edge from-layer="282" from-port="3" to-layer="283" to-port="0" />
		<edge from-layer="283" from-port="1" to-layer="285" to-port="0" />
		<edge from-layer="284" from-port="0" to-layer="285" to-port="1" />
		<edge from-layer="285" from-port="2" to-layer="287" to-port="0" />
		<edge from-layer="286" from-port="0" to-layer="287" to-port="1" />
		<edge from-layer="287" from-port="2" to-layer="290" to-port="0" />
		<edge from-layer="288" from-port="0" to-layer="290" to-port="1" />
		<edge from-layer="289" from-port="0" to-layer="290" to-port="2" />
		<edge from-layer="290" from-port="3" to-layer="291" to-port="0" />
		<edge from-layer="291" from-port="1" to-layer="293" to-port="0" />
		<edge from-layer="292" from-port="0" to-layer="293" to-port="1" />
		<edge from-layer="293" from-port="2" to-layer="295" to-port="0" />
		<edge from-layer="294" from-port="0" to-layer="295" to-port="1" />
		<edge from-layer="295" from-port="2" to-layer="296" to-port="1" />
		<edge from-layer="296" from-port="2" to-layer="299" to-port="0" />
		<edge from-layer="296" from-port="2" to-layer="313" to-port="0" />
		<edge from-layer="297" from-port="0" to-layer="299" to-port="1" />
		<edge from-layer="298" from-port="0" to-layer="299" to-port="2" />
		<edge from-layer="299" from-port="3" to-layer="300" to-port="0" />
		<edge from-layer="300" from-port="1" to-layer="302" to-port="0" />
		<edge from-layer="301" from-port="0" to-layer="302" to-port="1" />
		<edge from-layer="302" from-port="2" to-layer="304" to-port="0" />
		<edge from-layer="303" from-port="0" to-layer="304" to-port="1" />
		<edge from-layer="304" from-port="2" to-layer="307" to-port="0" />
		<edge from-layer="305" from-port="0" to-layer="307" to-port="1" />
		<edge from-layer="306" from-port="0" to-layer="307" to-port="2" />
		<edge from-layer="307" from-port="3" to-layer="308" to-port="0" />
		<edge from-layer="308" from-port="1" to-layer="310" to-port="0" />
		<edge from-layer="309" from-port="0" to-layer="310" to-port="1" />
		<edge from-layer="310" from-port="2" to-layer="312" to-port="0" />
		<edge from-layer="311" from-port="0" to-layer="312" to-port="1" />
		<edge from-layer="312" from-port="2" to-layer="313" to-port="1" />
		<edge from-layer="313" from-port="2" to-layer="316" to-port="0" />
		<edge from-layer="313" from-port="2" to-layer="330" to-port="0" />
		<edge from-layer="314" from-port="0" to-layer="316" to-port="1" />
		<edge from-layer="315" from-port="0" to-layer="316" to-port="2" />
		<edge from-layer="316" from-port="3" to-layer="317" to-port="0" />
		<edge from-layer="317" from-port="1" to-layer="319" to-port="0" />
		<edge from-layer="318" from-port="0" to-layer="319" to-port="1" />
		<edge from-layer="319" from-port="2" to-layer="321" to-port="0" />
		<edge from-layer="320" from-port="0" to-layer="321" to-port="1" />
		<edge from-layer="321" from-port="2" to-layer="324" to-port="0" />
		<edge from-layer="322" from-port="0" to-layer="324" to-port="1" />
		<edge from-layer="323" from-port="0" to-layer="324" to-port="2" />
		<edge from-layer="324" from-port="3" to-layer="325" to-port="0" />
		<edge from-layer="325" from-port="1" to-layer="327" to-port="0" />
		<edge from-layer="326" from-port="0" to-layer="327" to-port="1" />
		<edge from-layer="327" from-port="2" to-layer="329" to-port="0" />
		<edge from-layer="328" from-port="0" to-layer="329" to-port="1" />
		<edge from-layer="329" from-port="2" to-layer="330" to-port="1" />
		<edge from-layer="330" from-port="2" to-layer="333" to-port="0" />
		<edge from-layer="331" from-port="0" to-layer="333" to-port="1" />
		<edge from-layer="332" from-port="0" to-layer="333" to-port="2" />
		<edge from-layer="333" from-port="3" to-layer="334" to-port="0" />
		<edge from-layer="334" from-port="1" to-layer="336" to-port="0" />
		<edge from-layer="335" from-port="0" to-layer="336" to-port="1" />
		<edge from-layer="336" from-port="2" to-layer="338" to-port="0" />
		<edge from-layer="337" from-port="0" to-layer="338" to-port="1" />
		<edge from-layer="338" from-port="2" to-layer="339" 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>