0.1.0 MindSpore*1.1.0:  2033_2032_1_construct_wrapper:x :2033_2032_1_construct_wrapper:features.0.features.0.weight&2033_2032_1_construct_wrapper:output:1&2033_2032_1_construct_wrapper:output:1"Conv2D*#b pp:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*! out_channel z scalar:value0*! pad_mode*padz scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:uDefault/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/0-Conv2d/Conv2D-op0  &2033_2032_1_construct_wrapper:output:1 92033_2032_1_construct_wrapper:features.0.features.1.gamma 82033_2032_1_construct_wrapper:features.0.features.1.beta ?2033_2032_1_construct_wrapper:features.0.features.1.moving_mean C2033_2032_1_construct_wrapper:features.0.features.1.moving_variance!2033_2032_1_construct_wrapper:0:2!2033_2032_1_construct_wrapper:0:2" BatchNorm*b pp:shape1b  :shape2b  :shape3b  :shape4b  :shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:}Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/BatchNorm-op1 :[ValueNode]1(0):3"Constant* valuez scalar:value0  !2033_2032_1_construct_wrapper:0:2 [ValueNode]1(0):3(2033_2032_1_construct_wrapper:[CNode]2:4(2033_2032_1_construct_wrapper:[CNode]2:4" TupleGetItem*#b pp:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op2  (2033_2032_1_construct_wrapper:[CNode]2:4(2033_2032_1_construct_wrapper:[CNode]3:5(2033_2032_1_construct_wrapper:[CNode]3:5"ReLU6*#b pp:shape1z shape:shape1,*0 output_namesZoutputzscalar:List[value1,],** input_namesZxzscalar:List[value1,],:sDefault/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/2-ReLU6/ReLU6-op3  (2033_2032_1_construct_wrapper:[CNode]3:5 A2033_2032_1_construct_wrapper:features.1.conv.0.features.0.weight&2033_2032_1_construct_wrapper:output:6&2033_2032_1_construct_wrapper:output:6"Conv2D*#b pp:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groups z scalar:value0* format*NCHWz scalar:value0* group z scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*! out_channel z scalar:value0*! pad_mode*padz scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/1-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/0-Conv2d/Conv2D-op4  &2033_2032_1_construct_wrapper:output:6 @2033_2032_1_construct_wrapper:features.1.conv.0.features.1.gamma ?2033_2032_1_construct_wrapper:features.1.conv.0.features.1.beta F2033_2032_1_construct_wrapper:features.1.conv.0.features.1.moving_mean J2033_2032_1_construct_wrapper:features.1.conv.0.features.1.moving_variance!2033_2032_1_construct_wrapper:0:7!2033_2032_1_construct_wrapper:0:7" BatchNorm*b pp:shape1b  :shape2b  :shape3b  :shape4b  :shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:}Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/BatchNorm-op5 :[ValueNode]1(0):8"Constant* valuez scalar:value0  !2033_2032_1_construct_wrapper:0:7 [ValueNode]1(0):8(2033_2032_1_construct_wrapper:[CNode]2:9(2033_2032_1_construct_wrapper:[CNode]2:9" TupleGetItem*#b pp:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op6  (2033_2032_1_construct_wrapper:[CNode]2:9)2033_2032_1_construct_wrapper:[CNode]4:10)2033_2032_1_construct_wrapper:[CNode]4:10"ReLU6*#b pp:shape1z shape:shape1,*0 output_namesZoutputzscalar:List[value1,],** input_namesZxzscalar:List[value1,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/1-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/2-ReLU6/ReLU6-op7  )2033_2032_1_construct_wrapper:[CNode]4:10 62033_2032_1_construct_wrapper:features.1.conv.1.weight'2033_2032_1_construct_wrapper:output:11'2033_2032_1_construct_wrapper:output:11"Conv2D*#bpp:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*! out_channelz scalar:value0*" pad_mode*samez scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:wDefault/backbone-MobileNetV2Backbone/features-SequentialCell/1-InvertedResidual/conv-SequentialCell/1-Conv2d/Conv2D-op8  '2033_2032_1_construct_wrapper:output:11 52033_2032_1_construct_wrapper:features.1.conv.2.gamma 42033_2032_1_construct_wrapper:features.1.conv.2.beta ;2033_2032_1_construct_wrapper:features.1.conv.2.moving_mean ?2033_2032_1_construct_wrapper:features.1.conv.2.moving_variance)2033_2032_1_construct_wrapper:[CNode]5:12)2033_2032_1_construct_wrapper:[CNode]5:12" BatchNorm*bpp:shape1b :shape2b :shape3b :shape4b :shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:Default/backbone-MobileNetV2Backbone/features-SequentialCell/1-InvertedResidual/conv-SequentialCell/2-BatchNorm2d/BatchNorm-op9 ;[ValueNode]1(0):13"Constant* valuez scalar:value0  )2033_2032_1_construct_wrapper:[CNode]5:12 [ValueNode]1(0):13)2033_2032_1_construct_wrapper:[CNode]2:14)2033_2032_1_construct_wrapper:[CNode]2:14" TupleGetItem*#bpp:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op10  )2033_2032_1_construct_wrapper:[CNode]2:14 A2033_2032_1_construct_wrapper:features.2.conv.0.features.0.weight'2033_2032_1_construct_wrapper:output:15'2033_2032_1_construct_wrapper:output:15"Conv2D*#b`pp:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*! out_channel`z scalar:value0*! pad_mode*padz scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/2-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/0-Conv2d/Conv2D-op11  '2033_2032_1_construct_wrapper:output:15 @2033_2032_1_construct_wrapper:features.2.conv.0.features.1.gamma ?2033_2032_1_construct_wrapper:features.2.conv.0.features.1.beta F2033_2032_1_construct_wrapper:features.2.conv.0.features.1.moving_mean J2033_2032_1_construct_wrapper:features.2.conv.0.features.1.moving_variance"2033_2032_1_construct_wrapper:6:16"2033_2032_1_construct_wrapper:6:16" BatchNorm*b`pp:shape1b `:shape2b `:shape3b `:shape4b `:shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:Default/backbone-MobileNetV2Backbone/features-SequentialCell/11-InvertedResidual/conv-SequentialCell/3-BatchNorm2d/BatchNorm-op12 ;[ValueNode]1(0):17"Constant* valuez scalar:value0  "2033_2032_1_construct_wrapper:6:16 [ValueNode]1(0):17)2033_2032_1_construct_wrapper:[CNode]2:18)2033_2032_1_construct_wrapper:[CNode]2:18" TupleGetItem*#b`pp:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op13  )2033_2032_1_construct_wrapper:[CNode]2:18)2033_2032_1_construct_wrapper:[CNode]7:19)2033_2032_1_construct_wrapper:[CNode]7:19"ReLU6*#b`pp:shape1z shape:shape1,*0 output_namesZoutputzscalar:List[value1,],** input_namesZxzscalar:List[value1,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/2-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/2-ReLU6/ReLU6-op14  )2033_2032_1_construct_wrapper:[CNode]7:19 A2033_2032_1_construct_wrapper:features.2.conv.1.features.0.weight'2033_2032_1_construct_wrapper:output:20'2033_2032_1_construct_wrapper:output:20"Conv2D*#b`88:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groups`z scalar:value0* format*NCHWz scalar:value0* group`z scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*! out_channel`z scalar:value0*! pad_mode*padz scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/2-InvertedResidual/conv-SequentialCell/1-ConvBNReLU/features-SequentialCell/0-Conv2d/Conv2D-op15  '2033_2032_1_construct_wrapper:output:20 @2033_2032_1_construct_wrapper:features.2.conv.1.features.1.gamma ?2033_2032_1_construct_wrapper:features.2.conv.1.features.1.beta F2033_2032_1_construct_wrapper:features.2.conv.1.features.1.moving_mean J2033_2032_1_construct_wrapper:features.2.conv.1.features.1.moving_variance"2033_2032_1_construct_wrapper:6:21"2033_2032_1_construct_wrapper:6:21" BatchNorm*b`88:shape1b `:shape2b `:shape3b `:shape4b `:shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:Default/backbone-MobileNetV2Backbone/features-SequentialCell/11-InvertedResidual/conv-SequentialCell/3-BatchNorm2d/BatchNorm-op16 ;[ValueNode]1(0):22"Constant* valuez scalar:value0  "2033_2032_1_construct_wrapper:6:21 [ValueNode]1(0):22)2033_2032_1_construct_wrapper:[CNode]2:23)2033_2032_1_construct_wrapper:[CNode]2:23" TupleGetItem*#b`88:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op17  )2033_2032_1_construct_wrapper:[CNode]2:23)2033_2032_1_construct_wrapper:[CNode]8:24)2033_2032_1_construct_wrapper:[CNode]8:24"ReLU6*#b`88:shape1z shape:shape1,*0 output_namesZoutputzscalar:List[value1,],** input_namesZxzscalar:List[value1,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/2-InvertedResidual/conv-SequentialCell/1-ConvBNReLU/features-SequentialCell/2-ReLU6/ReLU6-op18  )2033_2032_1_construct_wrapper:[CNode]8:24 62033_2032_1_construct_wrapper:features.2.conv.2.weight'2033_2032_1_construct_wrapper:output:25'2033_2032_1_construct_wrapper:output:25"Conv2D*#b88:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*! out_channelz scalar:value0*" pad_mode*samez scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:xDefault/backbone-MobileNetV2Backbone/features-SequentialCell/2-InvertedResidual/conv-SequentialCell/2-Conv2d/Conv2D-op19  '2033_2032_1_construct_wrapper:output:25 52033_2032_1_construct_wrapper:features.2.conv.3.gamma 42033_2032_1_construct_wrapper:features.2.conv.3.beta ;2033_2032_1_construct_wrapper:features.2.conv.3.moving_mean ?2033_2032_1_construct_wrapper:features.2.conv.3.moving_variance"2033_2032_1_construct_wrapper:9:26"2033_2032_1_construct_wrapper:9:26" BatchNorm*b88:shape1b :shape2b :shape3b :shape4b :shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:Default/backbone-MobileNetV2Backbone/features-SequentialCell/2-InvertedResidual/conv-SequentialCell/3-BatchNorm2d/BatchNorm-op20 ;[ValueNode]1(0):27"Constant* valuez scalar:value0  "2033_2032_1_construct_wrapper:9:26 [ValueNode]1(0):27)2033_2032_1_construct_wrapper:[CNode]2:28)2033_2032_1_construct_wrapper:[CNode]2:28" TupleGetItem*#b88:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op21  )2033_2032_1_construct_wrapper:[CNode]2:28 A2033_2032_1_construct_wrapper:features.3.conv.0.features.0.weight'2033_2032_1_construct_wrapper:output:29'2033_2032_1_construct_wrapper:output:29"Conv2D*$b88:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*" out_channelz scalar:value0*! pad_mode*padz scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/3-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/0-Conv2d/Conv2D-op22  '2033_2032_1_construct_wrapper:output:29 @2033_2032_1_construct_wrapper:features.3.conv.0.features.1.gamma ?2033_2032_1_construct_wrapper:features.3.conv.0.features.1.beta F2033_2032_1_construct_wrapper:features.3.conv.0.features.1.moving_mean J2033_2032_1_construct_wrapper:features.3.conv.0.features.1.moving_variance#2033_2032_1_construct_wrapper:10:30#2033_2032_1_construct_wrapper:10:30" BatchNorm*b88:shape1b :shape2b :shape3b :shape4b :shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:Default/backbone-MobileNetV2Backbone/features-SequentialCell/3-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/BatchNorm-op23 ;[ValueNode]1(0):31"Constant* valuez scalar:value0  #2033_2032_1_construct_wrapper:10:30 [ValueNode]1(0):31)2033_2032_1_construct_wrapper:[CNode]2:32)2033_2032_1_construct_wrapper:[CNode]2:32" TupleGetItem*$b88:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op24  )2033_2032_1_construct_wrapper:[CNode]2:32*2033_2032_1_construct_wrapper:[CNode]11:33*2033_2032_1_construct_wrapper:[CNode]11:33"ReLU6*$b88:shape1z shape:shape1,*0 output_namesZoutputzscalar:List[value1,],** input_namesZxzscalar:List[value1,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/3-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/2-ReLU6/ReLU6-op25  *2033_2032_1_construct_wrapper:[CNode]11:33 A2033_2032_1_construct_wrapper:features.3.conv.1.features.0.weight'2033_2032_1_construct_wrapper:output:34'2033_2032_1_construct_wrapper:output:34"Conv2D*$b88:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*" out_channelz scalar:value0*! pad_mode*padz scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/3-InvertedResidual/conv-SequentialCell/1-ConvBNReLU/features-SequentialCell/0-Conv2d/Conv2D-op26  '2033_2032_1_construct_wrapper:output:34 @2033_2032_1_construct_wrapper:features.3.conv.1.features.1.gamma ?2033_2032_1_construct_wrapper:features.3.conv.1.features.1.beta F2033_2032_1_construct_wrapper:features.3.conv.1.features.1.moving_mean J2033_2032_1_construct_wrapper:features.3.conv.1.features.1.moving_variance#2033_2032_1_construct_wrapper:10:35#2033_2032_1_construct_wrapper:10:35" BatchNorm*b88:shape1b :shape2b :shape3b :shape4b :shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:Default/backbone-MobileNetV2Backbone/features-SequentialCell/3-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/BatchNorm-op27 ;[ValueNode]1(0):36"Constant* valuez scalar:value0  #2033_2032_1_construct_wrapper:10:35 [ValueNode]1(0):36)2033_2032_1_construct_wrapper:[CNode]2:37)2033_2032_1_construct_wrapper:[CNode]2:37" TupleGetItem*$b88:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op28  )2033_2032_1_construct_wrapper:[CNode]2:37*2033_2032_1_construct_wrapper:[CNode]12:38*2033_2032_1_construct_wrapper:[CNode]12:38"ReLU6*$b88:shape1z shape:shape1,*0 output_namesZoutputzscalar:List[value1,],** input_namesZxzscalar:List[value1,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/3-InvertedResidual/conv-SequentialCell/1-ConvBNReLU/features-SequentialCell/2-ReLU6/ReLU6-op29  *2033_2032_1_construct_wrapper:[CNode]12:38 62033_2032_1_construct_wrapper:features.3.conv.2.weight'2033_2032_1_construct_wrapper:output:39'2033_2032_1_construct_wrapper:output:39"Conv2D*#b88:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*! out_channelz scalar:value0*" pad_mode*samez scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:xDefault/backbone-MobileNetV2Backbone/features-SequentialCell/3-InvertedResidual/conv-SequentialCell/2-Conv2d/Conv2D-op30  '2033_2032_1_construct_wrapper:output:39 52033_2032_1_construct_wrapper:features.3.conv.3.gamma 42033_2032_1_construct_wrapper:features.3.conv.3.beta ;2033_2032_1_construct_wrapper:features.3.conv.3.moving_mean ?2033_2032_1_construct_wrapper:features.3.conv.3.moving_variance"2033_2032_1_construct_wrapper:9:40"2033_2032_1_construct_wrapper:9:40" BatchNorm*b88:shape1b :shape2b :shape3b :shape4b :shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:Default/backbone-MobileNetV2Backbone/features-SequentialCell/2-InvertedResidual/conv-SequentialCell/3-BatchNorm2d/BatchNorm-op31 ;[ValueNode]1(0):41"Constant* valuez scalar:value0  "2033_2032_1_construct_wrapper:9:40 [ValueNode]1(0):41)2033_2032_1_construct_wrapper:[CNode]2:42)2033_2032_1_construct_wrapper:[CNode]2:42" TupleGetItem*#b88:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op32  )2033_2032_1_construct_wrapper:[CNode]2:28 )2033_2032_1_construct_wrapper:[CNode]2:42*2033_2032_1_construct_wrapper:[CNode]13:43*2033_2032_1_construct_wrapper:[CNode]13:43"Add*#b88:shape1z shape:shape1,*0 output_namesZoutputzscalar:List[value1,],*4 input_namesZxZyzscalar:List[value1,value2,],:XDefault/backbone-MobileNetV2Backbone/features-SequentialCell/3-InvertedResidual/Add-op33  *2033_2032_1_construct_wrapper:[CNode]13:43 A2033_2032_1_construct_wrapper:features.4.conv.0.features.0.weight'2033_2032_1_construct_wrapper:output:44'2033_2032_1_construct_wrapper:output:44"Conv2D*$b88:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*" out_channelz scalar:value0*! pad_mode*padz scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/3-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/0-Conv2d/Conv2D-op34  '2033_2032_1_construct_wrapper:output:44 @2033_2032_1_construct_wrapper:features.4.conv.0.features.1.gamma ?2033_2032_1_construct_wrapper:features.4.conv.0.features.1.beta F2033_2032_1_construct_wrapper:features.4.conv.0.features.1.moving_mean J2033_2032_1_construct_wrapper:features.4.conv.0.features.1.moving_variance#2033_2032_1_construct_wrapper:10:45#2033_2032_1_construct_wrapper:10:45" BatchNorm*b88:shape1b :shape2b :shape3b :shape4b :shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:Default/backbone-MobileNetV2Backbone/features-SequentialCell/3-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/BatchNorm-op35 ;[ValueNode]1(0):46"Constant* valuez scalar:value0  #2033_2032_1_construct_wrapper:10:45 [ValueNode]1(0):46)2033_2032_1_construct_wrapper:[CNode]2:47)2033_2032_1_construct_wrapper:[CNode]2:47" TupleGetItem*$b88:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op36  )2033_2032_1_construct_wrapper:[CNode]2:47*2033_2032_1_construct_wrapper:[CNode]14:48*2033_2032_1_construct_wrapper:[CNode]14:48"ReLU6*$b88:shape1z shape:shape1,*0 output_namesZoutputzscalar:List[value1,],** input_namesZxzscalar:List[value1,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/4-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/2-ReLU6/ReLU6-op37  *2033_2032_1_construct_wrapper:[CNode]14:48 A2033_2032_1_construct_wrapper:features.4.conv.1.features.0.weight'2033_2032_1_construct_wrapper:output:49'2033_2032_1_construct_wrapper:output:49"Conv2D*$b:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*" out_channelz scalar:value0*! pad_mode*padz scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/4-InvertedResidual/conv-SequentialCell/1-ConvBNReLU/features-SequentialCell/0-Conv2d/Conv2D-op38  '2033_2032_1_construct_wrapper:output:49 @2033_2032_1_construct_wrapper:features.4.conv.1.features.1.gamma ?2033_2032_1_construct_wrapper:features.4.conv.1.features.1.beta F2033_2032_1_construct_wrapper:features.4.conv.1.features.1.moving_mean J2033_2032_1_construct_wrapper:features.4.conv.1.features.1.moving_variance#2033_2032_1_construct_wrapper:10:50#2033_2032_1_construct_wrapper:10:50" BatchNorm*b:shape1b :shape2b :shape3b :shape4b :shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:Default/backbone-MobileNetV2Backbone/features-SequentialCell/3-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/BatchNorm-op39 ;[ValueNode]1(0):51"Constant* valuez scalar:value0  #2033_2032_1_construct_wrapper:10:50 [ValueNode]1(0):51)2033_2032_1_construct_wrapper:[CNode]2:52)2033_2032_1_construct_wrapper:[CNode]2:52" TupleGetItem*$b:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op40  )2033_2032_1_construct_wrapper:[CNode]2:52*2033_2032_1_construct_wrapper:[CNode]15:53*2033_2032_1_construct_wrapper:[CNode]15:53"ReLU6*$b:shape1z shape:shape1,*0 output_namesZoutputzscalar:List[value1,],** input_namesZxzscalar:List[value1,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/4-InvertedResidual/conv-SequentialCell/1-ConvBNReLU/features-SequentialCell/2-ReLU6/ReLU6-op41  *2033_2032_1_construct_wrapper:[CNode]15:53 62033_2032_1_construct_wrapper:features.4.conv.2.weight'2033_2032_1_construct_wrapper:output:54'2033_2032_1_construct_wrapper:output:54"Conv2D*#b :shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*! out_channel z scalar:value0*" pad_mode*samez scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:xDefault/backbone-MobileNetV2Backbone/features-SequentialCell/4-InvertedResidual/conv-SequentialCell/2-Conv2d/Conv2D-op42  '2033_2032_1_construct_wrapper:output:54 52033_2032_1_construct_wrapper:features.4.conv.3.gamma 42033_2032_1_construct_wrapper:features.4.conv.3.beta ;2033_2032_1_construct_wrapper:features.4.conv.3.moving_mean ?2033_2032_1_construct_wrapper:features.4.conv.3.moving_variance"2033_2032_1_construct_wrapper:0:55"2033_2032_1_construct_wrapper:0:55" BatchNorm*b :shape1b  :shape2b  :shape3b  :shape4b  :shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:~Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/BatchNorm-op43 ;[ValueNode]1(0):56"Constant* valuez scalar:value0  "2033_2032_1_construct_wrapper:0:55 [ValueNode]1(0):56)2033_2032_1_construct_wrapper:[CNode]2:57)2033_2032_1_construct_wrapper:[CNode]2:57" TupleGetItem*#b :shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op44  )2033_2032_1_construct_wrapper:[CNode]2:57 A2033_2032_1_construct_wrapper:features.5.conv.0.features.0.weight'2033_2032_1_construct_wrapper:output:58'2033_2032_1_construct_wrapper:output:58"Conv2D*$b:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*" out_channelz scalar:value0*! pad_mode*padz scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/5-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/0-Conv2d/Conv2D-op45  '2033_2032_1_construct_wrapper:output:58 @2033_2032_1_construct_wrapper:features.5.conv.0.features.1.gamma ?2033_2032_1_construct_wrapper:features.5.conv.0.features.1.beta F2033_2032_1_construct_wrapper:features.5.conv.0.features.1.moving_mean J2033_2032_1_construct_wrapper:features.5.conv.0.features.1.moving_variance#2033_2032_1_construct_wrapper:16:59#2033_2032_1_construct_wrapper:16:59" BatchNorm*b:shape1b :shape2b :shape3b :shape4b :shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:Default/backbone-MobileNetV2Backbone/features-SequentialCell/5-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/BatchNorm-op46 ;[ValueNode]1(0):60"Constant* valuez scalar:value0  #2033_2032_1_construct_wrapper:16:59 [ValueNode]1(0):60)2033_2032_1_construct_wrapper:[CNode]2:61)2033_2032_1_construct_wrapper:[CNode]2:61" TupleGetItem*$b:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op47  )2033_2032_1_construct_wrapper:[CNode]2:61*2033_2032_1_construct_wrapper:[CNode]17:62*2033_2032_1_construct_wrapper:[CNode]17:62"ReLU6*$b:shape1z shape:shape1,*0 output_namesZoutputzscalar:List[value1,],** input_namesZxzscalar:List[value1,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/5-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/2-ReLU6/ReLU6-op48  *2033_2032_1_construct_wrapper:[CNode]17:62 A2033_2032_1_construct_wrapper:features.5.conv.1.features.0.weight'2033_2032_1_construct_wrapper:output:63'2033_2032_1_construct_wrapper:output:63"Conv2D*$b:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*" out_channelz scalar:value0*! pad_mode*padz scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/5-InvertedResidual/conv-SequentialCell/1-ConvBNReLU/features-SequentialCell/0-Conv2d/Conv2D-op49  '2033_2032_1_construct_wrapper:output:63 @2033_2032_1_construct_wrapper:features.5.conv.1.features.1.gamma ?2033_2032_1_construct_wrapper:features.5.conv.1.features.1.beta F2033_2032_1_construct_wrapper:features.5.conv.1.features.1.moving_mean J2033_2032_1_construct_wrapper:features.5.conv.1.features.1.moving_variance#2033_2032_1_construct_wrapper:16:64#2033_2032_1_construct_wrapper:16:64" BatchNorm*b:shape1b :shape2b :shape3b :shape4b :shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:Default/backbone-MobileNetV2Backbone/features-SequentialCell/5-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/BatchNorm-op50 ;[ValueNode]1(0):65"Constant* valuez scalar:value0  #2033_2032_1_construct_wrapper:16:64 [ValueNode]1(0):65)2033_2032_1_construct_wrapper:[CNode]2:66)2033_2032_1_construct_wrapper:[CNode]2:66" TupleGetItem*$b:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op51  )2033_2032_1_construct_wrapper:[CNode]2:66*2033_2032_1_construct_wrapper:[CNode]18:67*2033_2032_1_construct_wrapper:[CNode]18:67"ReLU6*$b:shape1z shape:shape1,*0 output_namesZoutputzscalar:List[value1,],** input_namesZxzscalar:List[value1,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/5-InvertedResidual/conv-SequentialCell/1-ConvBNReLU/features-SequentialCell/2-ReLU6/ReLU6-op52  *2033_2032_1_construct_wrapper:[CNode]18:67 62033_2032_1_construct_wrapper:features.5.conv.2.weight'2033_2032_1_construct_wrapper:output:68'2033_2032_1_construct_wrapper:output:68"Conv2D*#b :shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*! out_channel z scalar:value0*" pad_mode*samez scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:xDefault/backbone-MobileNetV2Backbone/features-SequentialCell/5-InvertedResidual/conv-SequentialCell/2-Conv2d/Conv2D-op53  '2033_2032_1_construct_wrapper:output:68 52033_2032_1_construct_wrapper:features.5.conv.3.gamma 42033_2032_1_construct_wrapper:features.5.conv.3.beta ;2033_2032_1_construct_wrapper:features.5.conv.3.moving_mean ?2033_2032_1_construct_wrapper:features.5.conv.3.moving_variance"2033_2032_1_construct_wrapper:0:69"2033_2032_1_construct_wrapper:0:69" BatchNorm*b :shape1b  :shape2b  :shape3b  :shape4b  :shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:~Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/BatchNorm-op54 ;[ValueNode]1(0):70"Constant* valuez scalar:value0  "2033_2032_1_construct_wrapper:0:69 [ValueNode]1(0):70)2033_2032_1_construct_wrapper:[CNode]2:71)2033_2032_1_construct_wrapper:[CNode]2:71" TupleGetItem*#b :shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op55  )2033_2032_1_construct_wrapper:[CNode]2:57 )2033_2032_1_construct_wrapper:[CNode]2:71*2033_2032_1_construct_wrapper:[CNode]19:72*2033_2032_1_construct_wrapper:[CNode]19:72"Add*#b :shape1z shape:shape1,*0 output_namesZoutputzscalar:List[value1,],*4 input_namesZxZyzscalar:List[value1,value2,],:XDefault/backbone-MobileNetV2Backbone/features-SequentialCell/5-InvertedResidual/Add-op56  *2033_2032_1_construct_wrapper:[CNode]19:72 A2033_2032_1_construct_wrapper:features.6.conv.0.features.0.weight'2033_2032_1_construct_wrapper:output:73'2033_2032_1_construct_wrapper:output:73"Conv2D*$b:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*" out_channelz scalar:value0*! pad_mode*padz scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/5-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/0-Conv2d/Conv2D-op57  '2033_2032_1_construct_wrapper:output:73 @2033_2032_1_construct_wrapper:features.6.conv.0.features.1.gamma ?2033_2032_1_construct_wrapper:features.6.conv.0.features.1.beta F2033_2032_1_construct_wrapper:features.6.conv.0.features.1.moving_mean J2033_2032_1_construct_wrapper:features.6.conv.0.features.1.moving_variance#2033_2032_1_construct_wrapper:16:74#2033_2032_1_construct_wrapper:16:74" BatchNorm*b:shape1b :shape2b :shape3b :shape4b :shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:Default/backbone-MobileNetV2Backbone/features-SequentialCell/5-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/BatchNorm-op58 ;[ValueNode]1(0):75"Constant* valuez scalar:value0  #2033_2032_1_construct_wrapper:16:74 [ValueNode]1(0):75)2033_2032_1_construct_wrapper:[CNode]2:76)2033_2032_1_construct_wrapper:[CNode]2:76" TupleGetItem*$b:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op59  )2033_2032_1_construct_wrapper:[CNode]2:76*2033_2032_1_construct_wrapper:[CNode]20:77*2033_2032_1_construct_wrapper:[CNode]20:77"ReLU6*$b:shape1z shape:shape1,*0 output_namesZoutputzscalar:List[value1,],** input_namesZxzscalar:List[value1,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/6-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/2-ReLU6/ReLU6-op60  *2033_2032_1_construct_wrapper:[CNode]20:77 A2033_2032_1_construct_wrapper:features.6.conv.1.features.0.weight'2033_2032_1_construct_wrapper:output:78'2033_2032_1_construct_wrapper:output:78"Conv2D*$b:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*" out_channelz scalar:value0*! pad_mode*padz scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/5-InvertedResidual/conv-SequentialCell/1-ConvBNReLU/features-SequentialCell/0-Conv2d/Conv2D-op61  '2033_2032_1_construct_wrapper:output:78 @2033_2032_1_construct_wrapper:features.6.conv.1.features.1.gamma ?2033_2032_1_construct_wrapper:features.6.conv.1.features.1.beta F2033_2032_1_construct_wrapper:features.6.conv.1.features.1.moving_mean J2033_2032_1_construct_wrapper:features.6.conv.1.features.1.moving_variance#2033_2032_1_construct_wrapper:16:79#2033_2032_1_construct_wrapper:16:79" BatchNorm*b:shape1b :shape2b :shape3b :shape4b :shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:Default/backbone-MobileNetV2Backbone/features-SequentialCell/5-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/BatchNorm-op62 ;[ValueNode]1(0):80"Constant* valuez scalar:value0  #2033_2032_1_construct_wrapper:16:79 [ValueNode]1(0):80)2033_2032_1_construct_wrapper:[CNode]2:81)2033_2032_1_construct_wrapper:[CNode]2:81" TupleGetItem*$b:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op63  )2033_2032_1_construct_wrapper:[CNode]2:81*2033_2032_1_construct_wrapper:[CNode]21:82*2033_2032_1_construct_wrapper:[CNode]21:82"ReLU6*$b:shape1z shape:shape1,*0 output_namesZoutputzscalar:List[value1,],** input_namesZxzscalar:List[value1,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/6-InvertedResidual/conv-SequentialCell/1-ConvBNReLU/features-SequentialCell/2-ReLU6/ReLU6-op64  *2033_2032_1_construct_wrapper:[CNode]21:82 62033_2032_1_construct_wrapper:features.6.conv.2.weight'2033_2032_1_construct_wrapper:output:83'2033_2032_1_construct_wrapper:output:83"Conv2D*#b :shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*! out_channel z scalar:value0*" pad_mode*samez scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:xDefault/backbone-MobileNetV2Backbone/features-SequentialCell/5-InvertedResidual/conv-SequentialCell/2-Conv2d/Conv2D-op65  '2033_2032_1_construct_wrapper:output:83 52033_2032_1_construct_wrapper:features.6.conv.3.gamma 42033_2032_1_construct_wrapper:features.6.conv.3.beta ;2033_2032_1_construct_wrapper:features.6.conv.3.moving_mean ?2033_2032_1_construct_wrapper:features.6.conv.3.moving_variance"2033_2032_1_construct_wrapper:0:84"2033_2032_1_construct_wrapper:0:84" BatchNorm*b :shape1b  :shape2b  :shape3b  :shape4b  :shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:~Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/BatchNorm-op66 ;[ValueNode]1(0):85"Constant* valuez scalar:value0  "2033_2032_1_construct_wrapper:0:84 [ValueNode]1(0):85)2033_2032_1_construct_wrapper:[CNode]2:86)2033_2032_1_construct_wrapper:[CNode]2:86" TupleGetItem*#b :shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op67  *2033_2032_1_construct_wrapper:[CNode]19:72 )2033_2032_1_construct_wrapper:[CNode]2:86*2033_2032_1_construct_wrapper:[CNode]22:87*2033_2032_1_construct_wrapper:[CNode]22:87"Add*#b :shape1z shape:shape1,*0 output_namesZoutputzscalar:List[value1,],*4 input_namesZxZyzscalar:List[value1,value2,],:XDefault/backbone-MobileNetV2Backbone/features-SequentialCell/6-InvertedResidual/Add-op68  *2033_2032_1_construct_wrapper:[CNode]22:87 A2033_2032_1_construct_wrapper:features.7.conv.0.features.0.weight'2033_2032_1_construct_wrapper:output:88'2033_2032_1_construct_wrapper:output:88"Conv2D*$b:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*" out_channelz scalar:value0*! pad_mode*padz scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/5-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/0-Conv2d/Conv2D-op69  '2033_2032_1_construct_wrapper:output:88 @2033_2032_1_construct_wrapper:features.7.conv.0.features.1.gamma ?2033_2032_1_construct_wrapper:features.7.conv.0.features.1.beta F2033_2032_1_construct_wrapper:features.7.conv.0.features.1.moving_mean J2033_2032_1_construct_wrapper:features.7.conv.0.features.1.moving_variance#2033_2032_1_construct_wrapper:16:89#2033_2032_1_construct_wrapper:16:89" BatchNorm*b:shape1b :shape2b :shape3b :shape4b :shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:Default/backbone-MobileNetV2Backbone/features-SequentialCell/5-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/BatchNorm-op70 ;[ValueNode]1(0):90"Constant* valuez scalar:value0  #2033_2032_1_construct_wrapper:16:89 [ValueNode]1(0):90)2033_2032_1_construct_wrapper:[CNode]2:91)2033_2032_1_construct_wrapper:[CNode]2:91" TupleGetItem*$b:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op71  )2033_2032_1_construct_wrapper:[CNode]2:91*2033_2032_1_construct_wrapper:[CNode]23:92*2033_2032_1_construct_wrapper:[CNode]23:92"ReLU6*$b:shape1z shape:shape1,*0 output_namesZoutputzscalar:List[value1,],** input_namesZxzscalar:List[value1,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/7-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/2-ReLU6/ReLU6-op72  *2033_2032_1_construct_wrapper:[CNode]23:92 A2033_2032_1_construct_wrapper:features.7.conv.1.features.0.weight'2033_2032_1_construct_wrapper:output:93'2033_2032_1_construct_wrapper:output:93"Conv2D*$b:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*" out_channelz scalar:value0*! pad_mode*padz scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/7-InvertedResidual/conv-SequentialCell/1-ConvBNReLU/features-SequentialCell/0-Conv2d/Conv2D-op73  '2033_2032_1_construct_wrapper:output:93 @2033_2032_1_construct_wrapper:features.7.conv.1.features.1.gamma ?2033_2032_1_construct_wrapper:features.7.conv.1.features.1.beta F2033_2032_1_construct_wrapper:features.7.conv.1.features.1.moving_mean J2033_2032_1_construct_wrapper:features.7.conv.1.features.1.moving_variance#2033_2032_1_construct_wrapper:16:94#2033_2032_1_construct_wrapper:16:94" BatchNorm*b:shape1b :shape2b :shape3b :shape4b :shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:Default/backbone-MobileNetV2Backbone/features-SequentialCell/5-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/BatchNorm-op74 ;[ValueNode]1(0):95"Constant* valuez scalar:value0  #2033_2032_1_construct_wrapper:16:94 [ValueNode]1(0):95)2033_2032_1_construct_wrapper:[CNode]2:96)2033_2032_1_construct_wrapper:[CNode]2:96" TupleGetItem*$b:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op75  )2033_2032_1_construct_wrapper:[CNode]2:96*2033_2032_1_construct_wrapper:[CNode]24:97*2033_2032_1_construct_wrapper:[CNode]24:97"ReLU6*$b:shape1z shape:shape1,*0 output_namesZoutputzscalar:List[value1,],** input_namesZxzscalar:List[value1,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/7-InvertedResidual/conv-SequentialCell/1-ConvBNReLU/features-SequentialCell/2-ReLU6/ReLU6-op76  *2033_2032_1_construct_wrapper:[CNode]24:97 62033_2032_1_construct_wrapper:features.7.conv.2.weight'2033_2032_1_construct_wrapper:output:98'2033_2032_1_construct_wrapper:output:98"Conv2D*#b@:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*! out_channel@z scalar:value0*" pad_mode*samez scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:xDefault/backbone-MobileNetV2Backbone/features-SequentialCell/7-InvertedResidual/conv-SequentialCell/2-Conv2d/Conv2D-op77  '2033_2032_1_construct_wrapper:output:98 52033_2032_1_construct_wrapper:features.7.conv.3.gamma 42033_2032_1_construct_wrapper:features.7.conv.3.beta ;2033_2032_1_construct_wrapper:features.7.conv.3.moving_mean ?2033_2032_1_construct_wrapper:features.7.conv.3.moving_variance#2033_2032_1_construct_wrapper:25:99#2033_2032_1_construct_wrapper:25:99" BatchNorm*b@:shape1b @:shape2b @:shape3b @:shape4b @:shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:Default/backbone-MobileNetV2Backbone/features-SequentialCell/7-InvertedResidual/conv-SequentialCell/3-BatchNorm2d/BatchNorm-op78 <[ValueNode]1(0):100"Constant* valuez scalar:value0  #2033_2032_1_construct_wrapper:25:99 [ValueNode]1(0):100*2033_2032_1_construct_wrapper:[CNode]2:101*2033_2032_1_construct_wrapper:[CNode]2:101" TupleGetItem*#b@:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op79  *2033_2032_1_construct_wrapper:[CNode]2:101 A2033_2032_1_construct_wrapper:features.8.conv.0.features.0.weight(2033_2032_1_construct_wrapper:output:102(2033_2032_1_construct_wrapper:output:102"Conv2D*$b:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*" out_channelz scalar:value0*! pad_mode*padz scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/8-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/0-Conv2d/Conv2D-op80  (2033_2032_1_construct_wrapper:output:102 @2033_2032_1_construct_wrapper:features.8.conv.0.features.1.gamma ?2033_2032_1_construct_wrapper:features.8.conv.0.features.1.beta F2033_2032_1_construct_wrapper:features.8.conv.0.features.1.moving_mean J2033_2032_1_construct_wrapper:features.8.conv.0.features.1.moving_variance$2033_2032_1_construct_wrapper:26:103$2033_2032_1_construct_wrapper:26:103" BatchNorm*b:shape1b :shape2b :shape3b :shape4b :shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:Default/backbone-MobileNetV2Backbone/features-SequentialCell/8-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/BatchNorm-op81 <[ValueNode]1(0):104"Constant* valuez scalar:value0  $2033_2032_1_construct_wrapper:26:103 [ValueNode]1(0):104*2033_2032_1_construct_wrapper:[CNode]2:105*2033_2032_1_construct_wrapper:[CNode]2:105" TupleGetItem*$b:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op82  *2033_2032_1_construct_wrapper:[CNode]2:105+2033_2032_1_construct_wrapper:[CNode]27:106+2033_2032_1_construct_wrapper:[CNode]27:106"ReLU6*$b:shape1z shape:shape1,*0 output_namesZoutputzscalar:List[value1,],** input_namesZxzscalar:List[value1,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/8-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/2-ReLU6/ReLU6-op83  +2033_2032_1_construct_wrapper:[CNode]27:106 A2033_2032_1_construct_wrapper:features.8.conv.1.features.0.weight(2033_2032_1_construct_wrapper:output:107(2033_2032_1_construct_wrapper:output:107"Conv2D*$b:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*" out_channelz scalar:value0*! pad_mode*padz scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/8-InvertedResidual/conv-SequentialCell/1-ConvBNReLU/features-SequentialCell/0-Conv2d/Conv2D-op84  (2033_2032_1_construct_wrapper:output:107 @2033_2032_1_construct_wrapper:features.8.conv.1.features.1.gamma ?2033_2032_1_construct_wrapper:features.8.conv.1.features.1.beta F2033_2032_1_construct_wrapper:features.8.conv.1.features.1.moving_mean J2033_2032_1_construct_wrapper:features.8.conv.1.features.1.moving_variance$2033_2032_1_construct_wrapper:26:108$2033_2032_1_construct_wrapper:26:108" BatchNorm*b:shape1b :shape2b :shape3b :shape4b :shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:Default/backbone-MobileNetV2Backbone/features-SequentialCell/8-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/BatchNorm-op85 <[ValueNode]1(0):109"Constant* valuez scalar:value0  $2033_2032_1_construct_wrapper:26:108 [ValueNode]1(0):109*2033_2032_1_construct_wrapper:[CNode]2:110*2033_2032_1_construct_wrapper:[CNode]2:110" TupleGetItem*$b:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op86  *2033_2032_1_construct_wrapper:[CNode]2:110+2033_2032_1_construct_wrapper:[CNode]28:111+2033_2032_1_construct_wrapper:[CNode]28:111"ReLU6*$b:shape1z shape:shape1,*0 output_namesZoutputzscalar:List[value1,],** input_namesZxzscalar:List[value1,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/8-InvertedResidual/conv-SequentialCell/1-ConvBNReLU/features-SequentialCell/2-ReLU6/ReLU6-op87  +2033_2032_1_construct_wrapper:[CNode]28:111 62033_2032_1_construct_wrapper:features.8.conv.2.weight(2033_2032_1_construct_wrapper:output:112(2033_2032_1_construct_wrapper:output:112"Conv2D*#b@:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*! out_channel@z scalar:value0*" pad_mode*samez scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:xDefault/backbone-MobileNetV2Backbone/features-SequentialCell/8-InvertedResidual/conv-SequentialCell/2-Conv2d/Conv2D-op88  (2033_2032_1_construct_wrapper:output:112 52033_2032_1_construct_wrapper:features.8.conv.3.gamma 42033_2032_1_construct_wrapper:features.8.conv.3.beta ;2033_2032_1_construct_wrapper:features.8.conv.3.moving_mean ?2033_2032_1_construct_wrapper:features.8.conv.3.moving_variance$2033_2032_1_construct_wrapper:25:113$2033_2032_1_construct_wrapper:25:113" BatchNorm*b@:shape1b @:shape2b @:shape3b @:shape4b @:shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:Default/backbone-MobileNetV2Backbone/features-SequentialCell/7-InvertedResidual/conv-SequentialCell/3-BatchNorm2d/BatchNorm-op89 <[ValueNode]1(0):114"Constant* valuez scalar:value0  $2033_2032_1_construct_wrapper:25:113 [ValueNode]1(0):114*2033_2032_1_construct_wrapper:[CNode]2:115*2033_2032_1_construct_wrapper:[CNode]2:115" TupleGetItem*#b@:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op90  *2033_2032_1_construct_wrapper:[CNode]2:101 *2033_2032_1_construct_wrapper:[CNode]2:115+2033_2032_1_construct_wrapper:[CNode]29:116+2033_2032_1_construct_wrapper:[CNode]29:116"Add*#b@:shape1z shape:shape1,*0 output_namesZoutputzscalar:List[value1,],*4 input_namesZxZyzscalar:List[value1,value2,],:XDefault/backbone-MobileNetV2Backbone/features-SequentialCell/8-InvertedResidual/Add-op91  +2033_2032_1_construct_wrapper:[CNode]29:116 A2033_2032_1_construct_wrapper:features.9.conv.0.features.0.weight(2033_2032_1_construct_wrapper:output:117(2033_2032_1_construct_wrapper:output:117"Conv2D*$b:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*" out_channelz scalar:value0*! pad_mode*padz scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/8-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/0-Conv2d/Conv2D-op92  (2033_2032_1_construct_wrapper:output:117 @2033_2032_1_construct_wrapper:features.9.conv.0.features.1.gamma ?2033_2032_1_construct_wrapper:features.9.conv.0.features.1.beta F2033_2032_1_construct_wrapper:features.9.conv.0.features.1.moving_mean J2033_2032_1_construct_wrapper:features.9.conv.0.features.1.moving_variance$2033_2032_1_construct_wrapper:26:118$2033_2032_1_construct_wrapper:26:118" BatchNorm*b:shape1b :shape2b :shape3b :shape4b :shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:Default/backbone-MobileNetV2Backbone/features-SequentialCell/8-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/BatchNorm-op93 <[ValueNode]1(0):119"Constant* valuez scalar:value0  $2033_2032_1_construct_wrapper:26:118 [ValueNode]1(0):119*2033_2032_1_construct_wrapper:[CNode]2:120*2033_2032_1_construct_wrapper:[CNode]2:120" TupleGetItem*$b:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op94  *2033_2032_1_construct_wrapper:[CNode]2:120+2033_2032_1_construct_wrapper:[CNode]30:121+2033_2032_1_construct_wrapper:[CNode]30:121"ReLU6*$b:shape1z shape:shape1,*0 output_namesZoutputzscalar:List[value1,],** input_namesZxzscalar:List[value1,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/9-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/2-ReLU6/ReLU6-op95  +2033_2032_1_construct_wrapper:[CNode]30:121 A2033_2032_1_construct_wrapper:features.9.conv.1.features.0.weight(2033_2032_1_construct_wrapper:output:122(2033_2032_1_construct_wrapper:output:122"Conv2D*$b:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*" out_channelz scalar:value0*! pad_mode*padz scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/8-InvertedResidual/conv-SequentialCell/1-ConvBNReLU/features-SequentialCell/0-Conv2d/Conv2D-op96  (2033_2032_1_construct_wrapper:output:122 @2033_2032_1_construct_wrapper:features.9.conv.1.features.1.gamma ?2033_2032_1_construct_wrapper:features.9.conv.1.features.1.beta F2033_2032_1_construct_wrapper:features.9.conv.1.features.1.moving_mean J2033_2032_1_construct_wrapper:features.9.conv.1.features.1.moving_variance$2033_2032_1_construct_wrapper:26:123$2033_2032_1_construct_wrapper:26:123" BatchNorm*b:shape1b :shape2b :shape3b :shape4b :shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:Default/backbone-MobileNetV2Backbone/features-SequentialCell/8-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/BatchNorm-op97 <[ValueNode]1(0):124"Constant* valuez scalar:value0  $2033_2032_1_construct_wrapper:26:123 [ValueNode]1(0):124*2033_2032_1_construct_wrapper:[CNode]2:125*2033_2032_1_construct_wrapper:[CNode]2:125" TupleGetItem*$b:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op98  *2033_2032_1_construct_wrapper:[CNode]2:125+2033_2032_1_construct_wrapper:[CNode]31:126+2033_2032_1_construct_wrapper:[CNode]31:126"ReLU6*$b:shape1z shape:shape1,*0 output_namesZoutputzscalar:List[value1,],** input_namesZxzscalar:List[value1,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/9-InvertedResidual/conv-SequentialCell/1-ConvBNReLU/features-SequentialCell/2-ReLU6/ReLU6-op99  +2033_2032_1_construct_wrapper:[CNode]31:126 62033_2032_1_construct_wrapper:features.9.conv.2.weight(2033_2032_1_construct_wrapper:output:127(2033_2032_1_construct_wrapper:output:127"Conv2D*#b@:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*! out_channel@z scalar:value0*" pad_mode*samez scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:yDefault/backbone-MobileNetV2Backbone/features-SequentialCell/8-InvertedResidual/conv-SequentialCell/2-Conv2d/Conv2D-op100  (2033_2032_1_construct_wrapper:output:127 52033_2032_1_construct_wrapper:features.9.conv.3.gamma 42033_2032_1_construct_wrapper:features.9.conv.3.beta ;2033_2032_1_construct_wrapper:features.9.conv.3.moving_mean ?2033_2032_1_construct_wrapper:features.9.conv.3.moving_variance$2033_2032_1_construct_wrapper:25:128$2033_2032_1_construct_wrapper:25:128" BatchNorm*b@:shape1b @:shape2b @:shape3b @:shape4b @:shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:Default/backbone-MobileNetV2Backbone/features-SequentialCell/7-InvertedResidual/conv-SequentialCell/3-BatchNorm2d/BatchNorm-op101 <[ValueNode]1(0):129"Constant* valuez scalar:value0  $2033_2032_1_construct_wrapper:25:128 [ValueNode]1(0):129*2033_2032_1_construct_wrapper:[CNode]2:130*2033_2032_1_construct_wrapper:[CNode]2:130" TupleGetItem*#b@:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op102  +2033_2032_1_construct_wrapper:[CNode]29:116 *2033_2032_1_construct_wrapper:[CNode]2:130+2033_2032_1_construct_wrapper:[CNode]32:131+2033_2032_1_construct_wrapper:[CNode]32:131"Add*#b@:shape1z shape:shape1,*0 output_namesZoutputzscalar:List[value1,],*4 input_namesZxZyzscalar:List[value1,value2,],:YDefault/backbone-MobileNetV2Backbone/features-SequentialCell/9-InvertedResidual/Add-op103  +2033_2032_1_construct_wrapper:[CNode]32:131 B2033_2032_1_construct_wrapper:features.10.conv.0.features.0.weight(2033_2032_1_construct_wrapper:output:132(2033_2032_1_construct_wrapper:output:132"Conv2D*$b:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*" out_channelz scalar:value0*! pad_mode*padz scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/8-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/0-Conv2d/Conv2D-op104  (2033_2032_1_construct_wrapper:output:132 A2033_2032_1_construct_wrapper:features.10.conv.0.features.1.gamma @2033_2032_1_construct_wrapper:features.10.conv.0.features.1.beta G2033_2032_1_construct_wrapper:features.10.conv.0.features.1.moving_mean K2033_2032_1_construct_wrapper:features.10.conv.0.features.1.moving_variance$2033_2032_1_construct_wrapper:26:133$2033_2032_1_construct_wrapper:26:133" BatchNorm*b:shape1b :shape2b :shape3b :shape4b :shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:Default/backbone-MobileNetV2Backbone/features-SequentialCell/8-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/BatchNorm-op105 <[ValueNode]1(0):134"Constant* valuez scalar:value0  $2033_2032_1_construct_wrapper:26:133 [ValueNode]1(0):134*2033_2032_1_construct_wrapper:[CNode]2:135*2033_2032_1_construct_wrapper:[CNode]2:135" TupleGetItem*$b:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op106  *2033_2032_1_construct_wrapper:[CNode]2:135+2033_2032_1_construct_wrapper:[CNode]33:136+2033_2032_1_construct_wrapper:[CNode]33:136"ReLU6*$b:shape1z shape:shape1,*0 output_namesZoutputzscalar:List[value1,],** input_namesZxzscalar:List[value1,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/10-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/2-ReLU6/ReLU6-op107  +2033_2032_1_construct_wrapper:[CNode]33:136 B2033_2032_1_construct_wrapper:features.10.conv.1.features.0.weight(2033_2032_1_construct_wrapper:output:137(2033_2032_1_construct_wrapper:output:137"Conv2D*$b:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*" out_channelz scalar:value0*! pad_mode*padz scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/8-InvertedResidual/conv-SequentialCell/1-ConvBNReLU/features-SequentialCell/0-Conv2d/Conv2D-op108  (2033_2032_1_construct_wrapper:output:137 A2033_2032_1_construct_wrapper:features.10.conv.1.features.1.gamma @2033_2032_1_construct_wrapper:features.10.conv.1.features.1.beta G2033_2032_1_construct_wrapper:features.10.conv.1.features.1.moving_mean K2033_2032_1_construct_wrapper:features.10.conv.1.features.1.moving_variance$2033_2032_1_construct_wrapper:26:138$2033_2032_1_construct_wrapper:26:138" BatchNorm*b:shape1b :shape2b :shape3b :shape4b :shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:Default/backbone-MobileNetV2Backbone/features-SequentialCell/8-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/BatchNorm-op109 <[ValueNode]1(0):139"Constant* valuez scalar:value0  $2033_2032_1_construct_wrapper:26:138 [ValueNode]1(0):139*2033_2032_1_construct_wrapper:[CNode]2:140*2033_2032_1_construct_wrapper:[CNode]2:140" TupleGetItem*$b:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op110  *2033_2032_1_construct_wrapper:[CNode]2:140+2033_2032_1_construct_wrapper:[CNode]34:141+2033_2032_1_construct_wrapper:[CNode]34:141"ReLU6*$b:shape1z shape:shape1,*0 output_namesZoutputzscalar:List[value1,],** input_namesZxzscalar:List[value1,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/10-InvertedResidual/conv-SequentialCell/1-ConvBNReLU/features-SequentialCell/2-ReLU6/ReLU6-op111  +2033_2032_1_construct_wrapper:[CNode]34:141 72033_2032_1_construct_wrapper:features.10.conv.2.weight(2033_2032_1_construct_wrapper:output:142(2033_2032_1_construct_wrapper:output:142"Conv2D*#b@:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*! out_channel@z scalar:value0*" pad_mode*samez scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:yDefault/backbone-MobileNetV2Backbone/features-SequentialCell/8-InvertedResidual/conv-SequentialCell/2-Conv2d/Conv2D-op112  (2033_2032_1_construct_wrapper:output:142 62033_2032_1_construct_wrapper:features.10.conv.3.gamma 52033_2032_1_construct_wrapper:features.10.conv.3.beta <2033_2032_1_construct_wrapper:features.10.conv.3.moving_mean @2033_2032_1_construct_wrapper:features.10.conv.3.moving_variance$2033_2032_1_construct_wrapper:25:143$2033_2032_1_construct_wrapper:25:143" BatchNorm*b@:shape1b @:shape2b @:shape3b @:shape4b @:shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:Default/backbone-MobileNetV2Backbone/features-SequentialCell/7-InvertedResidual/conv-SequentialCell/3-BatchNorm2d/BatchNorm-op113 <[ValueNode]1(0):144"Constant* valuez scalar:value0  $2033_2032_1_construct_wrapper:25:143 [ValueNode]1(0):144*2033_2032_1_construct_wrapper:[CNode]2:145*2033_2032_1_construct_wrapper:[CNode]2:145" TupleGetItem*#b@:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op114  +2033_2032_1_construct_wrapper:[CNode]32:131 *2033_2032_1_construct_wrapper:[CNode]2:145+2033_2032_1_construct_wrapper:[CNode]35:146+2033_2032_1_construct_wrapper:[CNode]35:146"Add*#b@:shape1z shape:shape1,*0 output_namesZoutputzscalar:List[value1,],*4 input_namesZxZyzscalar:List[value1,value2,],:ZDefault/backbone-MobileNetV2Backbone/features-SequentialCell/10-InvertedResidual/Add-op115  +2033_2032_1_construct_wrapper:[CNode]35:146 B2033_2032_1_construct_wrapper:features.11.conv.0.features.0.weight(2033_2032_1_construct_wrapper:output:147(2033_2032_1_construct_wrapper:output:147"Conv2D*$b:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*" out_channelz scalar:value0*! pad_mode*padz scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/8-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/0-Conv2d/Conv2D-op116  (2033_2032_1_construct_wrapper:output:147 A2033_2032_1_construct_wrapper:features.11.conv.0.features.1.gamma @2033_2032_1_construct_wrapper:features.11.conv.0.features.1.beta G2033_2032_1_construct_wrapper:features.11.conv.0.features.1.moving_mean K2033_2032_1_construct_wrapper:features.11.conv.0.features.1.moving_variance$2033_2032_1_construct_wrapper:26:148$2033_2032_1_construct_wrapper:26:148" BatchNorm*b:shape1b :shape2b :shape3b :shape4b :shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:Default/backbone-MobileNetV2Backbone/features-SequentialCell/8-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/BatchNorm-op117 <[ValueNode]1(0):149"Constant* valuez scalar:value0  $2033_2032_1_construct_wrapper:26:148 [ValueNode]1(0):149*2033_2032_1_construct_wrapper:[CNode]2:150*2033_2032_1_construct_wrapper:[CNode]2:150" TupleGetItem*$b:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op118  *2033_2032_1_construct_wrapper:[CNode]2:150+2033_2032_1_construct_wrapper:[CNode]36:151+2033_2032_1_construct_wrapper:[CNode]36:151"ReLU6*$b:shape1z shape:shape1,*0 output_namesZoutputzscalar:List[value1,],** input_namesZxzscalar:List[value1,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/11-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/2-ReLU6/ReLU6-op119  +2033_2032_1_construct_wrapper:[CNode]36:151 B2033_2032_1_construct_wrapper:features.11.conv.1.features.0.weight(2033_2032_1_construct_wrapper:output:152(2033_2032_1_construct_wrapper:output:152"Conv2D*$b:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*" out_channelz scalar:value0*! pad_mode*padz scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/8-InvertedResidual/conv-SequentialCell/1-ConvBNReLU/features-SequentialCell/0-Conv2d/Conv2D-op120  (2033_2032_1_construct_wrapper:output:152 A2033_2032_1_construct_wrapper:features.11.conv.1.features.1.gamma @2033_2032_1_construct_wrapper:features.11.conv.1.features.1.beta G2033_2032_1_construct_wrapper:features.11.conv.1.features.1.moving_mean K2033_2032_1_construct_wrapper:features.11.conv.1.features.1.moving_variance$2033_2032_1_construct_wrapper:26:153$2033_2032_1_construct_wrapper:26:153" BatchNorm*b:shape1b :shape2b :shape3b :shape4b :shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:Default/backbone-MobileNetV2Backbone/features-SequentialCell/8-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/BatchNorm-op121 <[ValueNode]1(0):154"Constant* valuez scalar:value0  $2033_2032_1_construct_wrapper:26:153 [ValueNode]1(0):154*2033_2032_1_construct_wrapper:[CNode]2:155*2033_2032_1_construct_wrapper:[CNode]2:155" TupleGetItem*$b:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op122  *2033_2032_1_construct_wrapper:[CNode]2:155+2033_2032_1_construct_wrapper:[CNode]37:156+2033_2032_1_construct_wrapper:[CNode]37:156"ReLU6*$b:shape1z shape:shape1,*0 output_namesZoutputzscalar:List[value1,],** input_namesZxzscalar:List[value1,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/11-InvertedResidual/conv-SequentialCell/1-ConvBNReLU/features-SequentialCell/2-ReLU6/ReLU6-op123  +2033_2032_1_construct_wrapper:[CNode]37:156 72033_2032_1_construct_wrapper:features.11.conv.2.weight(2033_2032_1_construct_wrapper:output:157(2033_2032_1_construct_wrapper:output:157"Conv2D*#b`:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*! out_channel`z scalar:value0*" pad_mode*samez scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:zDefault/backbone-MobileNetV2Backbone/features-SequentialCell/11-InvertedResidual/conv-SequentialCell/2-Conv2d/Conv2D-op124  (2033_2032_1_construct_wrapper:output:157 62033_2032_1_construct_wrapper:features.11.conv.3.gamma 52033_2032_1_construct_wrapper:features.11.conv.3.beta <2033_2032_1_construct_wrapper:features.11.conv.3.moving_mean @2033_2032_1_construct_wrapper:features.11.conv.3.moving_variance#2033_2032_1_construct_wrapper:6:158#2033_2032_1_construct_wrapper:6:158" BatchNorm*b`:shape1b `:shape2b `:shape3b `:shape4b `:shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:Default/backbone-MobileNetV2Backbone/features-SequentialCell/11-InvertedResidual/conv-SequentialCell/3-BatchNorm2d/BatchNorm-op125 <[ValueNode]1(0):159"Constant* valuez scalar:value0  #2033_2032_1_construct_wrapper:6:158 [ValueNode]1(0):159*2033_2032_1_construct_wrapper:[CNode]2:160*2033_2032_1_construct_wrapper:[CNode]2:160" TupleGetItem*#b`:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op126  *2033_2032_1_construct_wrapper:[CNode]2:160 B2033_2032_1_construct_wrapper:features.12.conv.0.features.0.weight(2033_2032_1_construct_wrapper:output:161(2033_2032_1_construct_wrapper:output:161"Conv2D*$b:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*" out_channelz scalar:value0*! pad_mode*padz scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/12-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/0-Conv2d/Conv2D-op127  (2033_2032_1_construct_wrapper:output:161 A2033_2032_1_construct_wrapper:features.12.conv.0.features.1.gamma @2033_2032_1_construct_wrapper:features.12.conv.0.features.1.beta G2033_2032_1_construct_wrapper:features.12.conv.0.features.1.moving_mean K2033_2032_1_construct_wrapper:features.12.conv.0.features.1.moving_variance$2033_2032_1_construct_wrapper:38:162$2033_2032_1_construct_wrapper:38:162" BatchNorm*b:shape1b :shape2b :shape3b :shape4b :shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:Default/backbone-MobileNetV2Backbone/features-SequentialCell/12-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/BatchNorm-op128 <[ValueNode]1(0):163"Constant* valuez scalar:value0  $2033_2032_1_construct_wrapper:38:162 [ValueNode]1(0):163*2033_2032_1_construct_wrapper:[CNode]2:164*2033_2032_1_construct_wrapper:[CNode]2:164" TupleGetItem*$b:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op129  *2033_2032_1_construct_wrapper:[CNode]2:164+2033_2032_1_construct_wrapper:[CNode]39:165+2033_2032_1_construct_wrapper:[CNode]39:165"ReLU6*$b:shape1z shape:shape1,*0 output_namesZoutputzscalar:List[value1,],** input_namesZxzscalar:List[value1,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/12-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/2-ReLU6/ReLU6-op130  +2033_2032_1_construct_wrapper:[CNode]39:165 B2033_2032_1_construct_wrapper:features.12.conv.1.features.0.weight(2033_2032_1_construct_wrapper:output:166(2033_2032_1_construct_wrapper:output:166"Conv2D*$b:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*" out_channelz scalar:value0*! pad_mode*padz scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/12-InvertedResidual/conv-SequentialCell/1-ConvBNReLU/features-SequentialCell/0-Conv2d/Conv2D-op131  (2033_2032_1_construct_wrapper:output:166 A2033_2032_1_construct_wrapper:features.12.conv.1.features.1.gamma @2033_2032_1_construct_wrapper:features.12.conv.1.features.1.beta G2033_2032_1_construct_wrapper:features.12.conv.1.features.1.moving_mean K2033_2032_1_construct_wrapper:features.12.conv.1.features.1.moving_variance$2033_2032_1_construct_wrapper:38:167$2033_2032_1_construct_wrapper:38:167" BatchNorm*b:shape1b :shape2b :shape3b :shape4b :shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:Default/backbone-MobileNetV2Backbone/features-SequentialCell/12-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/BatchNorm-op132 <[ValueNode]1(0):168"Constant* valuez scalar:value0  $2033_2032_1_construct_wrapper:38:167 [ValueNode]1(0):168*2033_2032_1_construct_wrapper:[CNode]2:169*2033_2032_1_construct_wrapper:[CNode]2:169" TupleGetItem*$b:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op133  *2033_2032_1_construct_wrapper:[CNode]2:169+2033_2032_1_construct_wrapper:[CNode]40:170+2033_2032_1_construct_wrapper:[CNode]40:170"ReLU6*$b:shape1z shape:shape1,*0 output_namesZoutputzscalar:List[value1,],** input_namesZxzscalar:List[value1,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/12-InvertedResidual/conv-SequentialCell/1-ConvBNReLU/features-SequentialCell/2-ReLU6/ReLU6-op134  +2033_2032_1_construct_wrapper:[CNode]40:170 72033_2032_1_construct_wrapper:features.12.conv.2.weight(2033_2032_1_construct_wrapper:output:171(2033_2032_1_construct_wrapper:output:171"Conv2D*#b`:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*! out_channel`z scalar:value0*" pad_mode*samez scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:zDefault/backbone-MobileNetV2Backbone/features-SequentialCell/12-InvertedResidual/conv-SequentialCell/2-Conv2d/Conv2D-op135  (2033_2032_1_construct_wrapper:output:171 62033_2032_1_construct_wrapper:features.12.conv.3.gamma 52033_2032_1_construct_wrapper:features.12.conv.3.beta <2033_2032_1_construct_wrapper:features.12.conv.3.moving_mean @2033_2032_1_construct_wrapper:features.12.conv.3.moving_variance#2033_2032_1_construct_wrapper:6:172#2033_2032_1_construct_wrapper:6:172" BatchNorm*b`:shape1b `:shape2b `:shape3b `:shape4b `:shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:Default/backbone-MobileNetV2Backbone/features-SequentialCell/11-InvertedResidual/conv-SequentialCell/3-BatchNorm2d/BatchNorm-op136 <[ValueNode]1(0):173"Constant* valuez scalar:value0  #2033_2032_1_construct_wrapper:6:172 [ValueNode]1(0):173*2033_2032_1_construct_wrapper:[CNode]2:174*2033_2032_1_construct_wrapper:[CNode]2:174" TupleGetItem*#b`:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op137  *2033_2032_1_construct_wrapper:[CNode]2:160 *2033_2032_1_construct_wrapper:[CNode]2:174+2033_2032_1_construct_wrapper:[CNode]41:175+2033_2032_1_construct_wrapper:[CNode]41:175"Add*#b`:shape1z shape:shape1,*0 output_namesZoutputzscalar:List[value1,],*4 input_namesZxZyzscalar:List[value1,value2,],:ZDefault/backbone-MobileNetV2Backbone/features-SequentialCell/12-InvertedResidual/Add-op138  +2033_2032_1_construct_wrapper:[CNode]41:175 B2033_2032_1_construct_wrapper:features.13.conv.0.features.0.weight(2033_2032_1_construct_wrapper:output:176(2033_2032_1_construct_wrapper:output:176"Conv2D*$b:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*" out_channelz scalar:value0*! pad_mode*padz scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/12-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/0-Conv2d/Conv2D-op139  (2033_2032_1_construct_wrapper:output:176 A2033_2032_1_construct_wrapper:features.13.conv.0.features.1.gamma @2033_2032_1_construct_wrapper:features.13.conv.0.features.1.beta G2033_2032_1_construct_wrapper:features.13.conv.0.features.1.moving_mean K2033_2032_1_construct_wrapper:features.13.conv.0.features.1.moving_variance$2033_2032_1_construct_wrapper:38:177$2033_2032_1_construct_wrapper:38:177" BatchNorm*b:shape1b :shape2b :shape3b :shape4b :shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:Default/backbone-MobileNetV2Backbone/features-SequentialCell/12-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/BatchNorm-op140 <[ValueNode]1(0):178"Constant* valuez scalar:value0  $2033_2032_1_construct_wrapper:38:177 [ValueNode]1(0):178*2033_2032_1_construct_wrapper:[CNode]2:179*2033_2032_1_construct_wrapper:[CNode]2:179" TupleGetItem*$b:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op141  *2033_2032_1_construct_wrapper:[CNode]2:179+2033_2032_1_construct_wrapper:[CNode]42:180+2033_2032_1_construct_wrapper:[CNode]42:180"ReLU6*$b:shape1z shape:shape1,*0 output_namesZoutputzscalar:List[value1,],** input_namesZxzscalar:List[value1,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/13-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/2-ReLU6/ReLU6-op142  +2033_2032_1_construct_wrapper:[CNode]42:180 B2033_2032_1_construct_wrapper:features.13.conv.1.features.0.weight(2033_2032_1_construct_wrapper:output:181(2033_2032_1_construct_wrapper:output:181"Conv2D*$b:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*" out_channelz scalar:value0*! pad_mode*padz scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/12-InvertedResidual/conv-SequentialCell/1-ConvBNReLU/features-SequentialCell/0-Conv2d/Conv2D-op143  (2033_2032_1_construct_wrapper:output:181 A2033_2032_1_construct_wrapper:features.13.conv.1.features.1.gamma @2033_2032_1_construct_wrapper:features.13.conv.1.features.1.beta G2033_2032_1_construct_wrapper:features.13.conv.1.features.1.moving_mean K2033_2032_1_construct_wrapper:features.13.conv.1.features.1.moving_variance$2033_2032_1_construct_wrapper:38:182$2033_2032_1_construct_wrapper:38:182" BatchNorm*b:shape1b :shape2b :shape3b :shape4b :shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:Default/backbone-MobileNetV2Backbone/features-SequentialCell/12-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/BatchNorm-op144 <[ValueNode]1(0):183"Constant* valuez scalar:value0  $2033_2032_1_construct_wrapper:38:182 [ValueNode]1(0):183*2033_2032_1_construct_wrapper:[CNode]2:184*2033_2032_1_construct_wrapper:[CNode]2:184" TupleGetItem*$b:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op145  *2033_2032_1_construct_wrapper:[CNode]2:184+2033_2032_1_construct_wrapper:[CNode]43:185+2033_2032_1_construct_wrapper:[CNode]43:185"ReLU6*$b:shape1z shape:shape1,*0 output_namesZoutputzscalar:List[value1,],** input_namesZxzscalar:List[value1,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/13-InvertedResidual/conv-SequentialCell/1-ConvBNReLU/features-SequentialCell/2-ReLU6/ReLU6-op146  +2033_2032_1_construct_wrapper:[CNode]43:185 72033_2032_1_construct_wrapper:features.13.conv.2.weight(2033_2032_1_construct_wrapper:output:186(2033_2032_1_construct_wrapper:output:186"Conv2D*#b`:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*! out_channel`z scalar:value0*" pad_mode*samez scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:zDefault/backbone-MobileNetV2Backbone/features-SequentialCell/12-InvertedResidual/conv-SequentialCell/2-Conv2d/Conv2D-op147  (2033_2032_1_construct_wrapper:output:186 62033_2032_1_construct_wrapper:features.13.conv.3.gamma 52033_2032_1_construct_wrapper:features.13.conv.3.beta <2033_2032_1_construct_wrapper:features.13.conv.3.moving_mean @2033_2032_1_construct_wrapper:features.13.conv.3.moving_variance#2033_2032_1_construct_wrapper:6:187#2033_2032_1_construct_wrapper:6:187" BatchNorm*b`:shape1b `:shape2b `:shape3b `:shape4b `:shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:Default/backbone-MobileNetV2Backbone/features-SequentialCell/11-InvertedResidual/conv-SequentialCell/3-BatchNorm2d/BatchNorm-op148 <[ValueNode]1(0):188"Constant* valuez scalar:value0  #2033_2032_1_construct_wrapper:6:187 [ValueNode]1(0):188*2033_2032_1_construct_wrapper:[CNode]2:189*2033_2032_1_construct_wrapper:[CNode]2:189" TupleGetItem*#b`:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op149  +2033_2032_1_construct_wrapper:[CNode]41:175 *2033_2032_1_construct_wrapper:[CNode]2:189+2033_2032_1_construct_wrapper:[CNode]44:190+2033_2032_1_construct_wrapper:[CNode]44:190"Add*#b`:shape1z shape:shape1,*0 output_namesZoutputzscalar:List[value1,],*4 input_namesZxZyzscalar:List[value1,value2,],:ZDefault/backbone-MobileNetV2Backbone/features-SequentialCell/13-InvertedResidual/Add-op150  +2033_2032_1_construct_wrapper:[CNode]44:190 B2033_2032_1_construct_wrapper:features.14.conv.0.features.0.weight(2033_2032_1_construct_wrapper:output:191(2033_2032_1_construct_wrapper:output:191"Conv2D*$b:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*" out_channelz scalar:value0*! pad_mode*padz scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/12-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/0-Conv2d/Conv2D-op151  (2033_2032_1_construct_wrapper:output:191 A2033_2032_1_construct_wrapper:features.14.conv.0.features.1.gamma @2033_2032_1_construct_wrapper:features.14.conv.0.features.1.beta G2033_2032_1_construct_wrapper:features.14.conv.0.features.1.moving_mean K2033_2032_1_construct_wrapper:features.14.conv.0.features.1.moving_variance$2033_2032_1_construct_wrapper:38:192$2033_2032_1_construct_wrapper:38:192" BatchNorm*b:shape1b :shape2b :shape3b :shape4b :shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:Default/backbone-MobileNetV2Backbone/features-SequentialCell/12-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/BatchNorm-op152 <[ValueNode]1(0):193"Constant* valuez scalar:value0  $2033_2032_1_construct_wrapper:38:192 [ValueNode]1(0):193*2033_2032_1_construct_wrapper:[CNode]2:194*2033_2032_1_construct_wrapper:[CNode]2:194" TupleGetItem*$b:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op153  *2033_2032_1_construct_wrapper:[CNode]2:194+2033_2032_1_construct_wrapper:[CNode]45:195+2033_2032_1_construct_wrapper:[CNode]45:195"ReLU6*$b:shape1z shape:shape1,*0 output_namesZoutputzscalar:List[value1,],** input_namesZxzscalar:List[value1,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/14-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/2-ReLU6/ReLU6-op154  +2033_2032_1_construct_wrapper:[CNode]45:195 B2033_2032_1_construct_wrapper:features.14.conv.1.features.0.weight(2033_2032_1_construct_wrapper:output:196(2033_2032_1_construct_wrapper:output:196"Conv2D*$b:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*" out_channelz scalar:value0*! pad_mode*padz scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/14-InvertedResidual/conv-SequentialCell/1-ConvBNReLU/features-SequentialCell/0-Conv2d/Conv2D-op155  (2033_2032_1_construct_wrapper:output:196 A2033_2032_1_construct_wrapper:features.14.conv.1.features.1.gamma @2033_2032_1_construct_wrapper:features.14.conv.1.features.1.beta G2033_2032_1_construct_wrapper:features.14.conv.1.features.1.moving_mean K2033_2032_1_construct_wrapper:features.14.conv.1.features.1.moving_variance$2033_2032_1_construct_wrapper:38:197$2033_2032_1_construct_wrapper:38:197" BatchNorm*b:shape1b :shape2b :shape3b :shape4b :shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:Default/backbone-MobileNetV2Backbone/features-SequentialCell/12-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/BatchNorm-op156 <[ValueNode]1(0):198"Constant* valuez scalar:value0  $2033_2032_1_construct_wrapper:38:197 [ValueNode]1(0):198*2033_2032_1_construct_wrapper:[CNode]2:199*2033_2032_1_construct_wrapper:[CNode]2:199" TupleGetItem*$b:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op157  *2033_2032_1_construct_wrapper:[CNode]2:199+2033_2032_1_construct_wrapper:[CNode]46:200+2033_2032_1_construct_wrapper:[CNode]46:200"ReLU6*$b:shape1z shape:shape1,*0 output_namesZoutputzscalar:List[value1,],** input_namesZxzscalar:List[value1,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/14-InvertedResidual/conv-SequentialCell/1-ConvBNReLU/features-SequentialCell/2-ReLU6/ReLU6-op158  +2033_2032_1_construct_wrapper:[CNode]46:200 72033_2032_1_construct_wrapper:features.14.conv.2.weight(2033_2032_1_construct_wrapper:output:201(2033_2032_1_construct_wrapper:output:201"Conv2D*$b:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*" out_channelz scalar:value0*" pad_mode*samez scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:zDefault/backbone-MobileNetV2Backbone/features-SequentialCell/14-InvertedResidual/conv-SequentialCell/2-Conv2d/Conv2D-op159  (2033_2032_1_construct_wrapper:output:201 62033_2032_1_construct_wrapper:features.14.conv.3.gamma 52033_2032_1_construct_wrapper:features.14.conv.3.beta <2033_2032_1_construct_wrapper:features.14.conv.3.moving_mean @2033_2032_1_construct_wrapper:features.14.conv.3.moving_variance$2033_2032_1_construct_wrapper:47:202$2033_2032_1_construct_wrapper:47:202" BatchNorm*b:shape1b :shape2b :shape3b :shape4b :shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:Default/backbone-MobileNetV2Backbone/features-SequentialCell/14-InvertedResidual/conv-SequentialCell/3-BatchNorm2d/BatchNorm-op160 <[ValueNode]1(0):203"Constant* valuez scalar:value0  $2033_2032_1_construct_wrapper:47:202 [ValueNode]1(0):203*2033_2032_1_construct_wrapper:[CNode]2:204*2033_2032_1_construct_wrapper:[CNode]2:204" TupleGetItem*$b:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op161  *2033_2032_1_construct_wrapper:[CNode]2:204 B2033_2032_1_construct_wrapper:features.15.conv.0.features.0.weight(2033_2032_1_construct_wrapper:output:205(2033_2032_1_construct_wrapper:output:205"Conv2D*$b:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*" out_channelz scalar:value0*! pad_mode*padz scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/15-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/0-Conv2d/Conv2D-op162  (2033_2032_1_construct_wrapper:output:205 A2033_2032_1_construct_wrapper:features.15.conv.0.features.1.gamma @2033_2032_1_construct_wrapper:features.15.conv.0.features.1.beta G2033_2032_1_construct_wrapper:features.15.conv.0.features.1.moving_mean K2033_2032_1_construct_wrapper:features.15.conv.0.features.1.moving_variance$2033_2032_1_construct_wrapper:48:206$2033_2032_1_construct_wrapper:48:206" BatchNorm*b:shape1b :shape2b :shape3b :shape4b :shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:Default/backbone-MobileNetV2Backbone/features-SequentialCell/15-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/BatchNorm-op163 <[ValueNode]1(0):207"Constant* valuez scalar:value0  $2033_2032_1_construct_wrapper:48:206 [ValueNode]1(0):207*2033_2032_1_construct_wrapper:[CNode]2:208*2033_2032_1_construct_wrapper:[CNode]2:208" TupleGetItem*$b:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op164  *2033_2032_1_construct_wrapper:[CNode]2:208+2033_2032_1_construct_wrapper:[CNode]49:209+2033_2032_1_construct_wrapper:[CNode]49:209"ReLU6*$b:shape1z shape:shape1,*0 output_namesZoutputzscalar:List[value1,],** input_namesZxzscalar:List[value1,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/15-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/2-ReLU6/ReLU6-op165  +2033_2032_1_construct_wrapper:[CNode]49:209 B2033_2032_1_construct_wrapper:features.15.conv.1.features.0.weight(2033_2032_1_construct_wrapper:output:210(2033_2032_1_construct_wrapper:output:210"Conv2D*$b:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*" out_channelz scalar:value0*! pad_mode*padz scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/15-InvertedResidual/conv-SequentialCell/1-ConvBNReLU/features-SequentialCell/0-Conv2d/Conv2D-op166  (2033_2032_1_construct_wrapper:output:210 A2033_2032_1_construct_wrapper:features.15.conv.1.features.1.gamma @2033_2032_1_construct_wrapper:features.15.conv.1.features.1.beta G2033_2032_1_construct_wrapper:features.15.conv.1.features.1.moving_mean K2033_2032_1_construct_wrapper:features.15.conv.1.features.1.moving_variance$2033_2032_1_construct_wrapper:48:211$2033_2032_1_construct_wrapper:48:211" BatchNorm*b:shape1b :shape2b :shape3b :shape4b :shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:Default/backbone-MobileNetV2Backbone/features-SequentialCell/15-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/BatchNorm-op167 <[ValueNode]1(0):212"Constant* valuez scalar:value0  $2033_2032_1_construct_wrapper:48:211 [ValueNode]1(0):212*2033_2032_1_construct_wrapper:[CNode]2:213*2033_2032_1_construct_wrapper:[CNode]2:213" TupleGetItem*$b:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op168  *2033_2032_1_construct_wrapper:[CNode]2:213+2033_2032_1_construct_wrapper:[CNode]50:214+2033_2032_1_construct_wrapper:[CNode]50:214"ReLU6*$b:shape1z shape:shape1,*0 output_namesZoutputzscalar:List[value1,],** input_namesZxzscalar:List[value1,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/15-InvertedResidual/conv-SequentialCell/1-ConvBNReLU/features-SequentialCell/2-ReLU6/ReLU6-op169  +2033_2032_1_construct_wrapper:[CNode]50:214 72033_2032_1_construct_wrapper:features.15.conv.2.weight(2033_2032_1_construct_wrapper:output:215(2033_2032_1_construct_wrapper:output:215"Conv2D*$b:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*" out_channelz scalar:value0*" pad_mode*samez scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:zDefault/backbone-MobileNetV2Backbone/features-SequentialCell/15-InvertedResidual/conv-SequentialCell/2-Conv2d/Conv2D-op170  (2033_2032_1_construct_wrapper:output:215 62033_2032_1_construct_wrapper:features.15.conv.3.gamma 52033_2032_1_construct_wrapper:features.15.conv.3.beta <2033_2032_1_construct_wrapper:features.15.conv.3.moving_mean @2033_2032_1_construct_wrapper:features.15.conv.3.moving_variance$2033_2032_1_construct_wrapper:47:216$2033_2032_1_construct_wrapper:47:216" BatchNorm*b:shape1b :shape2b :shape3b :shape4b :shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:Default/backbone-MobileNetV2Backbone/features-SequentialCell/14-InvertedResidual/conv-SequentialCell/3-BatchNorm2d/BatchNorm-op171 <[ValueNode]1(0):217"Constant* valuez scalar:value0  $2033_2032_1_construct_wrapper:47:216 [ValueNode]1(0):217*2033_2032_1_construct_wrapper:[CNode]2:218*2033_2032_1_construct_wrapper:[CNode]2:218" TupleGetItem*$b:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op172  *2033_2032_1_construct_wrapper:[CNode]2:204 *2033_2032_1_construct_wrapper:[CNode]2:218+2033_2032_1_construct_wrapper:[CNode]51:219+2033_2032_1_construct_wrapper:[CNode]51:219"Add*$b:shape1z shape:shape1,*0 output_namesZoutputzscalar:List[value1,],*4 input_namesZxZyzscalar:List[value1,value2,],:ZDefault/backbone-MobileNetV2Backbone/features-SequentialCell/15-InvertedResidual/Add-op173  +2033_2032_1_construct_wrapper:[CNode]51:219 B2033_2032_1_construct_wrapper:features.16.conv.0.features.0.weight(2033_2032_1_construct_wrapper:output:220(2033_2032_1_construct_wrapper:output:220"Conv2D*$b:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*" out_channelz scalar:value0*! pad_mode*padz scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/15-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/0-Conv2d/Conv2D-op174  (2033_2032_1_construct_wrapper:output:220 A2033_2032_1_construct_wrapper:features.16.conv.0.features.1.gamma @2033_2032_1_construct_wrapper:features.16.conv.0.features.1.beta G2033_2032_1_construct_wrapper:features.16.conv.0.features.1.moving_mean K2033_2032_1_construct_wrapper:features.16.conv.0.features.1.moving_variance$2033_2032_1_construct_wrapper:48:221$2033_2032_1_construct_wrapper:48:221" BatchNorm*b:shape1b :shape2b :shape3b :shape4b :shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:Default/backbone-MobileNetV2Backbone/features-SequentialCell/15-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/BatchNorm-op175 <[ValueNode]1(0):222"Constant* valuez scalar:value0  $2033_2032_1_construct_wrapper:48:221 [ValueNode]1(0):222*2033_2032_1_construct_wrapper:[CNode]2:223*2033_2032_1_construct_wrapper:[CNode]2:223" TupleGetItem*$b:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op176  *2033_2032_1_construct_wrapper:[CNode]2:223+2033_2032_1_construct_wrapper:[CNode]52:224+2033_2032_1_construct_wrapper:[CNode]52:224"ReLU6*$b:shape1z shape:shape1,*0 output_namesZoutputzscalar:List[value1,],** input_namesZxzscalar:List[value1,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/16-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/2-ReLU6/ReLU6-op177  +2033_2032_1_construct_wrapper:[CNode]52:224 B2033_2032_1_construct_wrapper:features.16.conv.1.features.0.weight(2033_2032_1_construct_wrapper:output:225(2033_2032_1_construct_wrapper:output:225"Conv2D*$b:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*" out_channelz scalar:value0*! pad_mode*padz scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/15-InvertedResidual/conv-SequentialCell/1-ConvBNReLU/features-SequentialCell/0-Conv2d/Conv2D-op178  (2033_2032_1_construct_wrapper:output:225 A2033_2032_1_construct_wrapper:features.16.conv.1.features.1.gamma @2033_2032_1_construct_wrapper:features.16.conv.1.features.1.beta G2033_2032_1_construct_wrapper:features.16.conv.1.features.1.moving_mean K2033_2032_1_construct_wrapper:features.16.conv.1.features.1.moving_variance$2033_2032_1_construct_wrapper:48:226$2033_2032_1_construct_wrapper:48:226" BatchNorm*b:shape1b :shape2b :shape3b :shape4b :shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:Default/backbone-MobileNetV2Backbone/features-SequentialCell/15-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/BatchNorm-op179 <[ValueNode]1(0):227"Constant* valuez scalar:value0  $2033_2032_1_construct_wrapper:48:226 [ValueNode]1(0):227*2033_2032_1_construct_wrapper:[CNode]2:228*2033_2032_1_construct_wrapper:[CNode]2:228" TupleGetItem*$b:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op180  *2033_2032_1_construct_wrapper:[CNode]2:228+2033_2032_1_construct_wrapper:[CNode]53:229+2033_2032_1_construct_wrapper:[CNode]53:229"ReLU6*$b:shape1z shape:shape1,*0 output_namesZoutputzscalar:List[value1,],** input_namesZxzscalar:List[value1,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/16-InvertedResidual/conv-SequentialCell/1-ConvBNReLU/features-SequentialCell/2-ReLU6/ReLU6-op181  +2033_2032_1_construct_wrapper:[CNode]53:229 72033_2032_1_construct_wrapper:features.16.conv.2.weight(2033_2032_1_construct_wrapper:output:230(2033_2032_1_construct_wrapper:output:230"Conv2D*$b:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*" out_channelz scalar:value0*" pad_mode*samez scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:zDefault/backbone-MobileNetV2Backbone/features-SequentialCell/15-InvertedResidual/conv-SequentialCell/2-Conv2d/Conv2D-op182  (2033_2032_1_construct_wrapper:output:230 62033_2032_1_construct_wrapper:features.16.conv.3.gamma 52033_2032_1_construct_wrapper:features.16.conv.3.beta <2033_2032_1_construct_wrapper:features.16.conv.3.moving_mean @2033_2032_1_construct_wrapper:features.16.conv.3.moving_variance$2033_2032_1_construct_wrapper:47:231$2033_2032_1_construct_wrapper:47:231" BatchNorm*b:shape1b :shape2b :shape3b :shape4b :shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:Default/backbone-MobileNetV2Backbone/features-SequentialCell/14-InvertedResidual/conv-SequentialCell/3-BatchNorm2d/BatchNorm-op183 <[ValueNode]1(0):232"Constant* valuez scalar:value0  $2033_2032_1_construct_wrapper:47:231 [ValueNode]1(0):232*2033_2032_1_construct_wrapper:[CNode]2:233*2033_2032_1_construct_wrapper:[CNode]2:233" TupleGetItem*$b:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op184  +2033_2032_1_construct_wrapper:[CNode]51:219 *2033_2032_1_construct_wrapper:[CNode]2:233+2033_2032_1_construct_wrapper:[CNode]54:234+2033_2032_1_construct_wrapper:[CNode]54:234"Add*$b:shape1z shape:shape1,*0 output_namesZoutputzscalar:List[value1,],*4 input_namesZxZyzscalar:List[value1,value2,],:ZDefault/backbone-MobileNetV2Backbone/features-SequentialCell/16-InvertedResidual/Add-op185  +2033_2032_1_construct_wrapper:[CNode]54:234 B2033_2032_1_construct_wrapper:features.17.conv.0.features.0.weight(2033_2032_1_construct_wrapper:output:235(2033_2032_1_construct_wrapper:output:235"Conv2D*$b:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*" out_channelz scalar:value0*! pad_mode*padz scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/15-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/0-Conv2d/Conv2D-op186  (2033_2032_1_construct_wrapper:output:235 A2033_2032_1_construct_wrapper:features.17.conv.0.features.1.gamma @2033_2032_1_construct_wrapper:features.17.conv.0.features.1.beta G2033_2032_1_construct_wrapper:features.17.conv.0.features.1.moving_mean K2033_2032_1_construct_wrapper:features.17.conv.0.features.1.moving_variance$2033_2032_1_construct_wrapper:48:236$2033_2032_1_construct_wrapper:48:236" BatchNorm*b:shape1b :shape2b :shape3b :shape4b :shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:Default/backbone-MobileNetV2Backbone/features-SequentialCell/15-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/BatchNorm-op187 <[ValueNode]1(0):237"Constant* valuez scalar:value0  $2033_2032_1_construct_wrapper:48:236 [ValueNode]1(0):237*2033_2032_1_construct_wrapper:[CNode]2:238*2033_2032_1_construct_wrapper:[CNode]2:238" TupleGetItem*$b:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op188  *2033_2032_1_construct_wrapper:[CNode]2:238+2033_2032_1_construct_wrapper:[CNode]55:239+2033_2032_1_construct_wrapper:[CNode]55:239"ReLU6*$b:shape1z shape:shape1,*0 output_namesZoutputzscalar:List[value1,],** input_namesZxzscalar:List[value1,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/17-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/2-ReLU6/ReLU6-op189  +2033_2032_1_construct_wrapper:[CNode]55:239 B2033_2032_1_construct_wrapper:features.17.conv.1.features.0.weight(2033_2032_1_construct_wrapper:output:240(2033_2032_1_construct_wrapper:output:240"Conv2D*$b:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*" out_channelz scalar:value0*! pad_mode*padz scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/15-InvertedResidual/conv-SequentialCell/1-ConvBNReLU/features-SequentialCell/0-Conv2d/Conv2D-op190  (2033_2032_1_construct_wrapper:output:240 A2033_2032_1_construct_wrapper:features.17.conv.1.features.1.gamma @2033_2032_1_construct_wrapper:features.17.conv.1.features.1.beta G2033_2032_1_construct_wrapper:features.17.conv.1.features.1.moving_mean K2033_2032_1_construct_wrapper:features.17.conv.1.features.1.moving_variance$2033_2032_1_construct_wrapper:48:241$2033_2032_1_construct_wrapper:48:241" BatchNorm*b:shape1b :shape2b :shape3b :shape4b :shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:Default/backbone-MobileNetV2Backbone/features-SequentialCell/15-InvertedResidual/conv-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/BatchNorm-op191 <[ValueNode]1(0):242"Constant* valuez scalar:value0  $2033_2032_1_construct_wrapper:48:241 [ValueNode]1(0):242*2033_2032_1_construct_wrapper:[CNode]2:243*2033_2032_1_construct_wrapper:[CNode]2:243" TupleGetItem*$b:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op192  *2033_2032_1_construct_wrapper:[CNode]2:243+2033_2032_1_construct_wrapper:[CNode]56:244+2033_2032_1_construct_wrapper:[CNode]56:244"ReLU6*$b:shape1z shape:shape1,*0 output_namesZoutputzscalar:List[value1,],** input_namesZxzscalar:List[value1,],:Default/backbone-MobileNetV2Backbone/features-SequentialCell/17-InvertedResidual/conv-SequentialCell/1-ConvBNReLU/features-SequentialCell/2-ReLU6/ReLU6-op193  +2033_2032_1_construct_wrapper:[CNode]56:244 72033_2032_1_construct_wrapper:features.17.conv.2.weight(2033_2032_1_construct_wrapper:output:245(2033_2032_1_construct_wrapper:output:245"Conv2D*$b:shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*" out_channelz scalar:value0*" pad_mode*samez scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:zDefault/backbone-MobileNetV2Backbone/features-SequentialCell/17-InvertedResidual/conv-SequentialCell/2-Conv2d/Conv2D-op194  (2033_2032_1_construct_wrapper:output:245 62033_2032_1_construct_wrapper:features.17.conv.3.gamma 52033_2032_1_construct_wrapper:features.17.conv.3.beta <2033_2032_1_construct_wrapper:features.17.conv.3.moving_mean @2033_2032_1_construct_wrapper:features.17.conv.3.moving_variance+2033_2032_1_construct_wrapper:[CNode]57:246+2033_2032_1_construct_wrapper:[CNode]57:246" BatchNorm*b:shape1b :shape2b :shape3b :shape4b :shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:Default/backbone-MobileNetV2Backbone/features-SequentialCell/17-InvertedResidual/conv-SequentialCell/3-BatchNorm2d/BatchNorm-op195 <[ValueNode]1(0):247"Constant* valuez scalar:value0  +2033_2032_1_construct_wrapper:[CNode]57:246 [ValueNode]1(0):247*2033_2032_1_construct_wrapper:[CNode]2:248*2033_2032_1_construct_wrapper:[CNode]2:248" TupleGetItem*$b:shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op196  *2033_2032_1_construct_wrapper:[CNode]2:248 ;2033_2032_1_construct_wrapper:features.18.features.0.weight(2033_2032_1_construct_wrapper:output:249(2033_2032_1_construct_wrapper:output:249"Conv2D*$b :shape1z shape:shape1,*B pad_listPPPPz+scalar:Tuple[value1,value2,value3,value4,],* groupsz scalar:value0* format*NCHWz scalar:value0* groupz scalar:value0*0 output_namesZoutputzscalar:List[value1,],*B dilationPPPPz+scalar:Tuple[value1,value2,value3,value4,],* modez scalar:value0*4 input_namesZxZwzscalar:List[value1,value2,],*3 kernel_sizePPzscalar:Tuple[value1,value2,],*" out_channel z scalar:value0*! pad_mode*padz scalar:value0*= padPPPPz+scalar:Tuple[value1,value2,value3,value4,],*@ stridePPPPz+scalar:Tuple[value1,value2,value3,value4,],:xDefault/backbone-MobileNetV2Backbone/features-SequentialCell/18-ConvBNReLU/features-SequentialCell/0-Conv2d/Conv2D-op197  (2033_2032_1_construct_wrapper:output:249 :2033_2032_1_construct_wrapper:features.18.features.1.gamma 92033_2032_1_construct_wrapper:features.18.features.1.beta @2033_2032_1_construct_wrapper:features.18.features.1.moving_mean D2033_2032_1_construct_wrapper:features.18.features.1.moving_variance+2033_2032_1_construct_wrapper:[CNode]58:250+2033_2032_1_construct_wrapper:[CNode]58:250" BatchNorm*b :shape1b  :shape2b  :shape3b  :shape4b  :shape5z1shape:Tuple[shape1,shape2,shape3,shape4,shape5,],* output_namesZyZ batch_meanZbatch_varianceZreserve_space_1Zreserve_space_2z1scalar:List[value1,value2,value3,value4,value5,],*e input_namesZxZscaleZoffsetZmeanZvariancez1scalar:List[value1,value2,value3,value4,value5,],* format*NCHWz scalar:value0*! momentum=z scalar:value0*! is_trainingz scalar:value0 * epsilon'7z scalar:value0:Default/backbone-MobileNetV2Backbone/features-SequentialCell/18-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/BatchNorm-op198 <[ValueNode]1(0):251"Constant* valuez scalar:value0  +2033_2032_1_construct_wrapper:[CNode]58:250 [ValueNode]1(0):251*2033_2032_1_construct_wrapper:[CNode]2:252*2033_2032_1_construct_wrapper:[CNode]2:252" TupleGetItem*$b :shape1z shape:shape1,:Default/backbone-MobileNetV2Backbone/features-SequentialCell/0-ConvBNReLU/features-SequentialCell/1-BatchNorm2d/TupleGetItem-op199  *2033_2032_1_construct_wrapper:[CNode]2:252+2033_2032_1_construct_wrapper:[CNode]59:253+2033_2032_1_construct_wrapper:[CNode]59:253"ReLU6*$b :shape1z shape:shape1,*0 output_namesZoutputzscalar:List[value1,],** input_namesZxzscalar:List[value1,],:vDefault/backbone-MobileNetV2Backbone/features-SequentialCell/18-ConvBNReLU/features-SequentialCell/2-ReLU6/ReLU6-op200 T[ValueNode]60((2, 3)):254"Constant*- valuePPzscalar:Tuple[value1,value2,],  +2033_2032_1_construct_wrapper:[CNode]59:253 [ValueNode]60((2, 3)):254#2033_2032_1_construct_wrapper:x:255#2033_2032_1_construct_wrapper:x:255" ReduceMean* b :shape1z shape:shape1,*+ output_namesZyzscalar:List[value1,],* keep_dimsz scalar:value0 *= input_namesZinput_xZaxiszscalar:List[value1,value2,],:TDefault/head-MobileNetV2Head/head-SequentialCell/0-GlobalAvgPooling/ReduceMean-op201  #2033_2032_1_construct_wrapper:x:255 +2033_2032_1_construct_wrapper:head.1.weight#2033_2032_1_construct_wrapper:x:256#2033_2032_1_construct_wrapper:x:256"MatMul* b:shape1z shape:shape1,*" transpose_x1z scalar:value0 *0 output_namesZoutputzscalar:List[value1,],*" transpose_x2z scalar:value0 *6 input_namesZx1Zx2zscalar:List[value1,value2,],*! transpose_az scalar:value0 *! transpose_bz scalar:value0 :EDefault/head-MobileNetV2Head/head-SequentialCell/1-Dense/MatMul-op202  #2033_2032_1_construct_wrapper:x:256 )2033_2032_1_construct_wrapper:head.1.bias#2033_2032_1_construct_wrapper:x:257#2033_2032_1_construct_wrapper:x:257"BiasAdd* b:shape1z shape:shape1,*0 output_namesZoutputzscalar:List[value1,],* format*NCHWz scalar:value0*4 input_namesZxZbzscalar:List[value1,value2,],:FDefault/head-MobileNetV2Head/head-SequentialCell/1-Dense/BiasAdd-op203  #2033_2032_1_construct_wrapper:x:257+2033_2032_1_construct_wrapper:[CNode]61:259#2033_2032_1_construct_wrapper:x:258"Softmax* b:shape1z shape:shape1,*0 output_namesZoutputzscalar:List[value1,],*, axisPzscalar:Tuple[value1,],** 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