| Shad Ansari | 47432b6 | 2021-09-27 22:46:25 +0000 | [diff] [blame] | 1 | <?xml version="1.0" ?> |
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| 502 | <dim>160</dim> |
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| 558 | <dim>1</dim> |
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| 563 | <port id="1" precision="FP16"> |
| 564 | <dim>1</dim> |
| 565 | <dim>8</dim> |
| 566 | <dim>1</dim> |
| 567 | <dim>1</dim> |
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| 569 | </input> |
| 570 | <output> |
| 571 | <port id="2" names="bottleneck1_2/dim_red/conv" precision="FP16"> |
| 572 | <dim>1</dim> |
| 573 | <dim>8</dim> |
| 574 | <dim>160</dim> |
| 575 | <dim>272</dim> |
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| 579 | <layer id="33" name="bottleneck1_2/dim_red/fn/weights3112040508" type="Const" version="opset1"> |
| 580 | <data element_type="f32" offset="2332" shape="1" size="4"/> |
| 581 | <output> |
| 582 | <port id="0" precision="FP32"> |
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| 587 | <layer id="34" name="bottleneck1_2/dim_red/fn" type="PReLU" version="opset1"> |
| 588 | <input> |
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| 590 | <dim>1</dim> |
| 591 | <dim>8</dim> |
| 592 | <dim>160</dim> |
| 593 | <dim>272</dim> |
| 594 | </port> |
| 595 | <port id="1" precision="FP32"> |
| 596 | <dim>1</dim> |
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| 598 | </input> |
| 599 | <output> |
| 600 | <port id="2" names="bottleneck1_2/dim_red/conv" precision="FP16"> |
| 601 | <dim>1</dim> |
| 602 | <dim>8</dim> |
| 603 | <dim>160</dim> |
| 604 | <dim>272</dim> |
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| 606 | </output> |
| 607 | </layer> |
| 608 | <layer id="35" name="bottleneck1_2/inner/dw1/bn/mean/Fused_Mul__copy" type="Const" version="opset1"> |
| 609 | <data element_type="f16" offset="3600" shape="8, 1, 1, 3, 3" size="144"/> |
| 610 | <output> |
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| 614 | <dim>1</dim> |
| 615 | <dim>3</dim> |
| 616 | <dim>3</dim> |
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| 618 | </output> |
| 619 | </layer> |
| 620 | <layer id="36" name="bottleneck1_2/inner/dw1/conv" type="GroupConvolution" version="opset1"> |
| 621 | <data auto_pad="explicit" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" strides="1, 1"/> |
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| 624 | <dim>1</dim> |
| 625 | <dim>8</dim> |
| 626 | <dim>160</dim> |
| 627 | <dim>272</dim> |
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| 630 | <dim>8</dim> |
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| 632 | <dim>1</dim> |
| 633 | <dim>3</dim> |
| 634 | <dim>3</dim> |
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| 638 | <port id="2" precision="FP16"> |
| 639 | <dim>1</dim> |
| 640 | <dim>8</dim> |
| 641 | <dim>160</dim> |
| 642 | <dim>272</dim> |
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| 648 | <output> |
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| 652 | <dim>1</dim> |
| 653 | <dim>1</dim> |
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| 655 | </output> |
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| 657 | <layer id="38" name="bottleneck1_2/inner/dw1/bn/variance/Fused_Add_" type="Add" version="opset1"> |
| 658 | <data auto_broadcast="numpy"/> |
| 659 | <input> |
| 660 | <port id="0" precision="FP16"> |
| 661 | <dim>1</dim> |
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| 663 | <dim>160</dim> |
| 664 | <dim>272</dim> |
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| 666 | <port id="1" precision="FP16"> |
| 667 | <dim>1</dim> |
| 668 | <dim>8</dim> |
| 669 | <dim>1</dim> |
| 670 | <dim>1</dim> |
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| 673 | <output> |
| 674 | <port id="2" names="bottleneck1_2/inner/dw1/conv" precision="FP16"> |
| 675 | <dim>1</dim> |
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| 677 | <dim>160</dim> |
| 678 | <dim>272</dim> |
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| 682 | <layer id="39" name="bottleneck1_2/inner/dw1/fn/weights3080440244" type="Const" version="opset1"> |
| 683 | <data element_type="f32" offset="2332" shape="1" size="4"/> |
| 684 | <output> |
| 685 | <port id="0" precision="FP32"> |
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| 690 | <layer id="40" name="bottleneck1_2/inner/dw1/fn" type="PReLU" version="opset1"> |
| 691 | <input> |
| 692 | <port id="0" precision="FP16"> |
| 693 | <dim>1</dim> |
| 694 | <dim>8</dim> |
| 695 | <dim>160</dim> |
| 696 | <dim>272</dim> |
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| 698 | <port id="1" precision="FP32"> |
| 699 | <dim>1</dim> |
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| 702 | <output> |
| 703 | <port id="2" names="bottleneck1_2/inner/dw1/conv" precision="FP16"> |
| 704 | <dim>1</dim> |
| 705 | <dim>8</dim> |
| 706 | <dim>160</dim> |
| 707 | <dim>272</dim> |
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| 709 | </output> |
| 710 | </layer> |
| 711 | <layer id="41" name="bottleneck1_2/dim_inc/bn/mean/Fused_Mul__copy" type="Const" version="opset1"> |
| 712 | <data element_type="f16" offset="3760" shape="32, 8, 1, 1" size="512"/> |
| 713 | <output> |
| 714 | <port id="0" precision="FP16"> |
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| 717 | <dim>1</dim> |
| 718 | <dim>1</dim> |
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| 720 | </output> |
| 721 | </layer> |
| 722 | <layer id="42" name="bottleneck1_2/dim_inc/conv" type="Convolution" version="opset1"> |
| 723 | <data auto_pad="explicit" dilations="1, 1" pads_begin="0, 0" pads_end="0, 0" strides="1, 1"/> |
| 724 | <input> |
| 725 | <port id="0" precision="FP16"> |
| 726 | <dim>1</dim> |
| 727 | <dim>8</dim> |
| 728 | <dim>160</dim> |
| 729 | <dim>272</dim> |
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| 731 | <port id="1" precision="FP16"> |
| 732 | <dim>32</dim> |
| 733 | <dim>8</dim> |
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| 735 | <dim>1</dim> |
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| 737 | </input> |
| 738 | <output> |
| 739 | <port id="2" precision="FP16"> |
| 740 | <dim>1</dim> |
| 741 | <dim>32</dim> |
| 742 | <dim>160</dim> |
| 743 | <dim>272</dim> |
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| 747 | <layer id="43" name="data_add_2369723702" type="Const" version="opset1"> |
| 748 | <data element_type="f16" offset="4272" shape="1, 32, 1, 1" size="64"/> |
| 749 | <output> |
| 750 | <port id="0" precision="FP16"> |
| 751 | <dim>1</dim> |
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| 753 | <dim>1</dim> |
| 754 | <dim>1</dim> |
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| 758 | <layer id="44" name="bottleneck1_2/dim_inc/bn/variance/Fused_Add_" type="Add" version="opset1"> |
| 759 | <data auto_broadcast="numpy"/> |
| 760 | <input> |
| 761 | <port id="0" precision="FP16"> |
| 762 | <dim>1</dim> |
| 763 | <dim>32</dim> |
| 764 | <dim>160</dim> |
| 765 | <dim>272</dim> |
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| 767 | <port id="1" precision="FP16"> |
| 768 | <dim>1</dim> |
| 769 | <dim>32</dim> |
| 770 | <dim>1</dim> |
| 771 | <dim>1</dim> |
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| 774 | <output> |
| 775 | <port id="2" names="bottleneck1_2/dim_inc/conv" precision="FP16"> |
| 776 | <dim>1</dim> |
| 777 | <dim>32</dim> |
| 778 | <dim>160</dim> |
| 779 | <dim>272</dim> |
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| 783 | <layer id="45" name="bottleneck1_2/add" type="Add" version="opset1"> |
| 784 | <data auto_broadcast="numpy"/> |
| 785 | <input> |
| 786 | <port id="0" precision="FP16"> |
| 787 | <dim>1</dim> |
| 788 | <dim>32</dim> |
| 789 | <dim>160</dim> |
| 790 | <dim>272</dim> |
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| 792 | <port id="1" precision="FP16"> |
| 793 | <dim>1</dim> |
| 794 | <dim>32</dim> |
| 795 | <dim>160</dim> |
| 796 | <dim>272</dim> |
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| 798 | </input> |
| 799 | <output> |
| 800 | <port id="2" names="bottleneck1_2/add" precision="FP16"> |
| 801 | <dim>1</dim> |
| 802 | <dim>32</dim> |
| 803 | <dim>160</dim> |
| 804 | <dim>272</dim> |
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| 808 | <layer id="46" name="bottleneck1_2/fn/weights3113640172" type="Const" version="opset1"> |
| 809 | <data element_type="f32" offset="2332" shape="1" size="4"/> |
| 810 | <output> |
| 811 | <port id="0" precision="FP32"> |
| 812 | <dim>1</dim> |
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| 816 | <layer id="47" name="bottleneck1_2/fn" type="PReLU" version="opset1"> |
| 817 | <input> |
| 818 | <port id="0" precision="FP16"> |
| 819 | <dim>1</dim> |
| 820 | <dim>32</dim> |
| 821 | <dim>160</dim> |
| 822 | <dim>272</dim> |
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| 824 | <port id="1" precision="FP32"> |
| 825 | <dim>1</dim> |
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| 827 | </input> |
| 828 | <output> |
| 829 | <port id="2" names="bottleneck1_2/add" precision="FP16"> |
| 830 | <dim>1</dim> |
| 831 | <dim>32</dim> |
| 832 | <dim>160</dim> |
| 833 | <dim>272</dim> |
| 834 | </port> |
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| 836 | </layer> |
| 837 | <layer id="48" name="bottleneck1_3/dim_red/bn/mean/Fused_Mul__copy" type="Const" version="opset1"> |
| 838 | <data element_type="f16" offset="4336" shape="8, 32, 1, 1" size="512"/> |
| 839 | <output> |
| 840 | <port id="0" precision="FP16"> |
| 841 | <dim>8</dim> |
| 842 | <dim>32</dim> |
| 843 | <dim>1</dim> |
| 844 | <dim>1</dim> |
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| 848 | <layer id="49" name="bottleneck1_3/dim_red/conv" type="Convolution" version="opset1"> |
| 849 | <data auto_pad="explicit" dilations="1, 1" pads_begin="0, 0" pads_end="0, 0" strides="1, 1"/> |
| 850 | <input> |
| 851 | <port id="0" precision="FP16"> |
| 852 | <dim>1</dim> |
| 853 | <dim>32</dim> |
| 854 | <dim>160</dim> |
| 855 | <dim>272</dim> |
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| 857 | <port id="1" precision="FP16"> |
| 858 | <dim>8</dim> |
| 859 | <dim>32</dim> |
| 860 | <dim>1</dim> |
| 861 | <dim>1</dim> |
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| 864 | <output> |
| 865 | <port id="2" precision="FP16"> |
| 866 | <dim>1</dim> |
| 867 | <dim>8</dim> |
| 868 | <dim>160</dim> |
| 869 | <dim>272</dim> |
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| 873 | <layer id="50" name="data_add_2370523710" type="Const" version="opset1"> |
| 874 | <data element_type="f16" offset="4848" shape="1, 8, 1, 1" size="16"/> |
| 875 | <output> |
| 876 | <port id="0" precision="FP16"> |
| 877 | <dim>1</dim> |
| 878 | <dim>8</dim> |
| 879 | <dim>1</dim> |
| 880 | <dim>1</dim> |
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| 884 | <layer id="51" name="bottleneck1_3/dim_red/bn/variance/Fused_Add_" type="Add" version="opset1"> |
| 885 | <data auto_broadcast="numpy"/> |
| 886 | <input> |
| 887 | <port id="0" precision="FP16"> |
| 888 | <dim>1</dim> |
| 889 | <dim>8</dim> |
| 890 | <dim>160</dim> |
| 891 | <dim>272</dim> |
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| 893 | <port id="1" precision="FP16"> |
| 894 | <dim>1</dim> |
| 895 | <dim>8</dim> |
| 896 | <dim>1</dim> |
| 897 | <dim>1</dim> |
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| 900 | <output> |
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| 902 | <dim>1</dim> |
| 903 | <dim>8</dim> |
| 904 | <dim>160</dim> |
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| 909 | <layer id="52" name="bottleneck1_3/dim_red/fn/weights3091240304" type="Const" version="opset1"> |
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| 912 | <port id="0" precision="FP32"> |
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| 917 | <layer id="53" name="bottleneck1_3/dim_red/fn" type="PReLU" version="opset1"> |
| 918 | <input> |
| 919 | <port id="0" precision="FP16"> |
| 920 | <dim>1</dim> |
| 921 | <dim>8</dim> |
| 922 | <dim>160</dim> |
| 923 | <dim>272</dim> |
| 924 | </port> |
| 925 | <port id="1" precision="FP32"> |
| 926 | <dim>1</dim> |
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| 929 | <output> |
| 930 | <port id="2" names="bottleneck1_3/dim_red/conv" precision="FP16"> |
| 931 | <dim>1</dim> |
| 932 | <dim>8</dim> |
| 933 | <dim>160</dim> |
| 934 | <dim>272</dim> |
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| 936 | </output> |
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| 938 | <layer id="54" name="bottleneck1_3/inner/dw1/bn/mean/Fused_Mul__copy" type="Const" version="opset1"> |
| 939 | <data element_type="f16" offset="4864" shape="8, 1, 1, 3, 3" size="144"/> |
| 940 | <output> |
| 941 | <port id="0" precision="FP16"> |
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| 944 | <dim>1</dim> |
| 945 | <dim>3</dim> |
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| 950 | <layer id="55" name="bottleneck1_3/inner/dw1/conv" type="GroupConvolution" version="opset1"> |
| 951 | <data auto_pad="explicit" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" strides="1, 1"/> |
| 952 | <input> |
| 953 | <port id="0" precision="FP16"> |
| 954 | <dim>1</dim> |
| 955 | <dim>8</dim> |
| 956 | <dim>160</dim> |
| 957 | <dim>272</dim> |
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| 959 | <port id="1" precision="FP16"> |
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| 962 | <dim>1</dim> |
| 963 | <dim>3</dim> |
| 964 | <dim>3</dim> |
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| 967 | <output> |
| 968 | <port id="2" precision="FP16"> |
| 969 | <dim>1</dim> |
| 970 | <dim>8</dim> |
| 971 | <dim>160</dim> |
| 972 | <dim>272</dim> |
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| 976 | <layer id="56" name="data_add_2371323718" type="Const" version="opset1"> |
| 977 | <data element_type="f16" offset="5008" shape="1, 8, 1, 1" size="16"/> |
| 978 | <output> |
| 979 | <port id="0" precision="FP16"> |
| 980 | <dim>1</dim> |
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| 982 | <dim>1</dim> |
| 983 | <dim>1</dim> |
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| 987 | <layer id="57" name="bottleneck1_3/inner/dw1/bn/variance/Fused_Add_" type="Add" version="opset1"> |
| 988 | <data auto_broadcast="numpy"/> |
| 989 | <input> |
| 990 | <port id="0" precision="FP16"> |
| 991 | <dim>1</dim> |
| 992 | <dim>8</dim> |
| 993 | <dim>160</dim> |
| 994 | <dim>272</dim> |
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| 996 | <port id="1" precision="FP16"> |
| 997 | <dim>1</dim> |
| 998 | <dim>8</dim> |
| 999 | <dim>1</dim> |
| 1000 | <dim>1</dim> |
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| 1002 | </input> |
| 1003 | <output> |
| 1004 | <port id="2" names="bottleneck1_3/inner/dw1/conv" precision="FP16"> |
| 1005 | <dim>1</dim> |
| 1006 | <dim>8</dim> |
| 1007 | <dim>160</dim> |
| 1008 | <dim>272</dim> |
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| 1012 | <layer id="58" name="bottleneck1_3/inner/dw1/fn/weights3110039956" type="Const" version="opset1"> |
| 1013 | <data element_type="f32" offset="2332" shape="1" size="4"/> |
| 1014 | <output> |
| 1015 | <port id="0" precision="FP32"> |
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| 1020 | <layer id="59" name="bottleneck1_3/inner/dw1/fn" type="PReLU" version="opset1"> |
| 1021 | <input> |
| 1022 | <port id="0" precision="FP16"> |
| 1023 | <dim>1</dim> |
| 1024 | <dim>8</dim> |
| 1025 | <dim>160</dim> |
| 1026 | <dim>272</dim> |
| 1027 | </port> |
| 1028 | <port id="1" precision="FP32"> |
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| 1032 | <output> |
| 1033 | <port id="2" names="bottleneck1_3/inner/dw1/conv" precision="FP16"> |
| 1034 | <dim>1</dim> |
| 1035 | <dim>8</dim> |
| 1036 | <dim>160</dim> |
| 1037 | <dim>272</dim> |
| 1038 | </port> |
| 1039 | </output> |
| 1040 | </layer> |
| 1041 | <layer id="60" name="bottleneck1_3/dim_inc/bn/mean/Fused_Mul__copy" type="Const" version="opset1"> |
| 1042 | <data element_type="f16" offset="5024" shape="32, 8, 1, 1" size="512"/> |
| 1043 | <output> |
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| 1046 | <dim>8</dim> |
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| 1048 | <dim>1</dim> |
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| 1052 | <layer id="61" name="bottleneck1_3/dim_inc/conv" type="Convolution" version="opset1"> |
| 1053 | <data auto_pad="explicit" dilations="1, 1" pads_begin="0, 0" pads_end="0, 0" strides="1, 1"/> |
| 1054 | <input> |
| 1055 | <port id="0" precision="FP16"> |
| 1056 | <dim>1</dim> |
| 1057 | <dim>8</dim> |
| 1058 | <dim>160</dim> |
| 1059 | <dim>272</dim> |
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| 1061 | <port id="1" precision="FP16"> |
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| 1063 | <dim>8</dim> |
| 1064 | <dim>1</dim> |
| 1065 | <dim>1</dim> |
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| 1067 | </input> |
| 1068 | <output> |
| 1069 | <port id="2" precision="FP16"> |
| 1070 | <dim>1</dim> |
| 1071 | <dim>32</dim> |
| 1072 | <dim>160</dim> |
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| 1255 | <port id="1" precision="FP32"> |
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| 1260 | <port id="2" names="bottleneck1_4/dim_red/conv" precision="FP16"> |
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| 1268 | <layer id="73" name="bottleneck1_4/inner/dw1/bn/mean/Fused_Mul__copy" type="Const" version="opset1"> |
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| 1318 | <data auto_broadcast="numpy"/> |
| 1319 | <input> |
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| 1350 | <layer id="78" name="bottleneck1_4/inner/dw1/fn" type="PReLU" version="opset1"> |
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| 1372 | <data element_type="f16" offset="6288" shape="32, 8, 1, 1" size="512"/> |
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| 1384 | <input> |
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| 1399 | <port id="2" precision="FP16"> |
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| 1418 | <layer id="82" name="bottleneck1_4/dim_inc/bn/variance/Fused_Add_" type="Add" version="opset1"> |
| 1419 | <data auto_broadcast="numpy"/> |
| 1420 | <input> |
| 1421 | <port id="0" precision="FP16"> |
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| 1427 | <port id="1" precision="FP16"> |
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| 1435 | <port id="2" names="bottleneck1_4/dim_inc/conv" precision="FP16"> |
| 1436 | <dim>1</dim> |
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| 1438 | <dim>160</dim> |
| 1439 | <dim>272</dim> |
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| 1443 | <layer id="83" name="bottleneck1_4/add" type="Add" version="opset1"> |
| 1444 | <data auto_broadcast="numpy"/> |
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| 1446 | <port id="0" precision="FP16"> |
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| 1459 | <output> |
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| 1468 | <layer id="84" name="bottleneck1_4/fn/weights3094440088" type="Const" version="opset1"> |
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| 1476 | <layer id="85" name="bottleneck1_4/fn" type="PReLU" version="opset1"> |
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| 1479 | <dim>1</dim> |
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| 1482 | <dim>272</dim> |
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| 1484 | <port id="1" precision="FP32"> |
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| 1498 | <data auto_pad="explicit" kernel="2, 2" pads_begin="0, 0" pads_end="0, 0" rounding_type="ceil" strides="2, 2"/> |
| 1499 | <input> |
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| 1508 | <port id="1" names="bottleneck2_0/skip/pooling" precision="FP16"> |
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| 1516 | <layer id="87" name="bottleneck2_0/skip/bn/mean/Fused_Mul__copy" type="Const" version="opset1"> |
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| 1558 | <dim>1</dim> |
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| 1565 | <input> |
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| 1583 | <dim>80</dim> |
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| 1859 | <dim>80</dim> |
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| 1868 | <dim>1</dim> |
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| 1870 | <dim>80</dim> |
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| 1884 | <dim>80</dim> |
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| 1913 | <dim>80</dim> |
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| 1918 | <layer id="110" name="bottleneck2_1/dim_red/bn/mean/Fused_Mul__copy" type="Const" version="opset1"> |
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| 1930 | <data auto_pad="explicit" dilations="1, 1" pads_begin="0, 0" pads_end="0, 0" strides="1, 1"/> |
| 1931 | <input> |
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| 1933 | <dim>1</dim> |
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| 1935 | <dim>80</dim> |
| 1936 | <dim>136</dim> |
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| 1938 | <port id="1" precision="FP16"> |
| 1939 | <dim>16</dim> |
| 1940 | <dim>64</dim> |
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| 1942 | <dim>1</dim> |
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| 1946 | <port id="2" precision="FP16"> |
| 1947 | <dim>1</dim> |
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| 1949 | <dim>80</dim> |
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| 1966 | <data auto_broadcast="numpy"/> |
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| 1971 | <dim>80</dim> |
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| 1982 | <port id="2" names="bottleneck2_1/dim_red/conv" precision="FP16"> |
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| 1984 | <dim>16</dim> |
| 1985 | <dim>80</dim> |
| 1986 | <dim>136</dim> |
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| 2001 | <dim>1</dim> |
| 2002 | <dim>16</dim> |
| 2003 | <dim>80</dim> |
| 2004 | <dim>136</dim> |
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| 2006 | <port id="1" precision="FP32"> |
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| 2011 | <port id="2" names="bottleneck2_1/dim_red/conv" precision="FP16"> |
| 2012 | <dim>1</dim> |
| 2013 | <dim>16</dim> |
| 2014 | <dim>80</dim> |
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| 2027 | <dim>3</dim> |
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| 2037 | <dim>80</dim> |
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| 2043 | <dim>1</dim> |
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| 2045 | <dim>3</dim> |
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| 2052 | <dim>80</dim> |
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| 2060 | <port id="0" precision="FP16"> |
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| 2064 | <dim>1</dim> |
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| 2069 | <data auto_broadcast="numpy"/> |
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| 2074 | <dim>80</dim> |
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| 2088 | <dim>80</dim> |
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| 2188 | <dim>64</dim> |
| 2189 | <dim>80</dim> |
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| 2200 | <dim>80</dim> |
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| 2206 | <dim>80</dim> |
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| 2214 | <dim>80</dim> |
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| 2230 | <dim>1</dim> |
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| 2242 | <dim>64</dim> |
| 2243 | <dim>80</dim> |
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| 2249 | <data element_type="f16" offset="19216" shape="16, 64, 1, 1" size="2048"/> |
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| 2254 | <dim>1</dim> |
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| 2261 | <input> |
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| 2265 | <dim>80</dim> |
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| 2272 | <dim>1</dim> |
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| 2278 | <dim>16</dim> |
| 2279 | <dim>80</dim> |
| 2280 | <dim>136</dim> |
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| 2284 | <layer id="131" name="data_add_2380923814" type="Const" version="opset1"> |
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| 2290 | <dim>1</dim> |
| 2291 | <dim>1</dim> |
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| 2296 | <data auto_broadcast="numpy"/> |
| 2297 | <input> |
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| 2299 | <dim>1</dim> |
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| 2301 | <dim>80</dim> |
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| 2315 | <dim>80</dim> |
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| 2320 | <layer id="133" name="bottleneck2_2/dim_red/fn/weights3090439815" type="Const" version="opset1"> |
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| 2331 | <dim>1</dim> |
| 2332 | <dim>16</dim> |
| 2333 | <dim>80</dim> |
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| 2336 | <port id="1" precision="FP32"> |
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| 2340 | <output> |
| 2341 | <port id="2" names="bottleneck2_2/dim_red/conv" precision="FP16"> |
| 2342 | <dim>1</dim> |
| 2343 | <dim>16</dim> |
| 2344 | <dim>80</dim> |
| 2345 | <dim>136</dim> |
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| 2349 | <layer id="135" name="bottleneck2_2/inner/dw1/bn/mean/Fused_Mul__copy" type="Const" version="opset1"> |
| 2350 | <data element_type="f16" offset="21296" shape="16, 1, 1, 3, 3" size="288"/> |
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| 2355 | <dim>1</dim> |
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| 2362 | <data auto_pad="explicit" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" strides="1, 1"/> |
| 2363 | <input> |
| 2364 | <port id="0" precision="FP16"> |
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| 2367 | <dim>80</dim> |
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| 2374 | <dim>3</dim> |
| 2375 | <dim>3</dim> |
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| 2380 | <dim>1</dim> |
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| 2382 | <dim>80</dim> |
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| 2388 | <data element_type="f16" offset="21584" shape="1, 16, 1, 1" size="32"/> |
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| 2394 | <dim>1</dim> |
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| 2398 | <layer id="138" name="bottleneck2_2/inner/dw1/bn/variance/Fused_Add_" type="Add" version="opset1"> |
| 2399 | <data auto_broadcast="numpy"/> |
| 2400 | <input> |
| 2401 | <port id="0" precision="FP16"> |
| 2402 | <dim>1</dim> |
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| 2404 | <dim>80</dim> |
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| 2407 | <port id="1" precision="FP16"> |
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| 2414 | <output> |
| 2415 | <port id="2" names="bottleneck2_2/inner/dw1/conv" precision="FP16"> |
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| 2418 | <dim>80</dim> |
| 2419 | <dim>136</dim> |
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| 2423 | <layer id="139" name="bottleneck2_2/inner/dw1/fn/weights3105240634" type="Const" version="opset1"> |
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| 2431 | <layer id="140" name="bottleneck2_2/inner/dw1/fn" type="PReLU" version="opset1"> |
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| 2433 | <port id="0" precision="FP16"> |
| 2434 | <dim>1</dim> |
| 2435 | <dim>16</dim> |
| 2436 | <dim>80</dim> |
| 2437 | <dim>136</dim> |
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| 2439 | <port id="1" precision="FP32"> |
| 2440 | <dim>1</dim> |
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| 2444 | <port id="2" names="bottleneck2_2/inner/dw1/conv" precision="FP16"> |
| 2445 | <dim>1</dim> |
| 2446 | <dim>16</dim> |
| 2447 | <dim>80</dim> |
| 2448 | <dim>136</dim> |
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| 2452 | <layer id="141" name="bottleneck2_2/dim_inc/bn/mean/Fused_Mul__copy" type="Const" version="opset1"> |
| 2453 | <data element_type="f16" offset="21616" shape="64, 16, 1, 1" size="2048"/> |
| 2454 | <output> |
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| 2456 | <dim>64</dim> |
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| 2463 | <layer id="142" name="bottleneck2_2/dim_inc/conv" type="Convolution" version="opset1"> |
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| 2465 | <input> |
| 2466 | <port id="0" precision="FP16"> |
| 2467 | <dim>1</dim> |
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| 2469 | <dim>80</dim> |
| 2470 | <dim>136</dim> |
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| 2473 | <dim>64</dim> |
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| 2476 | <dim>1</dim> |
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| 2480 | <port id="2" precision="FP16"> |
| 2481 | <dim>1</dim> |
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| 2483 | <dim>80</dim> |
| 2484 | <dim>136</dim> |
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| 2489 | <data element_type="f16" offset="23664" shape="1, 64, 1, 1" size="128"/> |
| 2490 | <output> |
| 2491 | <port id="0" precision="FP16"> |
| 2492 | <dim>1</dim> |
| 2493 | <dim>64</dim> |
| 2494 | <dim>1</dim> |
| 2495 | <dim>1</dim> |
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| 2499 | <layer id="144" name="bottleneck2_2/dim_inc/bn/variance/Fused_Add_" type="Add" version="opset1"> |
| 2500 | <data auto_broadcast="numpy"/> |
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| 2502 | <port id="0" precision="FP16"> |
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| 2505 | <dim>80</dim> |
| 2506 | <dim>136</dim> |
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| 2510 | <dim>64</dim> |
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| 2512 | <dim>1</dim> |
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| 2516 | <port id="2" names="bottleneck2_2/dim_inc/conv" precision="FP16"> |
| 2517 | <dim>1</dim> |
| 2518 | <dim>64</dim> |
| 2519 | <dim>80</dim> |
| 2520 | <dim>136</dim> |
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| 2524 | <layer id="145" name="bottleneck2_2/add" type="Add" version="opset1"> |
| 2525 | <data auto_broadcast="numpy"/> |
| 2526 | <input> |
| 2527 | <port id="0" precision="FP16"> |
| 2528 | <dim>1</dim> |
| 2529 | <dim>64</dim> |
| 2530 | <dim>80</dim> |
| 2531 | <dim>136</dim> |
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| 2535 | <dim>64</dim> |
| 2536 | <dim>80</dim> |
| 2537 | <dim>136</dim> |
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| 2541 | <port id="2" names="bottleneck2_2/add" precision="FP16"> |
| 2542 | <dim>1</dim> |
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| 2544 | <dim>80</dim> |
| 2545 | <dim>136</dim> |
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| 2549 | <layer id="146" name="bottleneck2_2/fn/weights3115240121" type="Const" version="opset1"> |
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| 2557 | <layer id="147" name="bottleneck2_2/fn" type="PReLU" version="opset1"> |
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| 2559 | <port id="0" precision="FP16"> |
| 2560 | <dim>1</dim> |
| 2561 | <dim>64</dim> |
| 2562 | <dim>80</dim> |
| 2563 | <dim>136</dim> |
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| 2565 | <port id="1" precision="FP32"> |
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| 2572 | <dim>64</dim> |
| 2573 | <dim>80</dim> |
| 2574 | <dim>136</dim> |
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| 2578 | <layer id="148" name="bottleneck2_3/dim_red/bn/mean/Fused_Mul__copy" type="Const" version="opset1"> |
| 2579 | <data element_type="f16" offset="23792" shape="16, 64, 1, 1" size="2048"/> |
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| 2583 | <dim>64</dim> |
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| 2591 | <input> |
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| 2593 | <dim>1</dim> |
| 2594 | <dim>64</dim> |
| 2595 | <dim>80</dim> |
| 2596 | <dim>136</dim> |
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| 2598 | <port id="1" precision="FP16"> |
| 2599 | <dim>16</dim> |
| 2600 | <dim>64</dim> |
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| 2602 | <dim>1</dim> |
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| 2609 | <dim>80</dim> |
| 2610 | <dim>136</dim> |
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| 2620 | <dim>1</dim> |
| 2621 | <dim>1</dim> |
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| 2625 | <layer id="151" name="bottleneck2_3/dim_red/bn/variance/Fused_Add_" type="Add" version="opset1"> |
| 2626 | <data auto_broadcast="numpy"/> |
| 2627 | <input> |
| 2628 | <port id="0" precision="FP16"> |
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| 2674 | <dim>80</dim> |
| 2675 | <dim>136</dim> |
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| 2695 | <dim>1</dim> |
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| 2712 | <dim>80</dim> |
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| 2728 | <layer id="157" name="bottleneck2_3/inner/dw1/bn/variance/Fused_Add_" type="Add" version="opset1"> |
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| 2734 | <dim>80</dim> |
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| 2748 | <dim>80</dim> |
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| 2766 | <dim>80</dim> |
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| 2769 | <port id="1" precision="FP32"> |
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| 2777 | <dim>80</dim> |
| 2778 | <dim>136</dim> |
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| 2782 | <layer id="160" name="bottleneck2_3/dim_inc/bn/mean/Fused_Mul__copy" type="Const" version="opset1"> |
| 2783 | <data element_type="f16" offset="26192" shape="64, 16, 1, 1" size="2048"/> |
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| 2795 | <input> |
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| 2799 | <dim>80</dim> |
| 2800 | <dim>136</dim> |
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| 2802 | <port id="1" precision="FP16"> |
| 2803 | <dim>64</dim> |
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| 2812 | <dim>64</dim> |
| 2813 | <dim>80</dim> |
| 2814 | <dim>136</dim> |
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| 2820 | <output> |
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| 2823 | <dim>64</dim> |
| 2824 | <dim>1</dim> |
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| 2829 | <layer id="163" name="bottleneck2_3/dim_inc/bn/variance/Fused_Add_" type="Add" version="opset1"> |
| 2830 | <data auto_broadcast="numpy"/> |
| 2831 | <input> |
| 2832 | <port id="0" precision="FP16"> |
| 2833 | <dim>1</dim> |
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| 2835 | <dim>80</dim> |
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| 2838 | <port id="1" precision="FP16"> |
| 2839 | <dim>1</dim> |
| 2840 | <dim>64</dim> |
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| 2847 | <dim>1</dim> |
| 2848 | <dim>64</dim> |
| 2849 | <dim>80</dim> |
| 2850 | <dim>136</dim> |
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| 2854 | <layer id="164" name="bottleneck2_3/add" type="Add" version="opset1"> |
| 2855 | <data auto_broadcast="numpy"/> |
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| 2858 | <dim>1</dim> |
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| 2860 | <dim>80</dim> |
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| 2864 | <dim>1</dim> |
| 2865 | <dim>64</dim> |
| 2866 | <dim>80</dim> |
| 2867 | <dim>136</dim> |
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| 2870 | <output> |
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| 2873 | <dim>64</dim> |
| 2874 | <dim>80</dim> |
| 2875 | <dim>136</dim> |
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| 2879 | <layer id="165" name="bottleneck2_3/fn/weights3106839797" type="Const" version="opset1"> |
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| 2887 | <layer id="166" name="bottleneck2_3/fn" type="PReLU" version="opset1"> |
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| 2889 | <port id="0" precision="FP16"> |
| 2890 | <dim>1</dim> |
| 2891 | <dim>64</dim> |
| 2892 | <dim>80</dim> |
| 2893 | <dim>136</dim> |
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| 2895 | <port id="1" precision="FP32"> |
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| 2899 | <output> |
| 2900 | <port id="2" names="bottleneck2_3/add" precision="FP16"> |
| 2901 | <dim>1</dim> |
| 2902 | <dim>64</dim> |
| 2903 | <dim>80</dim> |
| 2904 | <dim>136</dim> |
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| 2908 | <layer id="167" name="bottleneck2_4/dim_red/bn/mean/Fused_Mul__copy" type="Const" version="opset1"> |
| 2909 | <data element_type="f16" offset="28368" shape="16, 64, 1, 1" size="2048"/> |
| 2910 | <output> |
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| 2912 | <dim>16</dim> |
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| 2915 | <dim>1</dim> |
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| 2919 | <layer id="168" name="bottleneck2_4/dim_red/conv" type="Convolution" version="opset1"> |
| 2920 | <data auto_pad="explicit" dilations="1, 1" pads_begin="0, 0" pads_end="0, 0" strides="1, 1"/> |
| 2921 | <input> |
| 2922 | <port id="0" precision="FP16"> |
| 2923 | <dim>1</dim> |
| 2924 | <dim>64</dim> |
| 2925 | <dim>80</dim> |
| 2926 | <dim>136</dim> |
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| 2928 | <port id="1" precision="FP16"> |
| 2929 | <dim>16</dim> |
| 2930 | <dim>64</dim> |
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| 2932 | <dim>1</dim> |
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| 2935 | <output> |
| 2936 | <port id="2" precision="FP16"> |
| 2937 | <dim>1</dim> |
| 2938 | <dim>16</dim> |
| 2939 | <dim>80</dim> |
| 2940 | <dim>136</dim> |
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| 2944 | <layer id="169" name="data_add_2385723862" type="Const" version="opset1"> |
| 2945 | <data element_type="f16" offset="30416" shape="1, 16, 1, 1" size="32"/> |
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| 2948 | <dim>1</dim> |
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| 2950 | <dim>1</dim> |
| 2951 | <dim>1</dim> |
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| 2955 | <layer id="170" name="bottleneck2_4/dim_red/bn/variance/Fused_Add_" type="Add" version="opset1"> |
| 2956 | <data auto_broadcast="numpy"/> |
| 2957 | <input> |
| 2958 | <port id="0" precision="FP16"> |
| 2959 | <dim>1</dim> |
| 2960 | <dim>16</dim> |
| 2961 | <dim>80</dim> |
| 2962 | <dim>136</dim> |
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| 2964 | <port id="1" precision="FP16"> |
| 2965 | <dim>1</dim> |
| 2966 | <dim>16</dim> |
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| 2968 | <dim>1</dim> |
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| 2971 | <output> |
| 2972 | <port id="2" names="bottleneck2_4/dim_red/conv" precision="FP16"> |
| 2973 | <dim>1</dim> |
| 2974 | <dim>16</dim> |
| 2975 | <dim>80</dim> |
| 2976 | <dim>136</dim> |
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| 2980 | <layer id="171" name="bottleneck2_4/dim_red/fn/weights3101240241" type="Const" version="opset1"> |
| 2981 | <data element_type="f32" offset="2332" shape="1" size="4"/> |
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| 2983 | <port id="0" precision="FP32"> |
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| 2987 | </layer> |
| 2988 | <layer id="172" name="bottleneck2_4/dim_red/fn" type="PReLU" version="opset1"> |
| 2989 | <input> |
| 2990 | <port id="0" precision="FP16"> |
| 2991 | <dim>1</dim> |
| 2992 | <dim>16</dim> |
| 2993 | <dim>80</dim> |
| 2994 | <dim>136</dim> |
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| 2996 | <port id="1" precision="FP32"> |
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| 3000 | <output> |
| 3001 | <port id="2" names="bottleneck2_4/dim_red/conv" precision="FP16"> |
| 3002 | <dim>1</dim> |
| 3003 | <dim>16</dim> |
| 3004 | <dim>80</dim> |
| 3005 | <dim>136</dim> |
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| 3009 | <layer id="173" name="bottleneck2_4/inner/dw1/bn/mean/Fused_Mul__copy" type="Const" version="opset1"> |
| 3010 | <data element_type="f16" offset="30448" shape="16, 1, 1, 3, 3" size="288"/> |
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| 3014 | <dim>1</dim> |
| 3015 | <dim>1</dim> |
| 3016 | <dim>3</dim> |
| 3017 | <dim>3</dim> |
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| 3021 | <layer id="174" name="bottleneck2_4/inner/dw1/conv" type="GroupConvolution" version="opset1"> |
| 3022 | <data auto_pad="explicit" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" strides="1, 1"/> |
| 3023 | <input> |
| 3024 | <port id="0" precision="FP16"> |
| 3025 | <dim>1</dim> |
| 3026 | <dim>16</dim> |
| 3027 | <dim>80</dim> |
| 3028 | <dim>136</dim> |
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| 3030 | <port id="1" precision="FP16"> |
| 3031 | <dim>16</dim> |
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| 3033 | <dim>1</dim> |
| 3034 | <dim>3</dim> |
| 3035 | <dim>3</dim> |
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| 3038 | <output> |
| 3039 | <port id="2" precision="FP16"> |
| 3040 | <dim>1</dim> |
| 3041 | <dim>16</dim> |
| 3042 | <dim>80</dim> |
| 3043 | <dim>136</dim> |
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| 3047 | <layer id="175" name="data_add_2386523870" type="Const" version="opset1"> |
| 3048 | <data element_type="f16" offset="30736" shape="1, 16, 1, 1" size="32"/> |
| 3049 | <output> |
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| 3052 | <dim>16</dim> |
| 3053 | <dim>1</dim> |
| 3054 | <dim>1</dim> |
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| 3058 | <layer id="176" name="bottleneck2_4/inner/dw1/bn/variance/Fused_Add_" type="Add" version="opset1"> |
| 3059 | <data auto_broadcast="numpy"/> |
| 3060 | <input> |
| 3061 | <port id="0" precision="FP16"> |
| 3062 | <dim>1</dim> |
| 3063 | <dim>16</dim> |
| 3064 | <dim>80</dim> |
| 3065 | <dim>136</dim> |
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| 3067 | <port id="1" precision="FP16"> |
| 3068 | <dim>1</dim> |
| 3069 | <dim>16</dim> |
| 3070 | <dim>1</dim> |
| 3071 | <dim>1</dim> |
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| 3074 | <output> |
| 3075 | <port id="2" names="bottleneck2_4/inner/dw1/conv" precision="FP16"> |
| 3076 | <dim>1</dim> |
| 3077 | <dim>16</dim> |
| 3078 | <dim>80</dim> |
| 3079 | <dim>136</dim> |
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| 3083 | <layer id="177" name="bottleneck2_4/inner/dw1/fn/weights3116840295" type="Const" version="opset1"> |
| 3084 | <data element_type="f32" offset="2332" shape="1" size="4"/> |
| 3085 | <output> |
| 3086 | <port id="0" precision="FP32"> |
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| 3091 | <layer id="178" name="bottleneck2_4/inner/dw1/fn" type="PReLU" version="opset1"> |
| 3092 | <input> |
| 3093 | <port id="0" precision="FP16"> |
| 3094 | <dim>1</dim> |
| 3095 | <dim>16</dim> |
| 3096 | <dim>80</dim> |
| 3097 | <dim>136</dim> |
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| 3099 | <port id="1" precision="FP32"> |
| 3100 | <dim>1</dim> |
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| 3104 | <port id="2" names="bottleneck2_4/inner/dw1/conv" precision="FP16"> |
| 3105 | <dim>1</dim> |
| 3106 | <dim>16</dim> |
| 3107 | <dim>80</dim> |
| 3108 | <dim>136</dim> |
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| 3112 | <layer id="179" name="bottleneck2_4/dim_inc/bn/mean/Fused_Mul__copy" type="Const" version="opset1"> |
| 3113 | <data element_type="f16" offset="30768" shape="64, 16, 1, 1" size="2048"/> |
| 3114 | <output> |
| 3115 | <port id="0" precision="FP16"> |
| 3116 | <dim>64</dim> |
| 3117 | <dim>16</dim> |
| 3118 | <dim>1</dim> |
| 3119 | <dim>1</dim> |
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| 3122 | </layer> |
| 3123 | <layer id="180" name="bottleneck2_4/dim_inc/conv" type="Convolution" version="opset1"> |
| 3124 | <data auto_pad="explicit" dilations="1, 1" pads_begin="0, 0" pads_end="0, 0" strides="1, 1"/> |
| 3125 | <input> |
| 3126 | <port id="0" precision="FP16"> |
| 3127 | <dim>1</dim> |
| 3128 | <dim>16</dim> |
| 3129 | <dim>80</dim> |
| 3130 | <dim>136</dim> |
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| 3132 | <port id="1" precision="FP16"> |
| 3133 | <dim>64</dim> |
| 3134 | <dim>16</dim> |
| 3135 | <dim>1</dim> |
| 3136 | <dim>1</dim> |
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| 3138 | </input> |
| 3139 | <output> |
| 3140 | <port id="2" precision="FP16"> |
| 3141 | <dim>1</dim> |
| 3142 | <dim>64</dim> |
| 3143 | <dim>80</dim> |
| 3144 | <dim>136</dim> |
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| 3489 | <layer id="201" name="bottleneck2_5/dim_inc/bn/variance/Fused_Add_" type="Add" version="opset1"> |
| 3490 | <data auto_broadcast="numpy"/> |
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| 3514 | <layer id="202" name="bottleneck2_5/add" type="Add" version="opset1"> |
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| 3738 | <dim>80</dim> |
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| 3839 | <dim>80</dim> |
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| 3844 | <layer id="221" name="bottleneck2_6/add" type="Add" version="opset1"> |
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| 3877 | <layer id="223" name="bottleneck2_6/fn" type="PReLU" version="opset1"> |
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| 3880 | <dim>1</dim> |
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| 3885 | <port id="1" precision="FP32"> |
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| 3890 | <port id="2" names="bottleneck2_6/add" precision="FP16"> |
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| 3893 | <dim>80</dim> |
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| 3898 | <layer id="224" name="bottleneck2_7/dim_red/bn/mean/Fused_Mul__copy" type="Const" version="opset1"> |
| 3899 | <data element_type="f16" offset="42096" shape="16, 64, 1, 1" size="2048"/> |
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| 3910 | <data auto_pad="explicit" dilations="1, 1" pads_begin="0, 0" pads_end="0, 0" strides="1, 1"/> |
| 3911 | <input> |
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| 3913 | <dim>1</dim> |
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| 3915 | <dim>80</dim> |
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| 3925 | <output> |
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| 3929 | <dim>80</dim> |
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| 3945 | <layer id="227" name="bottleneck2_7/dim_red/bn/variance/Fused_Add_" type="Add" version="opset1"> |
| 3946 | <data auto_broadcast="numpy"/> |
| 3947 | <input> |
| 3948 | <port id="0" precision="FP16"> |
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| 3962 | <port id="2" names="bottleneck2_7/dim_red/conv" precision="FP16"> |
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| 3965 | <dim>80</dim> |
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| 3978 | <layer id="229" name="bottleneck2_7/dim_red/fn" type="PReLU" version="opset1"> |
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| 3986 | <port id="1" precision="FP32"> |
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| 3994 | <dim>80</dim> |
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| 3999 | <layer id="230" name="bottleneck2_7/inner/dw1/bn/mean/Fused_Mul__copy" type="Const" version="opset1"> |
| 4000 | <data element_type="f16" offset="44176" shape="16, 1, 1, 3, 3" size="288"/> |
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| 4025 | <dim>3</dim> |
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| 4029 | <port id="2" precision="FP16"> |
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| 4032 | <dim>80</dim> |
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| 4044 | <dim>1</dim> |
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| 4048 | <layer id="233" name="bottleneck2_7/inner/dw1/bn/variance/Fused_Add_" type="Add" version="opset1"> |
| 4049 | <data auto_broadcast="numpy"/> |
| 4050 | <input> |
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| 4065 | <port id="2" names="bottleneck2_7/inner/dw1/conv" precision="FP16"> |
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| 4068 | <dim>80</dim> |
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| 4084 | <dim>1</dim> |
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| 4086 | <dim>80</dim> |
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| 4089 | <port id="1" precision="FP32"> |
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| 4102 | <layer id="236" name="bottleneck2_7/dim_inc/bn/mean/Fused_Mul__copy" type="Const" version="opset1"> |
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| 4133 | <dim>80</dim> |
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| 4144 | <dim>1</dim> |
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| 4321 | <port id="2" names="bottleneck2_8/dim_red/conv" precision="FP16"> |
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| 4378 | <layer id="252" name="bottleneck2_8/inner/dw1/bn/variance/Fused_Add_" type="Add" version="opset1"> |
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| 4384 | <dim>80</dim> |
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| 4398 | <dim>80</dim> |
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| 4432 | <layer id="255" name="bottleneck2_8/dim_inc/bn/mean/Fused_Mul__copy" type="Const" version="opset1"> |
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| 4449 | <dim>80</dim> |
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| 4499 | <dim>80</dim> |
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| 4504 | <layer id="259" name="bottleneck2_8/add" type="Add" version="opset1"> |
| 4505 | <data auto_broadcast="numpy"/> |
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| 4529 | <layer id="260" name="bottleneck2_8/fn/weights3112840481" type="Const" version="opset1"> |
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| 4542 | <dim>80</dim> |
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| 4569 | <port id="1" names="bottleneck3_0/skip/pooling" precision="FP16"> |
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| 4577 | <layer id="263" name="bottleneck3_0/skip/bn/mean/Fused_Mul__copy" type="Const" version="opset1"> |
| 4578 | <data element_type="f16" offset="51248" shape="128, 64, 1, 1" size="16384"/> |
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| 4588 | <layer id="264" name="bottleneck3_0/skip/conv" type="Convolution" version="opset1"> |
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| 4597 | <port id="1" precision="FP16"> |
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| 4608 | <dim>40</dim> |
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| 4624 | <layer id="266" name="bottleneck3_0/skip/bn/variance/Fused_Add_" type="Add" version="opset1"> |
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| 4716 | <dim>80</dim> |
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| 4745 | <dim>80</dim> |
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| 4800 | <data auto_broadcast="numpy"/> |
| 4801 | <input> |
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| 4805 | <dim>40</dim> |
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| 4808 | <port id="1" precision="FP16"> |
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| 4819 | <dim>40</dim> |
| 4820 | <dim>68</dim> |
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| 4824 | <layer id="277" name="bottleneck3_0/inner/dw1/fn/weights3084840604" type="Const" version="opset1"> |
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| 4832 | <layer id="278" name="bottleneck3_0/inner/dw1/fn" type="PReLU" version="opset1"> |
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| 4838 | <dim>68</dim> |
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| 4840 | <port id="1" precision="FP32"> |
| 4841 | <dim>1</dim> |
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| 4845 | <port id="2" names="bottleneck3_0/inner/dw1/conv" precision="FP16"> |
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| 4848 | <dim>40</dim> |
| 4849 | <dim>68</dim> |
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| 4853 | <layer id="279" name="bottleneck3_0/dim_inc/bn/mean/Fused_Mul__copy" type="Const" version="opset1"> |
| 4854 | <data element_type="f16" offset="72688" shape="128, 32, 1, 1" size="8192"/> |
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| 4860 | <dim>1</dim> |
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| 4866 | <input> |
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| 4870 | <dim>40</dim> |
| 4871 | <dim>68</dim> |
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| 4873 | <port id="1" precision="FP16"> |
| 4874 | <dim>128</dim> |
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| 4877 | <dim>1</dim> |
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| 4884 | <dim>40</dim> |
| 4885 | <dim>68</dim> |
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| 4890 | <data element_type="f16" offset="80880" shape="1, 128, 1, 1" size="256"/> |
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| 4895 | <dim>1</dim> |
| 4896 | <dim>1</dim> |
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| 4900 | <layer id="282" name="bottleneck3_0/dim_inc/bn/variance/Fused_Add_" type="Add" version="opset1"> |
| 4901 | <data auto_broadcast="numpy"/> |
| 4902 | <input> |
| 4903 | <port id="0" precision="FP16"> |
| 4904 | <dim>1</dim> |
| 4905 | <dim>128</dim> |
| 4906 | <dim>40</dim> |
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| 4910 | <dim>1</dim> |
| 4911 | <dim>128</dim> |
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| 4913 | <dim>1</dim> |
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| 4916 | <output> |
| 4917 | <port id="2" names="bottleneck3_0/dim_inc/conv" precision="FP16"> |
| 4918 | <dim>1</dim> |
| 4919 | <dim>128</dim> |
| 4920 | <dim>40</dim> |
| 4921 | <dim>68</dim> |
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| 4925 | <layer id="283" name="bottleneck3_0/add" type="Add" version="opset1"> |
| 4926 | <data auto_broadcast="numpy"/> |
| 4927 | <input> |
| 4928 | <port id="0" precision="FP16"> |
| 4929 | <dim>1</dim> |
| 4930 | <dim>128</dim> |
| 4931 | <dim>40</dim> |
| 4932 | <dim>68</dim> |
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| 4934 | <port id="1" precision="FP16"> |
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| 4936 | <dim>128</dim> |
| 4937 | <dim>40</dim> |
| 4938 | <dim>68</dim> |
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| 4944 | <dim>128</dim> |
| 4945 | <dim>40</dim> |
| 4946 | <dim>68</dim> |
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| 4950 | <layer id="284" name="bottleneck3_0/fn/weights3096040034" type="Const" version="opset1"> |
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| 4958 | <layer id="285" name="bottleneck3_0/fn" type="PReLU" version="opset1"> |
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| 4960 | <port id="0" precision="FP16"> |
| 4961 | <dim>1</dim> |
| 4962 | <dim>128</dim> |
| 4963 | <dim>40</dim> |
| 4964 | <dim>68</dim> |
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| 4966 | <port id="1" precision="FP32"> |
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| 4970 | <output> |
| 4971 | <port id="2" names="bottleneck3_0/add" precision="FP16"> |
| 4972 | <dim>1</dim> |
| 4973 | <dim>128</dim> |
| 4974 | <dim>40</dim> |
| 4975 | <dim>68</dim> |
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| 4978 | </layer> |
| 4979 | <layer id="286" name="bottleneck3_1/dim_red/bn/mean/Fused_Mul__copy" type="Const" version="opset1"> |
| 4980 | <data element_type="f16" offset="81136" shape="32, 128, 1, 1" size="8192"/> |
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| 4986 | <dim>1</dim> |
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| 4991 | <data auto_pad="explicit" dilations="1, 1" pads_begin="0, 0" pads_end="0, 0" strides="1, 1"/> |
| 4992 | <input> |
| 4993 | <port id="0" precision="FP16"> |
| 4994 | <dim>1</dim> |
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| 4996 | <dim>40</dim> |
| 4997 | <dim>68</dim> |
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| 4999 | <port id="1" precision="FP16"> |
| 5000 | <dim>32</dim> |
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| 5006 | <output> |
| 5007 | <port id="2" precision="FP16"> |
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| 5010 | <dim>40</dim> |
| 5011 | <dim>68</dim> |
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| 5026 | <layer id="289" name="bottleneck3_1/dim_red/bn/variance/Fused_Add_" type="Add" version="opset1"> |
| 5027 | <data auto_broadcast="numpy"/> |
| 5028 | <input> |
| 5029 | <port id="0" precision="FP16"> |
| 5030 | <dim>1</dim> |
| 5031 | <dim>32</dim> |
| 5032 | <dim>40</dim> |
| 5033 | <dim>68</dim> |
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| 5035 | <port id="1" precision="FP16"> |
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| 5039 | <dim>1</dim> |
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| 5043 | <port id="2" names="bottleneck3_1/dim_red/conv" precision="FP16"> |
| 5044 | <dim>1</dim> |
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| 5046 | <dim>40</dim> |
| 5047 | <dim>68</dim> |
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| 5060 | <input> |
| 5061 | <port id="0" precision="FP16"> |
| 5062 | <dim>1</dim> |
| 5063 | <dim>32</dim> |
| 5064 | <dim>40</dim> |
| 5065 | <dim>68</dim> |
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| 5067 | <port id="1" precision="FP32"> |
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| 5072 | <port id="2" names="bottleneck3_1/dim_red/conv" precision="FP16"> |
| 5073 | <dim>1</dim> |
| 5074 | <dim>32</dim> |
| 5075 | <dim>40</dim> |
| 5076 | <dim>68</dim> |
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| 5080 | <layer id="292" name="bottleneck3_1/inner/dw1/bn/mean/Fused_Mul__copy" type="Const" version="opset1"> |
| 5081 | <data element_type="f16" offset="89392" shape="32, 1, 1, 3, 3" size="576"/> |
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| 5086 | <dim>1</dim> |
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| 5093 | <data auto_pad="explicit" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" strides="1, 1"/> |
| 5094 | <input> |
| 5095 | <port id="0" precision="FP16"> |
| 5096 | <dim>1</dim> |
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| 5098 | <dim>40</dim> |
| 5099 | <dim>68</dim> |
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| 5105 | <dim>3</dim> |
| 5106 | <dim>3</dim> |
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| 5110 | <port id="2" precision="FP16"> |
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| 5114 | <dim>68</dim> |
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| 5124 | <dim>1</dim> |
| 5125 | <dim>1</dim> |
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| 5129 | <layer id="295" name="bottleneck3_1/inner/dw1/bn/variance/Fused_Add_" type="Add" version="opset1"> |
| 5130 | <data auto_broadcast="numpy"/> |
| 5131 | <input> |
| 5132 | <port id="0" precision="FP16"> |
| 5133 | <dim>1</dim> |
| 5134 | <dim>32</dim> |
| 5135 | <dim>40</dim> |
| 5136 | <dim>68</dim> |
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| 5138 | <port id="1" precision="FP16"> |
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| 5140 | <dim>32</dim> |
| 5141 | <dim>1</dim> |
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| 5149 | <dim>40</dim> |
| 5150 | <dim>68</dim> |
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| 5162 | <layer id="297" name="bottleneck3_1/inner/dw1/fn" type="PReLU" version="opset1"> |
| 5163 | <input> |
| 5164 | <port id="0" precision="FP16"> |
| 5165 | <dim>1</dim> |
| 5166 | <dim>32</dim> |
| 5167 | <dim>40</dim> |
| 5168 | <dim>68</dim> |
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| 5170 | <port id="1" precision="FP32"> |
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| 5175 | <port id="2" names="bottleneck3_1/inner/dw1/conv" precision="FP16"> |
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| 5177 | <dim>32</dim> |
| 5178 | <dim>40</dim> |
| 5179 | <dim>68</dim> |
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| 5183 | <layer id="298" name="bottleneck3_1/dim_inc/bn/mean/Fused_Mul__copy" type="Const" version="opset1"> |
| 5184 | <data element_type="f16" offset="90032" shape="128, 32, 1, 1" size="8192"/> |
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| 5188 | <dim>32</dim> |
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| 5190 | <dim>1</dim> |
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| 5196 | <input> |
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| 5198 | <dim>1</dim> |
| 5199 | <dim>32</dim> |
| 5200 | <dim>40</dim> |
| 5201 | <dim>68</dim> |
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| 13637 | <edge from-layer="734" from-port="4" to-layer="740" to-port="0"/> |
| 13638 | <edge from-layer="735" from-port="1" to-layer="739" to-port="0"/> |
| 13639 | <edge from-layer="736" from-port="0" to-layer="739" to-port="1"/> |
| 13640 | <edge from-layer="737" from-port="0" to-layer="739" to-port="2"/> |
| 13641 | <edge from-layer="738" from-port="0" to-layer="739" to-port="3"/> |
| 13642 | <edge from-layer="739" from-port="4" to-layer="740" to-port="1"/> |
| 13643 | <edge from-layer="740" from-port="2" to-layer="742" to-port="0"/> |
| 13644 | <edge from-layer="741" from-port="0" to-layer="742" to-port="1"/> |
| 13645 | <edge from-layer="742" from-port="2" to-layer="743" to-port="2"/> |
| 13646 | <edge from-layer="743" from-port="3" to-layer="744" to-port="0"/> |
| 13647 | </edges> |
| 13648 | <meta_data> |
| 13649 | <MO_version value="2021.4.0-3827-c5b65f2cb1d-releases/2021/4"/> |
| 13650 | <cli_parameters> |
| 13651 | <caffe_parser_path value="DIR"/> |
| 13652 | <data_type value="FP16"/> |
| 13653 | <disable_nhwc_to_nchw value="False"/> |
| 13654 | <disable_omitting_optional value="False"/> |
| 13655 | <disable_resnet_optimization value="False"/> |
| 13656 | <disable_weights_compression value="False"/> |
| 13657 | <enable_concat_optimization value="False"/> |
| 13658 | <enable_flattening_nested_params value="False"/> |
| 13659 | <enable_ssd_gluoncv value="False"/> |
| 13660 | <extensions value="DIR"/> |
| 13661 | <framework value="caffe"/> |
| 13662 | <freeze_placeholder_with_value value="{}"/> |
| 13663 | <generate_deprecated_IR_V7 value="False"/> |
| 13664 | <input value="data"/> |
| 13665 | <input_model value="DIR/rmnet_lrelu_pd_ssd.caffemodel"/> |
| 13666 | <input_model_is_text value="False"/> |
| 13667 | <input_proto value="DIR/rmnet_lrelu_pd_ssd.prototxt"/> |
| 13668 | <input_shape value="[1,3,320,544]"/> |
| 13669 | <k value="DIR/CustomLayersMapping.xml"/> |
| 13670 | <keep_shape_ops value="True"/> |
| 13671 | <legacy_ir_generation value="False"/> |
| 13672 | <legacy_mxnet_model value="False"/> |
| 13673 | <log_level value="ERROR"/> |
| 13674 | <mean_scale_values value="{}"/> |
| 13675 | <mean_values value="()"/> |
| 13676 | <model_name value="person-detection-retail-0013"/> |
| 13677 | <output value="['detection_out']"/> |
| 13678 | <output_dir value="DIR"/> |
| 13679 | <placeholder_data_types value="{}"/> |
| 13680 | <placeholder_shapes value="{'data': array([ 1, 3, 320, 544])}"/> |
| 13681 | <progress value="False"/> |
| 13682 | <remove_memory value="False"/> |
| 13683 | <remove_output_softmax value="False"/> |
| 13684 | <reverse_input_channels value="False"/> |
| 13685 | <save_params_from_nd value="False"/> |
| 13686 | <scale_values value="()"/> |
| 13687 | <silent value="False"/> |
| 13688 | <static_shape value="False"/> |
| 13689 | <stream_output value="False"/> |
| 13690 | <transform value=""/> |
| 13691 | <unset unset_cli_parameters="batch, counts, disable_fusing, disable_gfusing, finegrain_fusing, input_checkpoint, input_meta_graph, input_symbol, mean_file, mean_file_offsets, move_to_preprocess, nd_prefix_name, pretrained_model_name, saved_model_dir, saved_model_tags, scale, tensorboard_logdir, tensorflow_custom_layer_libraries, tensorflow_custom_operations_config_update, tensorflow_object_detection_api_pipeline_config, tensorflow_use_custom_operations_config, transformations_config"/> |
| 13692 | </cli_parameters> |
| 13693 | </meta_data> |
| 13694 | </net> |