TfLite model analyzer on efficientdet

gistfile1.txt

=== /content/efficientdet.tflite ===

Your TFLite model has '1' subgraph(s). In the subgraph description below,
T# represents the Tensor numbers. For example, in Subgraph#0, the QUANTIZE op takes
tensor #0 as input and produces tensor #576 as output.

Subgraph#0 main(T#0) -> [T#1060, T#1058, T#1061, T#1059]
  Op#0 QUANTIZE(T#0) -> [T#576]
  Op#1 CONV_2D(T#576, T#8, T#9) -> [T#577]
  Op#2 DEPTHWISE_CONV_2D(T#577, T#10, T#11) -> [T#578]
  Op#3 CONV_2D(T#578, T#12, T#13) -> [T#579]
  Op#4 CONV_2D(T#579, T#14, T#15) -> [T#580]
  Op#5 DEPTHWISE_CONV_2D(T#580, T#16, T#17) -> [T#581]
  Op#6 CONV_2D(T#581, T#18, T#19) -> [T#582]
  Op#7 CONV_2D(T#582, T#20, T#21) -> [T#583]
  Op#8 DEPTHWISE_CONV_2D(T#583, T#22, T#23) -> [T#584]
  Op#9 CONV_2D(T#584, T#24, T#25) -> [T#585]
  Op#10 ADD(T#585, T#582) -> [T#586]
  Op#11 CONV_2D(T#586, T#26, T#27) -> [T#587]
  Op#12 DEPTHWISE_CONV_2D(T#587, T#28, T#29) -> [T#588]
  Op#13 CONV_2D(T#588, T#30, T#31) -> [T#589]
  Op#14 ADD(T#589, T#586) -> [T#590]
  Op#15 CONV_2D(T#590, T#32, T#33) -> [T#591]
  Op#16 DEPTHWISE_CONV_2D(T#591, T#34, T#35) -> [T#592]
  Op#17 CONV_2D(T#592, T#36, T#37) -> [T#593]
  Op#18 ADD(T#593, T#590) -> [T#594]
  Op#19 CONV_2D(T#594, T#38, T#39) -> [T#595]
  Op#20 DEPTHWISE_CONV_2D(T#595, T#40, T#41) -> [T#596]
  Op#21 CONV_2D(T#596, T#42, T#43) -> [T#597]
  Op#22 CONV_2D(T#597, T#44, T#45) -> [T#598]
  Op#23 DEPTHWISE_CONV_2D(T#598, T#46, T#47) -> [T#599]
  Op#24 CONV_2D(T#599, T#48, T#49) -> [T#600]
  Op#25 ADD(T#600, T#597) -> [T#601]
  Op#26 CONV_2D(T#601, T#50, T#51) -> [T#602]
  Op#27 DEPTHWISE_CONV_2D(T#602, T#52, T#53) -> [T#603]
  Op#28 CONV_2D(T#603, T#54, T#55) -> [T#604]
  Op#29 ADD(T#604, T#601) -> [T#605]
  Op#30 CONV_2D(T#605, T#56, T#57) -> [T#606]
  Op#31 DEPTHWISE_CONV_2D(T#606, T#58, T#59) -> [T#607]
  Op#32 CONV_2D(T#607, T#60, T#61) -> [T#608]
  Op#33 ADD(T#608, T#605) -> [T#609]
  Op#34 CONV_2D(T#609, T#62, T#63) -> [T#610]
  Op#35 DEPTHWISE_CONV_2D(T#610, T#64, T#65) -> [T#611]
  Op#36 CONV_2D(T#611, T#66, T#67) -> [T#612]
  Op#37 CONV_2D(T#612, T#68, T#69) -> [T#613]
  Op#38 DEPTHWISE_CONV_2D(T#613, T#70, T#71) -> [T#614]
  Op#39 CONV_2D(T#614, T#72, T#73) -> [T#615]
  Op#40 ADD(T#615, T#612) -> [T#616]
  Op#41 CONV_2D(T#616, T#74, T#75) -> [T#617]
  Op#42 DEPTHWISE_CONV_2D(T#617, T#76, T#77) -> [T#618]
  Op#43 CONV_2D(T#618, T#78, T#79) -> [T#619]
  Op#44 ADD(T#619, T#616) -> [T#620]
  Op#45 CONV_2D(T#620, T#80, T#81) -> [T#621]
  Op#46 DEPTHWISE_CONV_2D(T#621, T#82, T#83) -> [T#622]
  Op#47 CONV_2D(T#622, T#84, T#85) -> [T#623]
  Op#48 ADD(T#623, T#620) -> [T#624]
  Op#49 CONV_2D(T#624, T#86, T#87) -> [T#625]
  Op#50 DEPTHWISE_CONV_2D(T#625, T#88, T#89) -> [T#626]
  Op#51 CONV_2D(T#626, T#90, T#91) -> [T#627]
  Op#52 ADD(T#627, T#624) -> [T#628]
  Op#53 CONV_2D(T#628, T#92, T#93) -> [T#629]
  Op#54 DEPTHWISE_CONV_2D(T#629, T#94, T#95) -> [T#630]
  Op#55 CONV_2D(T#630, T#96, T#97) -> [T#631]
  Op#56 ADD(T#631, T#628) -> [T#632]
  Op#57 CONV_2D(T#632, T#98, T#99) -> [T#633]
  Op#58 DEPTHWISE_CONV_2D(T#633, T#100, T#101) -> [T#634]
  Op#59 CONV_2D(T#634, T#102, T#103) -> [T#635]
  Op#60 CONV_2D(T#635, T#104, T#105) -> [T#636]
  Op#61 DEPTHWISE_CONV_2D(T#636, T#106, T#107) -> [T#637]
  Op#62 CONV_2D(T#637, T#108, T#109) -> [T#638]
  Op#63 ADD(T#638, T#635) -> [T#639]
  Op#64 CONV_2D(T#639, T#110, T#111) -> [T#640]
  Op#65 DEPTHWISE_CONV_2D(T#640, T#112, T#113) -> [T#641]
  Op#66 CONV_2D(T#641, T#114, T#115) -> [T#642]
  Op#67 ADD(T#642, T#639) -> [T#643]
  Op#68 CONV_2D(T#643, T#116, T#117) -> [T#644]
  Op#69 DEPTHWISE_CONV_2D(T#644, T#118, T#119) -> [T#645]
  Op#70 CONV_2D(T#645, T#120, T#121) -> [T#646]
  Op#71 ADD(T#646, T#643) -> [T#647]
  Op#72 CONV_2D(T#647, T#122, T#123) -> [T#648]
  Op#73 DEPTHWISE_CONV_2D(T#648, T#124, T#125) -> [T#649]
  Op#74 CONV_2D(T#649, T#126, T#127) -> [T#650]
  Op#75 ADD(T#650, T#647) -> [T#651]
  Op#76 CONV_2D(T#651, T#128, T#129) -> [T#652]
  Op#77 DEPTHWISE_CONV_2D(T#652, T#130, T#131) -> [T#653]
  Op#78 CONV_2D(T#653, T#132, T#133) -> [T#654]
  Op#79 ADD(T#654, T#651) -> [T#655]
  Op#80 CONV_2D(T#655, T#134, T#135) -> [T#656]
  Op#81 DEPTHWISE_CONV_2D(T#656, T#136, T#137) -> [T#657]
  Op#82 CONV_2D(T#657, T#138, T#139) -> [T#658]
  Op#83 CONV_2D(T#658, T#140, T#141) -> [T#659]
  Op#84 DEPTHWISE_CONV_2D(T#659, T#142, T#143) -> [T#660]
  Op#85 CONV_2D(T#660, T#144, T#145) -> [T#661]
  Op#86 ADD(T#661, T#658) -> [T#662]
  Op#87 CONV_2D(T#662, T#146, T#147) -> [T#663]
  Op#88 DEPTHWISE_CONV_2D(T#663, T#148, T#149) -> [T#664]
  Op#89 CONV_2D(T#664, T#150, T#151) -> [T#665]
  Op#90 ADD(T#665, T#662) -> [T#666]
  Op#91 CONV_2D(T#666, T#152, T#153) -> [T#667]
  Op#92 DEPTHWISE_CONV_2D(T#667, T#154, T#155) -> [T#668]
  Op#93 CONV_2D(T#668, T#156, T#157) -> [T#669]
  Op#94 ADD(T#669, T#666) -> [T#670]
  Op#95 CONV_2D(T#670, T#158, T#159) -> [T#671]
  Op#96 DEPTHWISE_CONV_2D(T#671, T#160, T#161) -> [T#672]
  Op#97 CONV_2D(T#672, T#162, T#163) -> [T#673]
  Op#98 ADD(T#673, T#670) -> [T#674]
  Op#99 CONV_2D(T#674, T#164, T#165) -> [T#675]
  Op#100 DEPTHWISE_CONV_2D(T#675, T#166, T#167) -> [T#676]
  Op#101 CONV_2D(T#676, T#168, T#169) -> [T#677]
  Op#102 ADD(T#677, T#674) -> [T#678]
  Op#103 CONV_2D(T#678, T#170, T#171) -> [T#679]
  Op#104 DEPTHWISE_CONV_2D(T#679, T#172, T#173) -> [T#680]
  Op#105 CONV_2D(T#680, T#174, T#175) -> [T#681]
  Op#106 ADD(T#681, T#678) -> [T#682]
  Op#107 CONV_2D(T#682, T#176, T#177) -> [T#683]
  Op#108 DEPTHWISE_CONV_2D(T#683, T#178, T#179) -> [T#684]
  Op#109 CONV_2D(T#684, T#180, T#181) -> [T#685]
  Op#110 ADD(T#685, T#682) -> [T#686]
  Op#111 CONV_2D(T#686, T#182, T#183) -> [T#687]
  Op#112 DEPTHWISE_CONV_2D(T#687, T#184, T#185) -> [T#688]
  Op#113 CONV_2D(T#688, T#186, T#187) -> [T#689]
  Op#114 CONV_2D(T#689, T#188, T#189) -> [T#690]
  Op#115 CONV_2D(T#689, T#190, T#191) -> [T#691]
  Op#116 CONV_2D(T#655, T#192, T#193) -> [T#692]
  Op#117 CONV_2D(T#655, T#194, T#195) -> [T#693]
  Op#118 CONV_2D(T#609, T#196, T#197) -> [T#694]
  Op#119 CONV_2D(T#689, T#198, T#199) -> [T#695]
  Op#120 MAX_POOL_2D(T#695) -> [T#696]
  Op#121 MAX_POOL_2D(T#696) -> [T#697]
  Op#122 RESIZE_NEAREST_NEIGHBOR(T#697, T#1) -> [T#698]
  Op#123 ADD(T#696, T#698) -> [T#699]
  Op#124 DEPTHWISE_CONV_2D(T#699, T#200, T#201) -> [T#700]
  Op#125 CONV_2D(T#700, T#307, T#308) -> [T#701]
  Op#126 RESIZE_NEAREST_NEIGHBOR(T#701, T#2) -> [T#702]
  Op#127 ADD(T#690, T#702) -> [T#703]
  Op#128 DEPTHWISE_CONV_2D(T#703, T#309, T#202) -> [T#704]
  Op#129 CONV_2D(T#704, T#310, T#311) -> [T#705]
  Op#130 RESIZE_NEAREST_NEIGHBOR(T#705, T#3) -> [T#706]
  Op#131 ADD(T#692, T#706) -> [T#707]
  Op#132 DEPTHWISE_CONV_2D(T#707, T#312, T#203) -> [T#708]
  Op#133 CONV_2D(T#708, T#313, T#314) -> [T#709]
  Op#134 RESIZE_NEAREST_NEIGHBOR(T#709, T#4) -> [T#710]
  Op#135 ADD(T#694, T#710) -> [T#711]
  Op#136 DEPTHWISE_CONV_2D(T#711, T#315, T#204) -> [T#712]
  Op#137 CONV_2D(T#712, T#316, T#317) -> [T#713]
  Op#138 MAX_POOL_2D(T#713) -> [T#714]
  Op#139 ADD(T#693, T#709) -> [T#715]
  Op#140 ADD(T#715, T#714) -> [T#716]
  Op#141 DEPTHWISE_CONV_2D(T#716, T#318, T#205) -> [T#717]
  Op#142 CONV_2D(T#717, T#319, T#320) -> [T#718]
  Op#143 MAX_POOL_2D(T#718) -> [T#719]
  Op#144 ADD(T#691, T#705) -> [T#720]
  Op#145 ADD(T#720, T#719) -> [T#721]
  Op#146 DEPTHWISE_CONV_2D(T#721, T#321, T#206) -> [T#722]
  Op#147 CONV_2D(T#722, T#322, T#323) -> [T#723]
  Op#148 MAX_POOL_2D(T#723) -> [T#724]
  Op#149 ADD(T#696, T#701) -> [T#725]
  Op#150 ADD(T#725, T#724) -> [T#726]
  Op#151 DEPTHWISE_CONV_2D(T#726, T#324, T#207) -> [T#727]
  Op#152 CONV_2D(T#727, T#325, T#326) -> [T#728]
  Op#153 MAX_POOL_2D(T#728) -> [T#729]
  Op#154 ADD(T#697, T#729) -> [T#730]
  Op#155 DEPTHWISE_CONV_2D(T#730, T#327, T#208) -> [T#731]
  Op#156 CONV_2D(T#731, T#328, T#329) -> [T#732]
  Op#157 RESIZE_NEAREST_NEIGHBOR(T#732, T#1) -> [T#733]
  Op#158 ADD(T#728, T#733) -> [T#734]
  Op#159 DEPTHWISE_CONV_2D(T#734, T#330, T#209) -> [T#735]
  Op#160 CONV_2D(T#735, T#331, T#332) -> [T#736]
  Op#161 RESIZE_NEAREST_NEIGHBOR(T#736, T#2) -> [T#737]
  Op#162 ADD(T#723, T#737) -> [T#738]
  Op#163 DEPTHWISE_CONV_2D(T#738, T#333, T#210) -> [T#739]
  Op#164 CONV_2D(T#739, T#334, T#335) -> [T#740]
  Op#165 RESIZE_NEAREST_NEIGHBOR(T#740, T#3) -> [T#741]
  Op#166 ADD(T#718, T#741) -> [T#742]
  Op#167 DEPTHWISE_CONV_2D(T#742, T#336, T#211) -> [T#743]
  Op#168 CONV_2D(T#743, T#337, T#338) -> [T#744]
  Op#169 RESIZE_NEAREST_NEIGHBOR(T#744, T#4) -> [T#745]
  Op#170 ADD(T#713, T#745) -> [T#746]
  Op#171 DEPTHWISE_CONV_2D(T#746, T#339, T#212) -> [T#747]
  Op#172 CONV_2D(T#747, T#340, T#341) -> [T#748]
  Op#173 MAX_POOL_2D(T#748) -> [T#749]
  Op#174 ADD(T#718, T#744) -> [T#750]
  Op#175 ADD(T#750, T#749) -> [T#751]
  Op#176 DEPTHWISE_CONV_2D(T#751, T#342, T#213) -> [T#752]
  Op#177 CONV_2D(T#752, T#343, T#344) -> [T#753]
  Op#178 MAX_POOL_2D(T#753) -> [T#754]
  Op#179 ADD(T#723, T#740) -> [T#755]
  Op#180 ADD(T#755, T#754) -> [T#756]
  Op#181 DEPTHWISE_CONV_2D(T#756, T#345, T#214) -> [T#757]
  Op#182 CONV_2D(T#757, T#346, T#347) -> [T#758]
  Op#183 MAX_POOL_2D(T#758) -> [T#759]
  Op#184 ADD(T#728, T#736) -> [T#760]
  Op#185 ADD(T#760, T#759) -> [T#761]
  Op#186 DEPTHWISE_CONV_2D(T#761, T#348, T#215) -> [T#762]
  Op#187 CONV_2D(T#762, T#349, T#350) -> [T#763]
  Op#188 MAX_POOL_2D(T#763) -> [T#764]
  Op#189 ADD(T#732, T#764) -> [T#765]
  Op#190 DEPTHWISE_CONV_2D(T#765, T#351, T#216) -> [T#766]
  Op#191 CONV_2D(T#766, T#352, T#353) -> [T#767]
  Op#192 RESIZE_NEAREST_NEIGHBOR(T#767, T#1) -> [T#768]
  Op#193 ADD(T#763, T#768) -> [T#769]
  Op#194 DEPTHWISE_CONV_2D(T#769, T#354, T#217) -> [T#770]
  Op#195 CONV_2D(T#770, T#355, T#356) -> [T#771]
  Op#196 RESIZE_NEAREST_NEIGHBOR(T#771, T#2) -> [T#772]
  Op#197 ADD(T#758, T#772) -> [T#773]
  Op#198 DEPTHWISE_CONV_2D(T#773, T#357, T#218) -> [T#774]
  Op#199 CONV_2D(T#774, T#358, T#359) -> [T#775]
  Op#200 RESIZE_NEAREST_NEIGHBOR(T#775, T#3) -> [T#776]
  Op#201 ADD(T#753, T#776) -> [T#777]
  Op#202 DEPTHWISE_CONV_2D(T#777, T#360, T#219) -> [T#778]
  Op#203 CONV_2D(T#778, T#361, T#362) -> [T#779]
  Op#204 RESIZE_NEAREST_NEIGHBOR(T#779, T#4) -> [T#780]
  Op#205 ADD(T#748, T#780) -> [T#781]
  Op#206 DEPTHWISE_CONV_2D(T#781, T#363, T#220) -> [T#782]
  Op#207 CONV_2D(T#782, T#364, T#365) -> [T#783]
  Op#208 MAX_POOL_2D(T#783) -> [T#784]
  Op#209 ADD(T#753, T#779) -> [T#785]
  Op#210 ADD(T#785, T#784) -> [T#786]
  Op#211 DEPTHWISE_CONV_2D(T#786, T#366, T#221) -> [T#787]
  Op#212 CONV_2D(T#787, T#367, T#368) -> [T#788]
  Op#213 MAX_POOL_2D(T#788) -> [T#789]
  Op#214 ADD(T#758, T#775) -> [T#790]
  Op#215 ADD(T#790, T#789) -> [T#791]
  Op#216 DEPTHWISE_CONV_2D(T#791, T#369, T#222) -> [T#792]
  Op#217 CONV_2D(T#792, T#370, T#371) -> [T#793]
  Op#218 MAX_POOL_2D(T#793) -> [T#794]
  Op#219 ADD(T#763, T#771) -> [T#795]
  Op#220 ADD(T#795, T#794) -> [T#796]
  Op#221 DEPTHWISE_CONV_2D(T#796, T#372, T#223) -> [T#797]
  Op#222 CONV_2D(T#797, T#373, T#374) -> [T#798]
  Op#223 MAX_POOL_2D(T#798) -> [T#799]
  Op#224 ADD(T#767, T#799) -> [T#800]
  Op#225 DEPTHWISE_CONV_2D(T#800, T#375, T#224) -> [T#801]
  Op#226 CONV_2D(T#801, T#376, T#377) -> [T#802]
  Op#227 RESIZE_NEAREST_NEIGHBOR(T#802, T#1) -> [T#803]
  Op#228 ADD(T#798, T#803) -> [T#804]
  Op#229 DEPTHWISE_CONV_2D(T#804, T#378, T#225) -> [T#805]
  Op#230 CONV_2D(T#805, T#379, T#380) -> [T#806]
  Op#231 RESIZE_NEAREST_NEIGHBOR(T#806, T#2) -> [T#807]
  Op#232 ADD(T#793, T#807) -> [T#808]
  Op#233 DEPTHWISE_CONV_2D(T#808, T#381, T#226) -> [T#809]
  Op#234 CONV_2D(T#809, T#382, T#383) -> [T#810]
  Op#235 RESIZE_NEAREST_NEIGHBOR(T#810, T#3) -> [T#811]
  Op#236 ADD(T#788, T#811) -> [T#812]
  Op#237 DEPTHWISE_CONV_2D(T#812, T#384, T#227) -> [T#813]
  Op#238 CONV_2D(T#813, T#385, T#386) -> [T#814]
  Op#239 RESIZE_NEAREST_NEIGHBOR(T#814, T#4) -> [T#815]
  Op#240 ADD(T#783, T#815) -> [T#816]
  Op#241 DEPTHWISE_CONV_2D(T#816, T#387, T#228) -> [T#817]
  Op#242 CONV_2D(T#817, T#388, T#389) -> [T#818]
  Op#243 MAX_POOL_2D(T#818) -> [T#819]
  Op#244 ADD(T#788, T#814) -> [T#820]
  Op#245 ADD(T#820, T#819) -> [T#821]
  Op#246 DEPTHWISE_CONV_2D(T#821, T#390, T#229) -> [T#822]
  Op#247 CONV_2D(T#822, T#391, T#392) -> [T#823]
  Op#248 MAX_POOL_2D(T#823) -> [T#824]
  Op#249 ADD(T#793, T#810) -> [T#825]
  Op#250 ADD(T#825, T#824) -> [T#826]
  Op#251 DEPTHWISE_CONV_2D(T#826, T#393, T#230) -> [T#827]
  Op#252 CONV_2D(T#827, T#394, T#395) -> [T#828]
  Op#253 MAX_POOL_2D(T#828) -> [T#829]
  Op#254 ADD(T#798, T#806) -> [T#830]
  Op#255 ADD(T#830, T#829) -> [T#831]
  Op#256 DEPTHWISE_CONV_2D(T#831, T#396, T#231) -> [T#832]
  Op#257 CONV_2D(T#832, T#397, T#398) -> [T#833]
  Op#258 MAX_POOL_2D(T#833) -> [T#834]
  Op#259 ADD(T#802, T#834) -> [T#835]
  Op#260 DEPTHWISE_CONV_2D(T#835, T#399, T#232) -> [T#836]
  Op#261 CONV_2D(T#836, T#400, T#401) -> [T#837]
  Op#262 RESIZE_NEAREST_NEIGHBOR(T#837, T#1) -> [T#838]
  Op#263 ADD(T#833, T#838) -> [T#839]
  Op#264 DEPTHWISE_CONV_2D(T#839, T#402, T#233) -> [T#840]
  Op#265 CONV_2D(T#840, T#403, T#404) -> [T#841]
  Op#266 RESIZE_NEAREST_NEIGHBOR(T#841, T#2) -> [T#842]
  Op#267 ADD(T#828, T#842) -> [T#843]
  Op#268 DEPTHWISE_CONV_2D(T#843, T#405, T#234) -> [T#844]
  Op#269 CONV_2D(T#844, T#406, T#407) -> [T#845]
  Op#270 RESIZE_NEAREST_NEIGHBOR(T#845, T#3) -> [T#846]
  Op#271 ADD(T#823, T#846) -> [T#847]
  Op#272 DEPTHWISE_CONV_2D(T#847, T#408, T#235) -> [T#848]
  Op#273 CONV_2D(T#848, T#409, T#410) -> [T#849]
  Op#274 RESIZE_NEAREST_NEIGHBOR(T#849, T#4) -> [T#850]
  Op#275 ADD(T#818, T#850) -> [T#851]
  Op#276 DEPTHWISE_CONV_2D(T#851, T#411, T#236) -> [T#852]
  Op#277 CONV_2D(T#852, T#412, T#413) -> [T#853]
  Op#278 MAX_POOL_2D(T#853) -> [T#854]
  Op#279 ADD(T#823, T#849) -> [T#855]
  Op#280 ADD(T#855, T#854) -> [T#856]
  Op#281 DEPTHWISE_CONV_2D(T#856, T#414, T#237) -> [T#857]
  Op#282 CONV_2D(T#857, T#415, T#416) -> [T#858]
  Op#283 MAX_POOL_2D(T#858) -> [T#859]
  Op#284 ADD(T#828, T#845) -> [T#860]
  Op#285 ADD(T#860, T#859) -> [T#861]
  Op#286 DEPTHWISE_CONV_2D(T#861, T#417, T#238) -> [T#862]
  Op#287 CONV_2D(T#862, T#418, T#419) -> [T#863]
  Op#288 MAX_POOL_2D(T#863) -> [T#864]
  Op#289 ADD(T#833, T#841) -> [T#865]
  Op#290 ADD(T#865, T#864) -> [T#866]
  Op#291 DEPTHWISE_CONV_2D(T#866, T#420, T#239) -> [T#867]
  Op#292 CONV_2D(T#867, T#421, T#422) -> [T#868]
  Op#293 MAX_POOL_2D(T#868) -> [T#869]
  Op#294 ADD(T#837, T#869) -> [T#870]
  Op#295 DEPTHWISE_CONV_2D(T#870, T#423, T#240) -> [T#871]
  Op#296 CONV_2D(T#871, T#424, T#425) -> [T#872]
  Op#297 RESIZE_NEAREST_NEIGHBOR(T#872, T#1) -> [T#873]
  Op#298 ADD(T#868, T#873) -> [T#874]
  Op#299 DEPTHWISE_CONV_2D(T#874, T#426, T#241) -> [T#875]
  Op#300 CONV_2D(T#875, T#427, T#428) -> [T#876]
  Op#301 RESIZE_NEAREST_NEIGHBOR(T#876, T#2) -> [T#877]
  Op#302 ADD(T#863, T#877) -> [T#878]
  Op#303 DEPTHWISE_CONV_2D(T#878, T#429, T#242) -> [T#879]
  Op#304 CONV_2D(T#879, T#430, T#431) -> [T#880]
  Op#305 RESIZE_NEAREST_NEIGHBOR(T#880, T#3) -> [T#881]
  Op#306 ADD(T#858, T#881) -> [T#882]
  Op#307 DEPTHWISE_CONV_2D(T#882, T#432, T#243) -> [T#883]
  Op#308 CONV_2D(T#883, T#433, T#434) -> [T#884]
  Op#309 RESIZE_NEAREST_NEIGHBOR(T#884, T#4) -> [T#885]
  Op#310 ADD(T#853, T#885) -> [T#886]
  Op#311 DEPTHWISE_CONV_2D(T#886, T#435, T#244) -> [T#887]
  Op#312 CONV_2D(T#887, T#436, T#437) -> [T#888]
  Op#313 MAX_POOL_2D(T#888) -> [T#889]
  Op#314 ADD(T#858, T#884) -> [T#890]
  Op#315 ADD(T#890, T#889) -> [T#891]
  Op#316 DEPTHWISE_CONV_2D(T#891, T#438, T#245) -> [T#892]
  Op#317 CONV_2D(T#892, T#439, T#440) -> [T#893]
  Op#318 MAX_POOL_2D(T#893) -> [T#894]
  Op#319 ADD(T#863, T#880) -> [T#895]
  Op#320 ADD(T#895, T#894) -> [T#896]
  Op#321 DEPTHWISE_CONV_2D(T#896, T#441, T#246) -> [T#897]
  Op#322 CONV_2D(T#897, T#442, T#443) -> [T#898]
  Op#323 MAX_POOL_2D(T#898) -> [T#899]
  Op#324 ADD(T#868, T#876) -> [T#900]
  Op#325 ADD(T#900, T#899) -> [T#901]
  Op#326 DEPTHWISE_CONV_2D(T#901, T#444, T#247) -> [T#902]
  Op#327 CONV_2D(T#902, T#445, T#446) -> [T#903]
  Op#328 MAX_POOL_2D(T#903) -> [T#904]
  Op#329 ADD(T#872, T#904) -> [T#905]
  Op#330 DEPTHWISE_CONV_2D(T#905, T#447, T#248) -> [T#906]
  Op#331 CONV_2D(T#906, T#448, T#449) -> [T#907]
  Op#332 RESIZE_NEAREST_NEIGHBOR(T#907, T#1) -> [T#908]
  Op#333 ADD(T#903, T#908) -> [T#909]
  Op#334 DEPTHWISE_CONV_2D(T#909, T#450, T#249) -> [T#910]
  Op#335 CONV_2D(T#910, T#451, T#452) -> [T#911]
  Op#336 RESIZE_NEAREST_NEIGHBOR(T#911, T#2) -> [T#912]
  Op#337 ADD(T#898, T#912) -> [T#913]
  Op#338 DEPTHWISE_CONV_2D(T#913, T#453, T#250) -> [T#914]
  Op#339 CONV_2D(T#914, T#454, T#455) -> [T#915]
  Op#340 RESIZE_NEAREST_NEIGHBOR(T#915, T#3) -> [T#916]
  Op#341 ADD(T#893, T#916) -> [T#917]
  Op#342 DEPTHWISE_CONV_2D(T#917, T#456, T#251) -> [T#918]
  Op#343 CONV_2D(T#918, T#457, T#458) -> [T#919]
  Op#344 RESIZE_NEAREST_NEIGHBOR(T#919, T#4) -> [T#920]
  Op#345 ADD(T#888, T#920) -> [T#921]
  Op#346 DEPTHWISE_CONV_2D(T#921, T#459, T#252) -> [T#922]
  Op#347 CONV_2D(T#922, T#460, T#461) -> [T#923]
  Op#348 DEPTHWISE_CONV_2D(T#923, T#462, T#253) -> [T#924]
  Op#349 CONV_2D(T#924, T#463, T#464) -> [T#925]
  Op#350 DEPTHWISE_CONV_2D(T#925, T#465, T#254) -> [T#926]
  Op#351 CONV_2D(T#926, T#466, T#467) -> [T#927]
  Op#352 DEPTHWISE_CONV_2D(T#927, T#468, T#255) -> [T#928]
  Op#353 CONV_2D(T#928, T#469, T#470) -> [T#929]
  Op#354 DEPTHWISE_CONV_2D(T#929, T#471, T#256) -> [T#930]
  Op#355 CONV_2D(T#930, T#472, T#473) -> [T#931]
  Op#356 DEPTHWISE_CONV_2D(T#931, T#474, T#257) -> [T#932]
  Op#357 CONV_2D(T#932, T#475, T#476) -> [T#933]
  Op#358 DEPTHWISE_CONV_2D(T#923, T#481, T#258) -> [T#934]
  Op#359 CONV_2D(T#934, T#482, T#483) -> [T#935]
  Op#360 DEPTHWISE_CONV_2D(T#935, T#484, T#259) -> [T#936]
  Op#361 CONV_2D(T#936, T#485, T#486) -> [T#937]
  Op#362 DEPTHWISE_CONV_2D(T#937, T#487, T#260) -> [T#938]
  Op#363 CONV_2D(T#938, T#488, T#489) -> [T#939]
  Op#364 DEPTHWISE_CONV_2D(T#939, T#490, T#261) -> [T#940]
  Op#365 CONV_2D(T#940, T#491, T#492) -> [T#941]
  Op#366 DEPTHWISE_CONV_2D(T#941, T#493, T#262) -> [T#942]
  Op#367 CONV_2D(T#942, T#494, T#495) -> [T#943]
  Op#368 MAX_POOL_2D(T#923) -> [T#944]
  Op#369 ADD(T#893, T#919) -> [T#945]
  Op#370 ADD(T#945, T#944) -> [T#946]
  Op#371 DEPTHWISE_CONV_2D(T#946, T#500, T#263) -> [T#947]
  Op#372 CONV_2D(T#947, T#501, T#502) -> [T#948]
  Op#373 DEPTHWISE_CONV_2D(T#948, T#462, T#264) -> [T#949]
  Op#374 CONV_2D(T#949, T#503, T#504) -> [T#950]
  Op#375 DEPTHWISE_CONV_2D(T#950, T#465, T#265) -> [T#951]
  Op#376 CONV_2D(T#951, T#505, T#506) -> [T#952]
  Op#377 DEPTHWISE_CONV_2D(T#952, T#468, T#266) -> [T#953]
  Op#378 CONV_2D(T#953, T#507, T#508) -> [T#954]
  Op#379 DEPTHWISE_CONV_2D(T#954, T#471, T#267) -> [T#955]
  Op#380 CONV_2D(T#955, T#509, T#510) -> [T#956]
  Op#381 DEPTHWISE_CONV_2D(T#956, T#474, T#268) -> [T#957]
  Op#382 CONV_2D(T#957, T#475, T#477) -> [T#958]
  Op#383 DEPTHWISE_CONV_2D(T#948, T#481, T#269) -> [T#959]
  Op#384 CONV_2D(T#959, T#511, T#512) -> [T#960]
  Op#385 DEPTHWISE_CONV_2D(T#960, T#484, T#270) -> [T#961]
  Op#386 CONV_2D(T#961, T#513, T#514) -> [T#962]
  Op#387 DEPTHWISE_CONV_2D(T#962, T#487, T#271) -> [T#963]
  Op#388 CONV_2D(T#963, T#515, T#516) -> [T#964]
  Op#389 DEPTHWISE_CONV_2D(T#964, T#490, T#272) -> [T#965]
  Op#390 CONV_2D(T#965, T#517, T#518) -> [T#966]
  Op#391 DEPTHWISE_CONV_2D(T#966, T#493, T#273) -> [T#967]
  Op#392 CONV_2D(T#967, T#494, T#496) -> [T#968]
  Op#393 MAX_POOL_2D(T#948) -> [T#969]
  Op#394 ADD(T#898, T#915) -> [T#970]
  Op#395 ADD(T#970, T#969) -> [T#971]
  Op#396 DEPTHWISE_CONV_2D(T#971, T#519, T#274) -> [T#972]
  Op#397 CONV_2D(T#972, T#520, T#521) -> [T#973]
  Op#398 DEPTHWISE_CONV_2D(T#973, T#462, T#275) -> [T#974]
  Op#399 CONV_2D(T#974, T#522, T#523) -> [T#975]
  Op#400 DEPTHWISE_CONV_2D(T#975, T#465, T#276) -> [T#976]
  Op#401 CONV_2D(T#976, T#524, T#525) -> [T#977]
  Op#402 DEPTHWISE_CONV_2D(T#977, T#468, T#277) -> [T#978]
  Op#403 CONV_2D(T#978, T#526, T#527) -> [T#979]
  Op#404 DEPTHWISE_CONV_2D(T#979, T#471, T#278) -> [T#980]
  Op#405 CONV_2D(T#980, T#528, T#529) -> [T#981]
  Op#406 DEPTHWISE_CONV_2D(T#981, T#474, T#279) -> [T#982]
  Op#407 CONV_2D(T#982, T#475, T#478) -> [T#983]
  Op#408 DEPTHWISE_CONV_2D(T#973, T#481, T#280) -> [T#984]
  Op#409 CONV_2D(T#984, T#530, T#531) -> [T#985]
  Op#410 DEPTHWISE_CONV_2D(T#985, T#484, T#281) -> [T#986]
  Op#411 CONV_2D(T#986, T#532, T#533) -> [T#987]
  Op#412 DEPTHWISE_CONV_2D(T#987, T#487, T#282) -> [T#988]
  Op#413 CONV_2D(T#988, T#534, T#535) -> [T#989]
  Op#414 DEPTHWISE_CONV_2D(T#989, T#490, T#283) -> [T#990]
  Op#415 CONV_2D(T#990, T#536, T#537) -> [T#991]
  Op#416 DEPTHWISE_CONV_2D(T#991, T#493, T#284) -> [T#992]
  Op#417 CONV_2D(T#992, T#494, T#497) -> [T#993]
  Op#418 MAX_POOL_2D(T#973) -> [T#994]
  Op#419 ADD(T#903, T#911) -> [T#995]
  Op#420 ADD(T#995, T#994) -> [T#996]
  Op#421 DEPTHWISE_CONV_2D(T#996, T#538, T#285) -> [T#997]
  Op#422 CONV_2D(T#997, T#539, T#540) -> [T#998]
  Op#423 DEPTHWISE_CONV_2D(T#998, T#462, T#286) -> [T#999]
  Op#424 CONV_2D(T#999, T#541, T#542) -> [T#1000]
  Op#425 DEPTHWISE_CONV_2D(T#1000, T#465, T#287) -> [T#1001]
  Op#426 CONV_2D(T#1001, T#543, T#544) -> [T#1002]
  Op#427 DEPTHWISE_CONV_2D(T#1002, T#468, T#288) -> [T#1003]
  Op#428 CONV_2D(T#1003, T#545, T#546) -> [T#1004]
  Op#429 DEPTHWISE_CONV_2D(T#1004, T#471, T#289) -> [T#1005]
  Op#430 CONV_2D(T#1005, T#547, T#548) -> [T#1006]
  Op#431 DEPTHWISE_CONV_2D(T#1006, T#474, T#290) -> [T#1007]
  Op#432 CONV_2D(T#1007, T#475, T#479) -> [T#1008]
  Op#433 DEPTHWISE_CONV_2D(T#998, T#481, T#291) -> [T#1009]
  Op#434 CONV_2D(T#1009, T#549, T#550) -> [T#1010]
  Op#435 DEPTHWISE_CONV_2D(T#1010, T#484, T#292) -> [T#1011]
  Op#436 CONV_2D(T#1011, T#551, T#552) -> [T#1012]
  Op#437 DEPTHWISE_CONV_2D(T#1012, T#487, T#293) -> [T#1013]
  Op#438 CONV_2D(T#1013, T#553, T#554) -> [T#1014]
  Op#439 DEPTHWISE_CONV_2D(T#1014, T#490, T#294) -> [T#1015]
  Op#440 CONV_2D(T#1015, T#555, T#556) -> [T#1016]
  Op#441 DEPTHWISE_CONV_2D(T#1016, T#493, T#295) -> [T#1017]
  Op#442 CONV_2D(T#1017, T#494, T#498) -> [T#1018]
  Op#443 MAX_POOL_2D(T#998) -> [T#1019]
  Op#444 ADD(T#907, T#1019) -> [T#1020]
  Op#445 DEPTHWISE_CONV_2D(T#1020, T#557, T#296) -> [T#1021]
  Op#446 CONV_2D(T#1021, T#558, T#559) -> [T#1022]
  Op#447 DEPTHWISE_CONV_2D(T#1022, T#462, T#297) -> [T#1023]
  Op#448 CONV_2D(T#1023, T#560, T#561) -> [T#1024]
  Op#449 DEPTHWISE_CONV_2D(T#1024, T#465, T#298) -> [T#1025]
  Op#450 CONV_2D(T#1025, T#562, T#563) -> [T#1026]
  Op#451 DEPTHWISE_CONV_2D(T#1026, T#468, T#299) -> [T#1027]
  Op#452 CONV_2D(T#1027, T#564, T#565) -> [T#1028]
  Op#453 DEPTHWISE_CONV_2D(T#1028, T#471, T#300) -> [T#1029]
  Op#454 CONV_2D(T#1029, T#566, T#567) -> [T#1030]
  Op#455 DEPTHWISE_CONV_2D(T#1030, T#474, T#301) -> [T#1031]
  Op#456 CONV_2D(T#1031, T#475, T#480) -> [T#1032]
  Op#457 DEPTHWISE_CONV_2D(T#1022, T#481, T#302) -> [T#1033]
  Op#458 CONV_2D(T#1033, T#568, T#569) -> [T#1034]
  Op#459 DEPTHWISE_CONV_2D(T#1034, T#484, T#303) -> [T#1035]
  Op#460 CONV_2D(T#1035, T#570, T#571) -> [T#1036]
  Op#461 DEPTHWISE_CONV_2D(T#1036, T#487, T#304) -> [T#1037]
  Op#462 CONV_2D(T#1037, T#572, T#573) -> [T#1038]
  Op#463 DEPTHWISE_CONV_2D(T#1038, T#490, T#305) -> [T#1039]
  Op#464 CONV_2D(T#1039, T#574, T#575) -> [T#1040]
  Op#465 DEPTHWISE_CONV_2D(T#1040, T#493, T#306) -> [T#1041]
  Op#466 CONV_2D(T#1041, T#494, T#499) -> [T#1042]
  Op#467 RESHAPE(T#943, T#5) -> [T#1043]
  Op#468 RESHAPE(T#933, T#6) -> [T#1044]
  Op#469 RESHAPE(T#968, T#5) -> [T#1045]
  Op#470 RESHAPE(T#958, T#6) -> [T#1046]
  Op#471 RESHAPE(T#993, T#5) -> [T#1047]
  Op#472 RESHAPE(T#983, T#6) -> [T#1048]
  Op#473 RESHAPE(T#1018, T#5) -> [T#1049]
  Op#474 RESHAPE(T#1008, T#6) -> [T#1050]
  Op#475 RESHAPE(T#1042, T#5) -> [T#1051]
  Op#476 CONCATENATION(T#1043, T#1045, T#1047, T#1049, T#1051) -> [T#1052]
  Op#477 LOGISTIC(T#1052) -> [T#1053]
  Op#478 DEQUANTIZE(T#1053) -> [T#1054]
  Op#479 RESHAPE(T#1032, T#6) -> [T#1055]
  Op#480 CONCATENATION(T#1044, T#1046, T#1048, T#1050, T#1055) -> [T#1056]
  Op#481 DEQUANTIZE(T#1056) -> [T#1057]
  Op#482 TFLite_Detection_PostProcess(T#1057, T#1054, T#7) -> [T#1058, T#1059, T#1060, T#1061]
GPU COMPATIBILITY WARNING: Not supported custom op TFLite_Detection_PostProcess

GPU COMPATIBILITY WARNING: Subgraph#0 has GPU delegate compatibility issues at nodes 482 with TFLite runtime version 2.8.2

Tensors of Subgraph#0
  T#0(tflite_images:0) shape:[1, 640, 640, 3], type:UINT8
  T#1(fpn_cells/cell_0/fnode0/resample_1_4_5/ResizeNearestNeighbor/size) shape:[2], type:INT32 RO 8 bytes
  T#2(fpn_cells/cell_0/fnode1/resample_1_5_6/ResizeNearestNeighbor/size) shape:[2], type:INT32 RO 8 bytes
  T#3(fpn_cells/cell_0/fnode2/resample_1_6_7/ResizeNearestNeighbor/size) shape:[2], type:INT32 RO 8 bytes
  T#4(fpn_cells/cell_0/fnode3/resample_1_7_8/ResizeNearestNeighbor/size) shape:[2], type:INT32 RO 8 bytes
  T#5(Reshape/shape) shape:[3], type:INT32 RO 12 bytes
  T#6(Reshape_1/shape) shape:[3], type:INT32 RO 12 bytes
  T#7(stack) shape:[76725, 4], type:FLOAT32 RO 1227600 bytes
  T#8(efficientnet-lite4/stem/conv2d/Conv2D) shape:[32, 3, 3, 3], type:INT8 RO 864 bytes
  T#9(efficientnet-lite4/stem/tpu_batch_normalization/FusedBatchNormV3) shape:[32], type:INT32 RO 128 bytes
  T#10(efficientnet-lite4/blocks_0/tpu_batch_normalization/FusedBatchNormV3;efficientnet-lite4/blocks_0/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_4/conv2d_1/Conv2D) shape:[1, 3, 3, 32], type:INT8 RO 288 bytes
  T#11(efficientnet-lite4/blocks_0/tpu_batch_normalization/FusedBatchNormV3) shape:[32], type:INT32 RO 128 bytes
  T#12(efficientnet-lite4/blocks_0/conv2d/Conv2D) shape:[24, 1, 1, 32], type:INT8 RO 768 bytes
  T#13(efficientnet-lite4/blocks_0/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_0/conv2d/Conv2D) shape:[24], type:INT32 RO 96 bytes
  T#14(efficientnet-lite4/blocks_1/conv2d/Conv2D) shape:[144, 1, 1, 24], type:INT8 RO 3456 bytes
  T#15(efficientnet-lite4/blocks_1/tpu_batch_normalization/FusedBatchNormV3) shape:[144], type:INT32 RO 576 bytes
  T#16(efficientnet-lite4/blocks_1/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_1/depthwise_conv2d/depthwise) shape:[1, 3, 3, 144], type:INT8 RO 1296 bytes
  T#17(efficientnet-lite4/blocks_1/tpu_batch_normalization_1/FusedBatchNormV3) shape:[144], type:INT32 RO 576 bytes
  T#18(efficientnet-lite4/blocks_1/conv2d_1/Conv2D) shape:[32, 1, 1, 144], type:INT8 RO 4608 bytes
  T#19(efficientnet-lite4/blocks_1/tpu_batch_normalization_2/FusedBatchNormV3;efficientnet-lite4/blocks_4/conv2d_1/Conv2D;efficientnet-lite4/blocks_1/conv2d_1/Conv2D) shape:[32], type:INT32 RO 128 bytes
  T#20(efficientnet-lite4/blocks_2/conv2d/Conv2D) shape:[192, 1, 1, 32], type:INT8 RO 6144 bytes
  T#21(efficientnet-lite4/blocks_2/tpu_batch_normalization/FusedBatchNormV3) shape:[192], type:INT32 RO 768 bytes
  T#22(efficientnet-lite4/blocks_2/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_2/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_5/depthwise_conv2d/depthwise) shape:[1, 3, 3, 192], type:INT8 RO 1728 bytes
  T#23(efficientnet-lite4/blocks_2/tpu_batch_normalization_1/FusedBatchNormV3) shape:[192], type:INT32 RO 768 bytes
  T#24(efficientnet-lite4/blocks_2/conv2d_1/Conv2D) shape:[32, 1, 1, 192], type:INT8 RO 6144 bytes
  T#25(efficientnet-lite4/blocks_2/tpu_batch_normalization_2/FusedBatchNormV3;efficientnet-lite4/blocks_4/conv2d_1/Conv2D;efficientnet-lite4/blocks_2/conv2d_1/Conv2D) shape:[32], type:INT32 RO 128 bytes
  T#26(efficientnet-lite4/blocks_3/conv2d/Conv2D) shape:[192, 1, 1, 32], type:INT8 RO 6144 bytes
  T#27(efficientnet-lite4/blocks_3/tpu_batch_normalization/FusedBatchNormV3) shape:[192], type:INT32 RO 768 bytes
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  T#557(fpn_cells/cell_6/fnode7/op_after_combine12/conv/separable_conv2d/depthwise) shape:[1, 3, 3, 224], type:INT8 RO 2016 bytes
  T#558(fpn_cells/cell_6/fnode7/op_after_combine12/conv/separable_conv2d) shape:[224, 1, 1, 224], type:INT8 RO 50176 bytes
  T#559(fpn_cells/cell_6/fnode7/op_after_combine12/bn/FusedBatchNormV3;fpn_cells/cell_6/fnode7/op_after_combine12/conv/bias;fpn_cells/cell_6/fnode7/op_after_combine12/conv/BiasAdd) shape:[224], type:INT32 RO 896 bytes
  T#560(box_net/box-0/separable_conv2d_4) shape:[224, 1, 1, 224], type:INT8 RO 50176 bytes
  T#561(box_net/Relu6_16;box_net/box-0-bn-7/FusedBatchNormV3;box_net/box-0/bias;box_net/box-0/BiasAdd_4;class_net/class-predict/separable_conv2d_4/depthwise;box_net/box-0/separable_conv2d_4) shape:[224], type:INT32 RO 896 bytes
  T#562(box_net/box-1/separable_conv2d_4) shape:[224, 1, 1, 224], type:INT8 RO 50176 bytes
  T#563(box_net/Relu6_17;box_net/box-1-bn-7/FusedBatchNormV3;box_net/box-1/bias;box_net/box-1/BiasAdd_4;class_net/class-predict/separable_conv2d_4/depthwise;box_net/box-1/separable_conv2d_4) shape:[224], type:INT32 RO 896 bytes
  T#564(box_net/box-2/separable_conv2d_4) shape:[224, 1, 1, 224], type:INT8 RO 50176 bytes
  T#565(box_net/Relu6_18;box_net/box-2-bn-7/FusedBatchNormV3;box_net/box-2/bias;box_net/box-2/BiasAdd_4;class_net/class-predict/separable_conv2d_4/depthwise;box_net/box-2/separable_conv2d_4) shape:[224], type:INT32 RO 896 bytes
  T#566(box_net/box-3/separable_conv2d_4) shape:[224, 1, 1, 224], type:INT8 RO 50176 bytes
  T#567(box_net/Relu6_19;box_net/box-3-bn-7/FusedBatchNormV3;box_net/box-3/bias;box_net/box-3/BiasAdd_4;class_net/class-predict/separable_conv2d_4/depthwise;box_net/box-3/separable_conv2d_4) shape:[224], type:INT32 RO 896 bytes
  T#568(class_net/class-0/separable_conv2d_4) shape:[224, 1, 1, 224], type:INT8 RO 50176 bytes
  T#569(class_net/Relu6_16;class_net/class-0-bn-7/FusedBatchNormV3;class_net/class-0/bias;class_net/class-0/BiasAdd_4;class_net/class-predict/separable_conv2d_4/depthwise;class_net/class-0/separable_conv2d_4) shape:[224], type:INT32 RO 896 bytes
  T#570(class_net/class-1/separable_conv2d_4) shape:[224, 1, 1, 224], type:INT8 RO 50176 bytes
  T#571(class_net/Relu6_17;class_net/class-1-bn-7/FusedBatchNormV3;class_net/class-1/bias;class_net/class-1/BiasAdd_4;class_net/class-predict/separable_conv2d_4/depthwise;class_net/class-1/separable_conv2d_4) shape:[224], type:INT32 RO 896 bytes
  T#572(class_net/class-2/separable_conv2d_4) shape:[224, 1, 1, 224], type:INT8 RO 50176 bytes
  T#573(class_net/Relu6_18;class_net/class-2-bn-7/FusedBatchNormV3;class_net/class-2/bias;class_net/class-2/BiasAdd_4;class_net/class-predict/separable_conv2d_4/depthwise;class_net/class-2/separable_conv2d_4) shape:[224], type:INT32 RO 896 bytes
  T#574(class_net/class-3/separable_conv2d_4) shape:[224, 1, 1, 224], type:INT8 RO 50176 bytes
  T#575(class_net/Relu6_19;class_net/class-3-bn-7/FusedBatchNormV3;class_net/class-3/bias;class_net/class-3/BiasAdd_4;class_net/class-predict/separable_conv2d_4/depthwise;class_net/class-3/separable_conv2d_4) shape:[224], type:INT32 RO 896 bytes
  T#576(tfl.quantize) shape:[1, 640, 640, 3], type:INT8
  T#577(efficientnet-lite4/stem/Relu6;efficientnet-lite4/stem/tpu_batch_normalization/FusedBatchNormV3;efficientnet-lite4/blocks_4/conv2d_1/Conv2D;efficientnet-lite4/stem/conv2d/Conv2D) shape:[1, 320, 320, 32], type:INT8
  T#578(efficientnet-lite4/blocks_0/Relu6;efficientnet-lite4/blocks_0/tpu_batch_normalization/FusedBatchNormV3;efficientnet-lite4/blocks_0/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_4/conv2d_1/Conv2D) shape:[1, 320, 320, 32], type:INT8
  T#579(efficientnet-lite4/blocks_0/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_0/conv2d/Conv2D1) shape:[1, 320, 320, 24], type:INT8
  T#580(efficientnet-lite4/blocks_1/Relu6;efficientnet-lite4/blocks_1/tpu_batch_normalization/FusedBatchNormV3;efficientnet-lite4/blocks_1/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_1/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_1/conv2d/Conv2D) shape:[1, 320, 320, 144], type:INT8
  T#581(efficientnet-lite4/blocks_1/Relu6_1;efficientnet-lite4/blocks_1/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_1/depthwise_conv2d/depthwise) shape:[1, 160, 160, 144], type:INT8
  T#582(efficientnet-lite4/blocks_1/tpu_batch_normalization_2/FusedBatchNormV3;efficientnet-lite4/blocks_4/conv2d_1/Conv2D;efficientnet-lite4/blocks_1/conv2d_1/Conv2D1) shape:[1, 160, 160, 32], type:INT8
  T#583(efficientnet-lite4/blocks_2/Relu6;efficientnet-lite4/blocks_2/tpu_batch_normalization/FusedBatchNormV3;efficientnet-lite4/blocks_5/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_5/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_2/conv2d/Conv2D) shape:[1, 160, 160, 192], type:INT8
  T#584(efficientnet-lite4/blocks_2/Relu6_1;efficientnet-lite4/blocks_2/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_5/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_5/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_2/depthwise_conv2d/depthwise) shape:[1, 160, 160, 192], type:INT8
  T#585(efficientnet-lite4/blocks_2/tpu_batch_normalization_2/FusedBatchNormV3;efficientnet-lite4/blocks_4/conv2d_1/Conv2D;efficientnet-lite4/blocks_2/conv2d_1/Conv2D1) shape:[1, 160, 160, 32], type:INT8
  T#586(efficientnet-lite4/blocks_2/Add) shape:[1, 160, 160, 32], type:INT8
  T#587(efficientnet-lite4/blocks_3/Relu6;efficientnet-lite4/blocks_3/tpu_batch_normalization/FusedBatchNormV3;efficientnet-lite4/blocks_5/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_5/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_3/conv2d/Conv2D) shape:[1, 160, 160, 192], type:INT8
  T#588(efficientnet-lite4/blocks_3/Relu6_1;efficientnet-lite4/blocks_3/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_5/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_5/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_3/depthwise_conv2d/depthwise) shape:[1, 160, 160, 192], type:INT8
  T#589(efficientnet-lite4/blocks_3/tpu_batch_normalization_2/FusedBatchNormV3;efficientnet-lite4/blocks_4/conv2d_1/Conv2D;efficientnet-lite4/blocks_3/conv2d_1/Conv2D1) shape:[1, 160, 160, 32], type:INT8
  T#590(efficientnet-lite4/blocks_3/Add) shape:[1, 160, 160, 32], type:INT8
  T#591(efficientnet-lite4/blocks_4/Relu6;efficientnet-lite4/blocks_4/tpu_batch_normalization/FusedBatchNormV3;efficientnet-lite4/blocks_5/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_5/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_4/conv2d/Conv2D) shape:[1, 160, 160, 192], type:INT8
  T#592(efficientnet-lite4/blocks_4/Relu6_1;efficientnet-lite4/blocks_4/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_5/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_5/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_4/depthwise_conv2d/depthwise) shape:[1, 160, 160, 192], type:INT8
  T#593(efficientnet-lite4/blocks_4/tpu_batch_normalization_2/FusedBatchNormV3;efficientnet-lite4/blocks_4/conv2d_1/Conv2D1) shape:[1, 160, 160, 32], type:INT8
  T#594(efficientnet-lite4/blocks_4/Add) shape:[1, 160, 160, 32], type:INT8
  T#595(efficientnet-lite4/blocks_5/Relu6;efficientnet-lite4/blocks_5/tpu_batch_normalization/FusedBatchNormV3;efficientnet-lite4/blocks_5/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_5/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_5/conv2d/Conv2D) shape:[1, 160, 160, 192], type:INT8
  T#596(efficientnet-lite4/blocks_5/Relu6_1;efficientnet-lite4/blocks_5/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_5/depthwise_conv2d/depthwise) shape:[1, 80, 80, 192], type:INT8
  T#597(efficientnet-lite4/blocks_5/tpu_batch_normalization_2/FusedBatchNormV3;efficientnet-lite4/blocks_8/conv2d_1/Conv2D;efficientnet-lite4/blocks_5/conv2d_1/Conv2D1) shape:[1, 80, 80, 56], type:INT8
  T#598(efficientnet-lite4/blocks_6/Relu6;efficientnet-lite4/blocks_6/tpu_batch_normalization/FusedBatchNormV3;efficientnet-lite4/blocks_9/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_9/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_6/conv2d/Conv2D) shape:[1, 80, 80, 336], type:INT8
  T#599(efficientnet-lite4/blocks_6/Relu6_1;efficientnet-lite4/blocks_6/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_9/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_9/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_6/depthwise_conv2d/depthwise) shape:[1, 80, 80, 336], type:INT8
  T#600(efficientnet-lite4/blocks_6/tpu_batch_normalization_2/FusedBatchNormV3;efficientnet-lite4/blocks_8/conv2d_1/Conv2D;efficientnet-lite4/blocks_6/conv2d_1/Conv2D1) shape:[1, 80, 80, 56], type:INT8
  T#601(efficientnet-lite4/blocks_6/Add) shape:[1, 80, 80, 56], type:INT8
  T#602(efficientnet-lite4/blocks_7/Relu6;efficientnet-lite4/blocks_7/tpu_batch_normalization/FusedBatchNormV3;efficientnet-lite4/blocks_9/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_9/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_7/conv2d/Conv2D) shape:[1, 80, 80, 336], type:INT8
  T#603(efficientnet-lite4/blocks_7/Relu6_1;efficientnet-lite4/blocks_7/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_9/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_9/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_7/depthwise_conv2d/depthwise) shape:[1, 80, 80, 336], type:INT8
  T#604(efficientnet-lite4/blocks_7/tpu_batch_normalization_2/FusedBatchNormV3;efficientnet-lite4/blocks_8/conv2d_1/Conv2D;efficientnet-lite4/blocks_7/conv2d_1/Conv2D1) shape:[1, 80, 80, 56], type:INT8
  T#605(efficientnet-lite4/blocks_7/Add) shape:[1, 80, 80, 56], type:INT8
  T#606(efficientnet-lite4/blocks_8/Relu6;efficientnet-lite4/blocks_8/tpu_batch_normalization/FusedBatchNormV3;efficientnet-lite4/blocks_9/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_9/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_8/conv2d/Conv2D) shape:[1, 80, 80, 336], type:INT8
  T#607(efficientnet-lite4/blocks_8/Relu6_1;efficientnet-lite4/blocks_8/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_9/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_9/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_8/depthwise_conv2d/depthwise) shape:[1, 80, 80, 336], type:INT8
  T#608(efficientnet-lite4/blocks_8/tpu_batch_normalization_2/FusedBatchNormV3;efficientnet-lite4/blocks_8/conv2d_1/Conv2D1) shape:[1, 80, 80, 56], type:INT8
  T#609(efficientnet-lite4/blocks_8/Add) shape:[1, 80, 80, 56], type:INT8
  T#610(efficientnet-lite4/blocks_9/Relu6;efficientnet-lite4/blocks_9/tpu_batch_normalization/FusedBatchNormV3;efficientnet-lite4/blocks_9/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_9/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_9/conv2d/Conv2D) shape:[1, 80, 80, 336], type:INT8
  T#611(efficientnet-lite4/blocks_9/Relu6_1;efficientnet-lite4/blocks_9/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_9/depthwise_conv2d/depthwise) shape:[1, 40, 40, 336], type:INT8
  T#612(efficientnet-lite4/blocks_9/tpu_batch_normalization_2/FusedBatchNormV3;efficientnet-lite4/blocks_14/conv2d_1/Conv2D;efficientnet-lite4/blocks_9/conv2d_1/Conv2D1) shape:[1, 40, 40, 112], type:INT8
  T#613(efficientnet-lite4/blocks_10/Relu6;efficientnet-lite4/blocks_10/tpu_batch_normalization/FusedBatchNormV3;efficientnet-lite4/blocks_15/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_15/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_10/conv2d/Conv2D) shape:[1, 40, 40, 672], type:INT8
  T#614(efficientnet-lite4/blocks_10/Relu6_1;efficientnet-lite4/blocks_10/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_15/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_15/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_10/depthwise_conv2d/depthwise) shape:[1, 40, 40, 672], type:INT8
  T#615(efficientnet-lite4/blocks_10/tpu_batch_normalization_2/FusedBatchNormV3;efficientnet-lite4/blocks_14/conv2d_1/Conv2D;efficientnet-lite4/blocks_10/conv2d_1/Conv2D1) shape:[1, 40, 40, 112], type:INT8
  T#616(efficientnet-lite4/blocks_10/Add) shape:[1, 40, 40, 112], type:INT8
  T#617(efficientnet-lite4/blocks_11/Relu6;efficientnet-lite4/blocks_11/tpu_batch_normalization/FusedBatchNormV3;efficientnet-lite4/blocks_15/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_15/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_11/conv2d/Conv2D) shape:[1, 40, 40, 672], type:INT8
  T#618(efficientnet-lite4/blocks_11/Relu6_1;efficientnet-lite4/blocks_11/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_15/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_15/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_11/depthwise_conv2d/depthwise) shape:[1, 40, 40, 672], type:INT8
  T#619(efficientnet-lite4/blocks_11/tpu_batch_normalization_2/FusedBatchNormV3;efficientnet-lite4/blocks_14/conv2d_1/Conv2D;efficientnet-lite4/blocks_11/conv2d_1/Conv2D1) shape:[1, 40, 40, 112], type:INT8
  T#620(efficientnet-lite4/blocks_11/Add) shape:[1, 40, 40, 112], type:INT8
  T#621(efficientnet-lite4/blocks_12/Relu6;efficientnet-lite4/blocks_12/tpu_batch_normalization/FusedBatchNormV3;efficientnet-lite4/blocks_15/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_15/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_12/conv2d/Conv2D) shape:[1, 40, 40, 672], type:INT8
  T#622(efficientnet-lite4/blocks_12/Relu6_1;efficientnet-lite4/blocks_12/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_15/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_15/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_12/depthwise_conv2d/depthwise) shape:[1, 40, 40, 672], type:INT8
  T#623(efficientnet-lite4/blocks_12/tpu_batch_normalization_2/FusedBatchNormV3;efficientnet-lite4/blocks_14/conv2d_1/Conv2D;efficientnet-lite4/blocks_12/conv2d_1/Conv2D1) shape:[1, 40, 40, 112], type:INT8
  T#624(efficientnet-lite4/blocks_12/Add) shape:[1, 40, 40, 112], type:INT8
  T#625(efficientnet-lite4/blocks_13/Relu6;efficientnet-lite4/blocks_13/tpu_batch_normalization/FusedBatchNormV3;efficientnet-lite4/blocks_15/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_15/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_13/conv2d/Conv2D) shape:[1, 40, 40, 672], type:INT8
  T#626(efficientnet-lite4/blocks_13/Relu6_1;efficientnet-lite4/blocks_13/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_15/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_15/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_13/depthwise_conv2d/depthwise) shape:[1, 40, 40, 672], type:INT8
  T#627(efficientnet-lite4/blocks_13/tpu_batch_normalization_2/FusedBatchNormV3;efficientnet-lite4/blocks_14/conv2d_1/Conv2D;efficientnet-lite4/blocks_13/conv2d_1/Conv2D1) shape:[1, 40, 40, 112], type:INT8
  T#628(efficientnet-lite4/blocks_13/Add) shape:[1, 40, 40, 112], type:INT8
  T#629(efficientnet-lite4/blocks_14/Relu6;efficientnet-lite4/blocks_14/tpu_batch_normalization/FusedBatchNormV3;efficientnet-lite4/blocks_15/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_15/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_14/conv2d/Conv2D) shape:[1, 40, 40, 672], type:INT8
  T#630(efficientnet-lite4/blocks_14/Relu6_1;efficientnet-lite4/blocks_14/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_15/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_15/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_14/depthwise_conv2d/depthwise) shape:[1, 40, 40, 672], type:INT8
  T#631(efficientnet-lite4/blocks_14/tpu_batch_normalization_2/FusedBatchNormV3;efficientnet-lite4/blocks_14/conv2d_1/Conv2D1) shape:[1, 40, 40, 112], type:INT8
  T#632(efficientnet-lite4/blocks_14/Add) shape:[1, 40, 40, 112], type:INT8
  T#633(efficientnet-lite4/blocks_15/Relu6;efficientnet-lite4/blocks_15/tpu_batch_normalization/FusedBatchNormV3;efficientnet-lite4/blocks_15/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_15/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_15/conv2d/Conv2D) shape:[1, 40, 40, 672], type:INT8
  T#634(efficientnet-lite4/blocks_15/Relu6_1;efficientnet-lite4/blocks_15/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_15/depthwise_conv2d/depthwise) shape:[1, 40, 40, 672], type:INT8
  T#635(efficientnet-lite4/blocks_15/tpu_batch_normalization_2/FusedBatchNormV3;efficientnet-lite4/blocks_20/conv2d_1/Conv2D;efficientnet-lite4/blocks_15/conv2d_1/Conv2D1) shape:[1, 40, 40, 160], type:INT8
  T#636(efficientnet-lite4/blocks_16/Relu6;efficientnet-lite4/blocks_16/tpu_batch_normalization/FusedBatchNormV3;efficientnet-lite4/blocks_21/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_21/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_16/conv2d/Conv2D) shape:[1, 40, 40, 960], type:INT8
  T#637(efficientnet-lite4/blocks_16/Relu6_1;efficientnet-lite4/blocks_16/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_21/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_21/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_16/depthwise_conv2d/depthwise) shape:[1, 40, 40, 960], type:INT8
  T#638(efficientnet-lite4/blocks_16/tpu_batch_normalization_2/FusedBatchNormV3;efficientnet-lite4/blocks_20/conv2d_1/Conv2D;efficientnet-lite4/blocks_16/conv2d_1/Conv2D1) shape:[1, 40, 40, 160], type:INT8
  T#639(efficientnet-lite4/blocks_16/Add) shape:[1, 40, 40, 160], type:INT8
  T#640(efficientnet-lite4/blocks_17/Relu6;efficientnet-lite4/blocks_17/tpu_batch_normalization/FusedBatchNormV3;efficientnet-lite4/blocks_21/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_21/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_17/conv2d/Conv2D) shape:[1, 40, 40, 960], type:INT8
  T#641(efficientnet-lite4/blocks_17/Relu6_1;efficientnet-lite4/blocks_17/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_21/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_21/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_17/depthwise_conv2d/depthwise) shape:[1, 40, 40, 960], type:INT8
  T#642(efficientnet-lite4/blocks_17/tpu_batch_normalization_2/FusedBatchNormV3;efficientnet-lite4/blocks_20/conv2d_1/Conv2D;efficientnet-lite4/blocks_17/conv2d_1/Conv2D1) shape:[1, 40, 40, 160], type:INT8
  T#643(efficientnet-lite4/blocks_17/Add) shape:[1, 40, 40, 160], type:INT8
  T#644(efficientnet-lite4/blocks_18/Relu6;efficientnet-lite4/blocks_18/tpu_batch_normalization/FusedBatchNormV3;efficientnet-lite4/blocks_21/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_21/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_18/conv2d/Conv2D) shape:[1, 40, 40, 960], type:INT8
  T#645(efficientnet-lite4/blocks_18/Relu6_1;efficientnet-lite4/blocks_18/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_21/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_21/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_18/depthwise_conv2d/depthwise) shape:[1, 40, 40, 960], type:INT8
  T#646(efficientnet-lite4/blocks_18/tpu_batch_normalization_2/FusedBatchNormV3;efficientnet-lite4/blocks_20/conv2d_1/Conv2D;efficientnet-lite4/blocks_18/conv2d_1/Conv2D1) shape:[1, 40, 40, 160], type:INT8
  T#647(efficientnet-lite4/blocks_18/Add) shape:[1, 40, 40, 160], type:INT8
  T#648(efficientnet-lite4/blocks_19/Relu6;efficientnet-lite4/blocks_19/tpu_batch_normalization/FusedBatchNormV3;efficientnet-lite4/blocks_21/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_21/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_19/conv2d/Conv2D) shape:[1, 40, 40, 960], type:INT8
  T#649(efficientnet-lite4/blocks_19/Relu6_1;efficientnet-lite4/blocks_19/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_21/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_21/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_19/depthwise_conv2d/depthwise) shape:[1, 40, 40, 960], type:INT8
  T#650(efficientnet-lite4/blocks_19/tpu_batch_normalization_2/FusedBatchNormV3;efficientnet-lite4/blocks_20/conv2d_1/Conv2D;efficientnet-lite4/blocks_19/conv2d_1/Conv2D1) shape:[1, 40, 40, 160], type:INT8
  T#651(efficientnet-lite4/blocks_19/Add) shape:[1, 40, 40, 160], type:INT8
  T#652(efficientnet-lite4/blocks_20/Relu6;efficientnet-lite4/blocks_20/tpu_batch_normalization/FusedBatchNormV3;efficientnet-lite4/blocks_21/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_21/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_20/conv2d/Conv2D) shape:[1, 40, 40, 960], type:INT8
  T#653(efficientnet-lite4/blocks_20/Relu6_1;efficientnet-lite4/blocks_20/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_21/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_21/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_20/depthwise_conv2d/depthwise) shape:[1, 40, 40, 960], type:INT8
  T#654(efficientnet-lite4/blocks_20/tpu_batch_normalization_2/FusedBatchNormV3;efficientnet-lite4/blocks_20/conv2d_1/Conv2D1) shape:[1, 40, 40, 160], type:INT8
  T#655(efficientnet-lite4/blocks_20/Add) shape:[1, 40, 40, 160], type:INT8
  T#656(efficientnet-lite4/blocks_21/Relu6;efficientnet-lite4/blocks_21/tpu_batch_normalization/FusedBatchNormV3;efficientnet-lite4/blocks_21/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_21/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_21/conv2d/Conv2D) shape:[1, 40, 40, 960], type:INT8
  T#657(efficientnet-lite4/blocks_21/Relu6_1;efficientnet-lite4/blocks_21/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_21/depthwise_conv2d/depthwise) shape:[1, 20, 20, 960], type:INT8
  T#658(efficientnet-lite4/blocks_21/tpu_batch_normalization_2/FusedBatchNormV3;efficientnet-lite4/blocks_28/conv2d_1/Conv2D;efficientnet-lite4/blocks_21/conv2d_1/Conv2D1) shape:[1, 20, 20, 272], type:INT8
  T#659(efficientnet-lite4/blocks_22/Relu6;efficientnet-lite4/blocks_22/tpu_batch_normalization/FusedBatchNormV3;efficientnet-lite4/blocks_29/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_29/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_22/conv2d/Conv2D) shape:[1, 20, 20, 1632], type:INT8
  T#660(efficientnet-lite4/blocks_22/Relu6_1;efficientnet-lite4/blocks_22/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_29/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_29/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_22/depthwise_conv2d/depthwise) shape:[1, 20, 20, 1632], type:INT8
  T#661(efficientnet-lite4/blocks_22/tpu_batch_normalization_2/FusedBatchNormV3;efficientnet-lite4/blocks_28/conv2d_1/Conv2D;efficientnet-lite4/blocks_22/conv2d_1/Conv2D1) shape:[1, 20, 20, 272], type:INT8
  T#662(efficientnet-lite4/blocks_22/Add) shape:[1, 20, 20, 272], type:INT8
  T#663(efficientnet-lite4/blocks_23/Relu6;efficientnet-lite4/blocks_23/tpu_batch_normalization/FusedBatchNormV3;efficientnet-lite4/blocks_29/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_29/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_23/conv2d/Conv2D) shape:[1, 20, 20, 1632], type:INT8
  T#664(efficientnet-lite4/blocks_23/Relu6_1;efficientnet-lite4/blocks_23/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_29/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_29/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_23/depthwise_conv2d/depthwise) shape:[1, 20, 20, 1632], type:INT8
  T#665(efficientnet-lite4/blocks_23/tpu_batch_normalization_2/FusedBatchNormV3;efficientnet-lite4/blocks_28/conv2d_1/Conv2D;efficientnet-lite4/blocks_23/conv2d_1/Conv2D1) shape:[1, 20, 20, 272], type:INT8
  T#666(efficientnet-lite4/blocks_23/Add) shape:[1, 20, 20, 272], type:INT8
  T#667(efficientnet-lite4/blocks_24/Relu6;efficientnet-lite4/blocks_24/tpu_batch_normalization/FusedBatchNormV3;efficientnet-lite4/blocks_29/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_29/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_24/conv2d/Conv2D) shape:[1, 20, 20, 1632], type:INT8
  T#668(efficientnet-lite4/blocks_24/Relu6_1;efficientnet-lite4/blocks_24/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_29/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_29/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_24/depthwise_conv2d/depthwise) shape:[1, 20, 20, 1632], type:INT8
  T#669(efficientnet-lite4/blocks_24/tpu_batch_normalization_2/FusedBatchNormV3;efficientnet-lite4/blocks_28/conv2d_1/Conv2D;efficientnet-lite4/blocks_24/conv2d_1/Conv2D1) shape:[1, 20, 20, 272], type:INT8
  T#670(efficientnet-lite4/blocks_24/Add) shape:[1, 20, 20, 272], type:INT8
  T#671(efficientnet-lite4/blocks_25/Relu6;efficientnet-lite4/blocks_25/tpu_batch_normalization/FusedBatchNormV3;efficientnet-lite4/blocks_29/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_29/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_25/conv2d/Conv2D) shape:[1, 20, 20, 1632], type:INT8
  T#672(efficientnet-lite4/blocks_25/Relu6_1;efficientnet-lite4/blocks_25/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_29/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_29/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_25/depthwise_conv2d/depthwise) shape:[1, 20, 20, 1632], type:INT8
  T#673(efficientnet-lite4/blocks_25/tpu_batch_normalization_2/FusedBatchNormV3;efficientnet-lite4/blocks_28/conv2d_1/Conv2D;efficientnet-lite4/blocks_25/conv2d_1/Conv2D1) shape:[1, 20, 20, 272], type:INT8
  T#674(efficientnet-lite4/blocks_25/Add) shape:[1, 20, 20, 272], type:INT8
  T#675(efficientnet-lite4/blocks_26/Relu6;efficientnet-lite4/blocks_26/tpu_batch_normalization/FusedBatchNormV3;efficientnet-lite4/blocks_29/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_29/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_26/conv2d/Conv2D) shape:[1, 20, 20, 1632], type:INT8
  T#676(efficientnet-lite4/blocks_26/Relu6_1;efficientnet-lite4/blocks_26/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_29/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_29/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_26/depthwise_conv2d/depthwise) shape:[1, 20, 20, 1632], type:INT8
  T#677(efficientnet-lite4/blocks_26/tpu_batch_normalization_2/FusedBatchNormV3;efficientnet-lite4/blocks_28/conv2d_1/Conv2D;efficientnet-lite4/blocks_26/conv2d_1/Conv2D1) shape:[1, 20, 20, 272], type:INT8
  T#678(efficientnet-lite4/blocks_26/Add) shape:[1, 20, 20, 272], type:INT8
  T#679(efficientnet-lite4/blocks_27/Relu6;efficientnet-lite4/blocks_27/tpu_batch_normalization/FusedBatchNormV3;efficientnet-lite4/blocks_29/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_29/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_27/conv2d/Conv2D) shape:[1, 20, 20, 1632], type:INT8
  T#680(efficientnet-lite4/blocks_27/Relu6_1;efficientnet-lite4/blocks_27/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_29/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_29/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_27/depthwise_conv2d/depthwise) shape:[1, 20, 20, 1632], type:INT8
  T#681(efficientnet-lite4/blocks_27/tpu_batch_normalization_2/FusedBatchNormV3;efficientnet-lite4/blocks_28/conv2d_1/Conv2D;efficientnet-lite4/blocks_27/conv2d_1/Conv2D1) shape:[1, 20, 20, 272], type:INT8
  T#682(efficientnet-lite4/blocks_27/Add) shape:[1, 20, 20, 272], type:INT8
  T#683(efficientnet-lite4/blocks_28/Relu6;efficientnet-lite4/blocks_28/tpu_batch_normalization/FusedBatchNormV3;efficientnet-lite4/blocks_29/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_29/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_28/conv2d/Conv2D) shape:[1, 20, 20, 1632], type:INT8
  T#684(efficientnet-lite4/blocks_28/Relu6_1;efficientnet-lite4/blocks_28/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_29/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_29/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_28/depthwise_conv2d/depthwise) shape:[1, 20, 20, 1632], type:INT8
  T#685(efficientnet-lite4/blocks_28/tpu_batch_normalization_2/FusedBatchNormV3;efficientnet-lite4/blocks_28/conv2d_1/Conv2D1) shape:[1, 20, 20, 272], type:INT8
  T#686(efficientnet-lite4/blocks_28/Add) shape:[1, 20, 20, 272], type:INT8
  T#687(efficientnet-lite4/blocks_29/Relu6;efficientnet-lite4/blocks_29/tpu_batch_normalization/FusedBatchNormV3;efficientnet-lite4/blocks_29/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_29/depthwise_conv2d/depthwise;efficientnet-lite4/blocks_29/conv2d/Conv2D) shape:[1, 20, 20, 1632], type:INT8
  T#688(efficientnet-lite4/blocks_29/Relu6_1;efficientnet-lite4/blocks_29/tpu_batch_normalization_1/FusedBatchNormV3;efficientnet-lite4/blocks_29/depthwise_conv2d/depthwise) shape:[1, 20, 20, 1632], type:INT8
  T#689(efficientnet-lite4/blocks_29/tpu_batch_normalization_2/FusedBatchNormV3;efficientnet-lite4/blocks_29/conv2d_1/Conv2D1) shape:[1, 20, 20, 448], type:INT8
  T#690(fpn_cells/cell_0/fnode1/resample_0_2_6/bn/FusedBatchNormV3;fpn_cells/cell_0/fnode1/resample_0_2_6/conv2d/bias;fpn_cells/cell_0/fnode1/resample_0_2_6/conv2d/BiasAdd;class_net/class-predict/separable_conv2d_4/depthwise;fpn_cells/cell_0/fnode1/resample_0_2_6/conv2d/Conv2D) shape:[1, 20, 20, 224], type:INT8
  T#691(fpn_cells/cell_0/fnode5/resample_0_2_10/bn/FusedBatchNormV3;fpn_cells/cell_0/fnode5/resample_0_2_10/conv2d/bias;fpn_cells/cell_0/fnode5/resample_0_2_10/conv2d/BiasAdd;class_net/class-predict/separable_conv2d_4/depthwise;fpn_cells/cell_0/fnode5/resample_0_2_10/conv2d/Conv2D) shape:[1, 20, 20, 224], type:INT8
  T#692(fpn_cells/cell_0/fnode2/resample_0_1_7/bn/FusedBatchNormV3;fpn_cells/cell_0/fnode2/resample_0_1_7/conv2d/bias;fpn_cells/cell_0/fnode2/resample_0_1_7/conv2d/BiasAdd;class_net/class-predict/separable_conv2d_4/depthwise;fpn_cells/cell_0/fnode2/resample_0_1_7/conv2d/Conv2D) shape:[1, 40, 40, 224], type:INT8
  T#693(fpn_cells/cell_0/fnode4/resample_0_1_9/bn/FusedBatchNormV3;fpn_cells/cell_0/fnode4/resample_0_1_9/conv2d/bias;fpn_cells/cell_0/fnode4/resample_0_1_9/conv2d/BiasAdd;class_net/class-predict/separable_conv2d_4/depthwise;fpn_cells/cell_0/fnode4/resample_0_1_9/conv2d/Conv2D) shape:[1, 40, 40, 224], type:INT8
  T#694(fpn_cells/cell_0/fnode3/resample_0_0_8/bn/FusedBatchNormV3;fpn_cells/cell_0/fnode3/resample_0_0_8/conv2d/bias;fpn_cells/cell_0/fnode3/resample_0_0_8/conv2d/BiasAdd;class_net/class-predict/separable_conv2d_4/depthwise;fpn_cells/cell_0/fnode3/resample_0_0_8/conv2d/Conv2D) shape:[1, 80, 80, 224], type:INT8
  T#695(resample_p6/bn/FusedBatchNormV3;resample_p6/conv2d/bias;resample_p6/conv2d/BiasAdd;class_net/class-predict/separable_conv2d_4/depthwise;resample_p6/conv2d/Conv2D) shape:[1, 20, 20, 224], type:INT8
  T#696(resample_p6/max_pooling2d/MaxPool) shape:[1, 10, 10, 224], type:INT8
  T#697(resample_p7/max_pooling2d_1/MaxPool) shape:[1, 5, 5, 224], type:INT8
  T#698(fpn_cells/cell_0/fnode0/resample_1_4_5/ResizeNearestNeighbor) shape:[1, 10, 10, 224], type:INT8
  T#699(fpn_cells/cell_0/fnode0/op_after_combine5/Relu6;fpn_cells/cell_0/fnode0/add_n/add) shape:[1, 10, 10, 224], type:INT8
  T#700(fpn_cells/cell_0/fnode0/op_after_combine5/conv/separable_conv2d/depthwise1) shape:[1, 10, 10, 224], type:INT8
  T#701(fpn_cells/cell_0/fnode0/op_after_combine5/bn/FusedBatchNormV3;fpn_cells/cell_0/fnode0/op_after_combine5/conv/bias;fpn_cells/cell_0/fnode0/op_after_combine5/conv/BiasAdd;class_net/class-predict/separable_conv2d_4/depthwise;fpn_cells/cell_0/fnode0/op_after_combine5/conv/separable_conv2d) shape:[1, 10, 10, 224], type:INT8
  T#702(fpn_cells/cell_0/fnode1/resample_1_5_6/ResizeNearestNeighbor) shape:[1, 20, 20, 224], type:INT8
  T#703(fpn_cells/cell_0/fnode1/op_after_combine6/Relu6;fpn_cells/cell_0/fnode1/add_n/add) shape:[1, 20, 20, 224], type:INT8
  T#704(fpn_cells/cell_0/fnode1/op_after_combine6/conv/separable_conv2d/depthwise1) shape:[1, 20, 20, 224], type:INT8
  T#705(fpn_cells/cell_0/fnode1/op_after_combine6/bn/FusedBatchNormV3;fpn_cells/cell_0/fnode1/op_after_combine6/conv/bias;fpn_cells/cell_0/fnode1/op_after_combine6/conv/BiasAdd;class_net/class-predict/separable_conv2d_4/depthwise;fpn_cells/cell_0/fnode1/op_after_combine6/conv/separable_conv2d) shape:[1, 20, 20, 224], type:INT8
  T#706(fpn_cells/cell_0/fnode2/resample_1_6_7/ResizeNearestNeighbor) shape:[1, 40, 40, 224], type:INT8
  T#707(fpn_cells/cell_0/fnode2/op_after_combine7/Relu6;fpn_cells/cell_0/fnode2/add_n/add) shape:[1, 40, 40, 224], type:INT8
  T#708(fpn_cells/cell_0/fnode2/op_after_combine7/conv/separable_conv2d/depthwise1) shape:[1, 40, 40, 224], type:INT8
  T#709(fpn_cells/cell_0/fnode2/op_after_combine7/bn/FusedBatchNormV3;fpn_cells/cell_0/fnode2/op_after_combine7/conv/bias;fpn_cells/cell_0/fnode2/op_after_combine7/conv/BiasAdd;class_net/class-predict/separable_conv2d_4/depthwise;fpn_cells/cell_0/fnode2/op_after_combine7/conv/separable_conv2d) shape:[1, 40, 40, 224], type:INT8
  T#710(fpn_cells/cell_0/fnode3/resample_1_7_8/ResizeNearestNeighbor) shape:[1, 80, 80, 224], type:INT8
  T#711(fpn_cells/cell_0/fnode3/op_after_combine8/Relu6;fpn_cells/cell_0/fnode3/add_n/add) shape:[1, 80, 80, 224], type:INT8
  T#712(fpn_cells/cell_0/fnode3/op_after_combine8/conv/separable_conv2d/depthwise1) shape:[1, 80, 80, 224], type:INT8
  T#713(fpn_cells/cell_0/fnode3/op_after_combine8/bn/FusedBatchNormV3;fpn_cells/cell_0/fnode3/op_after_combine8/conv/bias;fpn_cells/cell_0/fnode3/op_after_combine8/conv/BiasAdd;class_net/class-predict/separable_conv2d_4/depthwise;fpn_cells/cell_0/fnode3/op_after_combine8/conv/separable_conv2d) shape:[1, 80, 80, 224], type:INT8
  T#714(fpn_cells/cell_0/fnode4/resample_2_8_9/max_pooling2d_2/MaxPool) shape:[1, 40, 40, 224], type:INT8
  T#715(fpn_cells/cell_0/fnode4/add_n/add) shape:[1, 40, 40, 224], type:INT8
  T#716(fpn_cells/cell_0/fnode4/op_after_combine9/Relu6;fpn_cells/cell_0/fnode4/add_n/add_1) shape:[1, 40, 40, 224], type:INT8
  T#717(fpn_cells/cell_0/fnode4/op_after_combine9/conv/separable_conv2d/depthwise1) shape:[1, 40, 40, 224], type:INT8
  T#718(fpn_cells/cell_0/fnode4/op_after_combine9/bn/FusedBatchNormV3;fpn_cells/cell_0/fnode4/op_after_combine9/conv/bias;fpn_cells/cell_0/fnode4/op_after_combine9/conv/BiasAdd;class_net/class-predict/separable_conv2d_4/depthwise;fpn_cells/cell_0/fnode4/op_after_combine9/conv/separable_conv2d) shape:[1, 40, 40, 224], type:INT8
  T#719(fpn_cells/cell_0/fnode5/resample_2_9_10/max_pooling2d_3/MaxPool) shape:[1, 20, 20, 224], type:INT8
  T#720(fpn_cells/cell_0/fnode5/add_n/add) shape:[1, 20, 20, 224], type:INT8
  T#721(fpn_cells/cell_0/fnode5/op_after_combine10/Relu6;fpn_cells/cell_0/fnode5/add_n/add_1) shape:[1, 20, 20, 224], type:INT8
  T#722(fpn_cells/cell_0/fnode5/op_after_combine10/conv/separable_conv2d/depthwise1) shape:[1, 20, 20, 224], type:INT8
  T#723(fpn_cells/cell_0/fnode5/op_after_combine10/bn/FusedBatchNormV3;fpn_cells/cell_0/fnode5/op_after_combine10/conv/bias;fpn_cells/cell_0/fnode5/op_after_combine10/conv/BiasAdd;class_net/class-predict/separable_conv2d_4/depthwise;fpn_cells/cell_0/fnode5/op_after_combine10/conv/separable_conv2d) shape:[1, 20, 20, 224], type:INT8
  T#724(fpn_cells/cell_0/fnode6/resample_2_10_11/max_pooling2d_4/MaxPool) shape:[1, 10, 10, 224], type:INT8
  T#725(fpn_cells/cell_0/fnode6/add_n/add) shape:[1, 10, 10, 224], type:INT8
  T#726(fpn_cells/cell_0/fnode6/op_after_combine11/Relu6;fpn_cells/cell_0/fnode6/add_n/add_1) shape:[1, 10, 10, 224], type:INT8
  T#727(fpn_cells/cell_0/fnode6/op_after_combine11/conv/separable_conv2d/depthwise1) shape:[1, 10, 10, 224], type:INT8
  T#728(fpn_cells/cell_0/fnode6/op_after_combine11/bn/FusedBatchNormV3;fpn_cells/cell_0/fnode6/op_after_combine11/conv/bias;fpn_cells/cell_0/fnode6/op_after_combine11/conv/BiasAdd;class_net/class-predict/separable_conv2d_4/depthwise;fpn_cells/cell_0/fnode6/op_after_combine11/conv/separable_conv2d) shape:[1, 10, 10, 224], type:INT8
  T#729(fpn_cells/cell_0/fnode7/resample_1_11_12/max_pooling2d_5/MaxPool) shape:[1, 5, 5, 224], type:INT8
  T#730(fpn_cells/cell_0/fnode7/op_after_combine12/Relu6;fpn_cells/cell_0/fnode7/add_n/add) shape:[1, 5, 5, 224], type:INT8
  T#731(fpn_cells/cell_0/fnode7/op_after_combine12/conv/separable_conv2d/depthwise1) shape:[1, 5, 5, 224], type:INT8
  T#732(fpn_cells/cell_0/fnode7/op_after_combine12/bn/FusedBatchNormV3;fpn_cells/cell_0/fnode7/op_after_combine12/conv/bias;fpn_cells/cell_0/fnode7/op_after_combine12/conv/BiasAdd;class_net/class-predict/separable_conv2d_4/depthwise;fpn_cells/cell_0/fnode7/op_after_combine12/conv/separable_conv2d) shape:[1, 5, 5, 224], type:INT8
  T#733(fpn_cells/cell_1/fnode0/resample_1_4_5/ResizeNearestNeighbor) shape:[1, 10, 10, 224], type:INT8
  T#734(fpn_cells/cell_1/fnode0/op_after_combine5/Relu6;fpn_cells/cell_1/fnode0/add_n/add) shape:[1, 10, 10, 224], type:INT8
  T#735(fpn_cells/cell_1/fnode0/op_after_combine5/conv/separable_conv2d/depthwise1) shape:[1, 10, 10, 224], type:INT8
  T#736(fpn_cells/cell_1/fnode0/op_after_combine5/bn/FusedBatchNormV3;fpn_cells/cell_1/fnode0/op_after_combine5/conv/bias;fpn_cells/cell_1/fnode0/op_after_combine5/conv/BiasAdd;class_net/class-predict/separable_conv2d_4/depthwise;fpn_cells/cell_1/fnode0/op_after_combine5/conv/separable_conv2d) shape:[1, 10, 10, 224], type:INT8
  T#737(fpn_cells/cell_1/fnode1/resample_1_5_6/ResizeNearestNeighbor) shape:[1, 20, 20, 224], type:INT8
  T#738(fpn_cells/cell_1/fnode1/op_after_combine6/Relu6;fpn_cells/cell_1/fnode1/add_n/add) shape:[1, 20, 20, 224], type:INT8
  T#739(fpn_cells/cell_1/fnode1/op_after_combine6/conv/separable_conv2d/depthwise1) shape:[1, 20, 20, 224], type:INT8
  T#740(fpn_cells/cell_1/fnode1/op_after_combine6/bn/FusedBatchNormV3;fpn_cells/cell_1/fnode1/op_after_combine6/conv/bias;fpn_cells/cell_1/fnode1/op_after_combine6/conv/BiasAdd;class_net/class-predict/separable_conv2d_4/depthwise;fpn_cells/cell_1/fnode1/op_after_combine6/conv/separable_conv2d) shape:[1, 20, 20, 224], type:INT8
  T#741(fpn_cells/cell_1/fnode2/resample_1_6_7/ResizeNearestNeighbor) shape:[1, 40, 40, 224], type:INT8
  T#742(fpn_cells/cell_1/fnode2/op_after_combine7/Relu6;fpn_cells/cell_1/fnode2/add_n/add) shape:[1, 40, 40, 224], type:INT8
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  T#744(fpn_cells/cell_1/fnode2/op_after_combine7/bn/FusedBatchNormV3;fpn_cells/cell_1/fnode2/op_after_combine7/conv/bias;fpn_cells/cell_1/fnode2/op_after_combine7/conv/BiasAdd;class_net/class-predict/separable_conv2d_4/depthwise;fpn_cells/cell_1/fnode2/op_after_combine7/conv/separable_conv2d) shape:[1, 40, 40, 224], type:INT8
  T#745(fpn_cells/cell_1/fnode3/resample_1_7_8/ResizeNearestNeighbor) shape:[1, 80, 80, 224], type:INT8
  T#746(fpn_cells/cell_1/fnode3/op_after_combine8/Relu6;fpn_cells/cell_1/fnode3/add_n/add) shape:[1, 80, 80, 224], type:INT8
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  T#748(fpn_cells/cell_1/fnode3/op_after_combine8/bn/FusedBatchNormV3;fpn_cells/cell_1/fnode3/op_after_combine8/conv/bias;fpn_cells/cell_1/fnode3/op_after_combine8/conv/BiasAdd;class_net/class-predict/separable_conv2d_4/depthwise;fpn_cells/cell_1/fnode3/op_after_combine8/conv/separable_conv2d) shape:[1, 80, 80, 224], type:INT8
  T#749(fpn_cells/cell_1/fnode4/resample_2_8_9/max_pooling2d_6/MaxPool) shape:[1, 40, 40, 224], type:INT8
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  T#751(fpn_cells/cell_1/fnode4/op_after_combine9/Relu6;fpn_cells/cell_1/fnode4/add_n/add_1) shape:[1, 40, 40, 224], type:INT8
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  T#753(fpn_cells/cell_1/fnode4/op_after_combine9/bn/FusedBatchNormV3;fpn_cells/cell_1/fnode4/op_after_combine9/conv/bias;fpn_cells/cell_1/fnode4/op_after_combine9/conv/BiasAdd;class_net/class-predict/separable_conv2d_4/depthwise;fpn_cells/cell_1/fnode4/op_after_combine9/conv/separable_conv2d) shape:[1, 40, 40, 224], type:INT8
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  T#758(fpn_cells/cell_1/fnode5/op_after_combine10/bn/FusedBatchNormV3;fpn_cells/cell_1/fnode5/op_after_combine10/conv/bias;fpn_cells/cell_1/fnode5/op_after_combine10/conv/BiasAdd;class_net/class-predict/separable_conv2d_4/depthwise;fpn_cells/cell_1/fnode5/op_after_combine10/conv/separable_conv2d) shape:[1, 20, 20, 224], type:INT8
  T#759(fpn_cells/cell_1/fnode6/resample_2_10_11/max_pooling2d_8/MaxPool) shape:[1, 10, 10, 224], type:INT8
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  T#763(fpn_cells/cell_1/fnode6/op_after_combine11/bn/FusedBatchNormV3;fpn_cells/cell_1/fnode6/op_after_combine11/conv/bias;fpn_cells/cell_1/fnode6/op_after_combine11/conv/BiasAdd;class_net/class-predict/separable_conv2d_4/depthwise;fpn_cells/cell_1/fnode6/op_after_combine11/conv/separable_conv2d) shape:[1, 10, 10, 224], type:INT8
  T#764(fpn_cells/cell_1/fnode7/resample_1_11_12/max_pooling2d_9/MaxPool) shape:[1, 5, 5, 224], type:INT8
  T#765(fpn_cells/cell_1/fnode7/op_after_combine12/Relu6;fpn_cells/cell_1/fnode7/add_n/add) shape:[1, 5, 5, 224], type:INT8
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  T#767(fpn_cells/cell_1/fnode7/op_after_combine12/bn/FusedBatchNormV3;fpn_cells/cell_1/fnode7/op_after_combine12/conv/bias;fpn_cells/cell_1/fnode7/op_after_combine12/conv/BiasAdd;class_net/class-predict/separable_conv2d_4/depthwise;fpn_cells/cell_1/fnode7/op_after_combine12/conv/separable_conv2d) shape:[1, 5, 5, 224], type:INT8
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  T#769(fpn_cells/cell_2/fnode0/op_after_combine5/Relu6;fpn_cells/cell_2/fnode0/add_n/add) shape:[1, 10, 10, 224], type:INT8
  T#770(fpn_cells/cell_2/fnode0/op_after_combine5/conv/separable_conv2d/depthwise1) shape:[1, 10, 10, 224], type:INT8
  T#771(fpn_cells/cell_2/fnode0/op_after_combine5/bn/FusedBatchNormV3;fpn_cells/cell_2/fnode0/op_after_combine5/conv/bias;fpn_cells/cell_2/fnode0/op_after_combine5/conv/BiasAdd;class_net/class-predict/separable_conv2d_4/depthwise;fpn_cells/cell_2/fnode0/op_after_combine5/conv/separable_conv2d) shape:[1, 10, 10, 224], type:INT8
  T#772(fpn_cells/cell_2/fnode1/resample_1_5_6/ResizeNearestNeighbor) shape:[1, 20, 20, 224], type:INT8
  T#773(fpn_cells/cell_2/fnode1/op_after_combine6/Relu6;fpn_cells/cell_2/fnode1/add_n/add) shape:[1, 20, 20, 224], type:INT8
  T#774(fpn_cells/cell_2/fnode1/op_after_combine6/conv/separable_conv2d/depthwise1) shape:[1, 20, 20, 224], type:INT8
  T#775(fpn_cells/cell_2/fnode1/op_after_combine6/bn/FusedBatchNormV3;fpn_cells/cell_2/fnode1/op_after_combine6/conv/bias;fpn_cells/cell_2/fnode1/op_after_combine6/conv/BiasAdd;class_net/class-predict/separable_conv2d_4/depthwise;fpn_cells/cell_2/fnode1/op_after_combine6/conv/separable_conv2d) shape:[1, 20, 20, 224], type:INT8
  T#776(fpn_cells/cell_2/fnode2/resample_1_6_7/ResizeNearestNeighbor) shape:[1, 40, 40, 224], type:INT8
  T#777(fpn_cells/cell_2/fnode2/op_after_combine7/Relu6;fpn_cells/cell_2/fnode2/add_n/add) shape:[1, 40, 40, 224], type:INT8
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  T#779(fpn_cells/cell_2/fnode2/op_after_combine7/bn/FusedBatchNormV3;fpn_cells/cell_2/fnode2/op_after_combine7/conv/bias;fpn_cells/cell_2/fnode2/op_after_combine7/conv/BiasAdd;class_net/class-predict/separable_conv2d_4/depthwise;fpn_cells/cell_2/fnode2/op_after_combine7/conv/separable_conv2d) shape:[1, 40, 40, 224], type:INT8
  T#780(fpn_cells/cell_2/fnode3/resample_1_7_8/ResizeNearestNeighbor) shape:[1, 80, 80, 224], type:INT8
  T#781(fpn_cells/cell_2/fnode3/op_after_combine8/Relu6;fpn_cells/cell_2/fnode3/add_n/add) shape:[1, 80, 80, 224], type:INT8
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  T#784(fpn_cells/cell_2/fnode4/resample_2_8_9/max_pooling2d_10/MaxPool) shape:[1, 40, 40, 224], type:INT8
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  T#789(fpn_cells/cell_2/fnode5/resample_2_9_10/max_pooling2d_11/MaxPool) shape:[1, 20, 20, 224], type:INT8
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  T#793(fpn_cells/cell_2/fnode5/op_after_combine10/bn/FusedBatchNormV3;fpn_cells/cell_2/fnode5/op_after_combine10/conv/bias;fpn_cells/cell_2/fnode5/op_after_combine10/conv/BiasAdd;class_net/class-predict/separable_conv2d_4/depthwise;fpn_cells/cell_2/fnode5/op_after_combine10/conv/separable_conv2d) shape:[1, 20, 20, 224], type:INT8
  T#794(fpn_cells/cell_2/fnode6/resample_2_10_11/max_pooling2d_12/MaxPool) shape:[1, 10, 10, 224], type:INT8
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  T#796(fpn_cells/cell_2/fnode6/op_after_combine11/Relu6;fpn_cells/cell_2/fnode6/add_n/add_1) shape:[1, 10, 10, 224], type:INT8
  T#797(fpn_cells/cell_2/fnode6/op_after_combine11/conv/separable_conv2d/depthwise1) shape:[1, 10, 10, 224], type:INT8
  T#798(fpn_cells/cell_2/fnode6/op_after_combine11/bn/FusedBatchNormV3;fpn_cells/cell_2/fnode6/op_after_combine11/conv/bias;fpn_cells/cell_2/fnode6/op_after_combine11/conv/BiasAdd;class_net/class-predict/separable_conv2d_4/depthwise;fpn_cells/cell_2/fnode6/op_after_combine11/conv/separable_conv2d) shape:[1, 10, 10, 224], type:INT8
  T#799(fpn_cells/cell_2/fnode7/resample_1_11_12/max_pooling2d_13/MaxPool) shape:[1, 5, 5, 224], type:INT8
  T#800(fpn_cells/cell_2/fnode7/op_after_combine12/Relu6;fpn_cells/cell_2/fnode7/add_n/add) shape:[1, 5, 5, 224], type:INT8
  T#801(fpn_cells/cell_2/fnode7/op_after_combine12/conv/separable_conv2d/depthwise1) shape:[1, 5, 5, 224], type:INT8
  T#802(fpn_cells/cell_2/fnode7/op_after_combine12/bn/FusedBatchNormV3;fpn_cells/cell_2/fnode7/op_after_combine12/conv/bias;fpn_cells/cell_2/fnode7/op_after_combine12/conv/BiasAdd;class_net/class-predict/separable_conv2d_4/depthwise;fpn_cells/cell_2/fnode7/op_after_combine12/conv/separable_conv2d) shape:[1, 5, 5, 224], type:INT8
  T#803(fpn_cells/cell_3/fnode0/resample_1_4_5/ResizeNearestNeighbor) shape:[1, 10, 10, 224], type:INT8
  T#804(fpn_cells/cell_3/fnode0/op_after_combine5/Relu6;fpn_cells/cell_3/fnode0/add_n/add) shape:[1, 10, 10, 224], type:INT8
  T#805(fpn_cells/cell_3/fnode0/op_after_combine5/conv/separable_conv2d/depthwise1) shape:[1, 10, 10, 224], type:INT8
  T#806(fpn_cells/cell_3/fnode0/op_after_combine5/bn/FusedBatchNormV3;fpn_cells/cell_3/fnode0/op_after_combine5/conv/bias;fpn_cells/cell_3/fnode0/op_after_combine5/conv/BiasAdd;class_net/class-predict/separable_conv2d_4/depthwise;fpn_cells/cell_3/fnode0/op_after_combine5/conv/separable_conv2d) shape:[1, 10, 10, 224], type:INT8
  T#807(fpn_cells/cell_3/fnode1/resample_1_5_6/ResizeNearestNeighbor) shape:[1, 20, 20, 224], type:INT8
  T#808(fpn_cells/cell_3/fnode1/op_after_combine6/Relu6;fpn_cells/cell_3/fnode1/add_n/add) shape:[1, 20, 20, 224], type:INT8
  T#809(fpn_cells/cell_3/fnode1/op_after_combine6/conv/separable_conv2d/depthwise1) shape:[1, 20, 20, 224], type:INT8
  T#810(fpn_cells/cell_3/fnode1/op_after_combine6/bn/FusedBatchNormV3;fpn_cells/cell_3/fnode1/op_after_combine6/conv/bias;fpn_cells/cell_3/fnode1/op_after_combine6/conv/BiasAdd;class_net/class-predict/separable_conv2d_4/depthwise;fpn_cells/cell_3/fnode1/op_after_combine6/conv/separable_conv2d) shape:[1, 20, 20, 224], type:INT8
  T#811(fpn_cells/cell_3/fnode2/resample_1_6_7/ResizeNearestNeighbor) shape:[1, 40, 40, 224], type:INT8
  T#812(fpn_cells/cell_3/fnode2/op_after_combine7/Relu6;fpn_cells/cell_3/fnode2/add_n/add) shape:[1, 40, 40, 224], type:INT8
  T#813(fpn_cells/cell_3/fnode2/op_after_combine7/conv/separable_conv2d/depthwise1) shape:[1, 40, 40, 224], type:INT8
  T#814(fpn_cells/cell_3/fnode2/op_after_combine7/bn/FusedBatchNormV3;fpn_cells/cell_3/fnode2/op_after_combine7/conv/bias;fpn_cells/cell_3/fnode2/op_after_combine7/conv/BiasAdd;class_net/class-predict/separable_conv2d_4/depthwise;fpn_cells/cell_3/fnode2/op_after_combine7/conv/separable_conv2d) shape:[1, 40, 40, 224], type:INT8
  T#815(fpn_cells/cell_3/fnode3/resample_1_7_8/ResizeNearestNeighbor) shape:[1, 80, 80, 224], type:INT8
  T#816(fpn_cells/cell_3/fnode3/op_after_combine8/Relu6;fpn_cells/cell_3/fnode3/add_n/add) shape:[1, 80, 80, 224], type:INT8
  T#817(fpn_cells/cell_3/fnode3/op_after_combine8/conv/separable_conv2d/depthwise1) shape:[1, 80, 80, 224], type:INT8
  T#818(fpn_cells/cell_3/fnode3/op_after_combine8/bn/FusedBatchNormV3;fpn_cells/cell_3/fnode3/op_after_combine8/conv/bias;fpn_cells/cell_3/fnode3/op_after_combine8/conv/BiasAdd;class_net/class-predict/separable_conv2d_4/depthwise;fpn_cells/cell_3/fnode3/op_after_combine8/conv/separable_conv2d) shape:[1, 80, 80, 224], type:INT8
  T#819(fpn_cells/cell_3/fnode4/resample_2_8_9/max_pooling2d_14/MaxPool) shape:[1, 40, 40, 224], type:INT8
  T#820(fpn_cells/cell_3/fnode4/add_n/add) shape:[1, 40, 40, 224], type:INT8
  T#821(fpn_cells/cell_3/fnode4/op_after_combine9/Relu6;fpn_cells/cell_3/fnode4/add_n/add_1) shape:[1, 40, 40, 224], type:INT8
  T#822(fpn_cells/cell_3/fnode4/op_after_combine9/conv/separable_conv2d/depthwise1) shape:[1, 40, 40, 224], type:INT8
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  T#824(fpn_cells/cell_3/fnode5/resample_2_9_10/max_pooling2d_15/MaxPool) shape:[1, 20, 20, 224], type:INT8
  T#825(fpn_cells/cell_3/fnode5/add_n/add) shape:[1, 20, 20, 224], type:INT8
  T#826(fpn_cells/cell_3/fnode5/op_after_combine10/Relu6;fpn_cells/cell_3/fnode5/add_n/add_1) shape:[1, 20, 20, 224], type:INT8
  T#827(fpn_cells/cell_3/fnode5/op_after_combine10/conv/separable_conv2d/depthwise1) shape:[1, 20, 20, 224], type:INT8
  T#828(fpn_cells/cell_3/fnode5/op_after_combine10/bn/FusedBatchNormV3;fpn_cells/cell_3/fnode5/op_after_combine10/conv/bias;fpn_cells/cell_3/fnode5/op_after_combine10/conv/BiasAdd;class_net/class-predict/separable_conv2d_4/depthwise;fpn_cells/cell_3/fnode5/op_after_combine10/conv/separable_conv2d) shape:[1, 20, 20, 224], type:INT8
  T#829(fpn_cells/cell_3/fnode6/resample_2_10_11/max_pooling2d_16/MaxPool) shape:[1, 10, 10, 224], type:INT8
  T#830(fpn_cells/cell_3/fnode6/add_n/add) shape:[1, 10, 10, 224], type:INT8
  T#831(fpn_cells/cell_3/fnode6/op_after_combine11/Relu6;fpn_cells/cell_3/fnode6/add_n/add_1) shape:[1, 10, 10, 224], type:INT8
  T#832(fpn_cells/cell_3/fnode6/op_after_combine11/conv/separable_conv2d/depthwise1) shape:[1, 10, 10, 224], type:INT8
  T#833(fpn_cells/cell_3/fnode6/op_after_combine11/bn/FusedBatchNormV3;fpn_cells/cell_3/fnode6/op_after_combine11/conv/bias;fpn_cells/cell_3/fnode6/op_after_combine11/conv/BiasAdd;class_net/class-predict/separable_conv2d_4/depthwise;fpn_cells/cell_3/fnode6/op_after_combine11/conv/separable_conv2d) shape:[1, 10, 10, 224], type:INT8
  T#834(fpn_cells/cell_3/fnode7/resample_1_11_12/max_pooling2d_17/MaxPool) shape:[1, 5, 5, 224], type:INT8
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  T#1057(tfl.dequantize) shape:[1, 76725, 4], type:FLOAT32
  T#1058(StatefulPartitionedCall_2:3) shape:[], type:FLOAT32
  T#1059(StatefulPartitionedCall_2:2) shape:[], type:FLOAT32
  T#1060(StatefulPartitionedCall_2:1) shape:[], type:FLOAT32
  T#1061(StatefulPartitionedCall_2:0) shape:[], type:FLOAT32

---------------------------------------------------------------
Your TFLite model has ‘1’ signature_def(s).

Signature#0 key: 'tflite'
- Subgraph: Subgraph#0
- Inputs: 
    'images' : T#0
- Outputs: 
    'output_0' : T#1061
    'output_1' : T#1060
    'output_2' : T#1059
    'output_3' : T#1058

---------------------------------------------------------------
              Model size:   20501528 bytes
    Non-data buffer size:    2573784 bytes (12.55 %)
  Total data buffer size:   17927744 bytes (87.45 %)
    (Zero value buffers):        896 bytes (00.00 %)

* Buffers of TFLite model are mostly used for constant tensors.
  And zero value buffers are buffers filled with zeros.
  Non-data buffers area are used to store operators, subgraphs and etc.
  You can find more details from https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/schema/schema.fbs