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modelsummary.txt
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modelsummary.txt
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----------------------------------------------------------------
Layer (type) Output Shape Param #
================================================================
Conv2d-1 [-1, 24, 32, 32] 648
BatchNorm2d-2 [-1, 24, 32, 32] 48
GELU-3 [-1, 24, 32, 32] 0
Conv2d-4 [-1, 48, 32, 32] 1,152
BatchNorm2d-5 [-1, 48, 32, 32] 96
GELU-6 [-1, 48, 32, 32] 0
Conv2d-7 [-1, 12, 32, 32] 5,184
BatchNorm2d-8 [-1, 24, 32, 32] 48
GELU-9 [-1, 24, 32, 32] 0
Conv2d-10 [-1, 48, 32, 32] 1,152
BatchNorm2d-11 [-1, 48, 32, 32] 96
GELU-12 [-1, 48, 32, 32] 0
Conv2d-13 [-1, 12, 32, 32] 5,184
botn-14 [-1, 36, 32, 32] 0
BatchNorm2d-15 [-1, 36, 32, 32] 72
GELU-16 [-1, 36, 32, 32] 0
Conv2d-17 [-1, 48, 32, 32] 1,728
BatchNorm2d-18 [-1, 48, 32, 32] 96
GELU-19 [-1, 48, 32, 32] 0
Conv2d-20 [-1, 12, 32, 32] 5,184
BatchNorm2d-21 [-1, 36, 32, 32] 72
GELU-22 [-1, 36, 32, 32] 0
Conv2d-23 [-1, 48, 32, 32] 1,728
BatchNorm2d-24 [-1, 48, 32, 32] 96
GELU-25 [-1, 48, 32, 32] 0
Conv2d-26 [-1, 12, 32, 32] 5,184
botn-27 [-1, 48, 32, 32] 0
BatchNorm2d-28 [-1, 48, 32, 32] 96
GELU-29 [-1, 48, 32, 32] 0
Conv2d-30 [-1, 48, 32, 32] 2,304
BatchNorm2d-31 [-1, 48, 32, 32] 96
GELU-32 [-1, 48, 32, 32] 0
Conv2d-33 [-1, 12, 32, 32] 5,184
BatchNorm2d-34 [-1, 48, 32, 32] 96
GELU-35 [-1, 48, 32, 32] 0
Conv2d-36 [-1, 48, 32, 32] 2,304
BatchNorm2d-37 [-1, 48, 32, 32] 96
GELU-38 [-1, 48, 32, 32] 0
Conv2d-39 [-1, 12, 32, 32] 5,184
botn-40 [-1, 60, 32, 32] 0
BatchNorm2d-41 [-1, 60, 32, 32] 120
GELU-42 [-1, 60, 32, 32] 0
Conv2d-43 [-1, 48, 32, 32] 2,880
BatchNorm2d-44 [-1, 48, 32, 32] 96
GELU-45 [-1, 48, 32, 32] 0
Conv2d-46 [-1, 12, 32, 32] 5,184
BatchNorm2d-47 [-1, 60, 32, 32] 120
GELU-48 [-1, 60, 32, 32] 0
Conv2d-49 [-1, 48, 32, 32] 2,880
BatchNorm2d-50 [-1, 48, 32, 32] 96
GELU-51 [-1, 48, 32, 32] 0
Conv2d-52 [-1, 12, 32, 32] 5,184
botn-53 [-1, 72, 32, 32] 0
BatchNorm2d-54 [-1, 72, 32, 32] 144
GELU-55 [-1, 72, 32, 32] 0
Conv2d-56 [-1, 48, 32, 32] 3,456
BatchNorm2d-57 [-1, 48, 32, 32] 96
GELU-58 [-1, 48, 32, 32] 0
Conv2d-59 [-1, 12, 32, 32] 5,184
BatchNorm2d-60 [-1, 72, 32, 32] 144
GELU-61 [-1, 72, 32, 32] 0
Conv2d-62 [-1, 48, 32, 32] 3,456
BatchNorm2d-63 [-1, 48, 32, 32] 96
GELU-64 [-1, 48, 32, 32] 0
Conv2d-65 [-1, 12, 32, 32] 5,184
botn-66 [-1, 84, 32, 32] 0
BatchNorm2d-67 [-1, 84, 32, 32] 168
GELU-68 [-1, 84, 32, 32] 0
Conv2d-69 [-1, 48, 32, 32] 4,032
BatchNorm2d-70 [-1, 48, 32, 32] 96
GELU-71 [-1, 48, 32, 32] 0
Conv2d-72 [-1, 12, 32, 32] 5,184
BatchNorm2d-73 [-1, 84, 32, 32] 168
GELU-74 [-1, 84, 32, 32] 0
Conv2d-75 [-1, 48, 32, 32] 4,032
BatchNorm2d-76 [-1, 48, 32, 32] 96
GELU-77 [-1, 48, 32, 32] 0
Conv2d-78 [-1, 12, 32, 32] 5,184
botn-79 [-1, 96, 32, 32] 0
BatchNorm2d-80 [-1, 96, 32, 32] 192
GELU-81 [-1, 96, 32, 32] 0
Conv2d-82 [-1, 48, 32, 32] 4,608
BatchNorm2d-83 [-1, 48, 32, 32] 96
GELU-84 [-1, 48, 32, 32] 0
Conv2d-85 [-1, 12, 32, 32] 5,184
BatchNorm2d-86 [-1, 96, 32, 32] 192
GELU-87 [-1, 96, 32, 32] 0
Conv2d-88 [-1, 48, 32, 32] 4,608
BatchNorm2d-89 [-1, 48, 32, 32] 96
GELU-90 [-1, 48, 32, 32] 0
Conv2d-91 [-1, 12, 32, 32] 5,184
botn-92 [-1, 108, 32, 32] 0
BatchNorm2d-93 [-1, 108, 32, 32] 216
GELU-94 [-1, 108, 32, 32] 0
Conv2d-95 [-1, 48, 32, 32] 5,184
BatchNorm2d-96 [-1, 48, 32, 32] 96
GELU-97 [-1, 48, 32, 32] 0
Conv2d-98 [-1, 12, 32, 32] 5,184
BatchNorm2d-99 [-1, 108, 32, 32] 216
GELU-100 [-1, 108, 32, 32] 0
Conv2d-101 [-1, 48, 32, 32] 5,184
BatchNorm2d-102 [-1, 48, 32, 32] 96
GELU-103 [-1, 48, 32, 32] 0
Conv2d-104 [-1, 12, 32, 32] 5,184
botn-105 [-1, 120, 32, 32] 0
BatchNorm2d-106 [-1, 120, 32, 32] 240
GELU-107 [-1, 120, 32, 32] 0
Conv2d-108 [-1, 60, 32, 32] 7,200
trs-109 [-1, 60, 16, 16] 0
BatchNorm2d-110 [-1, 60, 16, 16] 120
GELU-111 [-1, 60, 16, 16] 0
Conv2d-112 [-1, 48, 16, 16] 2,880
BatchNorm2d-113 [-1, 48, 16, 16] 96
GELU-114 [-1, 48, 16, 16] 0
Conv2d-115 [-1, 12, 16, 16] 5,184
BatchNorm2d-116 [-1, 60, 16, 16] 120
GELU-117 [-1, 60, 16, 16] 0
Conv2d-118 [-1, 48, 16, 16] 2,880
BatchNorm2d-119 [-1, 48, 16, 16] 96
GELU-120 [-1, 48, 16, 16] 0
Conv2d-121 [-1, 12, 16, 16] 5,184
botn-122 [-1, 72, 16, 16] 0
BatchNorm2d-123 [-1, 72, 16, 16] 144
GELU-124 [-1, 72, 16, 16] 0
Conv2d-125 [-1, 48, 16, 16] 3,456
BatchNorm2d-126 [-1, 48, 16, 16] 96
GELU-127 [-1, 48, 16, 16] 0
Conv2d-128 [-1, 12, 16, 16] 5,184
BatchNorm2d-129 [-1, 72, 16, 16] 144
GELU-130 [-1, 72, 16, 16] 0
Conv2d-131 [-1, 48, 16, 16] 3,456
BatchNorm2d-132 [-1, 48, 16, 16] 96
GELU-133 [-1, 48, 16, 16] 0
Conv2d-134 [-1, 12, 16, 16] 5,184
botn-135 [-1, 84, 16, 16] 0
BatchNorm2d-136 [-1, 84, 16, 16] 168
GELU-137 [-1, 84, 16, 16] 0
Conv2d-138 [-1, 48, 16, 16] 4,032
BatchNorm2d-139 [-1, 48, 16, 16] 96
GELU-140 [-1, 48, 16, 16] 0
Conv2d-141 [-1, 12, 16, 16] 5,184
BatchNorm2d-142 [-1, 84, 16, 16] 168
GELU-143 [-1, 84, 16, 16] 0
Conv2d-144 [-1, 48, 16, 16] 4,032
BatchNorm2d-145 [-1, 48, 16, 16] 96
GELU-146 [-1, 48, 16, 16] 0
Conv2d-147 [-1, 12, 16, 16] 5,184
botn-148 [-1, 96, 16, 16] 0
BatchNorm2d-149 [-1, 96, 16, 16] 192
GELU-150 [-1, 96, 16, 16] 0
Conv2d-151 [-1, 48, 16, 16] 4,608
BatchNorm2d-152 [-1, 48, 16, 16] 96
GELU-153 [-1, 48, 16, 16] 0
Conv2d-154 [-1, 12, 16, 16] 5,184
BatchNorm2d-155 [-1, 96, 16, 16] 192
GELU-156 [-1, 96, 16, 16] 0
Conv2d-157 [-1, 48, 16, 16] 4,608
BatchNorm2d-158 [-1, 48, 16, 16] 96
GELU-159 [-1, 48, 16, 16] 0
Conv2d-160 [-1, 12, 16, 16] 5,184
botn-161 [-1, 108, 16, 16] 0
BatchNorm2d-162 [-1, 108, 16, 16] 216
GELU-163 [-1, 108, 16, 16] 0
Conv2d-164 [-1, 48, 16, 16] 5,184
BatchNorm2d-165 [-1, 48, 16, 16] 96
GELU-166 [-1, 48, 16, 16] 0
Conv2d-167 [-1, 12, 16, 16] 5,184
BatchNorm2d-168 [-1, 108, 16, 16] 216
GELU-169 [-1, 108, 16, 16] 0
Conv2d-170 [-1, 48, 16, 16] 5,184
BatchNorm2d-171 [-1, 48, 16, 16] 96
GELU-172 [-1, 48, 16, 16] 0
Conv2d-173 [-1, 12, 16, 16] 5,184
botn-174 [-1, 120, 16, 16] 0
BatchNorm2d-175 [-1, 120, 16, 16] 240
GELU-176 [-1, 120, 16, 16] 0
Conv2d-177 [-1, 48, 16, 16] 5,760
BatchNorm2d-178 [-1, 48, 16, 16] 96
GELU-179 [-1, 48, 16, 16] 0
Conv2d-180 [-1, 12, 16, 16] 5,184
BatchNorm2d-181 [-1, 120, 16, 16] 240
GELU-182 [-1, 120, 16, 16] 0
Conv2d-183 [-1, 48, 16, 16] 5,760
BatchNorm2d-184 [-1, 48, 16, 16] 96
GELU-185 [-1, 48, 16, 16] 0
Conv2d-186 [-1, 12, 16, 16] 5,184
botn-187 [-1, 132, 16, 16] 0
BatchNorm2d-188 [-1, 132, 16, 16] 264
GELU-189 [-1, 132, 16, 16] 0
Conv2d-190 [-1, 48, 16, 16] 6,336
BatchNorm2d-191 [-1, 48, 16, 16] 96
GELU-192 [-1, 48, 16, 16] 0
Conv2d-193 [-1, 12, 16, 16] 5,184
BatchNorm2d-194 [-1, 132, 16, 16] 264
GELU-195 [-1, 132, 16, 16] 0
Conv2d-196 [-1, 48, 16, 16] 6,336
BatchNorm2d-197 [-1, 48, 16, 16] 96
GELU-198 [-1, 48, 16, 16] 0
Conv2d-199 [-1, 12, 16, 16] 5,184
botn-200 [-1, 144, 16, 16] 0
BatchNorm2d-201 [-1, 144, 16, 16] 288
GELU-202 [-1, 144, 16, 16] 0
Conv2d-203 [-1, 48, 16, 16] 6,912
BatchNorm2d-204 [-1, 48, 16, 16] 96
GELU-205 [-1, 48, 16, 16] 0
Conv2d-206 [-1, 12, 16, 16] 5,184
BatchNorm2d-207 [-1, 144, 16, 16] 288
GELU-208 [-1, 144, 16, 16] 0
Conv2d-209 [-1, 48, 16, 16] 6,912
BatchNorm2d-210 [-1, 48, 16, 16] 96
GELU-211 [-1, 48, 16, 16] 0
Conv2d-212 [-1, 12, 16, 16] 5,184
botn-213 [-1, 156, 16, 16] 0
BatchNorm2d-214 [-1, 156, 16, 16] 312
GELU-215 [-1, 156, 16, 16] 0
Conv2d-216 [-1, 78, 16, 16] 12,168
trs-217 [-1, 78, 8, 8] 0
BatchNorm2d-218 [-1, 78, 8, 8] 156
GELU-219 [-1, 78, 8, 8] 0
Conv2d-220 [-1, 48, 8, 8] 3,744
BatchNorm2d-221 [-1, 48, 8, 8] 96
GELU-222 [-1, 48, 8, 8] 0
Conv2d-223 [-1, 12, 8, 8] 5,184
BatchNorm2d-224 [-1, 78, 8, 8] 156
GELU-225 [-1, 78, 8, 8] 0
Conv2d-226 [-1, 48, 8, 8] 3,744
BatchNorm2d-227 [-1, 48, 8, 8] 96
GELU-228 [-1, 48, 8, 8] 0
Conv2d-229 [-1, 12, 8, 8] 5,184
botn-230 [-1, 90, 8, 8] 0
BatchNorm2d-231 [-1, 90, 8, 8] 180
GELU-232 [-1, 90, 8, 8] 0
Conv2d-233 [-1, 48, 8, 8] 4,320
BatchNorm2d-234 [-1, 48, 8, 8] 96
GELU-235 [-1, 48, 8, 8] 0
Conv2d-236 [-1, 12, 8, 8] 5,184
BatchNorm2d-237 [-1, 90, 8, 8] 180
GELU-238 [-1, 90, 8, 8] 0
Conv2d-239 [-1, 48, 8, 8] 4,320
BatchNorm2d-240 [-1, 48, 8, 8] 96
GELU-241 [-1, 48, 8, 8] 0
Conv2d-242 [-1, 12, 8, 8] 5,184
botn-243 [-1, 102, 8, 8] 0
BatchNorm2d-244 [-1, 102, 8, 8] 204
GELU-245 [-1, 102, 8, 8] 0
Conv2d-246 [-1, 48, 8, 8] 4,896
BatchNorm2d-247 [-1, 48, 8, 8] 96
GELU-248 [-1, 48, 8, 8] 0
Conv2d-249 [-1, 12, 8, 8] 5,184
BatchNorm2d-250 [-1, 102, 8, 8] 204
GELU-251 [-1, 102, 8, 8] 0
Conv2d-252 [-1, 48, 8, 8] 4,896
BatchNorm2d-253 [-1, 48, 8, 8] 96
GELU-254 [-1, 48, 8, 8] 0
Conv2d-255 [-1, 12, 8, 8] 5,184
botn-256 [-1, 114, 8, 8] 0
BatchNorm2d-257 [-1, 114, 8, 8] 228
GELU-258 [-1, 114, 8, 8] 0
Conv2d-259 [-1, 48, 8, 8] 5,472
BatchNorm2d-260 [-1, 48, 8, 8] 96
GELU-261 [-1, 48, 8, 8] 0
Conv2d-262 [-1, 12, 8, 8] 5,184
BatchNorm2d-263 [-1, 114, 8, 8] 228
GELU-264 [-1, 114, 8, 8] 0
Conv2d-265 [-1, 48, 8, 8] 5,472
BatchNorm2d-266 [-1, 48, 8, 8] 96
GELU-267 [-1, 48, 8, 8] 0
Conv2d-268 [-1, 12, 8, 8] 5,184
botn-269 [-1, 126, 8, 8] 0
BatchNorm2d-270 [-1, 126, 8, 8] 252
GELU-271 [-1, 126, 8, 8] 0
Conv2d-272 [-1, 48, 8, 8] 6,048
BatchNorm2d-273 [-1, 48, 8, 8] 96
GELU-274 [-1, 48, 8, 8] 0
Conv2d-275 [-1, 12, 8, 8] 5,184
BatchNorm2d-276 [-1, 126, 8, 8] 252
GELU-277 [-1, 126, 8, 8] 0
Conv2d-278 [-1, 48, 8, 8] 6,048
BatchNorm2d-279 [-1, 48, 8, 8] 96
GELU-280 [-1, 48, 8, 8] 0
Conv2d-281 [-1, 12, 8, 8] 5,184
botn-282 [-1, 138, 8, 8] 0
BatchNorm2d-283 [-1, 138, 8, 8] 276
GELU-284 [-1, 138, 8, 8] 0
Conv2d-285 [-1, 48, 8, 8] 6,624
BatchNorm2d-286 [-1, 48, 8, 8] 96
GELU-287 [-1, 48, 8, 8] 0
Conv2d-288 [-1, 12, 8, 8] 5,184
BatchNorm2d-289 [-1, 138, 8, 8] 276
GELU-290 [-1, 138, 8, 8] 0
Conv2d-291 [-1, 48, 8, 8] 6,624
BatchNorm2d-292 [-1, 48, 8, 8] 96
GELU-293 [-1, 48, 8, 8] 0
Conv2d-294 [-1, 12, 8, 8] 5,184
botn-295 [-1, 150, 8, 8] 0
BatchNorm2d-296 [-1, 150, 8, 8] 300
GELU-297 [-1, 150, 8, 8] 0
Conv2d-298 [-1, 48, 8, 8] 7,200
BatchNorm2d-299 [-1, 48, 8, 8] 96
GELU-300 [-1, 48, 8, 8] 0
Conv2d-301 [-1, 12, 8, 8] 5,184
BatchNorm2d-302 [-1, 150, 8, 8] 300
GELU-303 [-1, 150, 8, 8] 0
Conv2d-304 [-1, 48, 8, 8] 7,200
BatchNorm2d-305 [-1, 48, 8, 8] 96
GELU-306 [-1, 48, 8, 8] 0
Conv2d-307 [-1, 12, 8, 8] 5,184
botn-308 [-1, 162, 8, 8] 0
BatchNorm2d-309 [-1, 162, 8, 8] 324
GELU-310 [-1, 162, 8, 8] 0
Conv2d-311 [-1, 48, 8, 8] 7,776
BatchNorm2d-312 [-1, 48, 8, 8] 96
GELU-313 [-1, 48, 8, 8] 0
Conv2d-314 [-1, 12, 8, 8] 5,184
BatchNorm2d-315 [-1, 162, 8, 8] 324
GELU-316 [-1, 162, 8, 8] 0
Conv2d-317 [-1, 48, 8, 8] 7,776
BatchNorm2d-318 [-1, 48, 8, 8] 96
GELU-319 [-1, 48, 8, 8] 0
Conv2d-320 [-1, 12, 8, 8] 5,184
botn-321 [-1, 174, 8, 8] 0
BatchNorm2d-322 [-1, 174, 8, 8] 348
GELU-323 [-1, 174, 8, 8] 0
AvgPool2d-324 [-1, 174, 1, 1] 0
Linear-325 [-1, 10] 1,750
ResDen-326 [-1, 10] 0
================================================================
Total params: 506,506
Trainable params: 506,506
Non-trainable params: 0
----------------------------------------------------------------
Input size (MB): 0.01
Forward/backward pass size (MB): 61.14
Params size (MB): 1.93
Estimated Total Size (MB): 63.08
----------------------------------------------------------------