models/efficientnet_v2

import torch import torch.nn import torch.functional import torch.nn.functional class efficientnet_v2_m(torch.nn.Module): def __init__(self): super().__init__() self.features_0_0 = torch.nn.modules.conv.Conv2d(3, 24, 3, 2, 1, bias=False) self.features_0_1 = torch.nn.modules.batchnorm.BatchNorm2d(24) self.features_1_conv_0 = torch.nn.modules.conv.Conv2d(24, 24, 3, 1, 1, bias=False) self.features_1_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(24) self.features_1_conv_3 = torch.nn.modules.conv.Conv2d(24, 24, 1, 1, 0, bias=False) self.features_1_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(24) self.features_2_conv_0 = torch.nn.modules.conv.Conv2d(24, 24, 3, 1, 1, bias=False) self.features_2_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(24) self.features_2_conv_3 = torch.nn.modules.conv.Conv2d(24, 24, 1, 1, 0, bias=False) self.features_2_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(24) self.features_3_conv_0 = torch.nn.modules.conv.Conv2d(24, 24, 3, 1, 1, bias=False) self.features_3_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(24) self.features_3_conv_3 = torch.nn.modules.conv.Conv2d(24, 24, 1, 1, 0, bias=False) self.features_3_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(24) self.features_4_conv_0 = torch.nn.modules.conv.Conv2d(24, 96, 3, 2, 1, bias=False) self.features_4_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(96) self.features_4_conv_3 = torch.nn.modules.conv.Conv2d(96, 48, 1, 1, 0, bias=False) self.features_4_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(48) self.features_5_conv_0 = torch.nn.modules.conv.Conv2d(48, 192, 3, 1, 1, bias=False) self.features_5_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(192) self.features_5_conv_3 = torch.nn.modules.conv.Conv2d(192, 48, 1, 1, 0, bias=False) self.features_5_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(48) self.features_6_conv_0 = torch.nn.modules.conv.Conv2d(48, 192, 3, 1, 1, bias=False) self.features_6_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(192) self.features_6_conv_3 = torch.nn.modules.conv.Conv2d(192, 48, 1, 1, 0, bias=False) self.features_6_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(48) self.features_7_conv_0 = torch.nn.modules.conv.Conv2d(48, 192, 3, 1, 1, bias=False) self.features_7_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(192) self.features_7_conv_3 = torch.nn.modules.conv.Conv2d(192, 48, 1, 1, 0, bias=False) self.features_7_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(48) self.features_8_conv_0 = torch.nn.modules.conv.Conv2d(48, 192, 3, 1, 1, bias=False) self.features_8_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(192) self.features_8_conv_3 = torch.nn.modules.conv.Conv2d(192, 48, 1, 1, 0, bias=False) self.features_8_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(48) self.features_9_conv_0 = torch.nn.modules.conv.Conv2d(48, 192, 3, 2, 1, bias=False) self.features_9_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(192) self.features_9_conv_3 = torch.nn.modules.conv.Conv2d(192, 80, 1, 1, 0, bias=False) self.features_9_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(80) self.features_10_conv_0 = torch.nn.modules.conv.Conv2d(80, 320, 3, 1, 1, bias=False) self.features_10_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(320) self.features_10_conv_3 = torch.nn.modules.conv.Conv2d(320, 80, 1, 1, 0, bias=False) self.features_10_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(80) self.features_11_conv_0 = torch.nn.modules.conv.Conv2d(80, 320, 3, 1, 1, bias=False) self.features_11_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(320) self.features_11_conv_3 = torch.nn.modules.conv.Conv2d(320, 80, 1, 1, 0, bias=False) self.features_11_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(80) self.features_12_conv_0 = torch.nn.modules.conv.Conv2d(80, 320, 3, 1, 1, bias=False) self.features_12_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(320) self.features_12_conv_3 = torch.nn.modules.conv.Conv2d(320, 80, 1, 1, 0, bias=False) self.features_12_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(80) self.features_13_conv_0 = torch.nn.modules.conv.Conv2d(80, 320, 3, 1, 1, bias=False) self.features_13_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(320) self.features_13_conv_3 = torch.nn.modules.conv.Conv2d(320, 80, 1, 1, 0, bias=False) self.features_13_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(80) self.features_14_conv_0 = torch.nn.modules.conv.Conv2d(80, 320, 1, 1, 0, bias=False) self.features_14_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(320) self.features_14_conv_3 = torch.nn.modules.conv.Conv2d(320, 320, 3, 2, 1, groups=320, bias=False) self.features_14_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(320) self.features_14_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1) self.features_14_conv_6_fc_0 = torch.nn.modules.linear.Linear(320, 24) self.features_14_conv_6_fc_2 = torch.nn.modules.linear.Linear(24, 320) self.features_14_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_14_conv_7 = torch.nn.modules.conv.Conv2d(320, 160, 1, 1, 0, bias=False) self.features_14_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(160) self.features_15_conv_0 = torch.nn.modules.conv.Conv2d(160, 640, 1, 1, 0, bias=False) self.features_15_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(640) self.features_15_conv_3 = torch.nn.modules.conv.Conv2d(640, 640, 3, 1, 1, groups=640, bias=False) self.features_15_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(640) self.features_15_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1) self.features_15_conv_6_fc_0 = torch.nn.modules.linear.Linear(640, 40) self.features_15_conv_6_fc_2 = torch.nn.modules.linear.Linear(40, 640) self.features_15_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_15_conv_7 = torch.nn.modules.conv.Conv2d(640, 160, 1, 1, 0, bias=False) self.features_15_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(160) self.features_16_conv_0 = torch.nn.modules.conv.Conv2d(160, 640, 1, 1, 0, bias=False) self.features_16_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(640) self.features_16_conv_3 = torch.nn.modules.conv.Conv2d(640, 640, 3, 1, 1, groups=640, bias=False) self.features_16_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(640) self.features_16_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1) self.features_16_conv_6_fc_0 = torch.nn.modules.linear.Linear(640, 40) self.features_16_conv_6_fc_2 = torch.nn.modules.linear.Linear(40, 640) self.features_16_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_16_conv_7 = torch.nn.modules.conv.Conv2d(640, 160, 1, 1, 0, bias=False) self.features_16_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(160) self.features_17_conv_0 = torch.nn.modules.conv.Conv2d(160, 640, 1, 1, 0, bias=False) self.features_17_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(640) self.features_17_conv_3 = torch.nn.modules.conv.Conv2d(640, 640, 3, 1, 1, groups=640, bias=False) self.features_17_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(640) self.features_17_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1) self.features_17_conv_6_fc_0 = torch.nn.modules.linear.Linear(640, 40) self.features_17_conv_6_fc_2 = torch.nn.modules.linear.Linear(40, 640) self.features_17_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_17_conv_7 = torch.nn.modules.conv.Conv2d(640, 160, 1, 1, 0, bias=False) self.features_17_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(160) self.features_18_conv_0 = torch.nn.modules.conv.Conv2d(160, 640, 1, 1, 0, bias=False) self.features_18_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(640) self.features_18_conv_3 = torch.nn.modules.conv.Conv2d(640, 640, 3, 1, 1, groups=640, bias=False) self.features_18_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(640) self.features_18_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1) self.features_18_conv_6_fc_0 = torch.nn.modules.linear.Linear(640, 40) self.features_18_conv_6_fc_2 = torch.nn.modules.linear.Linear(40, 640) self.features_18_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_18_conv_7 = torch.nn.modules.conv.Conv2d(640, 160, 1, 1, 0, bias=False) self.features_18_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(160) self.features_19_conv_0 = torch.nn.modules.conv.Conv2d(160, 640, 1, 1, 0, bias=False) self.features_19_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(640) self.features_19_conv_3 = torch.nn.modules.conv.Conv2d(640, 640, 3, 1, 1, groups=640, bias=False) self.features_19_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(640) self.features_19_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1) self.features_19_conv_6_fc_0 = torch.nn.modules.linear.Linear(640, 40) self.features_19_conv_6_fc_2 = torch.nn.modules.linear.Linear(40, 640) self.features_19_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_19_conv_7 = torch.nn.modules.conv.Conv2d(640, 160, 1, 1, 0, bias=False) self.features_19_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(160) self.features_20_conv_0 = torch.nn.modules.conv.Conv2d(160, 640, 1, 1, 0, bias=False) self.features_20_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(640) self.features_20_conv_3 = torch.nn.modules.conv.Conv2d(640, 640, 3, 1, 1, groups=640, bias=False) self.features_20_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(640) self.features_20_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1) self.features_20_conv_6_fc_0 = torch.nn.modules.linear.Linear(640, 40) self.features_20_conv_6_fc_2 = torch.nn.modules.linear.Linear(40, 640) self.features_20_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_20_conv_7 = torch.nn.modules.conv.Conv2d(640, 160, 1, 1, 0, bias=False) self.features_20_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(160) self.features_21_conv_0 = torch.nn.modules.conv.Conv2d(160, 960, 1, 1, 0, bias=False) self.features_21_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(960) self.features_21_conv_3 = torch.nn.modules.conv.Conv2d(960, 960, 3, 1, 1, groups=960, bias=False) self.features_21_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(960) self.features_21_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1) self.features_21_conv_6_fc_0 = torch.nn.modules.linear.Linear(960, 40) self.features_21_conv_6_fc_2 = torch.nn.modules.linear.Linear(40, 960) self.features_21_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_21_conv_7 = torch.nn.modules.conv.Conv2d(960, 176, 1, 1, 0, bias=False) self.features_21_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(176) self.features_22_conv_0 = torch.nn.modules.conv.Conv2d(176, 1056, 1, 1, 0, bias=False) self.features_22_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1056) self.features_22_conv_3 = torch.nn.modules.conv.Conv2d(1056, 1056, 3, 1, 1, groups=1056, bias=False) self.features_22_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1056) self.features_22_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1) self.features_22_conv_6_fc_0 = torch.nn.modules.linear.Linear(1056, 48) self.features_22_conv_6_fc_2 = torch.nn.modules.linear.Linear(48, 1056) self.features_22_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_22_conv_7 = torch.nn.modules.conv.Conv2d(1056, 176, 1, 1, 0, bias=False) self.features_22_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(176) self.features_23_conv_0 = torch.nn.modules.conv.Conv2d(176, 1056, 1, 1, 0, bias=False) self.features_23_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1056) self.features_23_conv_3 = torch.nn.modules.conv.Conv2d(1056, 1056, 3, 1, 1, groups=1056, bias=False) self.features_23_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1056) self.features_23_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1) self.features_23_conv_6_fc_0 = torch.nn.modules.linear.Linear(1056, 48) self.features_23_conv_6_fc_2 = torch.nn.modules.linear.Linear(48, 1056) self.features_23_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_23_conv_7 = torch.nn.modules.conv.Conv2d(1056, 176, 1, 1, 0, bias=False) self.features_23_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(176) self.features_24_conv_0 = torch.nn.modules.conv.Conv2d(176, 1056, 1, 1, 0, bias=False) self.features_24_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1056) self.features_24_conv_3 = torch.nn.modules.conv.Conv2d(1056, 1056, 3, 1, 1, groups=1056, bias=False) self.features_24_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1056) self.features_24_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1) self.features_24_conv_6_fc_0 = torch.nn.modules.linear.Linear(1056, 48) self.features_24_conv_6_fc_2 = torch.nn.modules.linear.Linear(48, 1056) self.features_24_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_24_conv_7 = torch.nn.modules.conv.Conv2d(1056, 176, 1, 1, 0, bias=False) self.features_24_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(176) self.features_25_conv_0 = torch.nn.modules.conv.Conv2d(176, 1056, 1, 1, 0, bias=False) self.features_25_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1056) self.features_25_conv_3 = torch.nn.modules.conv.Conv2d(1056, 1056, 3, 1, 1, groups=1056, bias=False) self.features_25_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1056) self.features_25_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1) self.features_25_conv_6_fc_0 = torch.nn.modules.linear.Linear(1056, 48) self.features_25_conv_6_fc_2 = torch.nn.modules.linear.Linear(48, 1056) self.features_25_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_25_conv_7 = torch.nn.modules.conv.Conv2d(1056, 176, 1, 1, 0, bias=False) self.features_25_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(176) self.features_26_conv_0 = torch.nn.modules.conv.Conv2d(176, 1056, 1, 1, 0, bias=False) self.features_26_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1056) self.features_26_conv_3 = torch.nn.modules.conv.Conv2d(1056, 1056, 3, 1, 1, groups=1056, bias=False) self.features_26_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1056) self.features_26_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1) self.features_26_conv_6_fc_0 = torch.nn.modules.linear.Linear(1056, 48) self.features_26_conv_6_fc_2 = torch.nn.modules.linear.Linear(48, 1056) self.features_26_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_26_conv_7 = torch.nn.modules.conv.Conv2d(1056, 176, 1, 1, 0, bias=False) self.features_26_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(176) self.features_27_conv_0 = torch.nn.modules.conv.Conv2d(176, 1056, 1, 1, 0, bias=False) self.features_27_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1056) self.features_27_conv_3 = torch.nn.modules.conv.Conv2d(1056, 1056, 3, 1, 1, groups=1056, bias=False) self.features_27_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1056) self.features_27_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1) self.features_27_conv_6_fc_0 = torch.nn.modules.linear.Linear(1056, 48) self.features_27_conv_6_fc_2 = torch.nn.modules.linear.Linear(48, 1056) self.features_27_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_27_conv_7 = torch.nn.modules.conv.Conv2d(1056, 176, 1, 1, 0, bias=False) self.features_27_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(176) self.features_28_conv_0 = torch.nn.modules.conv.Conv2d(176, 1056, 1, 1, 0, bias=False) self.features_28_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1056) self.features_28_conv_3 = torch.nn.modules.conv.Conv2d(1056, 1056, 3, 1, 1, groups=1056, bias=False) self.features_28_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1056) self.features_28_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1) self.features_28_conv_6_fc_0 = torch.nn.modules.linear.Linear(1056, 48) self.features_28_conv_6_fc_2 = torch.nn.modules.linear.Linear(48, 1056) self.features_28_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_28_conv_7 = torch.nn.modules.conv.Conv2d(1056, 176, 1, 1, 0, bias=False) self.features_28_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(176) self.features_29_conv_0 = torch.nn.modules.conv.Conv2d(176, 1056, 1, 1, 0, bias=False) self.features_29_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1056) self.features_29_conv_3 = torch.nn.modules.conv.Conv2d(1056, 1056, 3, 1, 1, groups=1056, bias=False) self.features_29_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1056) self.features_29_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1) self.features_29_conv_6_fc_0 = torch.nn.modules.linear.Linear(1056, 48) self.features_29_conv_6_fc_2 = torch.nn.modules.linear.Linear(48, 1056) self.features_29_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_29_conv_7 = torch.nn.modules.conv.Conv2d(1056, 176, 1, 1, 0, bias=False) self.features_29_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(176) self.features_30_conv_0 = torch.nn.modules.conv.Conv2d(176, 1056, 1, 1, 0, bias=False) self.features_30_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1056) self.features_30_conv_3 = torch.nn.modules.conv.Conv2d(1056, 1056, 3, 1, 1, groups=1056, bias=False) self.features_30_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1056) self.features_30_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1) self.features_30_conv_6_fc_0 = torch.nn.modules.linear.Linear(1056, 48) self.features_30_conv_6_fc_2 = torch.nn.modules.linear.Linear(48, 1056) self.features_30_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_30_conv_7 = torch.nn.modules.conv.Conv2d(1056, 176, 1, 1, 0, bias=False) self.features_30_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(176) self.features_31_conv_0 = torch.nn.modules.conv.Conv2d(176, 1056, 1, 1, 0, bias=False) self.features_31_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1056) self.features_31_conv_3 = torch.nn.modules.conv.Conv2d(1056, 1056, 3, 1, 1, groups=1056, bias=False) self.features_31_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1056) self.features_31_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1) self.features_31_conv_6_fc_0 = torch.nn.modules.linear.Linear(1056, 48) self.features_31_conv_6_fc_2 = torch.nn.modules.linear.Linear(48, 1056) self.features_31_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_31_conv_7 = torch.nn.modules.conv.Conv2d(1056, 176, 1, 1, 0, bias=False) self.features_31_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(176) self.features_32_conv_0 = torch.nn.modules.conv.Conv2d(176, 1056, 1, 1, 0, bias=False) self.features_32_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1056) self.features_32_conv_3 = torch.nn.modules.conv.Conv2d(1056, 1056, 3, 1, 1, groups=1056, bias=False) self.features_32_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1056) self.features_32_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1) self.features_32_conv_6_fc_0 = torch.nn.modules.linear.Linear(1056, 48) self.features_32_conv_6_fc_2 = torch.nn.modules.linear.Linear(48, 1056) self.features_32_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_32_conv_7 = torch.nn.modules.conv.Conv2d(1056, 176, 1, 1, 0, bias=False) self.features_32_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(176) self.features_33_conv_0 = torch.nn.modules.conv.Conv2d(176, 1056, 1, 1, 0, bias=False) self.features_33_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1056) self.features_33_conv_3 = torch.nn.modules.conv.Conv2d(1056, 1056, 3, 1, 1, groups=1056, bias=False) self.features_33_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1056) self.features_33_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1) self.features_33_conv_6_fc_0 = torch.nn.modules.linear.Linear(1056, 48) self.features_33_conv_6_fc_2 = torch.nn.modules.linear.Linear(48, 1056) self.features_33_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_33_conv_7 = torch.nn.modules.conv.Conv2d(1056, 176, 1, 1, 0, bias=False) self.features_33_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(176) self.features_34_conv_0 = torch.nn.modules.conv.Conv2d(176, 1056, 1, 1, 0, bias=False) self.features_34_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1056) self.features_34_conv_3 = torch.nn.modules.conv.Conv2d(1056, 1056, 3, 1, 1, groups=1056, bias=False) self.features_34_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1056) self.features_34_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1) self.features_34_conv_6_fc_0 = torch.nn.modules.linear.Linear(1056, 48) self.features_34_conv_6_fc_2 = torch.nn.modules.linear.Linear(48, 1056) self.features_34_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_34_conv_7 = torch.nn.modules.conv.Conv2d(1056, 176, 1, 1, 0, bias=False) self.features_34_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(176) self.features_35_conv_0 = torch.nn.modules.conv.Conv2d(176, 1056, 1, 1, 0, bias=False) self.features_35_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1056) self.features_35_conv_3 = torch.nn.modules.conv.Conv2d(1056, 1056, 3, 2, 1, groups=1056, bias=False) self.features_35_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1056) self.features_35_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1) self.features_35_conv_6_fc_0 = torch.nn.modules.linear.Linear(1056, 48) self.features_35_conv_6_fc_2 = torch.nn.modules.linear.Linear(48, 1056) self.features_35_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_35_conv_7 = torch.nn.modules.conv.Conv2d(1056, 304, 1, 1, 0, bias=False) self.features_35_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(304) self.features_36_conv_0 = torch.nn.modules.conv.Conv2d(304, 1824, 1, 1, 0, bias=False) self.features_36_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1824) self.features_36_conv_3 = torch.nn.modules.conv.Conv2d(1824, 1824, 3, 1, 1, groups=1824, bias=False) self.features_36_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1824) self.features_36_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1) self.features_36_conv_6_fc_0 = torch.nn.modules.linear.Linear(1824, 80) self.features_36_conv_6_fc_2 = torch.nn.modules.linear.Linear(80, 1824) self.features_36_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_36_conv_7 = torch.nn.modules.conv.Conv2d(1824, 304, 1, 1, 0, bias=False) self.features_36_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(304) self.features_37_conv_0 = torch.nn.modules.conv.Conv2d(304, 1824, 1, 1, 0, bias=False) self.features_37_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1824) self.features_37_conv_3 = torch.nn.modules.conv.Conv2d(1824, 1824, 3, 1, 1, groups=1824, bias=False) self.features_37_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1824) self.features_37_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1) self.features_37_conv_6_fc_0 = torch.nn.modules.linear.Linear(1824, 80) self.features_37_conv_6_fc_2 = torch.nn.modules.linear.Linear(80, 1824) self.features_37_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_37_conv_7 = torch.nn.modules.conv.Conv2d(1824, 304, 1, 1, 0, bias=False) self.features_37_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(304) self.features_38_conv_0 = torch.nn.modules.conv.Conv2d(304, 1824, 1, 1, 0, bias=False) self.features_38_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1824) self.features_38_conv_3 = torch.nn.modules.conv.Conv2d(1824, 1824, 3, 1, 1, groups=1824, bias=False) self.features_38_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1824) self.features_38_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1) self.features_38_conv_6_fc_0 = torch.nn.modules.linear.Linear(1824, 80) self.features_38_conv_6_fc_2 = torch.nn.modules.linear.Linear(80, 1824) self.features_38_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_38_conv_7 = torch.nn.modules.conv.Conv2d(1824, 304, 1, 1, 0, bias=False) self.features_38_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(304) self.features_39_conv_0 = torch.nn.modules.conv.Conv2d(304, 1824, 1, 1, 0, bias=False) self.features_39_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1824) self.features_39_conv_3 = torch.nn.modules.conv.Conv2d(1824, 1824, 3, 1, 1, groups=1824, bias=False) self.features_39_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1824) self.features_39_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1) self.features_39_conv_6_fc_0 = torch.nn.modules.linear.Linear(1824, 80) self.features_39_conv_6_fc_2 = torch.nn.modules.linear.Linear(80, 1824) self.features_39_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_39_conv_7 = torch.nn.modules.conv.Conv2d(1824, 304, 1, 1, 0, bias=False) self.features_39_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(304) self.features_40_conv_0 = torch.nn.modules.conv.Conv2d(304, 1824, 1, 1, 0, bias=False) self.features_40_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1824) self.features_40_conv_3 = torch.nn.modules.conv.Conv2d(1824, 1824, 3, 1, 1, groups=1824, bias=False) self.features_40_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1824) self.features_40_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1) self.features_40_conv_6_fc_0 = torch.nn.modules.linear.Linear(1824, 80) self.features_40_conv_6_fc_2 = torch.nn.modules.linear.Linear(80, 1824) self.features_40_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_40_conv_7 = torch.nn.modules.conv.Conv2d(1824, 304, 1, 1, 0, bias=False) self.features_40_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(304) self.features_41_conv_0 = torch.nn.modules.conv.Conv2d(304, 1824, 1, 1, 0, bias=False) self.features_41_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1824) self.features_41_conv_3 = torch.nn.modules.conv.Conv2d(1824, 1824, 3, 1, 1, groups=1824, bias=False) self.features_41_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1824) self.features_41_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1) self.features_41_conv_6_fc_0 = torch.nn.modules.linear.Linear(1824, 80) self.features_41_conv_6_fc_2 = torch.nn.modules.linear.Linear(80, 1824) self.features_41_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_41_conv_7 = torch.nn.modules.conv.Conv2d(1824, 304, 1, 1, 0, bias=False) self.features_41_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(304) self.features_42_conv_0 = torch.nn.modules.conv.Conv2d(304, 1824, 1, 1, 0, bias=False) self.features_42_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1824) self.features_42_conv_3 = torch.nn.modules.conv.Conv2d(1824, 1824, 3, 1, 1, groups=1824, bias=False) self.features_42_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1824) self.features_42_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1) self.features_42_conv_6_fc_0 = torch.nn.modules.linear.Linear(1824, 80) self.features_42_conv_6_fc_2 = torch.nn.modules.linear.Linear(80, 1824) self.features_42_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_42_conv_7 = torch.nn.modules.conv.Conv2d(1824, 304, 1, 1, 0, bias=False) self.features_42_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(304) self.features_43_conv_0 = torch.nn.modules.conv.Conv2d(304, 1824, 1, 1, 0, bias=False) self.features_43_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1824) self.features_43_conv_3 = torch.nn.modules.conv.Conv2d(1824, 1824, 3, 1, 1, groups=1824, bias=False) self.features_43_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1824) self.features_43_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1) self.features_43_conv_6_fc_0 = torch.nn.modules.linear.Linear(1824, 80) self.features_43_conv_6_fc_2 = torch.nn.modules.linear.Linear(80, 1824) self.features_43_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_43_conv_7 = torch.nn.modules.conv.Conv2d(1824, 304, 1, 1, 0, bias=False) self.features_43_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(304) self.features_44_conv_0 = torch.nn.modules.conv.Conv2d(304, 1824, 1, 1, 0, bias=False) self.features_44_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1824) self.features_44_conv_3 = torch.nn.modules.conv.Conv2d(1824, 1824, 3, 1, 1, groups=1824, bias=False) self.features_44_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1824) self.features_44_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1) self.features_44_conv_6_fc_0 = torch.nn.modules.linear.Linear(1824, 80) self.features_44_conv_6_fc_2 = torch.nn.modules.linear.Linear(80, 1824) self.features_44_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_44_conv_7 = torch.nn.modules.conv.Conv2d(1824, 304, 1, 1, 0, bias=False) self.features_44_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(304) self.features_45_conv_0 = torch.nn.modules.conv.Conv2d(304, 1824, 1, 1, 0, bias=False) self.features_45_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1824) self.features_45_conv_3 = torch.nn.modules.conv.Conv2d(1824, 1824, 3, 1, 1, groups=1824, bias=False) self.features_45_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1824) self.features_45_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1) self.features_45_conv_6_fc_0 = torch.nn.modules.linear.Linear(1824, 80) self.features_45_conv_6_fc_2 = torch.nn.modules.linear.Linear(80, 1824) self.features_45_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_45_conv_7 = torch.nn.modules.conv.Conv2d(1824, 304, 1, 1, 0, bias=False) self.features_45_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(304) self.features_46_conv_0 = torch.nn.modules.conv.Conv2d(304, 1824, 1, 1, 0, bias=False) self.features_46_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1824) self.features_46_conv_3 = torch.nn.modules.conv.Conv2d(1824, 1824, 3, 1, 1, groups=1824, bias=False) self.features_46_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1824) self.features_46_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1) self.features_46_conv_6_fc_0 = torch.nn.modules.linear.Linear(1824, 80) self.features_46_conv_6_fc_2 = torch.nn.modules.linear.Linear(80, 1824) self.features_46_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_46_conv_7 = torch.nn.modules.conv.Conv2d(1824, 304, 1, 1, 0, bias=False) self.features_46_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(304) self.features_47_conv_0 = torch.nn.modules.conv.Conv2d(304, 1824, 1, 1, 0, bias=False) self.features_47_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1824) self.features_47_conv_3 = torch.nn.modules.conv.Conv2d(1824, 1824, 3, 1, 1, groups=1824, bias=False) self.features_47_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1824) self.features_47_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1) self.features_47_conv_6_fc_0 = torch.nn.modules.linear.Linear(1824, 80) self.features_47_conv_6_fc_2 = torch.nn.modules.linear.Linear(80, 1824) self.features_47_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_47_conv_7 = torch.nn.modules.conv.Conv2d(1824, 304, 1, 1, 0, bias=False) self.features_47_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(304) self.features_48_conv_0 = torch.nn.modules.conv.Conv2d(304, 1824, 1, 1, 0, bias=False) self.features_48_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1824) self.features_48_conv_3 = torch.nn.modules.conv.Conv2d(1824, 1824, 3, 1, 1, groups=1824, bias=False) self.features_48_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1824) self.features_48_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1) self.features_48_conv_6_fc_0 = torch.nn.modules.linear.Linear(1824, 80) self.features_48_conv_6_fc_2 = torch.nn.modules.linear.Linear(80, 1824) self.features_48_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_48_conv_7 = torch.nn.modules.conv.Conv2d(1824, 304, 1, 1, 0, bias=False) self.features_48_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(304) self.features_49_conv_0 = torch.nn.modules.conv.Conv2d(304, 1824, 1, 1, 0, bias=False) self.features_49_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1824) self.features_49_conv_3 = torch.nn.modules.conv.Conv2d(1824, 1824, 3, 1, 1, groups=1824, bias=False) self.features_49_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1824) self.features_49_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1) self.features_49_conv_6_fc_0 = torch.nn.modules.linear.Linear(1824, 80) self.features_49_conv_6_fc_2 = torch.nn.modules.linear.Linear(80, 1824) self.features_49_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_49_conv_7 = torch.nn.modules.conv.Conv2d(1824, 304, 1, 1, 0, bias=False) self.features_49_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(304) self.features_50_conv_0 = torch.nn.modules.conv.Conv2d(304, 1824, 1, 1, 0, bias=False) self.features_50_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1824) self.features_50_conv_3 = torch.nn.modules.conv.Conv2d(1824, 1824, 3, 1, 1, groups=1824, bias=False) self.features_50_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1824) self.features_50_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1) self.features_50_conv_6_fc_0 = torch.nn.modules.linear.Linear(1824, 80) self.features_50_conv_6_fc_2 = torch.nn.modules.linear.Linear(80, 1824) self.features_50_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_50_conv_7 = torch.nn.modules.conv.Conv2d(1824, 304, 1, 1, 0, bias=False) self.features_50_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(304) self.features_51_conv_0 = torch.nn.modules.conv.Conv2d(304, 1824, 1, 1, 0, bias=False) self.features_51_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1824) self.features_51_conv_3 = torch.nn.modules.conv.Conv2d(1824, 1824, 3, 1, 1, groups=1824, bias=False) self.features_51_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1824) self.features_51_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1) self.features_51_conv_6_fc_0 = torch.nn.modules.linear.Linear(1824, 80) self.features_51_conv_6_fc_2 = torch.nn.modules.linear.Linear(80, 1824) self.features_51_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_51_conv_7 = torch.nn.modules.conv.Conv2d(1824, 304, 1, 1, 0, bias=False) self.features_51_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(304) self.features_52_conv_0 = torch.nn.modules.conv.Conv2d(304, 1824, 1, 1, 0, bias=False) self.features_52_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1824) self.features_52_conv_3 = torch.nn.modules.conv.Conv2d(1824, 1824, 3, 1, 1, groups=1824, bias=False) self.features_52_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1824) self.features_52_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1) self.features_52_conv_6_fc_0 = torch.nn.modules.linear.Linear(1824, 80) self.features_52_conv_6_fc_2 = torch.nn.modules.linear.Linear(80, 1824) self.features_52_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_52_conv_7 = torch.nn.modules.conv.Conv2d(1824, 304, 1, 1, 0, bias=False) self.features_52_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(304) self.features_53_conv_0 = torch.nn.modules.conv.Conv2d(304, 1824, 1, 1, 0, bias=False) self.features_53_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1824) self.features_53_conv_3 = torch.nn.modules.conv.Conv2d(1824, 1824, 3, 1, 1, groups=1824, bias=False) self.features_53_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1824) self.features_53_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1) self.features_53_conv_6_fc_0 = torch.nn.modules.linear.Linear(1824, 80) self.features_53_conv_6_fc_2 = torch.nn.modules.linear.Linear(80, 1824) self.features_53_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_53_conv_7 = torch.nn.modules.conv.Conv2d(1824, 512, 1, 1, 0, bias=False) self.features_53_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(512) self.features_54_conv_0 = torch.nn.modules.conv.Conv2d(512, 3072, 1, 1, 0, bias=False) self.features_54_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3072) self.features_54_conv_3 = torch.nn.modules.conv.Conv2d(3072, 3072, 3, 1, 1, groups=3072, bias=False) self.features_54_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3072) self.features_54_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1) self.features_54_conv_6_fc_0 = torch.nn.modules.linear.Linear(3072, 128) self.features_54_conv_6_fc_2 = torch.nn.modules.linear.Linear(128, 3072) self.features_54_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_54_conv_7 = torch.nn.modules.conv.Conv2d(3072, 512, 1, 1, 0, bias=False) self.features_54_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(512) self.features_55_conv_0 = torch.nn.modules.conv.Conv2d(512, 3072, 1, 1, 0, bias=False) self.features_55_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3072) self.features_55_conv_3 = torch.nn.modules.conv.Conv2d(3072, 3072, 3, 1, 1, groups=3072, bias=False) self.features_55_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3072) self.features_55_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1) self.features_55_conv_6_fc_0 = torch.nn.modules.linear.Linear(3072, 128) self.features_55_conv_6_fc_2 = torch.nn.modules.linear.Linear(128, 3072) self.features_55_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_55_conv_7 = torch.nn.modules.conv.Conv2d(3072, 512, 1, 1, 0, bias=False) self.features_55_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(512) self.features_56_conv_0 = torch.nn.modules.conv.Conv2d(512, 3072, 1, 1, 0, bias=False) self.features_56_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3072) self.features_56_conv_3 = torch.nn.modules.conv.Conv2d(3072, 3072, 3, 1, 1, groups=3072, bias=False) self.features_56_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3072) self.features_56_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1) self.features_56_conv_6_fc_0 = torch.nn.modules.linear.Linear(3072, 128) self.features_56_conv_6_fc_2 = torch.nn.modules.linear.Linear(128, 3072) self.features_56_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_56_conv_7 = torch.nn.modules.conv.Conv2d(3072, 512, 1, 1, 0, bias=False) self.features_56_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(512) self.features_57_conv_0 = torch.nn.modules.conv.Conv2d(512, 3072, 1, 1, 0, bias=False) self.features_57_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3072) self.features_57_conv_3 = torch.nn.modules.conv.Conv2d(3072, 3072, 3, 1, 1, groups=3072, bias=False) self.features_57_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3072) self.features_57_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1) self.features_57_conv_6_fc_0 = torch.nn.modules.linear.Linear(3072, 128) self.features_57_conv_6_fc_2 = torch.nn.modules.linear.Linear(128, 3072) self.features_57_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_57_conv_7 = torch.nn.modules.conv.Conv2d(3072, 512, 1, 1, 0, bias=False) self.features_57_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(512) self.conv_0 = torch.nn.modules.conv.Conv2d(512, 1792, 1, 1, 0, bias=False) self.conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1792) self.avgpool = torch.nn.modules.pooling.AdaptiveAvgPool2d((1, 1)) self.classifier = torch.nn.modules.linear.Linear(1792, 1000) def forward(self, input_1): features_0_0 = self.features_0_0(input_1) features_0_1 = self.features_0_1(features_0_0) sigmoid_1 = torch.sigmoid(features_0_1) mul_1 = features_0_1.__mul__(sigmoid_1) features_1_conv_0 = self.features_1_conv_0(mul_1) features_1_conv_1 = self.features_1_conv_1(features_1_conv_0) sigmoid_2 = torch.sigmoid(features_1_conv_1) mul_2 = features_1_conv_1.__mul__(sigmoid_2) features_1_conv_3 = self.features_1_conv_3(mul_2) features_1_conv_4 = self.features_1_conv_4(features_1_conv_3) add_1 = mul_1.__add__(features_1_conv_4) features_2_conv_0 = self.features_2_conv_0(add_1) features_2_conv_1 = self.features_2_conv_1(features_2_conv_0) sigmoid_3 = torch.sigmoid(features_2_conv_1) mul_3 = features_2_conv_1.__mul__(sigmoid_3) features_2_conv_3 = self.features_2_conv_3(mul_3) features_2_conv_4 = self.features_2_conv_4(features_2_conv_3) add_2 = add_1.__add__(features_2_conv_4) features_3_conv_0 = self.features_3_conv_0(add_2) features_3_conv_1 = self.features_3_conv_1(features_3_conv_0) sigmoid_4 = torch.sigmoid(features_3_conv_1) mul_4 = features_3_conv_1.__mul__(sigmoid_4) features_3_conv_3 = self.features_3_conv_3(mul_4) features_3_conv_4 = self.features_3_conv_4(features_3_conv_3) add_3 = add_2.__add__(features_3_conv_4) features_4_conv_0 = self.features_4_conv_0(add_3) features_4_conv_1 = self.features_4_conv_1(features_4_conv_0) sigmoid_5 = torch.sigmoid(features_4_conv_1) mul_5 = features_4_conv_1.__mul__(sigmoid_5) features_4_conv_3 = self.features_4_conv_3(mul_5) features_4_conv_4 = self.features_4_conv_4(features_4_conv_3) features_5_conv_0 = self.features_5_conv_0(features_4_conv_4) features_5_conv_1 = self.features_5_conv_1(features_5_conv_0) sigmoid_6 = torch.sigmoid(features_5_conv_1) mul_6 = features_5_conv_1.__mul__(sigmoid_6) features_5_conv_3 = self.features_5_conv_3(mul_6) features_5_conv_4 = self.features_5_conv_4(features_5_conv_3) add_4 = features_4_conv_4.__add__(features_5_conv_4) features_6_conv_0 = self.features_6_conv_0(add_4) features_6_conv_1 = self.features_6_conv_1(features_6_conv_0) sigmoid_7 = torch.sigmoid(features_6_conv_1) mul_7 = features_6_conv_1.__mul__(sigmoid_7) features_6_conv_3 = self.features_6_conv_3(mul_7) features_6_conv_4 = self.features_6_conv_4(features_6_conv_3) add_5 = add_4.__add__(features_6_conv_4) features_7_conv_0 = self.features_7_conv_0(add_5) features_7_conv_1 = self.features_7_conv_1(features_7_conv_0) sigmoid_8 = torch.sigmoid(features_7_conv_1) mul_8 = features_7_conv_1.__mul__(sigmoid_8) features_7_conv_3 = self.features_7_conv_3(mul_8) features_7_conv_4 = self.features_7_conv_4(features_7_conv_3) add_6 = add_5.__add__(features_7_conv_4) features_8_conv_0 = self.features_8_conv_0(add_6) features_8_conv_1 = self.features_8_conv_1(features_8_conv_0) sigmoid_9 = torch.sigmoid(features_8_conv_1) mul_9 = features_8_conv_1.__mul__(sigmoid_9) features_8_conv_3 = self.features_8_conv_3(mul_9) features_8_conv_4 = self.features_8_conv_4(features_8_conv_3) add_7 = add_6.__add__(features_8_conv_4) features_9_conv_0 = self.features_9_conv_0(add_7) features_9_conv_1 = self.features_9_conv_1(features_9_conv_0) sigmoid_10 = torch.sigmoid(features_9_conv_1) mul_10 = features_9_conv_1.__mul__(sigmoid_10) features_9_conv_3 = self.features_9_conv_3(mul_10) features_9_conv_4 = self.features_9_conv_4(features_9_conv_3) features_10_conv_0 = self.features_10_conv_0(features_9_conv_4) features_10_conv_1 = self.features_10_conv_1(features_10_conv_0) sigmoid_11 = torch.sigmoid(features_10_conv_1) mul_11 = features_10_conv_1.__mul__(sigmoid_11) features_10_conv_3 = self.features_10_conv_3(mul_11) features_10_conv_4 = self.features_10_conv_4(features_10_conv_3) add_8 = features_9_conv_4.__add__(features_10_conv_4) features_11_conv_0 = self.features_11_conv_0(add_8) features_11_conv_1 = self.features_11_conv_1(features_11_conv_0) sigmoid_12 = torch.sigmoid(features_11_conv_1) mul_12 = features_11_conv_1.__mul__(sigmoid_12) features_11_conv_3 = self.features_11_conv_3(mul_12) features_11_conv_4 = self.features_11_conv_4(features_11_conv_3) add_9 = add_8.__add__(features_11_conv_4) features_12_conv_0 = self.features_12_conv_0(add_9) features_12_conv_1 = self.features_12_conv_1(features_12_conv_0) sigmoid_13 = torch.sigmoid(features_12_conv_1) mul_13 = features_12_conv_1.__mul__(sigmoid_13) features_12_conv_3 = self.features_12_conv_3(mul_13) features_12_conv_4 = self.features_12_conv_4(features_12_conv_3) add_10 = add_9.__add__(features_12_conv_4) features_13_conv_0 = self.features_13_conv_0(add_10) features_13_conv_1 = self.features_13_conv_1(features_13_conv_0) sigmoid_14 = torch.sigmoid(features_13_conv_1) mul_14 = features_13_conv_1.__mul__(sigmoid_14) features_13_conv_3 = self.features_13_conv_3(mul_14) features_13_conv_4 = self.features_13_conv_4(features_13_conv_3) add_11 = add_10.__add__(features_13_conv_4) features_14_conv_0 = self.features_14_conv_0(add_11) features_14_conv_1 = self.features_14_conv_1(features_14_conv_0) sigmoid_15 = torch.sigmoid(features_14_conv_1) mul_15 = features_14_conv_1.__mul__(sigmoid_15) features_14_conv_3 = self.features_14_conv_3(mul_15) features_14_conv_4 = self.features_14_conv_4(features_14_conv_3) sigmoid_16 = torch.sigmoid(features_14_conv_4) mul_16 = features_14_conv_4.__mul__(sigmoid_16) size_1 = mul_16.size() features_14_conv_6_avg_pool = self.features_14_conv_6_avg_pool(mul_16) view_1 = features_14_conv_6_avg_pool.view(size_1[0], size_1[1]) features_14_conv_6_fc_0 = self.features_14_conv_6_fc_0(view_1) sigmoid_17 = torch.sigmoid(features_14_conv_6_fc_0) mul_17 = features_14_conv_6_fc_0.__mul__(sigmoid_17) features_14_conv_6_fc_2 = self.features_14_conv_6_fc_2(mul_17) features_14_conv_6_fc_3 = self.features_14_conv_6_fc_3(features_14_conv_6_fc_2) view_2 = features_14_conv_6_fc_3.view(size_1[0], size_1[1], 1, 1) mul_18 = mul_16.__mul__(view_2) features_14_conv_7 = self.features_14_conv_7(mul_18) features_14_conv_8 = self.features_14_conv_8(features_14_conv_7) features_15_conv_0 = self.features_15_conv_0(features_14_conv_8) features_15_conv_1 = self.features_15_conv_1(features_15_conv_0) sigmoid_18 = torch.sigmoid(features_15_conv_1) mul_19 = features_15_conv_1.__mul__(sigmoid_18) features_15_conv_3 = self.features_15_conv_3(mul_19) features_15_conv_4 = self.features_15_conv_4(features_15_conv_3) sigmoid_19 = torch.sigmoid(features_15_conv_4) mul_20 = features_15_conv_4.__mul__(sigmoid_19) size_2 = mul_20.size() features_15_conv_6_avg_pool = self.features_15_conv_6_avg_pool(mul_20) view_3 = features_15_conv_6_avg_pool.view(size_2[0], size_2[1]) features_15_conv_6_fc_0 = self.features_15_conv_6_fc_0(view_3) sigmoid_20 = torch.sigmoid(features_15_conv_6_fc_0) mul_21 = features_15_conv_6_fc_0.__mul__(sigmoid_20) features_15_conv_6_fc_2 = self.features_15_conv_6_fc_2(mul_21) features_15_conv_6_fc_3 = self.features_15_conv_6_fc_3(features_15_conv_6_fc_2) view_4 = features_15_conv_6_fc_3.view(size_2[0], size_2[1], 1, 1) mul_22 = mul_20.__mul__(view_4) features_15_conv_7 = self.features_15_conv_7(mul_22) features_15_conv_8 = self.features_15_conv_8(features_15_conv_7) add_12 = features_14_conv_8.__add__(features_15_conv_8) features_16_conv_0 = self.features_16_conv_0(add_12) features_16_conv_1 = self.features_16_conv_1(features_16_conv_0) sigmoid_21 = torch.sigmoid(features_16_conv_1) mul_23 = features_16_conv_1.__mul__(sigmoid_21) features_16_conv_3 = self.features_16_conv_3(mul_23) features_16_conv_4 = self.features_16_conv_4(features_16_conv_3) sigmoid_22 = torch.sigmoid(features_16_conv_4) mul_24 = features_16_conv_4.__mul__(sigmoid_22) size_3 = mul_24.size() features_16_conv_6_avg_pool = self.features_16_conv_6_avg_pool(mul_24) view_5 = features_16_conv_6_avg_pool.view(size_3[0], size_3[1]) features_16_conv_6_fc_0 = self.features_16_conv_6_fc_0(view_5) sigmoid_23 = torch.sigmoid(features_16_conv_6_fc_0) mul_25 = features_16_conv_6_fc_0.__mul__(sigmoid_23) features_16_conv_6_fc_2 = self.features_16_conv_6_fc_2(mul_25) features_16_conv_6_fc_3 = self.features_16_conv_6_fc_3(features_16_conv_6_fc_2) view_6 = features_16_conv_6_fc_3.view(size_3[0], size_3[1], 1, 1) mul_26 = mul_24.__mul__(view_6) features_16_conv_7 = self.features_16_conv_7(mul_26) features_16_conv_8 = self.features_16_conv_8(features_16_conv_7) add_13 = add_12.__add__(features_16_conv_8) features_17_conv_0 = self.features_17_conv_0(add_13) features_17_conv_1 = self.features_17_conv_1(features_17_conv_0) sigmoid_24 = torch.sigmoid(features_17_conv_1) mul_27 = features_17_conv_1.__mul__(sigmoid_24) features_17_conv_3 = self.features_17_conv_3(mul_27) features_17_conv_4 = self.features_17_conv_4(features_17_conv_3) sigmoid_25 = torch.sigmoid(features_17_conv_4) mul_28 = features_17_conv_4.__mul__(sigmoid_25) size_4 = mul_28.size() features_17_conv_6_avg_pool = self.features_17_conv_6_avg_pool(mul_28) view_7 = features_17_conv_6_avg_pool.view(size_4[0], size_4[1]) features_17_conv_6_fc_0 = self.features_17_conv_6_fc_0(view_7) sigmoid_26 = torch.sigmoid(features_17_conv_6_fc_0) mul_29 = features_17_conv_6_fc_0.__mul__(sigmoid_26) features_17_conv_6_fc_2 = self.features_17_conv_6_fc_2(mul_29) features_17_conv_6_fc_3 = self.features_17_conv_6_fc_3(features_17_conv_6_fc_2) view_8 = features_17_conv_6_fc_3.view(size_4[0], size_4[1], 1, 1) mul_30 = mul_28.__mul__(view_8) features_17_conv_7 = self.features_17_conv_7(mul_30) features_17_conv_8 = self.features_17_conv_8(features_17_conv_7) add_14 = add_13.__add__(features_17_conv_8) features_18_conv_0 = self.features_18_conv_0(add_14) features_18_conv_1 = self.features_18_conv_1(features_18_conv_0) sigmoid_27 = torch.sigmoid(features_18_conv_1) mul_31 = features_18_conv_1.__mul__(sigmoid_27) features_18_conv_3 = self.features_18_conv_3(mul_31) features_18_conv_4 = self.features_18_conv_4(features_18_conv_3) sigmoid_28 = torch.sigmoid(features_18_conv_4) mul_32 = features_18_conv_4.__mul__(sigmoid_28) size_5 = mul_32.size() features_18_conv_6_avg_pool = self.features_18_conv_6_avg_pool(mul_32) view_9 = features_18_conv_6_avg_pool.view(size_5[0], size_5[1]) features_18_conv_6_fc_0 = self.features_18_conv_6_fc_0(view_9) sigmoid_29 = torch.sigmoid(features_18_conv_6_fc_0) mul_33 = features_18_conv_6_fc_0.__mul__(sigmoid_29) features_18_conv_6_fc_2 = self.features_18_conv_6_fc_2(mul_33) features_18_conv_6_fc_3 = self.features_18_conv_6_fc_3(features_18_conv_6_fc_2) view_10 = features_18_conv_6_fc_3.view(size_5[0], size_5[1], 1, 1) mul_34 = mul_32.__mul__(view_10) features_18_conv_7 = self.features_18_conv_7(mul_34) features_18_conv_8 = self.features_18_conv_8(features_18_conv_7) add_15 = add_14.__add__(features_18_conv_8) features_19_conv_0 = self.features_19_conv_0(add_15) features_19_conv_1 = self.features_19_conv_1(features_19_conv_0) sigmoid_30 = torch.sigmoid(features_19_conv_1) mul_35 = features_19_conv_1.__mul__(sigmoid_30) features_19_conv_3 = self.features_19_conv_3(mul_35) features_19_conv_4 = self.features_19_conv_4(features_19_conv_3) sigmoid_31 = torch.sigmoid(features_19_conv_4) mul_36 = features_19_conv_4.__mul__(sigmoid_31) size_6 = mul_36.size() features_19_conv_6_avg_pool = self.features_19_conv_6_avg_pool(mul_36) view_11 = features_19_conv_6_avg_pool.view(size_6[0], size_6[1]) features_19_conv_6_fc_0 = self.features_19_conv_6_fc_0(view_11) sigmoid_32 = torch.sigmoid(features_19_conv_6_fc_0) mul_37 = features_19_conv_6_fc_0.__mul__(sigmoid_32) features_19_conv_6_fc_2 = self.features_19_conv_6_fc_2(mul_37) features_19_conv_6_fc_3 = self.features_19_conv_6_fc_3(features_19_conv_6_fc_2) view_12 = features_19_conv_6_fc_3.view(size_6[0], size_6[1], 1, 1) mul_38 = mul_36.__mul__(view_12) features_19_conv_7 = self.features_19_conv_7(mul_38) features_19_conv_8 = self.features_19_conv_8(features_19_conv_7) add_16 = add_15.__add__(features_19_conv_8) features_20_conv_0 = self.features_20_conv_0(add_16) features_20_conv_1 = self.features_20_conv_1(features_20_conv_0) sigmoid_33 = torch.sigmoid(features_20_conv_1) mul_39 = features_20_conv_1.__mul__(sigmoid_33) features_20_conv_3 = self.features_20_conv_3(mul_39) features_20_conv_4 = self.features_20_conv_4(features_20_conv_3) sigmoid_34 = torch.sigmoid(features_20_conv_4) mul_40 = features_20_conv_4.__mul__(sigmoid_34) size_7 = mul_40.size() features_20_conv_6_avg_pool = self.features_20_conv_6_avg_pool(mul_40) view_13 = features_20_conv_6_avg_pool.view(size_7[0], size_7[1]) features_20_conv_6_fc_0 = self.features_20_conv_6_fc_0(view_13) sigmoid_35 = torch.sigmoid(features_20_conv_6_fc_0) mul_41 = features_20_conv_6_fc_0.__mul__(sigmoid_35) features_20_conv_6_fc_2 = self.features_20_conv_6_fc_2(mul_41) features_20_conv_6_fc_3 = self.features_20_conv_6_fc_3(features_20_conv_6_fc_2) view_14 = features_20_conv_6_fc_3.view(size_7[0], size_7[1], 1, 1) mul_42 = mul_40.__mul__(view_14) features_20_conv_7 = self.features_20_conv_7(mul_42) features_20_conv_8 = self.features_20_conv_8(features_20_conv_7) add_17 = add_16.__add__(features_20_conv_8) features_21_conv_0 = self.features_21_conv_0(add_17) features_21_conv_1 = self.features_21_conv_1(features_21_conv_0) sigmoid_36 = torch.sigmoid(features_21_conv_1) mul_43 = features_21_conv_1.__mul__(sigmoid_36) features_21_conv_3 = self.features_21_conv_3(mul_43) features_21_conv_4 = self.features_21_conv_4(features_21_conv_3) sigmoid_37 = torch.sigmoid(features_21_conv_4) mul_44 = features_21_conv_4.__mul__(sigmoid_37) size_8 = mul_44.size() features_21_conv_6_avg_pool = self.features_21_conv_6_avg_pool(mul_44) view_15 = features_21_conv_6_avg_pool.view(size_8[0], size_8[1]) features_21_conv_6_fc_0 = self.features_21_conv_6_fc_0(view_15) sigmoid_38 = torch.sigmoid(features_21_conv_6_fc_0) mul_45 = features_21_conv_6_fc_0.__mul__(sigmoid_38) features_21_conv_6_fc_2 = self.features_21_conv_6_fc_2(mul_45) features_21_conv_6_fc_3 = self.features_21_conv_6_fc_3(features_21_conv_6_fc_2) view_16 = features_21_conv_6_fc_3.view(size_8[0], size_8[1], 1, 1) mul_46 = mul_44.__mul__(view_16) features_21_conv_7 = self.features_21_conv_7(mul_46) features_21_conv_8 = self.features_21_conv_8(features_21_conv_7) features_22_conv_0 = self.features_22_conv_0(features_21_conv_8) features_22_conv_1 = self.features_22_conv_1(features_22_conv_0) sigmoid_39 = torch.sigmoid(features_22_conv_1) mul_47 = features_22_conv_1.__mul__(sigmoid_39) features_22_conv_3 = self.features_22_conv_3(mul_47) features_22_conv_4 = self.features_22_conv_4(features_22_conv_3) sigmoid_40 = torch.sigmoid(features_22_conv_4) mul_48 = features_22_conv_4.__mul__(sigmoid_40) size_9 = mul_48.size() features_22_conv_6_avg_pool = self.features_22_conv_6_avg_pool(mul_48) view_17 = features_22_conv_6_avg_pool.view(size_9[0], size_9[1]) features_22_conv_6_fc_0 = self.features_22_conv_6_fc_0(view_17) sigmoid_41 = torch.sigmoid(features_22_conv_6_fc_0) mul_49 = features_22_conv_6_fc_0.__mul__(sigmoid_41) features_22_conv_6_fc_2 = self.features_22_conv_6_fc_2(mul_49) features_22_conv_6_fc_3 = self.features_22_conv_6_fc_3(features_22_conv_6_fc_2) view_18 = features_22_conv_6_fc_3.view(size_9[0], size_9[1], 1, 1) mul_50 = mul_48.__mul__(view_18) features_22_conv_7 = self.features_22_conv_7(mul_50) features_22_conv_8 = self.features_22_conv_8(features_22_conv_7) add_18 = features_21_conv_8.__add__(features_22_conv_8) features_23_conv_0 = self.features_23_conv_0(add_18) features_23_conv_1 = self.features_23_conv_1(features_23_conv_0) sigmoid_42 = torch.sigmoid(features_23_conv_1) mul_51 = features_23_conv_1.__mul__(sigmoid_42) features_23_conv_3 = self.features_23_conv_3(mul_51) features_23_conv_4 = self.features_23_conv_4(features_23_conv_3) sigmoid_43 = torch.sigmoid(features_23_conv_4) mul_52 = features_23_conv_4.__mul__(sigmoid_43) size_10 = mul_52.size() features_23_conv_6_avg_pool = self.features_23_conv_6_avg_pool(mul_52) view_19 = features_23_conv_6_avg_pool.view(size_10[0], size_10[1]) features_23_conv_6_fc_0 = self.features_23_conv_6_fc_0(view_19) sigmoid_44 = torch.sigmoid(features_23_conv_6_fc_0) mul_53 = features_23_conv_6_fc_0.__mul__(sigmoid_44) features_23_conv_6_fc_2 = self.features_23_conv_6_fc_2(mul_53) features_23_conv_6_fc_3 = self.features_23_conv_6_fc_3(features_23_conv_6_fc_2) view_20 = features_23_conv_6_fc_3.view(size_10[0], size_10[1], 1, 1) mul_54 = mul_52.__mul__(view_20) features_23_conv_7 = self.features_23_conv_7(mul_54) features_23_conv_8 = self.features_23_conv_8(features_23_conv_7) add_19 = add_18.__add__(features_23_conv_8) features_24_conv_0 = self.features_24_conv_0(add_19) features_24_conv_1 = self.features_24_conv_1(features_24_conv_0) sigmoid_45 = torch.sigmoid(features_24_conv_1) mul_55 = features_24_conv_1.__mul__(sigmoid_45) features_24_conv_3 = self.features_24_conv_3(mul_55) features_24_conv_4 = self.features_24_conv_4(features_24_conv_3) sigmoid_46 = torch.sigmoid(features_24_conv_4) mul_56 = features_24_conv_4.__mul__(sigmoid_46) size_11 = mul_56.size() features_24_conv_6_avg_pool = self.features_24_conv_6_avg_pool(mul_56) view_21 = features_24_conv_6_avg_pool.view(size_11[0], size_11[1]) features_24_conv_6_fc_0 = self.features_24_conv_6_fc_0(view_21) sigmoid_47 = torch.sigmoid(features_24_conv_6_fc_0) mul_57 = features_24_conv_6_fc_0.__mul__(sigmoid_47) features_24_conv_6_fc_2 = self.features_24_conv_6_fc_2(mul_57) features_24_conv_6_fc_3 = self.features_24_conv_6_fc_3(features_24_conv_6_fc_2) view_22 = features_24_conv_6_fc_3.view(size_11[0], size_11[1], 1, 1) mul_58 = mul_56.__mul__(view_22) features_24_conv_7 = self.features_24_conv_7(mul_58) features_24_conv_8 = self.features_24_conv_8(features_24_conv_7) add_20 = add_19.__add__(features_24_conv_8) features_25_conv_0 = self.features_25_conv_0(add_20) features_25_conv_1 = self.features_25_conv_1(features_25_conv_0) sigmoid_48 = torch.sigmoid(features_25_conv_1) mul_59 = features_25_conv_1.__mul__(sigmoid_48) features_25_conv_3 = self.features_25_conv_3(mul_59) features_25_conv_4 = self.features_25_conv_4(features_25_conv_3) sigmoid_49 = torch.sigmoid(features_25_conv_4) mul_60 = features_25_conv_4.__mul__(sigmoid_49) size_12 = mul_60.size() features_25_conv_6_avg_pool = self.features_25_conv_6_avg_pool(mul_60) view_23 = features_25_conv_6_avg_pool.view(size_12[0], size_12[1]) features_25_conv_6_fc_0 = self.features_25_conv_6_fc_0(view_23) sigmoid_50 = torch.sigmoid(features_25_conv_6_fc_0) mul_61 = features_25_conv_6_fc_0.__mul__(sigmoid_50) features_25_conv_6_fc_2 = self.features_25_conv_6_fc_2(mul_61) features_25_conv_6_fc_3 = self.features_25_conv_6_fc_3(features_25_conv_6_fc_2) view_24 = features_25_conv_6_fc_3.view(size_12[0], size_12[1], 1, 1) mul_62 = mul_60.__mul__(view_24) features_25_conv_7 = self.features_25_conv_7(mul_62) features_25_conv_8 = self.features_25_conv_8(features_25_conv_7) add_21 = add_20.__add__(features_25_conv_8) features_26_conv_0 = self.features_26_conv_0(add_21) features_26_conv_1 = self.features_26_conv_1(features_26_conv_0) sigmoid_51 = torch.sigmoid(features_26_conv_1) mul_63 = features_26_conv_1.__mul__(sigmoid_51) features_26_conv_3 = self.features_26_conv_3(mul_63) features_26_conv_4 = self.features_26_conv_4(features_26_conv_3) sigmoid_52 = torch.sigmoid(features_26_conv_4) mul_64 = features_26_conv_4.__mul__(sigmoid_52) size_13 = mul_64.size() features_26_conv_6_avg_pool = self.features_26_conv_6_avg_pool(mul_64) view_25 = features_26_conv_6_avg_pool.view(size_13[0], size_13[1]) features_26_conv_6_fc_0 = self.features_26_conv_6_fc_0(view_25) sigmoid_53 = torch.sigmoid(features_26_conv_6_fc_0) mul_65 = features_26_conv_6_fc_0.__mul__(sigmoid_53) features_26_conv_6_fc_2 = self.features_26_conv_6_fc_2(mul_65) features_26_conv_6_fc_3 = self.features_26_conv_6_fc_3(features_26_conv_6_fc_2) view_26 = features_26_conv_6_fc_3.view(size_13[0], size_13[1], 1, 1) mul_66 = mul_64.__mul__(view_26) features_26_conv_7 = self.features_26_conv_7(mul_66) features_26_conv_8 = self.features_26_conv_8(features_26_conv_7) add_22 = add_21.__add__(features_26_conv_8) features_27_conv_0 = self.features_27_conv_0(add_22) features_27_conv_1 = self.features_27_conv_1(features_27_conv_0) sigmoid_54 = torch.sigmoid(features_27_conv_1) mul_67 = features_27_conv_1.__mul__(sigmoid_54) features_27_conv_3 = self.features_27_conv_3(mul_67) features_27_conv_4 = self.features_27_conv_4(features_27_conv_3) sigmoid_55 = torch.sigmoid(features_27_conv_4) mul_68 = features_27_conv_4.__mul__(sigmoid_55) size_14 = mul_68.size() features_27_conv_6_avg_pool = self.features_27_conv_6_avg_pool(mul_68) view_27 = features_27_conv_6_avg_pool.view(size_14[0], size_14[1]) features_27_conv_6_fc_0 = self.features_27_conv_6_fc_0(view_27) sigmoid_56 = torch.sigmoid(features_27_conv_6_fc_0) mul_69 = features_27_conv_6_fc_0.__mul__(sigmoid_56) features_27_conv_6_fc_2 = self.features_27_conv_6_fc_2(mul_69) features_27_conv_6_fc_3 = self.features_27_conv_6_fc_3(features_27_conv_6_fc_2) view_28 = features_27_conv_6_fc_3.view(size_14[0], size_14[1], 1, 1) mul_70 = mul_68.__mul__(view_28) features_27_conv_7 = self.features_27_conv_7(mul_70) features_27_conv_8 = self.features_27_conv_8(features_27_conv_7) add_23 = add_22.__add__(features_27_conv_8) features_28_conv_0 = self.features_28_conv_0(add_23) features_28_conv_1 = self.features_28_conv_1(features_28_conv_0) sigmoid_57 = torch.sigmoid(features_28_conv_1) mul_71 = features_28_conv_1.__mul__(sigmoid_57) features_28_conv_3 = self.features_28_conv_3(mul_71) features_28_conv_4 = self.features_28_conv_4(features_28_conv_3) sigmoid_58 = torch.sigmoid(features_28_conv_4) mul_72 = features_28_conv_4.__mul__(sigmoid_58) size_15 = mul_72.size() features_28_conv_6_avg_pool = self.features_28_conv_6_avg_pool(mul_72) view_29 = features_28_conv_6_avg_pool.view(size_15[0], size_15[1]) features_28_conv_6_fc_0 = self.features_28_conv_6_fc_0(view_29) sigmoid_59 = torch.sigmoid(features_28_conv_6_fc_0) mul_73 = features_28_conv_6_fc_0.__mul__(sigmoid_59) features_28_conv_6_fc_2 = self.features_28_conv_6_fc_2(mul_73) features_28_conv_6_fc_3 = self.features_28_conv_6_fc_3(features_28_conv_6_fc_2) view_30 = features_28_conv_6_fc_3.view(size_15[0], size_15[1], 1, 1) mul_74 = mul_72.__mul__(view_30) features_28_conv_7 = self.features_28_conv_7(mul_74) features_28_conv_8 = self.features_28_conv_8(features_28_conv_7) add_24 = add_23.__add__(features_28_conv_8) features_29_conv_0 = self.features_29_conv_0(add_24) features_29_conv_1 = self.features_29_conv_1(features_29_conv_0) sigmoid_60 = torch.sigmoid(features_29_conv_1) mul_75 = features_29_conv_1.__mul__(sigmoid_60) features_29_conv_3 = self.features_29_conv_3(mul_75) features_29_conv_4 = self.features_29_conv_4(features_29_conv_3) sigmoid_61 = torch.sigmoid(features_29_conv_4) mul_76 = features_29_conv_4.__mul__(sigmoid_61) size_16 = mul_76.size() features_29_conv_6_avg_pool = self.features_29_conv_6_avg_pool(mul_76) view_31 = features_29_conv_6_avg_pool.view(size_16[0], size_16[1]) features_29_conv_6_fc_0 = self.features_29_conv_6_fc_0(view_31) sigmoid_62 = torch.sigmoid(features_29_conv_6_fc_0) mul_77 = features_29_conv_6_fc_0.__mul__(sigmoid_62) features_29_conv_6_fc_2 = self.features_29_conv_6_fc_2(mul_77) features_29_conv_6_fc_3 = self.features_29_conv_6_fc_3(features_29_conv_6_fc_2) view_32 = features_29_conv_6_fc_3.view(size_16[0], size_16[1], 1, 1) mul_78 = mul_76.__mul__(view_32) features_29_conv_7 = self.features_29_conv_7(mul_78) features_29_conv_8 = self.features_29_conv_8(features_29_conv_7) add_25 = add_24.__add__(features_29_conv_8) features_30_conv_0 = self.features_30_conv_0(add_25) features_30_conv_1 = self.features_30_conv_1(features_30_conv_0) sigmoid_63 = torch.sigmoid(features_30_conv_1) mul_79 = features_30_conv_1.__mul__(sigmoid_63) features_30_conv_3 = self.features_30_conv_3(mul_79) features_30_conv_4 = self.features_30_conv_4(features_30_conv_3) sigmoid_64 = torch.sigmoid(features_30_conv_4) mul_80 = features_30_conv_4.__mul__(sigmoid_64) size_17 = mul_80.size() features_30_conv_6_avg_pool = self.features_30_conv_6_avg_pool(mul_80) view_33 = features_30_conv_6_avg_pool.view(size_17[0], size_17[1]) features_30_conv_6_fc_0 = self.features_30_conv_6_fc_0(view_33) sigmoid_65 = torch.sigmoid(features_30_conv_6_fc_0) mul_81 = features_30_conv_6_fc_0.__mul__(sigmoid_65) features_30_conv_6_fc_2 = self.features_30_conv_6_fc_2(mul_81) features_30_conv_6_fc_3 = self.features_30_conv_6_fc_3(features_30_conv_6_fc_2) view_34 = features_30_conv_6_fc_3.view(size_17[0], size_17[1], 1, 1) mul_82 = mul_80.__mul__(view_34) features_30_conv_7 = self.features_30_conv_7(mul_82) features_30_conv_8 = self.features_30_conv_8(features_30_conv_7) add_26 = add_25.__add__(features_30_conv_8) features_31_conv_0 = self.features_31_conv_0(add_26) features_31_conv_1 = self.features_31_conv_1(features_31_conv_0) sigmoid_66 = torch.sigmoid(features_31_conv_1) mul_83 = features_31_conv_1.__mul__(sigmoid_66) features_31_conv_3 = self.features_31_conv_3(mul_83) features_31_conv_4 = self.features_31_conv_4(features_31_conv_3) sigmoid_67 = torch.sigmoid(features_31_conv_4) mul_84 = features_31_conv_4.__mul__(sigmoid_67) size_18 = mul_84.size() features_31_conv_6_avg_pool = self.features_31_conv_6_avg_pool(mul_84) view_35 = features_31_conv_6_avg_pool.view(size_18[0], size_18[1]) features_31_conv_6_fc_0 = self.features_31_conv_6_fc_0(view_35) sigmoid_68 = torch.sigmoid(features_31_conv_6_fc_0) mul_85 = features_31_conv_6_fc_0.__mul__(sigmoid_68) features_31_conv_6_fc_2 = self.features_31_conv_6_fc_2(mul_85) features_31_conv_6_fc_3 = self.features_31_conv_6_fc_3(features_31_conv_6_fc_2) view_36 = features_31_conv_6_fc_3.view(size_18[0], size_18[1], 1, 1) mul_86 = mul_84.__mul__(view_36) features_31_conv_7 = self.features_31_conv_7(mul_86) features_31_conv_8 = self.features_31_conv_8(features_31_conv_7) add_27 = add_26.__add__(features_31_conv_8) features_32_conv_0 = self.features_32_conv_0(add_27) features_32_conv_1 = self.features_32_conv_1(features_32_conv_0) sigmoid_69 = torch.sigmoid(features_32_conv_1) mul_87 = features_32_conv_1.__mul__(sigmoid_69) features_32_conv_3 = self.features_32_conv_3(mul_87) features_32_conv_4 = self.features_32_conv_4(features_32_conv_3) sigmoid_70 = torch.sigmoid(features_32_conv_4) mul_88 = features_32_conv_4.__mul__(sigmoid_70) size_19 = mul_88.size() features_32_conv_6_avg_pool = self.features_32_conv_6_avg_pool(mul_88) view_37 = features_32_conv_6_avg_pool.view(size_19[0], size_19[1]) features_32_conv_6_fc_0 = self.features_32_conv_6_fc_0(view_37) sigmoid_71 = torch.sigmoid(features_32_conv_6_fc_0) mul_89 = features_32_conv_6_fc_0.__mul__(sigmoid_71) features_32_conv_6_fc_2 = self.features_32_conv_6_fc_2(mul_89) features_32_conv_6_fc_3 = self.features_32_conv_6_fc_3(features_32_conv_6_fc_2) view_38 = features_32_conv_6_fc_3.view(size_19[0], size_19[1], 1, 1) mul_90 = mul_88.__mul__(view_38) features_32_conv_7 = self.features_32_conv_7(mul_90) features_32_conv_8 = self.features_32_conv_8(features_32_conv_7) add_28 = add_27.__add__(features_32_conv_8) features_33_conv_0 = self.features_33_conv_0(add_28) features_33_conv_1 = self.features_33_conv_1(features_33_conv_0) sigmoid_72 = torch.sigmoid(features_33_conv_1) mul_91 = features_33_conv_1.__mul__(sigmoid_72) features_33_conv_3 = self.features_33_conv_3(mul_91) features_33_conv_4 = self.features_33_conv_4(features_33_conv_3) sigmoid_73 = torch.sigmoid(features_33_conv_4) mul_92 = features_33_conv_4.__mul__(sigmoid_73) size_20 = mul_92.size() features_33_conv_6_avg_pool = self.features_33_conv_6_avg_pool(mul_92) view_39 = features_33_conv_6_avg_pool.view(size_20[0], size_20[1]) features_33_conv_6_fc_0 = self.features_33_conv_6_fc_0(view_39) sigmoid_74 = torch.sigmoid(features_33_conv_6_fc_0) mul_93 = features_33_conv_6_fc_0.__mul__(sigmoid_74) features_33_conv_6_fc_2 = self.features_33_conv_6_fc_2(mul_93) features_33_conv_6_fc_3 = self.features_33_conv_6_fc_3(features_33_conv_6_fc_2) view_40 = features_33_conv_6_fc_3.view(size_20[0], size_20[1], 1, 1) mul_94 = mul_92.__mul__(view_40) features_33_conv_7 = self.features_33_conv_7(mul_94) features_33_conv_8 = self.features_33_conv_8(features_33_conv_7) add_29 = add_28.__add__(features_33_conv_8) features_34_conv_0 = self.features_34_conv_0(add_29) features_34_conv_1 = self.features_34_conv_1(features_34_conv_0) sigmoid_75 = torch.sigmoid(features_34_conv_1) mul_95 = features_34_conv_1.__mul__(sigmoid_75) features_34_conv_3 = self.features_34_conv_3(mul_95) features_34_conv_4 = self.features_34_conv_4(features_34_conv_3) sigmoid_76 = torch.sigmoid(features_34_conv_4) mul_96 = features_34_conv_4.__mul__(sigmoid_76) size_21 = mul_96.size() features_34_conv_6_avg_pool = self.features_34_conv_6_avg_pool(mul_96) view_41 = features_34_conv_6_avg_pool.view(size_21[0], size_21[1]) features_34_conv_6_fc_0 = self.features_34_conv_6_fc_0(view_41) sigmoid_77 = torch.sigmoid(features_34_conv_6_fc_0) mul_97 = features_34_conv_6_fc_0.__mul__(sigmoid_77) features_34_conv_6_fc_2 = self.features_34_conv_6_fc_2(mul_97) features_34_conv_6_fc_3 = self.features_34_conv_6_fc_3(features_34_conv_6_fc_2) view_42 = features_34_conv_6_fc_3.view(size_21[0], size_21[1], 1, 1) mul_98 = mul_96.__mul__(view_42) features_34_conv_7 = self.features_34_conv_7(mul_98) features_34_conv_8 = self.features_34_conv_8(features_34_conv_7) add_30 = add_29.__add__(features_34_conv_8) features_35_conv_0 = self.features_35_conv_0(add_30) features_35_conv_1 = self.features_35_conv_1(features_35_conv_0) sigmoid_78 = torch.sigmoid(features_35_conv_1) mul_99 = features_35_conv_1.__mul__(sigmoid_78) features_35_conv_3 = self.features_35_conv_3(mul_99) features_35_conv_4 = self.features_35_conv_4(features_35_conv_3) sigmoid_79 = torch.sigmoid(features_35_conv_4) mul_100 = features_35_conv_4.__mul__(sigmoid_79) size_22 = mul_100.size() features_35_conv_6_avg_pool = self.features_35_conv_6_avg_pool(mul_100) view_43 = features_35_conv_6_avg_pool.view(size_22[0], size_22[1]) features_35_conv_6_fc_0 = self.features_35_conv_6_fc_0(view_43) sigmoid_80 = torch.sigmoid(features_35_conv_6_fc_0) mul_101 = features_35_conv_6_fc_0.__mul__(sigmoid_80) features_35_conv_6_fc_2 = self.features_35_conv_6_fc_2(mul_101) features_35_conv_6_fc_3 = self.features_35_conv_6_fc_3(features_35_conv_6_fc_2) view_44 = features_35_conv_6_fc_3.view(size_22[0], size_22[1], 1, 1) mul_102 = mul_100.__mul__(view_44) features_35_conv_7 = self.features_35_conv_7(mul_102) features_35_conv_8 = self.features_35_conv_8(features_35_conv_7) features_36_conv_0 = self.features_36_conv_0(features_35_conv_8) features_36_conv_1 = self.features_36_conv_1(features_36_conv_0) sigmoid_81 = torch.sigmoid(features_36_conv_1) mul_103 = features_36_conv_1.__mul__(sigmoid_81) features_36_conv_3 = self.features_36_conv_3(mul_103) features_36_conv_4 = self.features_36_conv_4(features_36_conv_3) sigmoid_82 = torch.sigmoid(features_36_conv_4) mul_104 = features_36_conv_4.__mul__(sigmoid_82) size_23 = mul_104.size() features_36_conv_6_avg_pool = self.features_36_conv_6_avg_pool(mul_104) view_45 = features_36_conv_6_avg_pool.view(size_23[0], size_23[1]) features_36_conv_6_fc_0 = self.features_36_conv_6_fc_0(view_45) sigmoid_83 = torch.sigmoid(features_36_conv_6_fc_0) mul_105 = features_36_conv_6_fc_0.__mul__(sigmoid_83) features_36_conv_6_fc_2 = self.features_36_conv_6_fc_2(mul_105) features_36_conv_6_fc_3 = self.features_36_conv_6_fc_3(features_36_conv_6_fc_2) view_46 = features_36_conv_6_fc_3.view(size_23[0], size_23[1], 1, 1) mul_106 = mul_104.__mul__(view_46) features_36_conv_7 = self.features_36_conv_7(mul_106) features_36_conv_8 = self.features_36_conv_8(features_36_conv_7) add_31 = features_35_conv_8.__add__(features_36_conv_8) features_37_conv_0 = self.features_37_conv_0(add_31) features_37_conv_1 = self.features_37_conv_1(features_37_conv_0) sigmoid_84 = torch.sigmoid(features_37_conv_1) mul_107 = features_37_conv_1.__mul__(sigmoid_84) features_37_conv_3 = self.features_37_conv_3(mul_107) features_37_conv_4 = self.features_37_conv_4(features_37_conv_3) sigmoid_85 = torch.sigmoid(features_37_conv_4) mul_108 = features_37_conv_4.__mul__(sigmoid_85) size_24 = mul_108.size() features_37_conv_6_avg_pool = self.features_37_conv_6_avg_pool(mul_108) view_47 = features_37_conv_6_avg_pool.view(size_24[0], size_24[1]) features_37_conv_6_fc_0 = self.features_37_conv_6_fc_0(view_47) sigmoid_86 = torch.sigmoid(features_37_conv_6_fc_0) mul_109 = features_37_conv_6_fc_0.__mul__(sigmoid_86) features_37_conv_6_fc_2 = self.features_37_conv_6_fc_2(mul_109) features_37_conv_6_fc_3 = self.features_37_conv_6_fc_3(features_37_conv_6_fc_2) view_48 = features_37_conv_6_fc_3.view(size_24[0], size_24[1], 1, 1) mul_110 = mul_108.__mul__(view_48) features_37_conv_7 = self.features_37_conv_7(mul_110) features_37_conv_8 = self.features_37_conv_8(features_37_conv_7) add_32 = add_31.__add__(features_37_conv_8) features_38_conv_0 = self.features_38_conv_0(add_32) features_38_conv_1 = self.features_38_conv_1(features_38_conv_0) sigmoid_87 = torch.sigmoid(features_38_conv_1) mul_111 = features_38_conv_1.__mul__(sigmoid_87) features_38_conv_3 = self.features_38_conv_3(mul_111) features_38_conv_4 = self.features_38_conv_4(features_38_conv_3) sigmoid_88 = torch.sigmoid(features_38_conv_4) mul_112 = features_38_conv_4.__mul__(sigmoid_88) size_25 = mul_112.size() features_38_conv_6_avg_pool = self.features_38_conv_6_avg_pool(mul_112) view_49 = features_38_conv_6_avg_pool.view(size_25[0], size_25[1]) features_38_conv_6_fc_0 = self.features_38_conv_6_fc_0(view_49) sigmoid_89 = torch.sigmoid(features_38_conv_6_fc_0) mul_113 = features_38_conv_6_fc_0.__mul__(sigmoid_89) features_38_conv_6_fc_2 = self.features_38_conv_6_fc_2(mul_113) features_38_conv_6_fc_3 = self.features_38_conv_6_fc_3(features_38_conv_6_fc_2) view_50 = features_38_conv_6_fc_3.view(size_25[0], size_25[1], 1, 1) mul_114 = mul_112.__mul__(view_50) features_38_conv_7 = self.features_38_conv_7(mul_114) features_38_conv_8 = self.features_38_conv_8(features_38_conv_7) add_33 = add_32.__add__(features_38_conv_8) features_39_conv_0 = self.features_39_conv_0(add_33) features_39_conv_1 = self.features_39_conv_1(features_39_conv_0) sigmoid_90 = torch.sigmoid(features_39_conv_1) mul_115 = features_39_conv_1.__mul__(sigmoid_90) features_39_conv_3 = self.features_39_conv_3(mul_115) features_39_conv_4 = self.features_39_conv_4(features_39_conv_3) sigmoid_91 = torch.sigmoid(features_39_conv_4) mul_116 = features_39_conv_4.__mul__(sigmoid_91) size_26 = mul_116.size() features_39_conv_6_avg_pool = self.features_39_conv_6_avg_pool(mul_116) view_51 = features_39_conv_6_avg_pool.view(size_26[0], size_26[1]) features_39_conv_6_fc_0 = self.features_39_conv_6_fc_0(view_51) sigmoid_92 = torch.sigmoid(features_39_conv_6_fc_0) mul_117 = features_39_conv_6_fc_0.__mul__(sigmoid_92) features_39_conv_6_fc_2 = self.features_39_conv_6_fc_2(mul_117) features_39_conv_6_fc_3 = self.features_39_conv_6_fc_3(features_39_conv_6_fc_2) view_52 = features_39_conv_6_fc_3.view(size_26[0], size_26[1], 1, 1) mul_118 = mul_116.__mul__(view_52) features_39_conv_7 = self.features_39_conv_7(mul_118) features_39_conv_8 = self.features_39_conv_8(features_39_conv_7) add_34 = add_33.__add__(features_39_conv_8) features_40_conv_0 = self.features_40_conv_0(add_34) features_40_conv_1 = self.features_40_conv_1(features_40_conv_0) sigmoid_93 = torch.sigmoid(features_40_conv_1) mul_119 = features_40_conv_1.__mul__(sigmoid_93) features_40_conv_3 = self.features_40_conv_3(mul_119) features_40_conv_4 = self.features_40_conv_4(features_40_conv_3) sigmoid_94 = torch.sigmoid(features_40_conv_4) mul_120 = features_40_conv_4.__mul__(sigmoid_94) size_27 = mul_120.size() features_40_conv_6_avg_pool = self.features_40_conv_6_avg_pool(mul_120) view_53 = features_40_conv_6_avg_pool.view(size_27[0], size_27[1]) features_40_conv_6_fc_0 = self.features_40_conv_6_fc_0(view_53) sigmoid_95 = torch.sigmoid(features_40_conv_6_fc_0) mul_121 = features_40_conv_6_fc_0.__mul__(sigmoid_95) features_40_conv_6_fc_2 = self.features_40_conv_6_fc_2(mul_121) features_40_conv_6_fc_3 = self.features_40_conv_6_fc_3(features_40_conv_6_fc_2) view_54 = features_40_conv_6_fc_3.view(size_27[0], size_27[1], 1, 1) mul_122 = mul_120.__mul__(view_54) features_40_conv_7 = self.features_40_conv_7(mul_122) features_40_conv_8 = self.features_40_conv_8(features_40_conv_7) add_35 = add_34.__add__(features_40_conv_8) features_41_conv_0 = self.features_41_conv_0(add_35) features_41_conv_1 = self.features_41_conv_1(features_41_conv_0) sigmoid_96 = torch.sigmoid(features_41_conv_1) mul_123 = features_41_conv_1.__mul__(sigmoid_96) features_41_conv_3 = self.features_41_conv_3(mul_123) features_41_conv_4 = self.features_41_conv_4(features_41_conv_3) sigmoid_97 = torch.sigmoid(features_41_conv_4) mul_124 = features_41_conv_4.__mul__(sigmoid_97) size_28 = mul_124.size() features_41_conv_6_avg_pool = self.features_41_conv_6_avg_pool(mul_124) view_55 = features_41_conv_6_avg_pool.view(size_28[0], size_28[1]) features_41_conv_6_fc_0 = self.features_41_conv_6_fc_0(view_55) sigmoid_98 = torch.sigmoid(features_41_conv_6_fc_0) mul_125 = features_41_conv_6_fc_0.__mul__(sigmoid_98) features_41_conv_6_fc_2 = self.features_41_conv_6_fc_2(mul_125) features_41_conv_6_fc_3 = self.features_41_conv_6_fc_3(features_41_conv_6_fc_2) view_56 = features_41_conv_6_fc_3.view(size_28[0], size_28[1], 1, 1) mul_126 = mul_124.__mul__(view_56) features_41_conv_7 = self.features_41_conv_7(mul_126) features_41_conv_8 = self.features_41_conv_8(features_41_conv_7) add_36 = add_35.__add__(features_41_conv_8) features_42_conv_0 = self.features_42_conv_0(add_36) features_42_conv_1 = self.features_42_conv_1(features_42_conv_0) sigmoid_99 = torch.sigmoid(features_42_conv_1) mul_127 = features_42_conv_1.__mul__(sigmoid_99) features_42_conv_3 = self.features_42_conv_3(mul_127) features_42_conv_4 = self.features_42_conv_4(features_42_conv_3) sigmoid_100 = torch.sigmoid(features_42_conv_4) mul_128 = features_42_conv_4.__mul__(sigmoid_100) size_29 = mul_128.size() features_42_conv_6_avg_pool = self.features_42_conv_6_avg_pool(mul_128) view_57 = features_42_conv_6_avg_pool.view(size_29[0], size_29[1]) features_42_conv_6_fc_0 = self.features_42_conv_6_fc_0(view_57) sigmoid_101 = torch.sigmoid(features_42_conv_6_fc_0) mul_129 = features_42_conv_6_fc_0.__mul__(sigmoid_101) features_42_conv_6_fc_2 = self.features_42_conv_6_fc_2(mul_129) features_42_conv_6_fc_3 = self.features_42_conv_6_fc_3(features_42_conv_6_fc_2) view_58 = features_42_conv_6_fc_3.view(size_29[0], size_29[1], 1, 1) mul_130 = mul_128.__mul__(view_58) features_42_conv_7 = self.features_42_conv_7(mul_130) features_42_conv_8 = self.features_42_conv_8(features_42_conv_7) add_37 = add_36.__add__(features_42_conv_8) features_43_conv_0 = self.features_43_conv_0(add_37) features_43_conv_1 = self.features_43_conv_1(features_43_conv_0) sigmoid_102 = torch.sigmoid(features_43_conv_1) mul_131 = features_43_conv_1.__mul__(sigmoid_102) features_43_conv_3 = self.features_43_conv_3(mul_131) features_43_conv_4 = self.features_43_conv_4(features_43_conv_3) sigmoid_103 = torch.sigmoid(features_43_conv_4) mul_132 = features_43_conv_4.__mul__(sigmoid_103) size_30 = mul_132.size() features_43_conv_6_avg_pool = self.features_43_conv_6_avg_pool(mul_132) view_59 = features_43_conv_6_avg_pool.view(size_30[0], size_30[1]) features_43_conv_6_fc_0 = self.features_43_conv_6_fc_0(view_59) sigmoid_104 = torch.sigmoid(features_43_conv_6_fc_0) mul_133 = features_43_conv_6_fc_0.__mul__(sigmoid_104) features_43_conv_6_fc_2 = self.features_43_conv_6_fc_2(mul_133) features_43_conv_6_fc_3 = self.features_43_conv_6_fc_3(features_43_conv_6_fc_2) view_60 = features_43_conv_6_fc_3.view(size_30[0], size_30[1], 1, 1) mul_134 = mul_132.__mul__(view_60) features_43_conv_7 = self.features_43_conv_7(mul_134) features_43_conv_8 = self.features_43_conv_8(features_43_conv_7) add_38 = add_37.__add__(features_43_conv_8) features_44_conv_0 = self.features_44_conv_0(add_38) features_44_conv_1 = self.features_44_conv_1(features_44_conv_0) sigmoid_105 = torch.sigmoid(features_44_conv_1) mul_135 = features_44_conv_1.__mul__(sigmoid_105) features_44_conv_3 = self.features_44_conv_3(mul_135) features_44_conv_4 = self.features_44_conv_4(features_44_conv_3) sigmoid_106 = torch.sigmoid(features_44_conv_4) mul_136 = features_44_conv_4.__mul__(sigmoid_106) size_31 = mul_136.size() features_44_conv_6_avg_pool = self.features_44_conv_6_avg_pool(mul_136) view_61 = features_44_conv_6_avg_pool.view(size_31[0], size_31[1]) features_44_conv_6_fc_0 = self.features_44_conv_6_fc_0(view_61) sigmoid_107 = torch.sigmoid(features_44_conv_6_fc_0) mul_137 = features_44_conv_6_fc_0.__mul__(sigmoid_107) features_44_conv_6_fc_2 = self.features_44_conv_6_fc_2(mul_137) features_44_conv_6_fc_3 = self.features_44_conv_6_fc_3(features_44_conv_6_fc_2) view_62 = features_44_conv_6_fc_3.view(size_31[0], size_31[1], 1, 1) mul_138 = mul_136.__mul__(view_62) features_44_conv_7 = self.features_44_conv_7(mul_138) features_44_conv_8 = self.features_44_conv_8(features_44_conv_7) add_39 = add_38.__add__(features_44_conv_8) features_45_conv_0 = self.features_45_conv_0(add_39) features_45_conv_1 = self.features_45_conv_1(features_45_conv_0) sigmoid_108 = torch.sigmoid(features_45_conv_1) mul_139 = features_45_conv_1.__mul__(sigmoid_108) features_45_conv_3 = self.features_45_conv_3(mul_139) features_45_conv_4 = self.features_45_conv_4(features_45_conv_3) sigmoid_109 = torch.sigmoid(features_45_conv_4) mul_140 = features_45_conv_4.__mul__(sigmoid_109) size_32 = mul_140.size() features_45_conv_6_avg_pool = self.features_45_conv_6_avg_pool(mul_140) view_63 = features_45_conv_6_avg_pool.view(size_32[0], size_32[1]) features_45_conv_6_fc_0 = self.features_45_conv_6_fc_0(view_63) sigmoid_110 = torch.sigmoid(features_45_conv_6_fc_0) mul_141 = features_45_conv_6_fc_0.__mul__(sigmoid_110) features_45_conv_6_fc_2 = self.features_45_conv_6_fc_2(mul_141) features_45_conv_6_fc_3 = self.features_45_conv_6_fc_3(features_45_conv_6_fc_2) view_64 = features_45_conv_6_fc_3.view(size_32[0], size_32[1], 1, 1) mul_142 = mul_140.__mul__(view_64) features_45_conv_7 = self.features_45_conv_7(mul_142) features_45_conv_8 = self.features_45_conv_8(features_45_conv_7) add_40 = add_39.__add__(features_45_conv_8) features_46_conv_0 = self.features_46_conv_0(add_40) features_46_conv_1 = self.features_46_conv_1(features_46_conv_0) sigmoid_111 = torch.sigmoid(features_46_conv_1) mul_143 = features_46_conv_1.__mul__(sigmoid_111) features_46_conv_3 = self.features_46_conv_3(mul_143) features_46_conv_4 = self.features_46_conv_4(features_46_conv_3) sigmoid_112 = torch.sigmoid(features_46_conv_4) mul_144 = features_46_conv_4.__mul__(sigmoid_112) size_33 = mul_144.size() features_46_conv_6_avg_pool = self.features_46_conv_6_avg_pool(mul_144) view_65 = features_46_conv_6_avg_pool.view(size_33[0], size_33[1]) features_46_conv_6_fc_0 = self.features_46_conv_6_fc_0(view_65) sigmoid_113 = torch.sigmoid(features_46_conv_6_fc_0) mul_145 = features_46_conv_6_fc_0.__mul__(sigmoid_113) features_46_conv_6_fc_2 = self.features_46_conv_6_fc_2(mul_145) features_46_conv_6_fc_3 = self.features_46_conv_6_fc_3(features_46_conv_6_fc_2) view_66 = features_46_conv_6_fc_3.view(size_33[0], size_33[1], 1, 1) mul_146 = mul_144.__mul__(view_66) features_46_conv_7 = self.features_46_conv_7(mul_146) features_46_conv_8 = self.features_46_conv_8(features_46_conv_7) add_41 = add_40.__add__(features_46_conv_8) features_47_conv_0 = self.features_47_conv_0(add_41) features_47_conv_1 = self.features_47_conv_1(features_47_conv_0) sigmoid_114 = torch.sigmoid(features_47_conv_1) mul_147 = features_47_conv_1.__mul__(sigmoid_114) features_47_conv_3 = self.features_47_conv_3(mul_147) features_47_conv_4 = self.features_47_conv_4(features_47_conv_3) sigmoid_115 = torch.sigmoid(features_47_conv_4) mul_148 = features_47_conv_4.__mul__(sigmoid_115) size_34 = mul_148.size() features_47_conv_6_avg_pool = self.features_47_conv_6_avg_pool(mul_148) view_67 = features_47_conv_6_avg_pool.view(size_34[0], size_34[1]) features_47_conv_6_fc_0 = self.features_47_conv_6_fc_0(view_67) sigmoid_116 = torch.sigmoid(features_47_conv_6_fc_0) mul_149 = features_47_conv_6_fc_0.__mul__(sigmoid_116) features_47_conv_6_fc_2 = self.features_47_conv_6_fc_2(mul_149) features_47_conv_6_fc_3 = self.features_47_conv_6_fc_3(features_47_conv_6_fc_2) view_68 = features_47_conv_6_fc_3.view(size_34[0], size_34[1], 1, 1) mul_150 = mul_148.__mul__(view_68) features_47_conv_7 = self.features_47_conv_7(mul_150) features_47_conv_8 = self.features_47_conv_8(features_47_conv_7) add_42 = add_41.__add__(features_47_conv_8) features_48_conv_0 = self.features_48_conv_0(add_42) features_48_conv_1 = self.features_48_conv_1(features_48_conv_0) sigmoid_117 = torch.sigmoid(features_48_conv_1) mul_151 = features_48_conv_1.__mul__(sigmoid_117) features_48_conv_3 = self.features_48_conv_3(mul_151) features_48_conv_4 = self.features_48_conv_4(features_48_conv_3) sigmoid_118 = torch.sigmoid(features_48_conv_4) mul_152 = features_48_conv_4.__mul__(sigmoid_118) size_35 = mul_152.size() features_48_conv_6_avg_pool = self.features_48_conv_6_avg_pool(mul_152) view_69 = features_48_conv_6_avg_pool.view(size_35[0], size_35[1]) features_48_conv_6_fc_0 = self.features_48_conv_6_fc_0(view_69) sigmoid_119 = torch.sigmoid(features_48_conv_6_fc_0) mul_153 = features_48_conv_6_fc_0.__mul__(sigmoid_119) features_48_conv_6_fc_2 = self.features_48_conv_6_fc_2(mul_153) features_48_conv_6_fc_3 = self.features_48_conv_6_fc_3(features_48_conv_6_fc_2) view_70 = features_48_conv_6_fc_3.view(size_35[0], size_35[1], 1, 1) mul_154 = mul_152.__mul__(view_70) features_48_conv_7 = self.features_48_conv_7(mul_154) features_48_conv_8 = self.features_48_conv_8(features_48_conv_7) add_43 = add_42.__add__(features_48_conv_8) features_49_conv_0 = self.features_49_conv_0(add_43) features_49_conv_1 = self.features_49_conv_1(features_49_conv_0) sigmoid_120 = torch.sigmoid(features_49_conv_1) mul_155 = features_49_conv_1.__mul__(sigmoid_120) features_49_conv_3 = self.features_49_conv_3(mul_155) features_49_conv_4 = self.features_49_conv_4(features_49_conv_3) sigmoid_121 = torch.sigmoid(features_49_conv_4) mul_156 = features_49_conv_4.__mul__(sigmoid_121) size_36 = mul_156.size() features_49_conv_6_avg_pool = self.features_49_conv_6_avg_pool(mul_156) view_71 = features_49_conv_6_avg_pool.view(size_36[0], size_36[1]) features_49_conv_6_fc_0 = self.features_49_conv_6_fc_0(view_71) sigmoid_122 = torch.sigmoid(features_49_conv_6_fc_0) mul_157 = features_49_conv_6_fc_0.__mul__(sigmoid_122) features_49_conv_6_fc_2 = self.features_49_conv_6_fc_2(mul_157) features_49_conv_6_fc_3 = self.features_49_conv_6_fc_3(features_49_conv_6_fc_2) view_72 = features_49_conv_6_fc_3.view(size_36[0], size_36[1], 1, 1) mul_158 = mul_156.__mul__(view_72) features_49_conv_7 = self.features_49_conv_7(mul_158) features_49_conv_8 = self.features_49_conv_8(features_49_conv_7) add_44 = add_43.__add__(features_49_conv_8) features_50_conv_0 = self.features_50_conv_0(add_44) features_50_conv_1 = self.features_50_conv_1(features_50_conv_0) sigmoid_123 = torch.sigmoid(features_50_conv_1) mul_159 = features_50_conv_1.__mul__(sigmoid_123) features_50_conv_3 = self.features_50_conv_3(mul_159) features_50_conv_4 = self.features_50_conv_4(features_50_conv_3) sigmoid_124 = torch.sigmoid(features_50_conv_4) mul_160 = features_50_conv_4.__mul__(sigmoid_124) size_37 = mul_160.size() features_50_conv_6_avg_pool = self.features_50_conv_6_avg_pool(mul_160) view_73 = features_50_conv_6_avg_pool.view(size_37[0], size_37[1]) features_50_conv_6_fc_0 = self.features_50_conv_6_fc_0(view_73) sigmoid_125 = torch.sigmoid(features_50_conv_6_fc_0) mul_161 = features_50_conv_6_fc_0.__mul__(sigmoid_125) features_50_conv_6_fc_2 = self.features_50_conv_6_fc_2(mul_161) features_50_conv_6_fc_3 = self.features_50_conv_6_fc_3(features_50_conv_6_fc_2) view_74 = features_50_conv_6_fc_3.view(size_37[0], size_37[1], 1, 1) mul_162 = mul_160.__mul__(view_74) features_50_conv_7 = self.features_50_conv_7(mul_162) features_50_conv_8 = self.features_50_conv_8(features_50_conv_7) add_45 = add_44.__add__(features_50_conv_8) features_51_conv_0 = self.features_51_conv_0(add_45) features_51_conv_1 = self.features_51_conv_1(features_51_conv_0) sigmoid_126 = torch.sigmoid(features_51_conv_1) mul_163 = features_51_conv_1.__mul__(sigmoid_126) features_51_conv_3 = self.features_51_conv_3(mul_163) features_51_conv_4 = self.features_51_conv_4(features_51_conv_3) sigmoid_127 = torch.sigmoid(features_51_conv_4) mul_164 = features_51_conv_4.__mul__(sigmoid_127) size_38 = mul_164.size() features_51_conv_6_avg_pool = self.features_51_conv_6_avg_pool(mul_164) view_75 = features_51_conv_6_avg_pool.view(size_38[0], size_38[1]) features_51_conv_6_fc_0 = self.features_51_conv_6_fc_0(view_75) sigmoid_128 = torch.sigmoid(features_51_conv_6_fc_0) mul_165 = features_51_conv_6_fc_0.__mul__(sigmoid_128) features_51_conv_6_fc_2 = self.features_51_conv_6_fc_2(mul_165) features_51_conv_6_fc_3 = self.features_51_conv_6_fc_3(features_51_conv_6_fc_2) view_76 = features_51_conv_6_fc_3.view(size_38[0], size_38[1], 1, 1) mul_166 = mul_164.__mul__(view_76) features_51_conv_7 = self.features_51_conv_7(mul_166) features_51_conv_8 = self.features_51_conv_8(features_51_conv_7) add_46 = add_45.__add__(features_51_conv_8) features_52_conv_0 = self.features_52_conv_0(add_46) features_52_conv_1 = self.features_52_conv_1(features_52_conv_0) sigmoid_129 = torch.sigmoid(features_52_conv_1) mul_167 = features_52_conv_1.__mul__(sigmoid_129) features_52_conv_3 = self.features_52_conv_3(mul_167) features_52_conv_4 = self.features_52_conv_4(features_52_conv_3) sigmoid_130 = torch.sigmoid(features_52_conv_4) mul_168 = features_52_conv_4.__mul__(sigmoid_130) size_39 = mul_168.size() features_52_conv_6_avg_pool = self.features_52_conv_6_avg_pool(mul_168) view_77 = features_52_conv_6_avg_pool.view(size_39[0], size_39[1]) features_52_conv_6_fc_0 = self.features_52_conv_6_fc_0(view_77) sigmoid_131 = torch.sigmoid(features_52_conv_6_fc_0) mul_169 = features_52_conv_6_fc_0.__mul__(sigmoid_131) features_52_conv_6_fc_2 = self.features_52_conv_6_fc_2(mul_169) features_52_conv_6_fc_3 = self.features_52_conv_6_fc_3(features_52_conv_6_fc_2) view_78 = features_52_conv_6_fc_3.view(size_39[0], size_39[1], 1, 1) mul_170 = mul_168.__mul__(view_78) features_52_conv_7 = self.features_52_conv_7(mul_170) features_52_conv_8 = self.features_52_conv_8(features_52_conv_7) add_47 = add_46.__add__(features_52_conv_8) features_53_conv_0 = self.features_53_conv_0(add_47) features_53_conv_1 = self.features_53_conv_1(features_53_conv_0) sigmoid_132 = torch.sigmoid(features_53_conv_1) mul_171 = features_53_conv_1.__mul__(sigmoid_132) features_53_conv_3 = self.features_53_conv_3(mul_171) features_53_conv_4 = self.features_53_conv_4(features_53_conv_3) sigmoid_133 = torch.sigmoid(features_53_conv_4) mul_172 = features_53_conv_4.__mul__(sigmoid_133) size_40 = mul_172.size() features_53_conv_6_avg_pool = self.features_53_conv_6_avg_pool(mul_172) view_79 = features_53_conv_6_avg_pool.view(size_40[0], size_40[1]) features_53_conv_6_fc_0 = self.features_53_conv_6_fc_0(view_79) sigmoid_134 = torch.sigmoid(features_53_conv_6_fc_0) mul_173 = features_53_conv_6_fc_0.__mul__(sigmoid_134) features_53_conv_6_fc_2 = self.features_53_conv_6_fc_2(mul_173) features_53_conv_6_fc_3 = self.features_53_conv_6_fc_3(features_53_conv_6_fc_2) view_80 = features_53_conv_6_fc_3.view(size_40[0], size_40[1], 1, 1) mul_174 = mul_172.__mul__(view_80) features_53_conv_7 = self.features_53_conv_7(mul_174) features_53_conv_8 = self.features_53_conv_8(features_53_conv_7) features_54_conv_0 = self.features_54_conv_0(features_53_conv_8) features_54_conv_1 = self.features_54_conv_1(features_54_conv_0) sigmoid_135 = torch.sigmoid(features_54_conv_1) mul_175 = features_54_conv_1.__mul__(sigmoid_135) features_54_conv_3 = self.features_54_conv_3(mul_175) features_54_conv_4 = self.features_54_conv_4(features_54_conv_3) sigmoid_136 = torch.sigmoid(features_54_conv_4) mul_176 = features_54_conv_4.__mul__(sigmoid_136) size_41 = mul_176.size() features_54_conv_6_avg_pool = self.features_54_conv_6_avg_pool(mul_176) view_81 = features_54_conv_6_avg_pool.view(size_41[0], size_41[1]) features_54_conv_6_fc_0 = self.features_54_conv_6_fc_0(view_81) sigmoid_137 = torch.sigmoid(features_54_conv_6_fc_0) mul_177 = features_54_conv_6_fc_0.__mul__(sigmoid_137) features_54_conv_6_fc_2 = self.features_54_conv_6_fc_2(mul_177) features_54_conv_6_fc_3 = self.features_54_conv_6_fc_3(features_54_conv_6_fc_2) view_82 = features_54_conv_6_fc_3.view(size_41[0], size_41[1], 1, 1) mul_178 = mul_176.__mul__(view_82) features_54_conv_7 = self.features_54_conv_7(mul_178) features_54_conv_8 = self.features_54_conv_8(features_54_conv_7) add_48 = features_53_conv_8.__add__(features_54_conv_8) features_55_conv_0 = self.features_55_conv_0(add_48) features_55_conv_1 = self.features_55_conv_1(features_55_conv_0) sigmoid_138 = torch.sigmoid(features_55_conv_1) mul_179 = features_55_conv_1.__mul__(sigmoid_138) features_55_conv_3 = self.features_55_conv_3(mul_179) features_55_conv_4 = self.features_55_conv_4(features_55_conv_3) sigmoid_139 = torch.sigmoid(features_55_conv_4) mul_180 = features_55_conv_4.__mul__(sigmoid_139) size_42 = mul_180.size() features_55_conv_6_avg_pool = self.features_55_conv_6_avg_pool(mul_180) view_83 = features_55_conv_6_avg_pool.view(size_42[0], size_42[1]) features_55_conv_6_fc_0 = self.features_55_conv_6_fc_0(view_83) sigmoid_140 = torch.sigmoid(features_55_conv_6_fc_0) mul_181 = features_55_conv_6_fc_0.__mul__(sigmoid_140) features_55_conv_6_fc_2 = self.features_55_conv_6_fc_2(mul_181) features_55_conv_6_fc_3 = self.features_55_conv_6_fc_3(features_55_conv_6_fc_2) view_84 = features_55_conv_6_fc_3.view(size_42[0], size_42[1], 1, 1) mul_182 = mul_180.__mul__(view_84) features_55_conv_7 = self.features_55_conv_7(mul_182) features_55_conv_8 = self.features_55_conv_8(features_55_conv_7) add_49 = add_48.__add__(features_55_conv_8) features_56_conv_0 = self.features_56_conv_0(add_49) features_56_conv_1 = self.features_56_conv_1(features_56_conv_0) sigmoid_141 = torch.sigmoid(features_56_conv_1) mul_183 = features_56_conv_1.__mul__(sigmoid_141) features_56_conv_3 = self.features_56_conv_3(mul_183) features_56_conv_4 = self.features_56_conv_4(features_56_conv_3) sigmoid_142 = torch.sigmoid(features_56_conv_4) mul_184 = features_56_conv_4.__mul__(sigmoid_142) size_43 = mul_184.size() features_56_conv_6_avg_pool = self.features_56_conv_6_avg_pool(mul_184) view_85 = features_56_conv_6_avg_pool.view(size_43[0], size_43[1]) features_56_conv_6_fc_0 = self.features_56_conv_6_fc_0(view_85) sigmoid_143 = torch.sigmoid(features_56_conv_6_fc_0) mul_185 = features_56_conv_6_fc_0.__mul__(sigmoid_143) features_56_conv_6_fc_2 = self.features_56_conv_6_fc_2(mul_185) features_56_conv_6_fc_3 = self.features_56_conv_6_fc_3(features_56_conv_6_fc_2) view_86 = features_56_conv_6_fc_3.view(size_43[0], size_43[1], 1, 1) mul_186 = mul_184.__mul__(view_86) features_56_conv_7 = self.features_56_conv_7(mul_186) features_56_conv_8 = self.features_56_conv_8(features_56_conv_7) add_50 = add_49.__add__(features_56_conv_8) features_57_conv_0 = self.features_57_conv_0(add_50) features_57_conv_1 = self.features_57_conv_1(features_57_conv_0) sigmoid_144 = torch.sigmoid(features_57_conv_1) mul_187 = features_57_conv_1.__mul__(sigmoid_144) features_57_conv_3 = self.features_57_conv_3(mul_187) features_57_conv_4 = self.features_57_conv_4(features_57_conv_3) sigmoid_145 = torch.sigmoid(features_57_conv_4) mul_188 = features_57_conv_4.__mul__(sigmoid_145) size_44 = mul_188.size() features_57_conv_6_avg_pool = self.features_57_conv_6_avg_pool(mul_188) view_87 = features_57_conv_6_avg_pool.view(size_44[0], size_44[1]) features_57_conv_6_fc_0 = self.features_57_conv_6_fc_0(view_87) sigmoid_146 = torch.sigmoid(features_57_conv_6_fc_0) mul_189 = features_57_conv_6_fc_0.__mul__(sigmoid_146) features_57_conv_6_fc_2 = self.features_57_conv_6_fc_2(mul_189) features_57_conv_6_fc_3 = self.features_57_conv_6_fc_3(features_57_conv_6_fc_2) view_88 = features_57_conv_6_fc_3.view(size_44[0], size_44[1], 1, 1) mul_190 = mul_188.__mul__(view_88) features_57_conv_7 = self.features_57_conv_7(mul_190) features_57_conv_8 = self.features_57_conv_8(features_57_conv_7) add_51 = add_50.__add__(features_57_conv_8) conv_0 = self.conv_0(add_51) conv_1 = self.conv_1(conv_0) sigmoid_147 = torch.sigmoid(conv_1) mul_191 = conv_1.__mul__(sigmoid_147) avgpool = self.avgpool(mul_191) size_45 = avgpool.size(0) view_89 = avgpool.view(size_45, -1) classifier = self.classifier(view_89) return classifier if __name__ == "__main__": model = efficientnet_v2_m() model.eval() model.cpu() dummy_input_0 = torch.ones((1, 3, 224, 224), dtype=torch.float32) output = model(dummy_input_0) print(output)

models/efficientnet_v2_m.py (1,535 lines of code) (raw):