
import torch
import torch.nn
import torch.functional
import torch.nn.functional


class efficientnet_v2_s(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, 96, 3, 2, 1, bias=False)
        self.features_3_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(96)
        self.features_3_conv_3 = torch.nn.modules.conv.Conv2d(96, 48, 1, 1, 0, bias=False)
        self.features_3_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(48)
        self.features_4_conv_0 = torch.nn.modules.conv.Conv2d(48, 192, 3, 1, 1, bias=False)
        self.features_4_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(192)
        self.features_4_conv_3 = torch.nn.modules.conv.Conv2d(192, 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, 2, 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, 64, 1, 1, 0, bias=False)
        self.features_7_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(64)
        self.features_8_conv_0 = torch.nn.modules.conv.Conv2d(64, 256, 3, 1, 1, bias=False)
        self.features_8_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(256)
        self.features_8_conv_3 = torch.nn.modules.conv.Conv2d(256, 64, 1, 1, 0, bias=False)
        self.features_8_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(64)
        self.features_9_conv_0 = torch.nn.modules.conv.Conv2d(64, 256, 3, 1, 1, bias=False)
        self.features_9_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(256)
        self.features_9_conv_3 = torch.nn.modules.conv.Conv2d(256, 64, 1, 1, 0, bias=False)
        self.features_9_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(64)
        self.features_10_conv_0 = torch.nn.modules.conv.Conv2d(64, 256, 3, 1, 1, bias=False)
        self.features_10_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(256)
        self.features_10_conv_3 = torch.nn.modules.conv.Conv2d(256, 64, 1, 1, 0, bias=False)
        self.features_10_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(64)
        self.features_11_conv_0 = torch.nn.modules.conv.Conv2d(64, 256, 1, 1, 0, bias=False)
        self.features_11_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(256)
        self.features_11_conv_3 = torch.nn.modules.conv.Conv2d(256, 256, 3, 2, 1, groups=256, bias=False)
        self.features_11_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(256)
        self.features_11_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1)
        self.features_11_conv_6_fc_0 = torch.nn.modules.linear.Linear(256, 16)
        self.features_11_conv_6_fc_2 = torch.nn.modules.linear.Linear(16, 256)
        self.features_11_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_11_conv_7 = torch.nn.modules.conv.Conv2d(256, 128, 1, 1, 0, bias=False)
        self.features_11_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(128)
        self.features_12_conv_0 = torch.nn.modules.conv.Conv2d(128, 512, 1, 1, 0, bias=False)
        self.features_12_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(512)
        self.features_12_conv_3 = torch.nn.modules.conv.Conv2d(512, 512, 3, 1, 1, groups=512, bias=False)
        self.features_12_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(512)
        self.features_12_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1)
        self.features_12_conv_6_fc_0 = torch.nn.modules.linear.Linear(512, 32)
        self.features_12_conv_6_fc_2 = torch.nn.modules.linear.Linear(32, 512)
        self.features_12_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_12_conv_7 = torch.nn.modules.conv.Conv2d(512, 128, 1, 1, 0, bias=False)
        self.features_12_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(128)
        self.features_13_conv_0 = torch.nn.modules.conv.Conv2d(128, 512, 1, 1, 0, bias=False)
        self.features_13_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(512)
        self.features_13_conv_3 = torch.nn.modules.conv.Conv2d(512, 512, 3, 1, 1, groups=512, bias=False)
        self.features_13_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(512)
        self.features_13_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1)
        self.features_13_conv_6_fc_0 = torch.nn.modules.linear.Linear(512, 32)
        self.features_13_conv_6_fc_2 = torch.nn.modules.linear.Linear(32, 512)
        self.features_13_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_13_conv_7 = torch.nn.modules.conv.Conv2d(512, 128, 1, 1, 0, bias=False)
        self.features_13_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(128)
        self.features_14_conv_0 = torch.nn.modules.conv.Conv2d(128, 512, 1, 1, 0, bias=False)
        self.features_14_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(512)
        self.features_14_conv_3 = torch.nn.modules.conv.Conv2d(512, 512, 3, 1, 1, groups=512, bias=False)
        self.features_14_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(512)
        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(512, 32)
        self.features_14_conv_6_fc_2 = torch.nn.modules.linear.Linear(32, 512)
        self.features_14_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_14_conv_7 = torch.nn.modules.conv.Conv2d(512, 128, 1, 1, 0, bias=False)
        self.features_14_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(128)
        self.features_15_conv_0 = torch.nn.modules.conv.Conv2d(128, 512, 1, 1, 0, bias=False)
        self.features_15_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(512)
        self.features_15_conv_3 = torch.nn.modules.conv.Conv2d(512, 512, 3, 1, 1, groups=512, bias=False)
        self.features_15_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(512)
        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(512, 32)
        self.features_15_conv_6_fc_2 = torch.nn.modules.linear.Linear(32, 512)
        self.features_15_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_15_conv_7 = torch.nn.modules.conv.Conv2d(512, 128, 1, 1, 0, bias=False)
        self.features_15_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(128)
        self.features_16_conv_0 = torch.nn.modules.conv.Conv2d(128, 512, 1, 1, 0, bias=False)
        self.features_16_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(512)
        self.features_16_conv_3 = torch.nn.modules.conv.Conv2d(512, 512, 3, 1, 1, groups=512, bias=False)
        self.features_16_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(512)
        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(512, 32)
        self.features_16_conv_6_fc_2 = torch.nn.modules.linear.Linear(32, 512)
        self.features_16_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_16_conv_7 = torch.nn.modules.conv.Conv2d(512, 128, 1, 1, 0, bias=False)
        self.features_16_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(128)
        self.features_17_conv_0 = torch.nn.modules.conv.Conv2d(128, 768, 1, 1, 0, bias=False)
        self.features_17_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(768)
        self.features_17_conv_3 = torch.nn.modules.conv.Conv2d(768, 768, 3, 1, 1, groups=768, bias=False)
        self.features_17_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(768)
        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(768, 32)
        self.features_17_conv_6_fc_2 = torch.nn.modules.linear.Linear(32, 768)
        self.features_17_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_17_conv_7 = torch.nn.modules.conv.Conv2d(768, 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, 960, 1, 1, 0, bias=False)
        self.features_18_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(960)
        self.features_18_conv_3 = torch.nn.modules.conv.Conv2d(960, 960, 3, 1, 1, groups=960, bias=False)
        self.features_18_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(960)
        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(960, 40)
        self.features_18_conv_6_fc_2 = torch.nn.modules.linear.Linear(40, 960)
        self.features_18_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_18_conv_7 = torch.nn.modules.conv.Conv2d(960, 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, 960, 1, 1, 0, bias=False)
        self.features_19_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(960)
        self.features_19_conv_3 = torch.nn.modules.conv.Conv2d(960, 960, 3, 1, 1, groups=960, bias=False)
        self.features_19_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(960)
        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(960, 40)
        self.features_19_conv_6_fc_2 = torch.nn.modules.linear.Linear(40, 960)
        self.features_19_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_19_conv_7 = torch.nn.modules.conv.Conv2d(960, 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, 960, 1, 1, 0, bias=False)
        self.features_20_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(960)
        self.features_20_conv_3 = torch.nn.modules.conv.Conv2d(960, 960, 3, 1, 1, groups=960, bias=False)
        self.features_20_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(960)
        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(960, 40)
        self.features_20_conv_6_fc_2 = torch.nn.modules.linear.Linear(40, 960)
        self.features_20_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_20_conv_7 = torch.nn.modules.conv.Conv2d(960, 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, 160, 1, 1, 0, bias=False)
        self.features_21_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(160)
        self.features_22_conv_0 = torch.nn.modules.conv.Conv2d(160, 960, 1, 1, 0, bias=False)
        self.features_22_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(960)
        self.features_22_conv_3 = torch.nn.modules.conv.Conv2d(960, 960, 3, 1, 1, groups=960, bias=False)
        self.features_22_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(960)
        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(960, 40)
        self.features_22_conv_6_fc_2 = torch.nn.modules.linear.Linear(40, 960)
        self.features_22_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_22_conv_7 = torch.nn.modules.conv.Conv2d(960, 160, 1, 1, 0, bias=False)
        self.features_22_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(160)
        self.features_23_conv_0 = torch.nn.modules.conv.Conv2d(160, 960, 1, 1, 0, bias=False)
        self.features_23_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(960)
        self.features_23_conv_3 = torch.nn.modules.conv.Conv2d(960, 960, 3, 1, 1, groups=960, bias=False)
        self.features_23_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(960)
        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(960, 40)
        self.features_23_conv_6_fc_2 = torch.nn.modules.linear.Linear(40, 960)
        self.features_23_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_23_conv_7 = torch.nn.modules.conv.Conv2d(960, 160, 1, 1, 0, bias=False)
        self.features_23_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(160)
        self.features_24_conv_0 = torch.nn.modules.conv.Conv2d(160, 960, 1, 1, 0, bias=False)
        self.features_24_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(960)
        self.features_24_conv_3 = torch.nn.modules.conv.Conv2d(960, 960, 3, 1, 1, groups=960, bias=False)
        self.features_24_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(960)
        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(960, 40)
        self.features_24_conv_6_fc_2 = torch.nn.modules.linear.Linear(40, 960)
        self.features_24_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_24_conv_7 = torch.nn.modules.conv.Conv2d(960, 160, 1, 1, 0, bias=False)
        self.features_24_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(160)
        self.features_25_conv_0 = torch.nn.modules.conv.Conv2d(160, 960, 1, 1, 0, bias=False)
        self.features_25_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(960)
        self.features_25_conv_3 = torch.nn.modules.conv.Conv2d(960, 960, 3, 1, 1, groups=960, bias=False)
        self.features_25_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(960)
        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(960, 40)
        self.features_25_conv_6_fc_2 = torch.nn.modules.linear.Linear(40, 960)
        self.features_25_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_25_conv_7 = torch.nn.modules.conv.Conv2d(960, 160, 1, 1, 0, bias=False)
        self.features_25_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(160)
        self.features_26_conv_0 = torch.nn.modules.conv.Conv2d(160, 960, 1, 1, 0, bias=False)
        self.features_26_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(960)
        self.features_26_conv_3 = torch.nn.modules.conv.Conv2d(960, 960, 3, 2, 1, groups=960, bias=False)
        self.features_26_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(960)
        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(960, 40)
        self.features_26_conv_6_fc_2 = torch.nn.modules.linear.Linear(40, 960)
        self.features_26_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_26_conv_7 = torch.nn.modules.conv.Conv2d(960, 256, 1, 1, 0, bias=False)
        self.features_26_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(256)
        self.features_27_conv_0 = torch.nn.modules.conv.Conv2d(256, 1536, 1, 1, 0, bias=False)
        self.features_27_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        self.features_27_conv_3 = torch.nn.modules.conv.Conv2d(1536, 1536, 3, 1, 1, groups=1536, bias=False)
        self.features_27_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        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(1536, 64)
        self.features_27_conv_6_fc_2 = torch.nn.modules.linear.Linear(64, 1536)
        self.features_27_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_27_conv_7 = torch.nn.modules.conv.Conv2d(1536, 256, 1, 1, 0, bias=False)
        self.features_27_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(256)
        self.features_28_conv_0 = torch.nn.modules.conv.Conv2d(256, 1536, 1, 1, 0, bias=False)
        self.features_28_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        self.features_28_conv_3 = torch.nn.modules.conv.Conv2d(1536, 1536, 3, 1, 1, groups=1536, bias=False)
        self.features_28_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        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(1536, 64)
        self.features_28_conv_6_fc_2 = torch.nn.modules.linear.Linear(64, 1536)
        self.features_28_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_28_conv_7 = torch.nn.modules.conv.Conv2d(1536, 256, 1, 1, 0, bias=False)
        self.features_28_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(256)
        self.features_29_conv_0 = torch.nn.modules.conv.Conv2d(256, 1536, 1, 1, 0, bias=False)
        self.features_29_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        self.features_29_conv_3 = torch.nn.modules.conv.Conv2d(1536, 1536, 3, 1, 1, groups=1536, bias=False)
        self.features_29_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        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(1536, 64)
        self.features_29_conv_6_fc_2 = torch.nn.modules.linear.Linear(64, 1536)
        self.features_29_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_29_conv_7 = torch.nn.modules.conv.Conv2d(1536, 256, 1, 1, 0, bias=False)
        self.features_29_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(256)
        self.features_30_conv_0 = torch.nn.modules.conv.Conv2d(256, 1536, 1, 1, 0, bias=False)
        self.features_30_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        self.features_30_conv_3 = torch.nn.modules.conv.Conv2d(1536, 1536, 3, 1, 1, groups=1536, bias=False)
        self.features_30_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        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(1536, 64)
        self.features_30_conv_6_fc_2 = torch.nn.modules.linear.Linear(64, 1536)
        self.features_30_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_30_conv_7 = torch.nn.modules.conv.Conv2d(1536, 256, 1, 1, 0, bias=False)
        self.features_30_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(256)
        self.features_31_conv_0 = torch.nn.modules.conv.Conv2d(256, 1536, 1, 1, 0, bias=False)
        self.features_31_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        self.features_31_conv_3 = torch.nn.modules.conv.Conv2d(1536, 1536, 3, 1, 1, groups=1536, bias=False)
        self.features_31_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        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(1536, 64)
        self.features_31_conv_6_fc_2 = torch.nn.modules.linear.Linear(64, 1536)
        self.features_31_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_31_conv_7 = torch.nn.modules.conv.Conv2d(1536, 256, 1, 1, 0, bias=False)
        self.features_31_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(256)
        self.features_32_conv_0 = torch.nn.modules.conv.Conv2d(256, 1536, 1, 1, 0, bias=False)
        self.features_32_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        self.features_32_conv_3 = torch.nn.modules.conv.Conv2d(1536, 1536, 3, 1, 1, groups=1536, bias=False)
        self.features_32_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        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(1536, 64)
        self.features_32_conv_6_fc_2 = torch.nn.modules.linear.Linear(64, 1536)
        self.features_32_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_32_conv_7 = torch.nn.modules.conv.Conv2d(1536, 256, 1, 1, 0, bias=False)
        self.features_32_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(256)
        self.features_33_conv_0 = torch.nn.modules.conv.Conv2d(256, 1536, 1, 1, 0, bias=False)
        self.features_33_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        self.features_33_conv_3 = torch.nn.modules.conv.Conv2d(1536, 1536, 3, 1, 1, groups=1536, bias=False)
        self.features_33_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        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(1536, 64)
        self.features_33_conv_6_fc_2 = torch.nn.modules.linear.Linear(64, 1536)
        self.features_33_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_33_conv_7 = torch.nn.modules.conv.Conv2d(1536, 256, 1, 1, 0, bias=False)
        self.features_33_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(256)
        self.features_34_conv_0 = torch.nn.modules.conv.Conv2d(256, 1536, 1, 1, 0, bias=False)
        self.features_34_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        self.features_34_conv_3 = torch.nn.modules.conv.Conv2d(1536, 1536, 3, 1, 1, groups=1536, bias=False)
        self.features_34_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        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(1536, 64)
        self.features_34_conv_6_fc_2 = torch.nn.modules.linear.Linear(64, 1536)
        self.features_34_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_34_conv_7 = torch.nn.modules.conv.Conv2d(1536, 256, 1, 1, 0, bias=False)
        self.features_34_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(256)
        self.features_35_conv_0 = torch.nn.modules.conv.Conv2d(256, 1536, 1, 1, 0, bias=False)
        self.features_35_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        self.features_35_conv_3 = torch.nn.modules.conv.Conv2d(1536, 1536, 3, 1, 1, groups=1536, bias=False)
        self.features_35_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        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(1536, 64)
        self.features_35_conv_6_fc_2 = torch.nn.modules.linear.Linear(64, 1536)
        self.features_35_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_35_conv_7 = torch.nn.modules.conv.Conv2d(1536, 256, 1, 1, 0, bias=False)
        self.features_35_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(256)
        self.features_36_conv_0 = torch.nn.modules.conv.Conv2d(256, 1536, 1, 1, 0, bias=False)
        self.features_36_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        self.features_36_conv_3 = torch.nn.modules.conv.Conv2d(1536, 1536, 3, 1, 1, groups=1536, bias=False)
        self.features_36_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        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(1536, 64)
        self.features_36_conv_6_fc_2 = torch.nn.modules.linear.Linear(64, 1536)
        self.features_36_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_36_conv_7 = torch.nn.modules.conv.Conv2d(1536, 256, 1, 1, 0, bias=False)
        self.features_36_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(256)
        self.features_37_conv_0 = torch.nn.modules.conv.Conv2d(256, 1536, 1, 1, 0, bias=False)
        self.features_37_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        self.features_37_conv_3 = torch.nn.modules.conv.Conv2d(1536, 1536, 3, 1, 1, groups=1536, bias=False)
        self.features_37_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        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(1536, 64)
        self.features_37_conv_6_fc_2 = torch.nn.modules.linear.Linear(64, 1536)
        self.features_37_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_37_conv_7 = torch.nn.modules.conv.Conv2d(1536, 256, 1, 1, 0, bias=False)
        self.features_37_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(256)
        self.features_38_conv_0 = torch.nn.modules.conv.Conv2d(256, 1536, 1, 1, 0, bias=False)
        self.features_38_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        self.features_38_conv_3 = torch.nn.modules.conv.Conv2d(1536, 1536, 3, 1, 1, groups=1536, bias=False)
        self.features_38_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        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(1536, 64)
        self.features_38_conv_6_fc_2 = torch.nn.modules.linear.Linear(64, 1536)
        self.features_38_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_38_conv_7 = torch.nn.modules.conv.Conv2d(1536, 256, 1, 1, 0, bias=False)
        self.features_38_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(256)
        self.features_39_conv_0 = torch.nn.modules.conv.Conv2d(256, 1536, 1, 1, 0, bias=False)
        self.features_39_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        self.features_39_conv_3 = torch.nn.modules.conv.Conv2d(1536, 1536, 3, 1, 1, groups=1536, bias=False)
        self.features_39_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        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(1536, 64)
        self.features_39_conv_6_fc_2 = torch.nn.modules.linear.Linear(64, 1536)
        self.features_39_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_39_conv_7 = torch.nn.modules.conv.Conv2d(1536, 256, 1, 1, 0, bias=False)
        self.features_39_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(256)
        self.features_40_conv_0 = torch.nn.modules.conv.Conv2d(256, 1536, 1, 1, 0, bias=False)
        self.features_40_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        self.features_40_conv_3 = torch.nn.modules.conv.Conv2d(1536, 1536, 3, 1, 1, groups=1536, bias=False)
        self.features_40_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        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(1536, 64)
        self.features_40_conv_6_fc_2 = torch.nn.modules.linear.Linear(64, 1536)
        self.features_40_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_40_conv_7 = torch.nn.modules.conv.Conv2d(1536, 256, 1, 1, 0, bias=False)
        self.features_40_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(256)
        self.conv_0 = torch.nn.modules.conv.Conv2d(256, 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)
        features_4_conv_0 = self.features_4_conv_0(features_3_conv_4)
        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)
        add_3 = features_3_conv_4.__add__(features_4_conv_4)
        features_5_conv_0 = self.features_5_conv_0(add_3)
        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 = add_3.__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)
        features_8_conv_0 = self.features_8_conv_0(features_7_conv_4)
        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_6 = features_7_conv_4.__add__(features_8_conv_4)
        features_9_conv_0 = self.features_9_conv_0(add_6)
        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)
        add_7 = add_6.__add__(features_9_conv_4)
        features_10_conv_0 = self.features_10_conv_0(add_7)
        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 = add_7.__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)
        sigmoid_13 = torch.sigmoid(features_11_conv_4)
        mul_13 = features_11_conv_4.__mul__(sigmoid_13)
        size_1 = mul_13.size()
        features_11_conv_6_avg_pool = self.features_11_conv_6_avg_pool(mul_13)
        view_1 = features_11_conv_6_avg_pool.view(size_1[0], size_1[1])
        features_11_conv_6_fc_0 = self.features_11_conv_6_fc_0(view_1)
        sigmoid_14 = torch.sigmoid(features_11_conv_6_fc_0)
        mul_14 = features_11_conv_6_fc_0.__mul__(sigmoid_14)
        features_11_conv_6_fc_2 = self.features_11_conv_6_fc_2(mul_14)
        features_11_conv_6_fc_3 = self.features_11_conv_6_fc_3(features_11_conv_6_fc_2)
        view_2 = features_11_conv_6_fc_3.view(size_1[0], size_1[1], 1, 1)
        mul_15 = mul_13.__mul__(view_2)
        features_11_conv_7 = self.features_11_conv_7(mul_15)
        features_11_conv_8 = self.features_11_conv_8(features_11_conv_7)
        features_12_conv_0 = self.features_12_conv_0(features_11_conv_8)
        features_12_conv_1 = self.features_12_conv_1(features_12_conv_0)
        sigmoid_15 = torch.sigmoid(features_12_conv_1)
        mul_16 = features_12_conv_1.__mul__(sigmoid_15)
        features_12_conv_3 = self.features_12_conv_3(mul_16)
        features_12_conv_4 = self.features_12_conv_4(features_12_conv_3)
        sigmoid_16 = torch.sigmoid(features_12_conv_4)
        mul_17 = features_12_conv_4.__mul__(sigmoid_16)
        size_2 = mul_17.size()
        features_12_conv_6_avg_pool = self.features_12_conv_6_avg_pool(mul_17)
        view_3 = features_12_conv_6_avg_pool.view(size_2[0], size_2[1])
        features_12_conv_6_fc_0 = self.features_12_conv_6_fc_0(view_3)
        sigmoid_17 = torch.sigmoid(features_12_conv_6_fc_0)
        mul_18 = features_12_conv_6_fc_0.__mul__(sigmoid_17)
        features_12_conv_6_fc_2 = self.features_12_conv_6_fc_2(mul_18)
        features_12_conv_6_fc_3 = self.features_12_conv_6_fc_3(features_12_conv_6_fc_2)
        view_4 = features_12_conv_6_fc_3.view(size_2[0], size_2[1], 1, 1)
        mul_19 = mul_17.__mul__(view_4)
        features_12_conv_7 = self.features_12_conv_7(mul_19)
        features_12_conv_8 = self.features_12_conv_8(features_12_conv_7)
        add_9 = features_11_conv_8.__add__(features_12_conv_8)
        features_13_conv_0 = self.features_13_conv_0(add_9)
        features_13_conv_1 = self.features_13_conv_1(features_13_conv_0)
        sigmoid_18 = torch.sigmoid(features_13_conv_1)
        mul_20 = features_13_conv_1.__mul__(sigmoid_18)
        features_13_conv_3 = self.features_13_conv_3(mul_20)
        features_13_conv_4 = self.features_13_conv_4(features_13_conv_3)
        sigmoid_19 = torch.sigmoid(features_13_conv_4)
        mul_21 = features_13_conv_4.__mul__(sigmoid_19)
        size_3 = mul_21.size()
        features_13_conv_6_avg_pool = self.features_13_conv_6_avg_pool(mul_21)
        view_5 = features_13_conv_6_avg_pool.view(size_3[0], size_3[1])
        features_13_conv_6_fc_0 = self.features_13_conv_6_fc_0(view_5)
        sigmoid_20 = torch.sigmoid(features_13_conv_6_fc_0)
        mul_22 = features_13_conv_6_fc_0.__mul__(sigmoid_20)
        features_13_conv_6_fc_2 = self.features_13_conv_6_fc_2(mul_22)
        features_13_conv_6_fc_3 = self.features_13_conv_6_fc_3(features_13_conv_6_fc_2)
        view_6 = features_13_conv_6_fc_3.view(size_3[0], size_3[1], 1, 1)
        mul_23 = mul_21.__mul__(view_6)
        features_13_conv_7 = self.features_13_conv_7(mul_23)
        features_13_conv_8 = self.features_13_conv_8(features_13_conv_7)
        add_10 = add_9.__add__(features_13_conv_8)
        features_14_conv_0 = self.features_14_conv_0(add_10)
        features_14_conv_1 = self.features_14_conv_1(features_14_conv_0)
        sigmoid_21 = torch.sigmoid(features_14_conv_1)
        mul_24 = features_14_conv_1.__mul__(sigmoid_21)
        features_14_conv_3 = self.features_14_conv_3(mul_24)
        features_14_conv_4 = self.features_14_conv_4(features_14_conv_3)
        sigmoid_22 = torch.sigmoid(features_14_conv_4)
        mul_25 = features_14_conv_4.__mul__(sigmoid_22)
        size_4 = mul_25.size()
        features_14_conv_6_avg_pool = self.features_14_conv_6_avg_pool(mul_25)
        view_7 = features_14_conv_6_avg_pool.view(size_4[0], size_4[1])
        features_14_conv_6_fc_0 = self.features_14_conv_6_fc_0(view_7)
        sigmoid_23 = torch.sigmoid(features_14_conv_6_fc_0)
        mul_26 = features_14_conv_6_fc_0.__mul__(sigmoid_23)
        features_14_conv_6_fc_2 = self.features_14_conv_6_fc_2(mul_26)
        features_14_conv_6_fc_3 = self.features_14_conv_6_fc_3(features_14_conv_6_fc_2)
        view_8 = features_14_conv_6_fc_3.view(size_4[0], size_4[1], 1, 1)
        mul_27 = mul_25.__mul__(view_8)
        features_14_conv_7 = self.features_14_conv_7(mul_27)
        features_14_conv_8 = self.features_14_conv_8(features_14_conv_7)
        add_11 = add_10.__add__(features_14_conv_8)
        features_15_conv_0 = self.features_15_conv_0(add_11)
        features_15_conv_1 = self.features_15_conv_1(features_15_conv_0)
        sigmoid_24 = torch.sigmoid(features_15_conv_1)
        mul_28 = features_15_conv_1.__mul__(sigmoid_24)
        features_15_conv_3 = self.features_15_conv_3(mul_28)
        features_15_conv_4 = self.features_15_conv_4(features_15_conv_3)
        sigmoid_25 = torch.sigmoid(features_15_conv_4)
        mul_29 = features_15_conv_4.__mul__(sigmoid_25)
        size_5 = mul_29.size()
        features_15_conv_6_avg_pool = self.features_15_conv_6_avg_pool(mul_29)
        view_9 = features_15_conv_6_avg_pool.view(size_5[0], size_5[1])
        features_15_conv_6_fc_0 = self.features_15_conv_6_fc_0(view_9)
        sigmoid_26 = torch.sigmoid(features_15_conv_6_fc_0)
        mul_30 = features_15_conv_6_fc_0.__mul__(sigmoid_26)
        features_15_conv_6_fc_2 = self.features_15_conv_6_fc_2(mul_30)
        features_15_conv_6_fc_3 = self.features_15_conv_6_fc_3(features_15_conv_6_fc_2)
        view_10 = features_15_conv_6_fc_3.view(size_5[0], size_5[1], 1, 1)
        mul_31 = mul_29.__mul__(view_10)
        features_15_conv_7 = self.features_15_conv_7(mul_31)
        features_15_conv_8 = self.features_15_conv_8(features_15_conv_7)
        add_12 = add_11.__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_27 = torch.sigmoid(features_16_conv_1)
        mul_32 = features_16_conv_1.__mul__(sigmoid_27)
        features_16_conv_3 = self.features_16_conv_3(mul_32)
        features_16_conv_4 = self.features_16_conv_4(features_16_conv_3)
        sigmoid_28 = torch.sigmoid(features_16_conv_4)
        mul_33 = features_16_conv_4.__mul__(sigmoid_28)
        size_6 = mul_33.size()
        features_16_conv_6_avg_pool = self.features_16_conv_6_avg_pool(mul_33)
        view_11 = features_16_conv_6_avg_pool.view(size_6[0], size_6[1])
        features_16_conv_6_fc_0 = self.features_16_conv_6_fc_0(view_11)
        sigmoid_29 = torch.sigmoid(features_16_conv_6_fc_0)
        mul_34 = features_16_conv_6_fc_0.__mul__(sigmoid_29)
        features_16_conv_6_fc_2 = self.features_16_conv_6_fc_2(mul_34)
        features_16_conv_6_fc_3 = self.features_16_conv_6_fc_3(features_16_conv_6_fc_2)
        view_12 = features_16_conv_6_fc_3.view(size_6[0], size_6[1], 1, 1)
        mul_35 = mul_33.__mul__(view_12)
        features_16_conv_7 = self.features_16_conv_7(mul_35)
        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_30 = torch.sigmoid(features_17_conv_1)
        mul_36 = features_17_conv_1.__mul__(sigmoid_30)
        features_17_conv_3 = self.features_17_conv_3(mul_36)
        features_17_conv_4 = self.features_17_conv_4(features_17_conv_3)
        sigmoid_31 = torch.sigmoid(features_17_conv_4)
        mul_37 = features_17_conv_4.__mul__(sigmoid_31)
        size_7 = mul_37.size()
        features_17_conv_6_avg_pool = self.features_17_conv_6_avg_pool(mul_37)
        view_13 = features_17_conv_6_avg_pool.view(size_7[0], size_7[1])
        features_17_conv_6_fc_0 = self.features_17_conv_6_fc_0(view_13)
        sigmoid_32 = torch.sigmoid(features_17_conv_6_fc_0)
        mul_38 = features_17_conv_6_fc_0.__mul__(sigmoid_32)
        features_17_conv_6_fc_2 = self.features_17_conv_6_fc_2(mul_38)
        features_17_conv_6_fc_3 = self.features_17_conv_6_fc_3(features_17_conv_6_fc_2)
        view_14 = features_17_conv_6_fc_3.view(size_7[0], size_7[1], 1, 1)
        mul_39 = mul_37.__mul__(view_14)
        features_17_conv_7 = self.features_17_conv_7(mul_39)
        features_17_conv_8 = self.features_17_conv_8(features_17_conv_7)
        features_18_conv_0 = self.features_18_conv_0(features_17_conv_8)
        features_18_conv_1 = self.features_18_conv_1(features_18_conv_0)
        sigmoid_33 = torch.sigmoid(features_18_conv_1)
        mul_40 = features_18_conv_1.__mul__(sigmoid_33)
        features_18_conv_3 = self.features_18_conv_3(mul_40)
        features_18_conv_4 = self.features_18_conv_4(features_18_conv_3)
        sigmoid_34 = torch.sigmoid(features_18_conv_4)
        mul_41 = features_18_conv_4.__mul__(sigmoid_34)
        size_8 = mul_41.size()
        features_18_conv_6_avg_pool = self.features_18_conv_6_avg_pool(mul_41)
        view_15 = features_18_conv_6_avg_pool.view(size_8[0], size_8[1])
        features_18_conv_6_fc_0 = self.features_18_conv_6_fc_0(view_15)
        sigmoid_35 = torch.sigmoid(features_18_conv_6_fc_0)
        mul_42 = features_18_conv_6_fc_0.__mul__(sigmoid_35)
        features_18_conv_6_fc_2 = self.features_18_conv_6_fc_2(mul_42)
        features_18_conv_6_fc_3 = self.features_18_conv_6_fc_3(features_18_conv_6_fc_2)
        view_16 = features_18_conv_6_fc_3.view(size_8[0], size_8[1], 1, 1)
        mul_43 = mul_41.__mul__(view_16)
        features_18_conv_7 = self.features_18_conv_7(mul_43)
        features_18_conv_8 = self.features_18_conv_8(features_18_conv_7)
        add_14 = features_17_conv_8.__add__(features_18_conv_8)
        features_19_conv_0 = self.features_19_conv_0(add_14)
        features_19_conv_1 = self.features_19_conv_1(features_19_conv_0)
        sigmoid_36 = torch.sigmoid(features_19_conv_1)
        mul_44 = features_19_conv_1.__mul__(sigmoid_36)
        features_19_conv_3 = self.features_19_conv_3(mul_44)
        features_19_conv_4 = self.features_19_conv_4(features_19_conv_3)
        sigmoid_37 = torch.sigmoid(features_19_conv_4)
        mul_45 = features_19_conv_4.__mul__(sigmoid_37)
        size_9 = mul_45.size()
        features_19_conv_6_avg_pool = self.features_19_conv_6_avg_pool(mul_45)
        view_17 = features_19_conv_6_avg_pool.view(size_9[0], size_9[1])
        features_19_conv_6_fc_0 = self.features_19_conv_6_fc_0(view_17)
        sigmoid_38 = torch.sigmoid(features_19_conv_6_fc_0)
        mul_46 = features_19_conv_6_fc_0.__mul__(sigmoid_38)
        features_19_conv_6_fc_2 = self.features_19_conv_6_fc_2(mul_46)
        features_19_conv_6_fc_3 = self.features_19_conv_6_fc_3(features_19_conv_6_fc_2)
        view_18 = features_19_conv_6_fc_3.view(size_9[0], size_9[1], 1, 1)
        mul_47 = mul_45.__mul__(view_18)
        features_19_conv_7 = self.features_19_conv_7(mul_47)
        features_19_conv_8 = self.features_19_conv_8(features_19_conv_7)
        add_15 = add_14.__add__(features_19_conv_8)
        features_20_conv_0 = self.features_20_conv_0(add_15)
        features_20_conv_1 = self.features_20_conv_1(features_20_conv_0)
        sigmoid_39 = torch.sigmoid(features_20_conv_1)
        mul_48 = features_20_conv_1.__mul__(sigmoid_39)
        features_20_conv_3 = self.features_20_conv_3(mul_48)
        features_20_conv_4 = self.features_20_conv_4(features_20_conv_3)
        sigmoid_40 = torch.sigmoid(features_20_conv_4)
        mul_49 = features_20_conv_4.__mul__(sigmoid_40)
        size_10 = mul_49.size()
        features_20_conv_6_avg_pool = self.features_20_conv_6_avg_pool(mul_49)
        view_19 = features_20_conv_6_avg_pool.view(size_10[0], size_10[1])
        features_20_conv_6_fc_0 = self.features_20_conv_6_fc_0(view_19)
        sigmoid_41 = torch.sigmoid(features_20_conv_6_fc_0)
        mul_50 = features_20_conv_6_fc_0.__mul__(sigmoid_41)
        features_20_conv_6_fc_2 = self.features_20_conv_6_fc_2(mul_50)
        features_20_conv_6_fc_3 = self.features_20_conv_6_fc_3(features_20_conv_6_fc_2)
        view_20 = features_20_conv_6_fc_3.view(size_10[0], size_10[1], 1, 1)
        mul_51 = mul_49.__mul__(view_20)
        features_20_conv_7 = self.features_20_conv_7(mul_51)
        features_20_conv_8 = self.features_20_conv_8(features_20_conv_7)
        add_16 = add_15.__add__(features_20_conv_8)
        features_21_conv_0 = self.features_21_conv_0(add_16)
        features_21_conv_1 = self.features_21_conv_1(features_21_conv_0)
        sigmoid_42 = torch.sigmoid(features_21_conv_1)
        mul_52 = features_21_conv_1.__mul__(sigmoid_42)
        features_21_conv_3 = self.features_21_conv_3(mul_52)
        features_21_conv_4 = self.features_21_conv_4(features_21_conv_3)
        sigmoid_43 = torch.sigmoid(features_21_conv_4)
        mul_53 = features_21_conv_4.__mul__(sigmoid_43)
        size_11 = mul_53.size()
        features_21_conv_6_avg_pool = self.features_21_conv_6_avg_pool(mul_53)
        view_21 = features_21_conv_6_avg_pool.view(size_11[0], size_11[1])
        features_21_conv_6_fc_0 = self.features_21_conv_6_fc_0(view_21)
        sigmoid_44 = torch.sigmoid(features_21_conv_6_fc_0)
        mul_54 = features_21_conv_6_fc_0.__mul__(sigmoid_44)
        features_21_conv_6_fc_2 = self.features_21_conv_6_fc_2(mul_54)
        features_21_conv_6_fc_3 = self.features_21_conv_6_fc_3(features_21_conv_6_fc_2)
        view_22 = features_21_conv_6_fc_3.view(size_11[0], size_11[1], 1, 1)
        mul_55 = mul_53.__mul__(view_22)
        features_21_conv_7 = self.features_21_conv_7(mul_55)
        features_21_conv_8 = self.features_21_conv_8(features_21_conv_7)
        add_17 = add_16.__add__(features_21_conv_8)
        features_22_conv_0 = self.features_22_conv_0(add_17)
        features_22_conv_1 = self.features_22_conv_1(features_22_conv_0)
        sigmoid_45 = torch.sigmoid(features_22_conv_1)
        mul_56 = features_22_conv_1.__mul__(sigmoid_45)
        features_22_conv_3 = self.features_22_conv_3(mul_56)
        features_22_conv_4 = self.features_22_conv_4(features_22_conv_3)
        sigmoid_46 = torch.sigmoid(features_22_conv_4)
        mul_57 = features_22_conv_4.__mul__(sigmoid_46)
        size_12 = mul_57.size()
        features_22_conv_6_avg_pool = self.features_22_conv_6_avg_pool(mul_57)
        view_23 = features_22_conv_6_avg_pool.view(size_12[0], size_12[1])
        features_22_conv_6_fc_0 = self.features_22_conv_6_fc_0(view_23)
        sigmoid_47 = torch.sigmoid(features_22_conv_6_fc_0)
        mul_58 = features_22_conv_6_fc_0.__mul__(sigmoid_47)
        features_22_conv_6_fc_2 = self.features_22_conv_6_fc_2(mul_58)
        features_22_conv_6_fc_3 = self.features_22_conv_6_fc_3(features_22_conv_6_fc_2)
        view_24 = features_22_conv_6_fc_3.view(size_12[0], size_12[1], 1, 1)
        mul_59 = mul_57.__mul__(view_24)
        features_22_conv_7 = self.features_22_conv_7(mul_59)
        features_22_conv_8 = self.features_22_conv_8(features_22_conv_7)
        add_18 = add_17.__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_48 = torch.sigmoid(features_23_conv_1)
        mul_60 = features_23_conv_1.__mul__(sigmoid_48)
        features_23_conv_3 = self.features_23_conv_3(mul_60)
        features_23_conv_4 = self.features_23_conv_4(features_23_conv_3)
        sigmoid_49 = torch.sigmoid(features_23_conv_4)
        mul_61 = features_23_conv_4.__mul__(sigmoid_49)
        size_13 = mul_61.size()
        features_23_conv_6_avg_pool = self.features_23_conv_6_avg_pool(mul_61)
        view_25 = features_23_conv_6_avg_pool.view(size_13[0], size_13[1])
        features_23_conv_6_fc_0 = self.features_23_conv_6_fc_0(view_25)
        sigmoid_50 = torch.sigmoid(features_23_conv_6_fc_0)
        mul_62 = features_23_conv_6_fc_0.__mul__(sigmoid_50)
        features_23_conv_6_fc_2 = self.features_23_conv_6_fc_2(mul_62)
        features_23_conv_6_fc_3 = self.features_23_conv_6_fc_3(features_23_conv_6_fc_2)
        view_26 = features_23_conv_6_fc_3.view(size_13[0], size_13[1], 1, 1)
        mul_63 = mul_61.__mul__(view_26)
        features_23_conv_7 = self.features_23_conv_7(mul_63)
        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_51 = torch.sigmoid(features_24_conv_1)
        mul_64 = features_24_conv_1.__mul__(sigmoid_51)
        features_24_conv_3 = self.features_24_conv_3(mul_64)
        features_24_conv_4 = self.features_24_conv_4(features_24_conv_3)
        sigmoid_52 = torch.sigmoid(features_24_conv_4)
        mul_65 = features_24_conv_4.__mul__(sigmoid_52)
        size_14 = mul_65.size()
        features_24_conv_6_avg_pool = self.features_24_conv_6_avg_pool(mul_65)
        view_27 = features_24_conv_6_avg_pool.view(size_14[0], size_14[1])
        features_24_conv_6_fc_0 = self.features_24_conv_6_fc_0(view_27)
        sigmoid_53 = torch.sigmoid(features_24_conv_6_fc_0)
        mul_66 = features_24_conv_6_fc_0.__mul__(sigmoid_53)
        features_24_conv_6_fc_2 = self.features_24_conv_6_fc_2(mul_66)
        features_24_conv_6_fc_3 = self.features_24_conv_6_fc_3(features_24_conv_6_fc_2)
        view_28 = features_24_conv_6_fc_3.view(size_14[0], size_14[1], 1, 1)
        mul_67 = mul_65.__mul__(view_28)
        features_24_conv_7 = self.features_24_conv_7(mul_67)
        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_54 = torch.sigmoid(features_25_conv_1)
        mul_68 = features_25_conv_1.__mul__(sigmoid_54)
        features_25_conv_3 = self.features_25_conv_3(mul_68)
        features_25_conv_4 = self.features_25_conv_4(features_25_conv_3)
        sigmoid_55 = torch.sigmoid(features_25_conv_4)
        mul_69 = features_25_conv_4.__mul__(sigmoid_55)
        size_15 = mul_69.size()
        features_25_conv_6_avg_pool = self.features_25_conv_6_avg_pool(mul_69)
        view_29 = features_25_conv_6_avg_pool.view(size_15[0], size_15[1])
        features_25_conv_6_fc_0 = self.features_25_conv_6_fc_0(view_29)
        sigmoid_56 = torch.sigmoid(features_25_conv_6_fc_0)
        mul_70 = features_25_conv_6_fc_0.__mul__(sigmoid_56)
        features_25_conv_6_fc_2 = self.features_25_conv_6_fc_2(mul_70)
        features_25_conv_6_fc_3 = self.features_25_conv_6_fc_3(features_25_conv_6_fc_2)
        view_30 = features_25_conv_6_fc_3.view(size_15[0], size_15[1], 1, 1)
        mul_71 = mul_69.__mul__(view_30)
        features_25_conv_7 = self.features_25_conv_7(mul_71)
        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_57 = torch.sigmoid(features_26_conv_1)
        mul_72 = features_26_conv_1.__mul__(sigmoid_57)
        features_26_conv_3 = self.features_26_conv_3(mul_72)
        features_26_conv_4 = self.features_26_conv_4(features_26_conv_3)
        sigmoid_58 = torch.sigmoid(features_26_conv_4)
        mul_73 = features_26_conv_4.__mul__(sigmoid_58)
        size_16 = mul_73.size()
        features_26_conv_6_avg_pool = self.features_26_conv_6_avg_pool(mul_73)
        view_31 = features_26_conv_6_avg_pool.view(size_16[0], size_16[1])
        features_26_conv_6_fc_0 = self.features_26_conv_6_fc_0(view_31)
        sigmoid_59 = torch.sigmoid(features_26_conv_6_fc_0)
        mul_74 = features_26_conv_6_fc_0.__mul__(sigmoid_59)
        features_26_conv_6_fc_2 = self.features_26_conv_6_fc_2(mul_74)
        features_26_conv_6_fc_3 = self.features_26_conv_6_fc_3(features_26_conv_6_fc_2)
        view_32 = features_26_conv_6_fc_3.view(size_16[0], size_16[1], 1, 1)
        mul_75 = mul_73.__mul__(view_32)
        features_26_conv_7 = self.features_26_conv_7(mul_75)
        features_26_conv_8 = self.features_26_conv_8(features_26_conv_7)
        features_27_conv_0 = self.features_27_conv_0(features_26_conv_8)
        features_27_conv_1 = self.features_27_conv_1(features_27_conv_0)
        sigmoid_60 = torch.sigmoid(features_27_conv_1)
        mul_76 = features_27_conv_1.__mul__(sigmoid_60)
        features_27_conv_3 = self.features_27_conv_3(mul_76)
        features_27_conv_4 = self.features_27_conv_4(features_27_conv_3)
        sigmoid_61 = torch.sigmoid(features_27_conv_4)
        mul_77 = features_27_conv_4.__mul__(sigmoid_61)
        size_17 = mul_77.size()
        features_27_conv_6_avg_pool = self.features_27_conv_6_avg_pool(mul_77)
        view_33 = features_27_conv_6_avg_pool.view(size_17[0], size_17[1])
        features_27_conv_6_fc_0 = self.features_27_conv_6_fc_0(view_33)
        sigmoid_62 = torch.sigmoid(features_27_conv_6_fc_0)
        mul_78 = features_27_conv_6_fc_0.__mul__(sigmoid_62)
        features_27_conv_6_fc_2 = self.features_27_conv_6_fc_2(mul_78)
        features_27_conv_6_fc_3 = self.features_27_conv_6_fc_3(features_27_conv_6_fc_2)
        view_34 = features_27_conv_6_fc_3.view(size_17[0], size_17[1], 1, 1)
        mul_79 = mul_77.__mul__(view_34)
        features_27_conv_7 = self.features_27_conv_7(mul_79)
        features_27_conv_8 = self.features_27_conv_8(features_27_conv_7)
        add_22 = features_26_conv_8.__add__(features_27_conv_8)
        features_28_conv_0 = self.features_28_conv_0(add_22)
        features_28_conv_1 = self.features_28_conv_1(features_28_conv_0)
        sigmoid_63 = torch.sigmoid(features_28_conv_1)
        mul_80 = features_28_conv_1.__mul__(sigmoid_63)
        features_28_conv_3 = self.features_28_conv_3(mul_80)
        features_28_conv_4 = self.features_28_conv_4(features_28_conv_3)
        sigmoid_64 = torch.sigmoid(features_28_conv_4)
        mul_81 = features_28_conv_4.__mul__(sigmoid_64)
        size_18 = mul_81.size()
        features_28_conv_6_avg_pool = self.features_28_conv_6_avg_pool(mul_81)
        view_35 = features_28_conv_6_avg_pool.view(size_18[0], size_18[1])
        features_28_conv_6_fc_0 = self.features_28_conv_6_fc_0(view_35)
        sigmoid_65 = torch.sigmoid(features_28_conv_6_fc_0)
        mul_82 = features_28_conv_6_fc_0.__mul__(sigmoid_65)
        features_28_conv_6_fc_2 = self.features_28_conv_6_fc_2(mul_82)
        features_28_conv_6_fc_3 = self.features_28_conv_6_fc_3(features_28_conv_6_fc_2)
        view_36 = features_28_conv_6_fc_3.view(size_18[0], size_18[1], 1, 1)
        mul_83 = mul_81.__mul__(view_36)
        features_28_conv_7 = self.features_28_conv_7(mul_83)
        features_28_conv_8 = self.features_28_conv_8(features_28_conv_7)
        add_23 = add_22.__add__(features_28_conv_8)
        features_29_conv_0 = self.features_29_conv_0(add_23)
        features_29_conv_1 = self.features_29_conv_1(features_29_conv_0)
        sigmoid_66 = torch.sigmoid(features_29_conv_1)
        mul_84 = features_29_conv_1.__mul__(sigmoid_66)
        features_29_conv_3 = self.features_29_conv_3(mul_84)
        features_29_conv_4 = self.features_29_conv_4(features_29_conv_3)
        sigmoid_67 = torch.sigmoid(features_29_conv_4)
        mul_85 = features_29_conv_4.__mul__(sigmoid_67)
        size_19 = mul_85.size()
        features_29_conv_6_avg_pool = self.features_29_conv_6_avg_pool(mul_85)
        view_37 = features_29_conv_6_avg_pool.view(size_19[0], size_19[1])
        features_29_conv_6_fc_0 = self.features_29_conv_6_fc_0(view_37)
        sigmoid_68 = torch.sigmoid(features_29_conv_6_fc_0)
        mul_86 = features_29_conv_6_fc_0.__mul__(sigmoid_68)
        features_29_conv_6_fc_2 = self.features_29_conv_6_fc_2(mul_86)
        features_29_conv_6_fc_3 = self.features_29_conv_6_fc_3(features_29_conv_6_fc_2)
        view_38 = features_29_conv_6_fc_3.view(size_19[0], size_19[1], 1, 1)
        mul_87 = mul_85.__mul__(view_38)
        features_29_conv_7 = self.features_29_conv_7(mul_87)
        features_29_conv_8 = self.features_29_conv_8(features_29_conv_7)
        add_24 = add_23.__add__(features_29_conv_8)
        features_30_conv_0 = self.features_30_conv_0(add_24)
        features_30_conv_1 = self.features_30_conv_1(features_30_conv_0)
        sigmoid_69 = torch.sigmoid(features_30_conv_1)
        mul_88 = features_30_conv_1.__mul__(sigmoid_69)
        features_30_conv_3 = self.features_30_conv_3(mul_88)
        features_30_conv_4 = self.features_30_conv_4(features_30_conv_3)
        sigmoid_70 = torch.sigmoid(features_30_conv_4)
        mul_89 = features_30_conv_4.__mul__(sigmoid_70)
        size_20 = mul_89.size()
        features_30_conv_6_avg_pool = self.features_30_conv_6_avg_pool(mul_89)
        view_39 = features_30_conv_6_avg_pool.view(size_20[0], size_20[1])
        features_30_conv_6_fc_0 = self.features_30_conv_6_fc_0(view_39)
        sigmoid_71 = torch.sigmoid(features_30_conv_6_fc_0)
        mul_90 = features_30_conv_6_fc_0.__mul__(sigmoid_71)
        features_30_conv_6_fc_2 = self.features_30_conv_6_fc_2(mul_90)
        features_30_conv_6_fc_3 = self.features_30_conv_6_fc_3(features_30_conv_6_fc_2)
        view_40 = features_30_conv_6_fc_3.view(size_20[0], size_20[1], 1, 1)
        mul_91 = mul_89.__mul__(view_40)
        features_30_conv_7 = self.features_30_conv_7(mul_91)
        features_30_conv_8 = self.features_30_conv_8(features_30_conv_7)
        add_25 = add_24.__add__(features_30_conv_8)
        features_31_conv_0 = self.features_31_conv_0(add_25)
        features_31_conv_1 = self.features_31_conv_1(features_31_conv_0)
        sigmoid_72 = torch.sigmoid(features_31_conv_1)
        mul_92 = features_31_conv_1.__mul__(sigmoid_72)
        features_31_conv_3 = self.features_31_conv_3(mul_92)
        features_31_conv_4 = self.features_31_conv_4(features_31_conv_3)
        sigmoid_73 = torch.sigmoid(features_31_conv_4)
        mul_93 = features_31_conv_4.__mul__(sigmoid_73)
        size_21 = mul_93.size()
        features_31_conv_6_avg_pool = self.features_31_conv_6_avg_pool(mul_93)
        view_41 = features_31_conv_6_avg_pool.view(size_21[0], size_21[1])
        features_31_conv_6_fc_0 = self.features_31_conv_6_fc_0(view_41)
        sigmoid_74 = torch.sigmoid(features_31_conv_6_fc_0)
        mul_94 = features_31_conv_6_fc_0.__mul__(sigmoid_74)
        features_31_conv_6_fc_2 = self.features_31_conv_6_fc_2(mul_94)
        features_31_conv_6_fc_3 = self.features_31_conv_6_fc_3(features_31_conv_6_fc_2)
        view_42 = features_31_conv_6_fc_3.view(size_21[0], size_21[1], 1, 1)
        mul_95 = mul_93.__mul__(view_42)
        features_31_conv_7 = self.features_31_conv_7(mul_95)
        features_31_conv_8 = self.features_31_conv_8(features_31_conv_7)
        add_26 = add_25.__add__(features_31_conv_8)
        features_32_conv_0 = self.features_32_conv_0(add_26)
        features_32_conv_1 = self.features_32_conv_1(features_32_conv_0)
        sigmoid_75 = torch.sigmoid(features_32_conv_1)
        mul_96 = features_32_conv_1.__mul__(sigmoid_75)
        features_32_conv_3 = self.features_32_conv_3(mul_96)
        features_32_conv_4 = self.features_32_conv_4(features_32_conv_3)
        sigmoid_76 = torch.sigmoid(features_32_conv_4)
        mul_97 = features_32_conv_4.__mul__(sigmoid_76)
        size_22 = mul_97.size()
        features_32_conv_6_avg_pool = self.features_32_conv_6_avg_pool(mul_97)
        view_43 = features_32_conv_6_avg_pool.view(size_22[0], size_22[1])
        features_32_conv_6_fc_0 = self.features_32_conv_6_fc_0(view_43)
        sigmoid_77 = torch.sigmoid(features_32_conv_6_fc_0)
        mul_98 = features_32_conv_6_fc_0.__mul__(sigmoid_77)
        features_32_conv_6_fc_2 = self.features_32_conv_6_fc_2(mul_98)
        features_32_conv_6_fc_3 = self.features_32_conv_6_fc_3(features_32_conv_6_fc_2)
        view_44 = features_32_conv_6_fc_3.view(size_22[0], size_22[1], 1, 1)
        mul_99 = mul_97.__mul__(view_44)
        features_32_conv_7 = self.features_32_conv_7(mul_99)
        features_32_conv_8 = self.features_32_conv_8(features_32_conv_7)
        add_27 = add_26.__add__(features_32_conv_8)
        features_33_conv_0 = self.features_33_conv_0(add_27)
        features_33_conv_1 = self.features_33_conv_1(features_33_conv_0)
        sigmoid_78 = torch.sigmoid(features_33_conv_1)
        mul_100 = features_33_conv_1.__mul__(sigmoid_78)
        features_33_conv_3 = self.features_33_conv_3(mul_100)
        features_33_conv_4 = self.features_33_conv_4(features_33_conv_3)
        sigmoid_79 = torch.sigmoid(features_33_conv_4)
        mul_101 = features_33_conv_4.__mul__(sigmoid_79)
        size_23 = mul_101.size()
        features_33_conv_6_avg_pool = self.features_33_conv_6_avg_pool(mul_101)
        view_45 = features_33_conv_6_avg_pool.view(size_23[0], size_23[1])
        features_33_conv_6_fc_0 = self.features_33_conv_6_fc_0(view_45)
        sigmoid_80 = torch.sigmoid(features_33_conv_6_fc_0)
        mul_102 = features_33_conv_6_fc_0.__mul__(sigmoid_80)
        features_33_conv_6_fc_2 = self.features_33_conv_6_fc_2(mul_102)
        features_33_conv_6_fc_3 = self.features_33_conv_6_fc_3(features_33_conv_6_fc_2)
        view_46 = features_33_conv_6_fc_3.view(size_23[0], size_23[1], 1, 1)
        mul_103 = mul_101.__mul__(view_46)
        features_33_conv_7 = self.features_33_conv_7(mul_103)
        features_33_conv_8 = self.features_33_conv_8(features_33_conv_7)
        add_28 = add_27.__add__(features_33_conv_8)
        features_34_conv_0 = self.features_34_conv_0(add_28)
        features_34_conv_1 = self.features_34_conv_1(features_34_conv_0)
        sigmoid_81 = torch.sigmoid(features_34_conv_1)
        mul_104 = features_34_conv_1.__mul__(sigmoid_81)
        features_34_conv_3 = self.features_34_conv_3(mul_104)
        features_34_conv_4 = self.features_34_conv_4(features_34_conv_3)
        sigmoid_82 = torch.sigmoid(features_34_conv_4)
        mul_105 = features_34_conv_4.__mul__(sigmoid_82)
        size_24 = mul_105.size()
        features_34_conv_6_avg_pool = self.features_34_conv_6_avg_pool(mul_105)
        view_47 = features_34_conv_6_avg_pool.view(size_24[0], size_24[1])
        features_34_conv_6_fc_0 = self.features_34_conv_6_fc_0(view_47)
        sigmoid_83 = torch.sigmoid(features_34_conv_6_fc_0)
        mul_106 = features_34_conv_6_fc_0.__mul__(sigmoid_83)
        features_34_conv_6_fc_2 = self.features_34_conv_6_fc_2(mul_106)
        features_34_conv_6_fc_3 = self.features_34_conv_6_fc_3(features_34_conv_6_fc_2)
        view_48 = features_34_conv_6_fc_3.view(size_24[0], size_24[1], 1, 1)
        mul_107 = mul_105.__mul__(view_48)
        features_34_conv_7 = self.features_34_conv_7(mul_107)
        features_34_conv_8 = self.features_34_conv_8(features_34_conv_7)
        add_29 = add_28.__add__(features_34_conv_8)
        features_35_conv_0 = self.features_35_conv_0(add_29)
        features_35_conv_1 = self.features_35_conv_1(features_35_conv_0)
        sigmoid_84 = torch.sigmoid(features_35_conv_1)
        mul_108 = features_35_conv_1.__mul__(sigmoid_84)
        features_35_conv_3 = self.features_35_conv_3(mul_108)
        features_35_conv_4 = self.features_35_conv_4(features_35_conv_3)
        sigmoid_85 = torch.sigmoid(features_35_conv_4)
        mul_109 = features_35_conv_4.__mul__(sigmoid_85)
        size_25 = mul_109.size()
        features_35_conv_6_avg_pool = self.features_35_conv_6_avg_pool(mul_109)
        view_49 = features_35_conv_6_avg_pool.view(size_25[0], size_25[1])
        features_35_conv_6_fc_0 = self.features_35_conv_6_fc_0(view_49)
        sigmoid_86 = torch.sigmoid(features_35_conv_6_fc_0)
        mul_110 = features_35_conv_6_fc_0.__mul__(sigmoid_86)
        features_35_conv_6_fc_2 = self.features_35_conv_6_fc_2(mul_110)
        features_35_conv_6_fc_3 = self.features_35_conv_6_fc_3(features_35_conv_6_fc_2)
        view_50 = features_35_conv_6_fc_3.view(size_25[0], size_25[1], 1, 1)
        mul_111 = mul_109.__mul__(view_50)
        features_35_conv_7 = self.features_35_conv_7(mul_111)
        features_35_conv_8 = self.features_35_conv_8(features_35_conv_7)
        add_30 = add_29.__add__(features_35_conv_8)
        features_36_conv_0 = self.features_36_conv_0(add_30)
        features_36_conv_1 = self.features_36_conv_1(features_36_conv_0)
        sigmoid_87 = torch.sigmoid(features_36_conv_1)
        mul_112 = features_36_conv_1.__mul__(sigmoid_87)
        features_36_conv_3 = self.features_36_conv_3(mul_112)
        features_36_conv_4 = self.features_36_conv_4(features_36_conv_3)
        sigmoid_88 = torch.sigmoid(features_36_conv_4)
        mul_113 = features_36_conv_4.__mul__(sigmoid_88)
        size_26 = mul_113.size()
        features_36_conv_6_avg_pool = self.features_36_conv_6_avg_pool(mul_113)
        view_51 = features_36_conv_6_avg_pool.view(size_26[0], size_26[1])
        features_36_conv_6_fc_0 = self.features_36_conv_6_fc_0(view_51)
        sigmoid_89 = torch.sigmoid(features_36_conv_6_fc_0)
        mul_114 = features_36_conv_6_fc_0.__mul__(sigmoid_89)
        features_36_conv_6_fc_2 = self.features_36_conv_6_fc_2(mul_114)
        features_36_conv_6_fc_3 = self.features_36_conv_6_fc_3(features_36_conv_6_fc_2)
        view_52 = features_36_conv_6_fc_3.view(size_26[0], size_26[1], 1, 1)
        mul_115 = mul_113.__mul__(view_52)
        features_36_conv_7 = self.features_36_conv_7(mul_115)
        features_36_conv_8 = self.features_36_conv_8(features_36_conv_7)
        add_31 = add_30.__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_90 = torch.sigmoid(features_37_conv_1)
        mul_116 = features_37_conv_1.__mul__(sigmoid_90)
        features_37_conv_3 = self.features_37_conv_3(mul_116)
        features_37_conv_4 = self.features_37_conv_4(features_37_conv_3)
        sigmoid_91 = torch.sigmoid(features_37_conv_4)
        mul_117 = features_37_conv_4.__mul__(sigmoid_91)
        size_27 = mul_117.size()
        features_37_conv_6_avg_pool = self.features_37_conv_6_avg_pool(mul_117)
        view_53 = features_37_conv_6_avg_pool.view(size_27[0], size_27[1])
        features_37_conv_6_fc_0 = self.features_37_conv_6_fc_0(view_53)
        sigmoid_92 = torch.sigmoid(features_37_conv_6_fc_0)
        mul_118 = features_37_conv_6_fc_0.__mul__(sigmoid_92)
        features_37_conv_6_fc_2 = self.features_37_conv_6_fc_2(mul_118)
        features_37_conv_6_fc_3 = self.features_37_conv_6_fc_3(features_37_conv_6_fc_2)
        view_54 = features_37_conv_6_fc_3.view(size_27[0], size_27[1], 1, 1)
        mul_119 = mul_117.__mul__(view_54)
        features_37_conv_7 = self.features_37_conv_7(mul_119)
        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_93 = torch.sigmoid(features_38_conv_1)
        mul_120 = features_38_conv_1.__mul__(sigmoid_93)
        features_38_conv_3 = self.features_38_conv_3(mul_120)
        features_38_conv_4 = self.features_38_conv_4(features_38_conv_3)
        sigmoid_94 = torch.sigmoid(features_38_conv_4)
        mul_121 = features_38_conv_4.__mul__(sigmoid_94)
        size_28 = mul_121.size()
        features_38_conv_6_avg_pool = self.features_38_conv_6_avg_pool(mul_121)
        view_55 = features_38_conv_6_avg_pool.view(size_28[0], size_28[1])
        features_38_conv_6_fc_0 = self.features_38_conv_6_fc_0(view_55)
        sigmoid_95 = torch.sigmoid(features_38_conv_6_fc_0)
        mul_122 = features_38_conv_6_fc_0.__mul__(sigmoid_95)
        features_38_conv_6_fc_2 = self.features_38_conv_6_fc_2(mul_122)
        features_38_conv_6_fc_3 = self.features_38_conv_6_fc_3(features_38_conv_6_fc_2)
        view_56 = features_38_conv_6_fc_3.view(size_28[0], size_28[1], 1, 1)
        mul_123 = mul_121.__mul__(view_56)
        features_38_conv_7 = self.features_38_conv_7(mul_123)
        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_96 = torch.sigmoid(features_39_conv_1)
        mul_124 = features_39_conv_1.__mul__(sigmoid_96)
        features_39_conv_3 = self.features_39_conv_3(mul_124)
        features_39_conv_4 = self.features_39_conv_4(features_39_conv_3)
        sigmoid_97 = torch.sigmoid(features_39_conv_4)
        mul_125 = features_39_conv_4.__mul__(sigmoid_97)
        size_29 = mul_125.size()
        features_39_conv_6_avg_pool = self.features_39_conv_6_avg_pool(mul_125)
        view_57 = features_39_conv_6_avg_pool.view(size_29[0], size_29[1])
        features_39_conv_6_fc_0 = self.features_39_conv_6_fc_0(view_57)
        sigmoid_98 = torch.sigmoid(features_39_conv_6_fc_0)
        mul_126 = features_39_conv_6_fc_0.__mul__(sigmoid_98)
        features_39_conv_6_fc_2 = self.features_39_conv_6_fc_2(mul_126)
        features_39_conv_6_fc_3 = self.features_39_conv_6_fc_3(features_39_conv_6_fc_2)
        view_58 = features_39_conv_6_fc_3.view(size_29[0], size_29[1], 1, 1)
        mul_127 = mul_125.__mul__(view_58)
        features_39_conv_7 = self.features_39_conv_7(mul_127)
        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_99 = torch.sigmoid(features_40_conv_1)
        mul_128 = features_40_conv_1.__mul__(sigmoid_99)
        features_40_conv_3 = self.features_40_conv_3(mul_128)
        features_40_conv_4 = self.features_40_conv_4(features_40_conv_3)
        sigmoid_100 = torch.sigmoid(features_40_conv_4)
        mul_129 = features_40_conv_4.__mul__(sigmoid_100)
        size_30 = mul_129.size()
        features_40_conv_6_avg_pool = self.features_40_conv_6_avg_pool(mul_129)
        view_59 = features_40_conv_6_avg_pool.view(size_30[0], size_30[1])
        features_40_conv_6_fc_0 = self.features_40_conv_6_fc_0(view_59)
        sigmoid_101 = torch.sigmoid(features_40_conv_6_fc_0)
        mul_130 = features_40_conv_6_fc_0.__mul__(sigmoid_101)
        features_40_conv_6_fc_2 = self.features_40_conv_6_fc_2(mul_130)
        features_40_conv_6_fc_3 = self.features_40_conv_6_fc_3(features_40_conv_6_fc_2)
        view_60 = features_40_conv_6_fc_3.view(size_30[0], size_30[1], 1, 1)
        mul_131 = mul_129.__mul__(view_60)
        features_40_conv_7 = self.features_40_conv_7(mul_131)
        features_40_conv_8 = self.features_40_conv_8(features_40_conv_7)
        add_35 = add_34.__add__(features_40_conv_8)
        conv_0 = self.conv_0(add_35)
        conv_1 = self.conv_1(conv_0)
        sigmoid_102 = torch.sigmoid(conv_1)
        mul_132 = conv_1.__mul__(sigmoid_102)
        avgpool = self.avgpool(mul_132)
        size_31 = avgpool.size(0)
        view_61 = avgpool.view(size_31, -1)
        classifier = self.classifier(view_61)
        return classifier


if __name__ == "__main__":
    model = efficientnet_v2_s()

    model.eval()
    model.cpu()

    dummy_input_0 = torch.ones((1, 3, 224, 224), dtype=torch.float32)

    output = model(dummy_input_0)
    print(output)