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


class efficientnet_v2_xl(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, 32, 1, 1, 0, bias=False)
        self.features_1_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(32)
        self.features_2_conv_0 = torch.nn.modules.conv.Conv2d(32, 32, 3, 1, 1, bias=False)
        self.features_2_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(32)
        self.features_2_conv_3 = torch.nn.modules.conv.Conv2d(32, 32, 1, 1, 0, bias=False)
        self.features_2_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(32)
        self.features_3_conv_0 = torch.nn.modules.conv.Conv2d(32, 32, 3, 1, 1, bias=False)
        self.features_3_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(32)
        self.features_3_conv_3 = torch.nn.modules.conv.Conv2d(32, 32, 1, 1, 0, bias=False)
        self.features_3_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(32)
        self.features_4_conv_0 = torch.nn.modules.conv.Conv2d(32, 32, 3, 1, 1, bias=False)
        self.features_4_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(32)
        self.features_4_conv_3 = torch.nn.modules.conv.Conv2d(32, 32, 1, 1, 0, bias=False)
        self.features_4_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(32)
        self.features_5_conv_0 = torch.nn.modules.conv.Conv2d(32, 128, 3, 2, 1, bias=False)
        self.features_5_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(128)
        self.features_5_conv_3 = torch.nn.modules.conv.Conv2d(128, 64, 1, 1, 0, bias=False)
        self.features_5_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(64)
        self.features_6_conv_0 = torch.nn.modules.conv.Conv2d(64, 256, 3, 1, 1, bias=False)
        self.features_6_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(256)
        self.features_6_conv_3 = torch.nn.modules.conv.Conv2d(256, 64, 1, 1, 0, bias=False)
        self.features_6_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(64)
        self.features_7_conv_0 = torch.nn.modules.conv.Conv2d(64, 256, 3, 1, 1, bias=False)
        self.features_7_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(256)
        self.features_7_conv_3 = torch.nn.modules.conv.Conv2d(256, 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, 3, 1, 1, bias=False)
        self.features_11_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(256)
        self.features_11_conv_3 = torch.nn.modules.conv.Conv2d(256, 64, 1, 1, 0, bias=False)
        self.features_11_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(64)
        self.features_12_conv_0 = torch.nn.modules.conv.Conv2d(64, 256, 3, 1, 1, bias=False)
        self.features_12_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(256)
        self.features_12_conv_3 = torch.nn.modules.conv.Conv2d(256, 64, 1, 1, 0, bias=False)
        self.features_12_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(64)
        self.features_13_conv_0 = torch.nn.modules.conv.Conv2d(64, 256, 3, 2, 1, bias=False)
        self.features_13_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(256)
        self.features_13_conv_3 = torch.nn.modules.conv.Conv2d(256, 96, 1, 1, 0, bias=False)
        self.features_13_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(96)
        self.features_14_conv_0 = torch.nn.modules.conv.Conv2d(96, 384, 3, 1, 1, bias=False)
        self.features_14_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(384)
        self.features_14_conv_3 = torch.nn.modules.conv.Conv2d(384, 96, 1, 1, 0, bias=False)
        self.features_14_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(96)
        self.features_15_conv_0 = torch.nn.modules.conv.Conv2d(96, 384, 3, 1, 1, bias=False)
        self.features_15_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(384)
        self.features_15_conv_3 = torch.nn.modules.conv.Conv2d(384, 96, 1, 1, 0, bias=False)
        self.features_15_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(96)
        self.features_16_conv_0 = torch.nn.modules.conv.Conv2d(96, 384, 3, 1, 1, bias=False)
        self.features_16_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(384)
        self.features_16_conv_3 = torch.nn.modules.conv.Conv2d(384, 96, 1, 1, 0, bias=False)
        self.features_16_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(96)
        self.features_17_conv_0 = torch.nn.modules.conv.Conv2d(96, 384, 3, 1, 1, bias=False)
        self.features_17_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(384)
        self.features_17_conv_3 = torch.nn.modules.conv.Conv2d(384, 96, 1, 1, 0, bias=False)
        self.features_17_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(96)
        self.features_18_conv_0 = torch.nn.modules.conv.Conv2d(96, 384, 3, 1, 1, bias=False)
        self.features_18_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(384)
        self.features_18_conv_3 = torch.nn.modules.conv.Conv2d(384, 96, 1, 1, 0, bias=False)
        self.features_18_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(96)
        self.features_19_conv_0 = torch.nn.modules.conv.Conv2d(96, 384, 3, 1, 1, bias=False)
        self.features_19_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(384)
        self.features_19_conv_3 = torch.nn.modules.conv.Conv2d(384, 96, 1, 1, 0, bias=False)
        self.features_19_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(96)
        self.features_20_conv_0 = torch.nn.modules.conv.Conv2d(96, 384, 3, 1, 1, bias=False)
        self.features_20_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(384)
        self.features_20_conv_3 = torch.nn.modules.conv.Conv2d(384, 96, 1, 1, 0, bias=False)
        self.features_20_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(96)
        self.features_21_conv_0 = torch.nn.modules.conv.Conv2d(96, 384, 1, 1, 0, bias=False)
        self.features_21_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(384)
        self.features_21_conv_3 = torch.nn.modules.conv.Conv2d(384, 384, 3, 2, 1, groups=384, bias=False)
        self.features_21_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(384)
        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(384, 24)
        self.features_21_conv_6_fc_2 = torch.nn.modules.linear.Linear(24, 384)
        self.features_21_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_21_conv_7 = torch.nn.modules.conv.Conv2d(384, 192, 1, 1, 0, bias=False)
        self.features_21_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(192)
        self.features_22_conv_0 = torch.nn.modules.conv.Conv2d(192, 768, 1, 1, 0, bias=False)
        self.features_22_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(768)
        self.features_22_conv_3 = torch.nn.modules.conv.Conv2d(768, 768, 3, 1, 1, groups=768, bias=False)
        self.features_22_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(768)
        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(768, 48)
        self.features_22_conv_6_fc_2 = torch.nn.modules.linear.Linear(48, 768)
        self.features_22_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_22_conv_7 = torch.nn.modules.conv.Conv2d(768, 192, 1, 1, 0, bias=False)
        self.features_22_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(192)
        self.features_23_conv_0 = torch.nn.modules.conv.Conv2d(192, 768, 1, 1, 0, bias=False)
        self.features_23_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(768)
        self.features_23_conv_3 = torch.nn.modules.conv.Conv2d(768, 768, 3, 1, 1, groups=768, bias=False)
        self.features_23_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(768)
        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(768, 48)
        self.features_23_conv_6_fc_2 = torch.nn.modules.linear.Linear(48, 768)
        self.features_23_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_23_conv_7 = torch.nn.modules.conv.Conv2d(768, 192, 1, 1, 0, bias=False)
        self.features_23_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(192)
        self.features_24_conv_0 = torch.nn.modules.conv.Conv2d(192, 768, 1, 1, 0, bias=False)
        self.features_24_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(768)
        self.features_24_conv_3 = torch.nn.modules.conv.Conv2d(768, 768, 3, 1, 1, groups=768, bias=False)
        self.features_24_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(768)
        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(768, 48)
        self.features_24_conv_6_fc_2 = torch.nn.modules.linear.Linear(48, 768)
        self.features_24_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_24_conv_7 = torch.nn.modules.conv.Conv2d(768, 192, 1, 1, 0, bias=False)
        self.features_24_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(192)
        self.features_25_conv_0 = torch.nn.modules.conv.Conv2d(192, 768, 1, 1, 0, bias=False)
        self.features_25_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(768)
        self.features_25_conv_3 = torch.nn.modules.conv.Conv2d(768, 768, 3, 1, 1, groups=768, bias=False)
        self.features_25_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(768)
        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(768, 48)
        self.features_25_conv_6_fc_2 = torch.nn.modules.linear.Linear(48, 768)
        self.features_25_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_25_conv_7 = torch.nn.modules.conv.Conv2d(768, 192, 1, 1, 0, bias=False)
        self.features_25_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(192)
        self.features_26_conv_0 = torch.nn.modules.conv.Conv2d(192, 768, 1, 1, 0, bias=False)
        self.features_26_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(768)
        self.features_26_conv_3 = torch.nn.modules.conv.Conv2d(768, 768, 3, 1, 1, groups=768, bias=False)
        self.features_26_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(768)
        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(768, 48)
        self.features_26_conv_6_fc_2 = torch.nn.modules.linear.Linear(48, 768)
        self.features_26_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_26_conv_7 = torch.nn.modules.conv.Conv2d(768, 192, 1, 1, 0, bias=False)
        self.features_26_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(192)
        self.features_27_conv_0 = torch.nn.modules.conv.Conv2d(192, 768, 1, 1, 0, bias=False)
        self.features_27_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(768)
        self.features_27_conv_3 = torch.nn.modules.conv.Conv2d(768, 768, 3, 1, 1, groups=768, bias=False)
        self.features_27_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(768)
        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(768, 48)
        self.features_27_conv_6_fc_2 = torch.nn.modules.linear.Linear(48, 768)
        self.features_27_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_27_conv_7 = torch.nn.modules.conv.Conv2d(768, 192, 1, 1, 0, bias=False)
        self.features_27_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(192)
        self.features_28_conv_0 = torch.nn.modules.conv.Conv2d(192, 768, 1, 1, 0, bias=False)
        self.features_28_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(768)
        self.features_28_conv_3 = torch.nn.modules.conv.Conv2d(768, 768, 3, 1, 1, groups=768, bias=False)
        self.features_28_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(768)
        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(768, 48)
        self.features_28_conv_6_fc_2 = torch.nn.modules.linear.Linear(48, 768)
        self.features_28_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_28_conv_7 = torch.nn.modules.conv.Conv2d(768, 192, 1, 1, 0, bias=False)
        self.features_28_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(192)
        self.features_29_conv_0 = torch.nn.modules.conv.Conv2d(192, 768, 1, 1, 0, bias=False)
        self.features_29_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(768)
        self.features_29_conv_3 = torch.nn.modules.conv.Conv2d(768, 768, 3, 1, 1, groups=768, bias=False)
        self.features_29_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(768)
        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(768, 48)
        self.features_29_conv_6_fc_2 = torch.nn.modules.linear.Linear(48, 768)
        self.features_29_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_29_conv_7 = torch.nn.modules.conv.Conv2d(768, 192, 1, 1, 0, bias=False)
        self.features_29_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(192)
        self.features_30_conv_0 = torch.nn.modules.conv.Conv2d(192, 768, 1, 1, 0, bias=False)
        self.features_30_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(768)
        self.features_30_conv_3 = torch.nn.modules.conv.Conv2d(768, 768, 3, 1, 1, groups=768, bias=False)
        self.features_30_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(768)
        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(768, 48)
        self.features_30_conv_6_fc_2 = torch.nn.modules.linear.Linear(48, 768)
        self.features_30_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_30_conv_7 = torch.nn.modules.conv.Conv2d(768, 192, 1, 1, 0, bias=False)
        self.features_30_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(192)
        self.features_31_conv_0 = torch.nn.modules.conv.Conv2d(192, 768, 1, 1, 0, bias=False)
        self.features_31_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(768)
        self.features_31_conv_3 = torch.nn.modules.conv.Conv2d(768, 768, 3, 1, 1, groups=768, bias=False)
        self.features_31_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(768)
        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(768, 48)
        self.features_31_conv_6_fc_2 = torch.nn.modules.linear.Linear(48, 768)
        self.features_31_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_31_conv_7 = torch.nn.modules.conv.Conv2d(768, 192, 1, 1, 0, bias=False)
        self.features_31_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(192)
        self.features_32_conv_0 = torch.nn.modules.conv.Conv2d(192, 768, 1, 1, 0, bias=False)
        self.features_32_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(768)
        self.features_32_conv_3 = torch.nn.modules.conv.Conv2d(768, 768, 3, 1, 1, groups=768, bias=False)
        self.features_32_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(768)
        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(768, 48)
        self.features_32_conv_6_fc_2 = torch.nn.modules.linear.Linear(48, 768)
        self.features_32_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_32_conv_7 = torch.nn.modules.conv.Conv2d(768, 192, 1, 1, 0, bias=False)
        self.features_32_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(192)
        self.features_33_conv_0 = torch.nn.modules.conv.Conv2d(192, 768, 1, 1, 0, bias=False)
        self.features_33_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(768)
        self.features_33_conv_3 = torch.nn.modules.conv.Conv2d(768, 768, 3, 1, 1, groups=768, bias=False)
        self.features_33_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(768)
        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(768, 48)
        self.features_33_conv_6_fc_2 = torch.nn.modules.linear.Linear(48, 768)
        self.features_33_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_33_conv_7 = torch.nn.modules.conv.Conv2d(768, 192, 1, 1, 0, bias=False)
        self.features_33_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(192)
        self.features_34_conv_0 = torch.nn.modules.conv.Conv2d(192, 768, 1, 1, 0, bias=False)
        self.features_34_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(768)
        self.features_34_conv_3 = torch.nn.modules.conv.Conv2d(768, 768, 3, 1, 1, groups=768, bias=False)
        self.features_34_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(768)
        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(768, 48)
        self.features_34_conv_6_fc_2 = torch.nn.modules.linear.Linear(48, 768)
        self.features_34_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_34_conv_7 = torch.nn.modules.conv.Conv2d(768, 192, 1, 1, 0, bias=False)
        self.features_34_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(192)
        self.features_35_conv_0 = torch.nn.modules.conv.Conv2d(192, 768, 1, 1, 0, bias=False)
        self.features_35_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(768)
        self.features_35_conv_3 = torch.nn.modules.conv.Conv2d(768, 768, 3, 1, 1, groups=768, bias=False)
        self.features_35_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(768)
        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(768, 48)
        self.features_35_conv_6_fc_2 = torch.nn.modules.linear.Linear(48, 768)
        self.features_35_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_35_conv_7 = torch.nn.modules.conv.Conv2d(768, 192, 1, 1, 0, bias=False)
        self.features_35_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(192)
        self.features_36_conv_0 = torch.nn.modules.conv.Conv2d(192, 768, 1, 1, 0, bias=False)
        self.features_36_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(768)
        self.features_36_conv_3 = torch.nn.modules.conv.Conv2d(768, 768, 3, 1, 1, groups=768, bias=False)
        self.features_36_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(768)
        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(768, 48)
        self.features_36_conv_6_fc_2 = torch.nn.modules.linear.Linear(48, 768)
        self.features_36_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_36_conv_7 = torch.nn.modules.conv.Conv2d(768, 192, 1, 1, 0, bias=False)
        self.features_36_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(192)
        self.features_37_conv_0 = torch.nn.modules.conv.Conv2d(192, 1152, 1, 1, 0, bias=False)
        self.features_37_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1152)
        self.features_37_conv_3 = torch.nn.modules.conv.Conv2d(1152, 1152, 3, 1, 1, groups=1152, bias=False)
        self.features_37_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1152)
        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(1152, 48)
        self.features_37_conv_6_fc_2 = torch.nn.modules.linear.Linear(48, 1152)
        self.features_37_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_37_conv_7 = torch.nn.modules.conv.Conv2d(1152, 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.features_41_conv_0 = torch.nn.modules.conv.Conv2d(256, 1536, 1, 1, 0, bias=False)
        self.features_41_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        self.features_41_conv_3 = torch.nn.modules.conv.Conv2d(1536, 1536, 3, 1, 1, groups=1536, bias=False)
        self.features_41_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        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(1536, 64)
        self.features_41_conv_6_fc_2 = torch.nn.modules.linear.Linear(64, 1536)
        self.features_41_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_41_conv_7 = torch.nn.modules.conv.Conv2d(1536, 256, 1, 1, 0, bias=False)
        self.features_41_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(256)
        self.features_42_conv_0 = torch.nn.modules.conv.Conv2d(256, 1536, 1, 1, 0, bias=False)
        self.features_42_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        self.features_42_conv_3 = torch.nn.modules.conv.Conv2d(1536, 1536, 3, 1, 1, groups=1536, bias=False)
        self.features_42_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        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(1536, 64)
        self.features_42_conv_6_fc_2 = torch.nn.modules.linear.Linear(64, 1536)
        self.features_42_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_42_conv_7 = torch.nn.modules.conv.Conv2d(1536, 256, 1, 1, 0, bias=False)
        self.features_42_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(256)
        self.features_43_conv_0 = torch.nn.modules.conv.Conv2d(256, 1536, 1, 1, 0, bias=False)
        self.features_43_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        self.features_43_conv_3 = torch.nn.modules.conv.Conv2d(1536, 1536, 3, 1, 1, groups=1536, bias=False)
        self.features_43_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        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(1536, 64)
        self.features_43_conv_6_fc_2 = torch.nn.modules.linear.Linear(64, 1536)
        self.features_43_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_43_conv_7 = torch.nn.modules.conv.Conv2d(1536, 256, 1, 1, 0, bias=False)
        self.features_43_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(256)
        self.features_44_conv_0 = torch.nn.modules.conv.Conv2d(256, 1536, 1, 1, 0, bias=False)
        self.features_44_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        self.features_44_conv_3 = torch.nn.modules.conv.Conv2d(1536, 1536, 3, 1, 1, groups=1536, bias=False)
        self.features_44_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        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(1536, 64)
        self.features_44_conv_6_fc_2 = torch.nn.modules.linear.Linear(64, 1536)
        self.features_44_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_44_conv_7 = torch.nn.modules.conv.Conv2d(1536, 256, 1, 1, 0, bias=False)
        self.features_44_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(256)
        self.features_45_conv_0 = torch.nn.modules.conv.Conv2d(256, 1536, 1, 1, 0, bias=False)
        self.features_45_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        self.features_45_conv_3 = torch.nn.modules.conv.Conv2d(1536, 1536, 3, 1, 1, groups=1536, bias=False)
        self.features_45_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        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(1536, 64)
        self.features_45_conv_6_fc_2 = torch.nn.modules.linear.Linear(64, 1536)
        self.features_45_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_45_conv_7 = torch.nn.modules.conv.Conv2d(1536, 256, 1, 1, 0, bias=False)
        self.features_45_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(256)
        self.features_46_conv_0 = torch.nn.modules.conv.Conv2d(256, 1536, 1, 1, 0, bias=False)
        self.features_46_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        self.features_46_conv_3 = torch.nn.modules.conv.Conv2d(1536, 1536, 3, 1, 1, groups=1536, bias=False)
        self.features_46_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        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(1536, 64)
        self.features_46_conv_6_fc_2 = torch.nn.modules.linear.Linear(64, 1536)
        self.features_46_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_46_conv_7 = torch.nn.modules.conv.Conv2d(1536, 256, 1, 1, 0, bias=False)
        self.features_46_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(256)
        self.features_47_conv_0 = torch.nn.modules.conv.Conv2d(256, 1536, 1, 1, 0, bias=False)
        self.features_47_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        self.features_47_conv_3 = torch.nn.modules.conv.Conv2d(1536, 1536, 3, 1, 1, groups=1536, bias=False)
        self.features_47_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        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(1536, 64)
        self.features_47_conv_6_fc_2 = torch.nn.modules.linear.Linear(64, 1536)
        self.features_47_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_47_conv_7 = torch.nn.modules.conv.Conv2d(1536, 256, 1, 1, 0, bias=False)
        self.features_47_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(256)
        self.features_48_conv_0 = torch.nn.modules.conv.Conv2d(256, 1536, 1, 1, 0, bias=False)
        self.features_48_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        self.features_48_conv_3 = torch.nn.modules.conv.Conv2d(1536, 1536, 3, 1, 1, groups=1536, bias=False)
        self.features_48_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        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(1536, 64)
        self.features_48_conv_6_fc_2 = torch.nn.modules.linear.Linear(64, 1536)
        self.features_48_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_48_conv_7 = torch.nn.modules.conv.Conv2d(1536, 256, 1, 1, 0, bias=False)
        self.features_48_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(256)
        self.features_49_conv_0 = torch.nn.modules.conv.Conv2d(256, 1536, 1, 1, 0, bias=False)
        self.features_49_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        self.features_49_conv_3 = torch.nn.modules.conv.Conv2d(1536, 1536, 3, 1, 1, groups=1536, bias=False)
        self.features_49_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        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(1536, 64)
        self.features_49_conv_6_fc_2 = torch.nn.modules.linear.Linear(64, 1536)
        self.features_49_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_49_conv_7 = torch.nn.modules.conv.Conv2d(1536, 256, 1, 1, 0, bias=False)
        self.features_49_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(256)
        self.features_50_conv_0 = torch.nn.modules.conv.Conv2d(256, 1536, 1, 1, 0, bias=False)
        self.features_50_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        self.features_50_conv_3 = torch.nn.modules.conv.Conv2d(1536, 1536, 3, 1, 1, groups=1536, bias=False)
        self.features_50_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        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(1536, 64)
        self.features_50_conv_6_fc_2 = torch.nn.modules.linear.Linear(64, 1536)
        self.features_50_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_50_conv_7 = torch.nn.modules.conv.Conv2d(1536, 256, 1, 1, 0, bias=False)
        self.features_50_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(256)
        self.features_51_conv_0 = torch.nn.modules.conv.Conv2d(256, 1536, 1, 1, 0, bias=False)
        self.features_51_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        self.features_51_conv_3 = torch.nn.modules.conv.Conv2d(1536, 1536, 3, 1, 1, groups=1536, bias=False)
        self.features_51_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        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(1536, 64)
        self.features_51_conv_6_fc_2 = torch.nn.modules.linear.Linear(64, 1536)
        self.features_51_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_51_conv_7 = torch.nn.modules.conv.Conv2d(1536, 256, 1, 1, 0, bias=False)
        self.features_51_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(256)
        self.features_52_conv_0 = torch.nn.modules.conv.Conv2d(256, 1536, 1, 1, 0, bias=False)
        self.features_52_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        self.features_52_conv_3 = torch.nn.modules.conv.Conv2d(1536, 1536, 3, 1, 1, groups=1536, bias=False)
        self.features_52_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        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(1536, 64)
        self.features_52_conv_6_fc_2 = torch.nn.modules.linear.Linear(64, 1536)
        self.features_52_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_52_conv_7 = torch.nn.modules.conv.Conv2d(1536, 256, 1, 1, 0, bias=False)
        self.features_52_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(256)
        self.features_53_conv_0 = torch.nn.modules.conv.Conv2d(256, 1536, 1, 1, 0, bias=False)
        self.features_53_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        self.features_53_conv_3 = torch.nn.modules.conv.Conv2d(1536, 1536, 3, 1, 1, groups=1536, bias=False)
        self.features_53_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        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(1536, 64)
        self.features_53_conv_6_fc_2 = torch.nn.modules.linear.Linear(64, 1536)
        self.features_53_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_53_conv_7 = torch.nn.modules.conv.Conv2d(1536, 256, 1, 1, 0, bias=False)
        self.features_53_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(256)
        self.features_54_conv_0 = torch.nn.modules.conv.Conv2d(256, 1536, 1, 1, 0, bias=False)
        self.features_54_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        self.features_54_conv_3 = torch.nn.modules.conv.Conv2d(1536, 1536, 3, 1, 1, groups=1536, bias=False)
        self.features_54_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        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(1536, 64)
        self.features_54_conv_6_fc_2 = torch.nn.modules.linear.Linear(64, 1536)
        self.features_54_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_54_conv_7 = torch.nn.modules.conv.Conv2d(1536, 256, 1, 1, 0, bias=False)
        self.features_54_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(256)
        self.features_55_conv_0 = torch.nn.modules.conv.Conv2d(256, 1536, 1, 1, 0, bias=False)
        self.features_55_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        self.features_55_conv_3 = torch.nn.modules.conv.Conv2d(1536, 1536, 3, 1, 1, groups=1536, bias=False)
        self.features_55_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        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(1536, 64)
        self.features_55_conv_6_fc_2 = torch.nn.modules.linear.Linear(64, 1536)
        self.features_55_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_55_conv_7 = torch.nn.modules.conv.Conv2d(1536, 256, 1, 1, 0, bias=False)
        self.features_55_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(256)
        self.features_56_conv_0 = torch.nn.modules.conv.Conv2d(256, 1536, 1, 1, 0, bias=False)
        self.features_56_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        self.features_56_conv_3 = torch.nn.modules.conv.Conv2d(1536, 1536, 3, 1, 1, groups=1536, bias=False)
        self.features_56_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        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(1536, 64)
        self.features_56_conv_6_fc_2 = torch.nn.modules.linear.Linear(64, 1536)
        self.features_56_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_56_conv_7 = torch.nn.modules.conv.Conv2d(1536, 256, 1, 1, 0, bias=False)
        self.features_56_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(256)
        self.features_57_conv_0 = torch.nn.modules.conv.Conv2d(256, 1536, 1, 1, 0, bias=False)
        self.features_57_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        self.features_57_conv_3 = torch.nn.modules.conv.Conv2d(1536, 1536, 3, 1, 1, groups=1536, bias=False)
        self.features_57_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        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(1536, 64)
        self.features_57_conv_6_fc_2 = torch.nn.modules.linear.Linear(64, 1536)
        self.features_57_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_57_conv_7 = torch.nn.modules.conv.Conv2d(1536, 256, 1, 1, 0, bias=False)
        self.features_57_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(256)
        self.features_58_conv_0 = torch.nn.modules.conv.Conv2d(256, 1536, 1, 1, 0, bias=False)
        self.features_58_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        self.features_58_conv_3 = torch.nn.modules.conv.Conv2d(1536, 1536, 3, 1, 1, groups=1536, bias=False)
        self.features_58_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        self.features_58_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1)
        self.features_58_conv_6_fc_0 = torch.nn.modules.linear.Linear(1536, 64)
        self.features_58_conv_6_fc_2 = torch.nn.modules.linear.Linear(64, 1536)
        self.features_58_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_58_conv_7 = torch.nn.modules.conv.Conv2d(1536, 256, 1, 1, 0, bias=False)
        self.features_58_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(256)
        self.features_59_conv_0 = torch.nn.modules.conv.Conv2d(256, 1536, 1, 1, 0, bias=False)
        self.features_59_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        self.features_59_conv_3 = torch.nn.modules.conv.Conv2d(1536, 1536, 3, 1, 1, groups=1536, bias=False)
        self.features_59_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        self.features_59_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1)
        self.features_59_conv_6_fc_0 = torch.nn.modules.linear.Linear(1536, 64)
        self.features_59_conv_6_fc_2 = torch.nn.modules.linear.Linear(64, 1536)
        self.features_59_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_59_conv_7 = torch.nn.modules.conv.Conv2d(1536, 256, 1, 1, 0, bias=False)
        self.features_59_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(256)
        self.features_60_conv_0 = torch.nn.modules.conv.Conv2d(256, 1536, 1, 1, 0, bias=False)
        self.features_60_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        self.features_60_conv_3 = torch.nn.modules.conv.Conv2d(1536, 1536, 3, 1, 1, groups=1536, bias=False)
        self.features_60_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        self.features_60_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1)
        self.features_60_conv_6_fc_0 = torch.nn.modules.linear.Linear(1536, 64)
        self.features_60_conv_6_fc_2 = torch.nn.modules.linear.Linear(64, 1536)
        self.features_60_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_60_conv_7 = torch.nn.modules.conv.Conv2d(1536, 256, 1, 1, 0, bias=False)
        self.features_60_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(256)
        self.features_61_conv_0 = torch.nn.modules.conv.Conv2d(256, 1536, 1, 1, 0, bias=False)
        self.features_61_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        self.features_61_conv_3 = torch.nn.modules.conv.Conv2d(1536, 1536, 3, 2, 1, groups=1536, bias=False)
        self.features_61_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1536)
        self.features_61_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1)
        self.features_61_conv_6_fc_0 = torch.nn.modules.linear.Linear(1536, 64)
        self.features_61_conv_6_fc_2 = torch.nn.modules.linear.Linear(64, 1536)
        self.features_61_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_61_conv_7 = torch.nn.modules.conv.Conv2d(1536, 512, 1, 1, 0, bias=False)
        self.features_61_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(512)
        self.features_62_conv_0 = torch.nn.modules.conv.Conv2d(512, 3072, 1, 1, 0, bias=False)
        self.features_62_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_62_conv_3 = torch.nn.modules.conv.Conv2d(3072, 3072, 3, 1, 1, groups=3072, bias=False)
        self.features_62_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_62_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1)
        self.features_62_conv_6_fc_0 = torch.nn.modules.linear.Linear(3072, 128)
        self.features_62_conv_6_fc_2 = torch.nn.modules.linear.Linear(128, 3072)
        self.features_62_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_62_conv_7 = torch.nn.modules.conv.Conv2d(3072, 512, 1, 1, 0, bias=False)
        self.features_62_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(512)
        self.features_63_conv_0 = torch.nn.modules.conv.Conv2d(512, 3072, 1, 1, 0, bias=False)
        self.features_63_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_63_conv_3 = torch.nn.modules.conv.Conv2d(3072, 3072, 3, 1, 1, groups=3072, bias=False)
        self.features_63_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_63_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1)
        self.features_63_conv_6_fc_0 = torch.nn.modules.linear.Linear(3072, 128)
        self.features_63_conv_6_fc_2 = torch.nn.modules.linear.Linear(128, 3072)
        self.features_63_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_63_conv_7 = torch.nn.modules.conv.Conv2d(3072, 512, 1, 1, 0, bias=False)
        self.features_63_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(512)
        self.features_64_conv_0 = torch.nn.modules.conv.Conv2d(512, 3072, 1, 1, 0, bias=False)
        self.features_64_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_64_conv_3 = torch.nn.modules.conv.Conv2d(3072, 3072, 3, 1, 1, groups=3072, bias=False)
        self.features_64_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_64_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1)
        self.features_64_conv_6_fc_0 = torch.nn.modules.linear.Linear(3072, 128)
        self.features_64_conv_6_fc_2 = torch.nn.modules.linear.Linear(128, 3072)
        self.features_64_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_64_conv_7 = torch.nn.modules.conv.Conv2d(3072, 512, 1, 1, 0, bias=False)
        self.features_64_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(512)
        self.features_65_conv_0 = torch.nn.modules.conv.Conv2d(512, 3072, 1, 1, 0, bias=False)
        self.features_65_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_65_conv_3 = torch.nn.modules.conv.Conv2d(3072, 3072, 3, 1, 1, groups=3072, bias=False)
        self.features_65_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_65_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1)
        self.features_65_conv_6_fc_0 = torch.nn.modules.linear.Linear(3072, 128)
        self.features_65_conv_6_fc_2 = torch.nn.modules.linear.Linear(128, 3072)
        self.features_65_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_65_conv_7 = torch.nn.modules.conv.Conv2d(3072, 512, 1, 1, 0, bias=False)
        self.features_65_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(512)
        self.features_66_conv_0 = torch.nn.modules.conv.Conv2d(512, 3072, 1, 1, 0, bias=False)
        self.features_66_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_66_conv_3 = torch.nn.modules.conv.Conv2d(3072, 3072, 3, 1, 1, groups=3072, bias=False)
        self.features_66_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_66_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1)
        self.features_66_conv_6_fc_0 = torch.nn.modules.linear.Linear(3072, 128)
        self.features_66_conv_6_fc_2 = torch.nn.modules.linear.Linear(128, 3072)
        self.features_66_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_66_conv_7 = torch.nn.modules.conv.Conv2d(3072, 512, 1, 1, 0, bias=False)
        self.features_66_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(512)
        self.features_67_conv_0 = torch.nn.modules.conv.Conv2d(512, 3072, 1, 1, 0, bias=False)
        self.features_67_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_67_conv_3 = torch.nn.modules.conv.Conv2d(3072, 3072, 3, 1, 1, groups=3072, bias=False)
        self.features_67_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_67_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1)
        self.features_67_conv_6_fc_0 = torch.nn.modules.linear.Linear(3072, 128)
        self.features_67_conv_6_fc_2 = torch.nn.modules.linear.Linear(128, 3072)
        self.features_67_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_67_conv_7 = torch.nn.modules.conv.Conv2d(3072, 512, 1, 1, 0, bias=False)
        self.features_67_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(512)
        self.features_68_conv_0 = torch.nn.modules.conv.Conv2d(512, 3072, 1, 1, 0, bias=False)
        self.features_68_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_68_conv_3 = torch.nn.modules.conv.Conv2d(3072, 3072, 3, 1, 1, groups=3072, bias=False)
        self.features_68_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_68_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1)
        self.features_68_conv_6_fc_0 = torch.nn.modules.linear.Linear(3072, 128)
        self.features_68_conv_6_fc_2 = torch.nn.modules.linear.Linear(128, 3072)
        self.features_68_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_68_conv_7 = torch.nn.modules.conv.Conv2d(3072, 512, 1, 1, 0, bias=False)
        self.features_68_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(512)
        self.features_69_conv_0 = torch.nn.modules.conv.Conv2d(512, 3072, 1, 1, 0, bias=False)
        self.features_69_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_69_conv_3 = torch.nn.modules.conv.Conv2d(3072, 3072, 3, 1, 1, groups=3072, bias=False)
        self.features_69_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_69_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1)
        self.features_69_conv_6_fc_0 = torch.nn.modules.linear.Linear(3072, 128)
        self.features_69_conv_6_fc_2 = torch.nn.modules.linear.Linear(128, 3072)
        self.features_69_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_69_conv_7 = torch.nn.modules.conv.Conv2d(3072, 512, 1, 1, 0, bias=False)
        self.features_69_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(512)
        self.features_70_conv_0 = torch.nn.modules.conv.Conv2d(512, 3072, 1, 1, 0, bias=False)
        self.features_70_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_70_conv_3 = torch.nn.modules.conv.Conv2d(3072, 3072, 3, 1, 1, groups=3072, bias=False)
        self.features_70_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_70_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1)
        self.features_70_conv_6_fc_0 = torch.nn.modules.linear.Linear(3072, 128)
        self.features_70_conv_6_fc_2 = torch.nn.modules.linear.Linear(128, 3072)
        self.features_70_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_70_conv_7 = torch.nn.modules.conv.Conv2d(3072, 512, 1, 1, 0, bias=False)
        self.features_70_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(512)
        self.features_71_conv_0 = torch.nn.modules.conv.Conv2d(512, 3072, 1, 1, 0, bias=False)
        self.features_71_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_71_conv_3 = torch.nn.modules.conv.Conv2d(3072, 3072, 3, 1, 1, groups=3072, bias=False)
        self.features_71_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_71_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1)
        self.features_71_conv_6_fc_0 = torch.nn.modules.linear.Linear(3072, 128)
        self.features_71_conv_6_fc_2 = torch.nn.modules.linear.Linear(128, 3072)
        self.features_71_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_71_conv_7 = torch.nn.modules.conv.Conv2d(3072, 512, 1, 1, 0, bias=False)
        self.features_71_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(512)
        self.features_72_conv_0 = torch.nn.modules.conv.Conv2d(512, 3072, 1, 1, 0, bias=False)
        self.features_72_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_72_conv_3 = torch.nn.modules.conv.Conv2d(3072, 3072, 3, 1, 1, groups=3072, bias=False)
        self.features_72_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_72_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1)
        self.features_72_conv_6_fc_0 = torch.nn.modules.linear.Linear(3072, 128)
        self.features_72_conv_6_fc_2 = torch.nn.modules.linear.Linear(128, 3072)
        self.features_72_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_72_conv_7 = torch.nn.modules.conv.Conv2d(3072, 512, 1, 1, 0, bias=False)
        self.features_72_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(512)
        self.features_73_conv_0 = torch.nn.modules.conv.Conv2d(512, 3072, 1, 1, 0, bias=False)
        self.features_73_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_73_conv_3 = torch.nn.modules.conv.Conv2d(3072, 3072, 3, 1, 1, groups=3072, bias=False)
        self.features_73_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_73_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1)
        self.features_73_conv_6_fc_0 = torch.nn.modules.linear.Linear(3072, 128)
        self.features_73_conv_6_fc_2 = torch.nn.modules.linear.Linear(128, 3072)
        self.features_73_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_73_conv_7 = torch.nn.modules.conv.Conv2d(3072, 512, 1, 1, 0, bias=False)
        self.features_73_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(512)
        self.features_74_conv_0 = torch.nn.modules.conv.Conv2d(512, 3072, 1, 1, 0, bias=False)
        self.features_74_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_74_conv_3 = torch.nn.modules.conv.Conv2d(3072, 3072, 3, 1, 1, groups=3072, bias=False)
        self.features_74_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_74_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1)
        self.features_74_conv_6_fc_0 = torch.nn.modules.linear.Linear(3072, 128)
        self.features_74_conv_6_fc_2 = torch.nn.modules.linear.Linear(128, 3072)
        self.features_74_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_74_conv_7 = torch.nn.modules.conv.Conv2d(3072, 512, 1, 1, 0, bias=False)
        self.features_74_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(512)
        self.features_75_conv_0 = torch.nn.modules.conv.Conv2d(512, 3072, 1, 1, 0, bias=False)
        self.features_75_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_75_conv_3 = torch.nn.modules.conv.Conv2d(3072, 3072, 3, 1, 1, groups=3072, bias=False)
        self.features_75_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_75_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1)
        self.features_75_conv_6_fc_0 = torch.nn.modules.linear.Linear(3072, 128)
        self.features_75_conv_6_fc_2 = torch.nn.modules.linear.Linear(128, 3072)
        self.features_75_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_75_conv_7 = torch.nn.modules.conv.Conv2d(3072, 512, 1, 1, 0, bias=False)
        self.features_75_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(512)
        self.features_76_conv_0 = torch.nn.modules.conv.Conv2d(512, 3072, 1, 1, 0, bias=False)
        self.features_76_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_76_conv_3 = torch.nn.modules.conv.Conv2d(3072, 3072, 3, 1, 1, groups=3072, bias=False)
        self.features_76_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_76_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1)
        self.features_76_conv_6_fc_0 = torch.nn.modules.linear.Linear(3072, 128)
        self.features_76_conv_6_fc_2 = torch.nn.modules.linear.Linear(128, 3072)
        self.features_76_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_76_conv_7 = torch.nn.modules.conv.Conv2d(3072, 512, 1, 1, 0, bias=False)
        self.features_76_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(512)
        self.features_77_conv_0 = torch.nn.modules.conv.Conv2d(512, 3072, 1, 1, 0, bias=False)
        self.features_77_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_77_conv_3 = torch.nn.modules.conv.Conv2d(3072, 3072, 3, 1, 1, groups=3072, bias=False)
        self.features_77_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_77_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1)
        self.features_77_conv_6_fc_0 = torch.nn.modules.linear.Linear(3072, 128)
        self.features_77_conv_6_fc_2 = torch.nn.modules.linear.Linear(128, 3072)
        self.features_77_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_77_conv_7 = torch.nn.modules.conv.Conv2d(3072, 512, 1, 1, 0, bias=False)
        self.features_77_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(512)
        self.features_78_conv_0 = torch.nn.modules.conv.Conv2d(512, 3072, 1, 1, 0, bias=False)
        self.features_78_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_78_conv_3 = torch.nn.modules.conv.Conv2d(3072, 3072, 3, 1, 1, groups=3072, bias=False)
        self.features_78_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_78_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1)
        self.features_78_conv_6_fc_0 = torch.nn.modules.linear.Linear(3072, 128)
        self.features_78_conv_6_fc_2 = torch.nn.modules.linear.Linear(128, 3072)
        self.features_78_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_78_conv_7 = torch.nn.modules.conv.Conv2d(3072, 512, 1, 1, 0, bias=False)
        self.features_78_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(512)
        self.features_79_conv_0 = torch.nn.modules.conv.Conv2d(512, 3072, 1, 1, 0, bias=False)
        self.features_79_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_79_conv_3 = torch.nn.modules.conv.Conv2d(3072, 3072, 3, 1, 1, groups=3072, bias=False)
        self.features_79_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_79_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1)
        self.features_79_conv_6_fc_0 = torch.nn.modules.linear.Linear(3072, 128)
        self.features_79_conv_6_fc_2 = torch.nn.modules.linear.Linear(128, 3072)
        self.features_79_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_79_conv_7 = torch.nn.modules.conv.Conv2d(3072, 512, 1, 1, 0, bias=False)
        self.features_79_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(512)
        self.features_80_conv_0 = torch.nn.modules.conv.Conv2d(512, 3072, 1, 1, 0, bias=False)
        self.features_80_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_80_conv_3 = torch.nn.modules.conv.Conv2d(3072, 3072, 3, 1, 1, groups=3072, bias=False)
        self.features_80_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_80_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1)
        self.features_80_conv_6_fc_0 = torch.nn.modules.linear.Linear(3072, 128)
        self.features_80_conv_6_fc_2 = torch.nn.modules.linear.Linear(128, 3072)
        self.features_80_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_80_conv_7 = torch.nn.modules.conv.Conv2d(3072, 512, 1, 1, 0, bias=False)
        self.features_80_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(512)
        self.features_81_conv_0 = torch.nn.modules.conv.Conv2d(512, 3072, 1, 1, 0, bias=False)
        self.features_81_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_81_conv_3 = torch.nn.modules.conv.Conv2d(3072, 3072, 3, 1, 1, groups=3072, bias=False)
        self.features_81_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_81_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1)
        self.features_81_conv_6_fc_0 = torch.nn.modules.linear.Linear(3072, 128)
        self.features_81_conv_6_fc_2 = torch.nn.modules.linear.Linear(128, 3072)
        self.features_81_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_81_conv_7 = torch.nn.modules.conv.Conv2d(3072, 512, 1, 1, 0, bias=False)
        self.features_81_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(512)
        self.features_82_conv_0 = torch.nn.modules.conv.Conv2d(512, 3072, 1, 1, 0, bias=False)
        self.features_82_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_82_conv_3 = torch.nn.modules.conv.Conv2d(3072, 3072, 3, 1, 1, groups=3072, bias=False)
        self.features_82_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_82_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1)
        self.features_82_conv_6_fc_0 = torch.nn.modules.linear.Linear(3072, 128)
        self.features_82_conv_6_fc_2 = torch.nn.modules.linear.Linear(128, 3072)
        self.features_82_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_82_conv_7 = torch.nn.modules.conv.Conv2d(3072, 512, 1, 1, 0, bias=False)
        self.features_82_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(512)
        self.features_83_conv_0 = torch.nn.modules.conv.Conv2d(512, 3072, 1, 1, 0, bias=False)
        self.features_83_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_83_conv_3 = torch.nn.modules.conv.Conv2d(3072, 3072, 3, 1, 1, groups=3072, bias=False)
        self.features_83_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_83_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1)
        self.features_83_conv_6_fc_0 = torch.nn.modules.linear.Linear(3072, 128)
        self.features_83_conv_6_fc_2 = torch.nn.modules.linear.Linear(128, 3072)
        self.features_83_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_83_conv_7 = torch.nn.modules.conv.Conv2d(3072, 512, 1, 1, 0, bias=False)
        self.features_83_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(512)
        self.features_84_conv_0 = torch.nn.modules.conv.Conv2d(512, 3072, 1, 1, 0, bias=False)
        self.features_84_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_84_conv_3 = torch.nn.modules.conv.Conv2d(3072, 3072, 3, 1, 1, groups=3072, bias=False)
        self.features_84_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_84_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1)
        self.features_84_conv_6_fc_0 = torch.nn.modules.linear.Linear(3072, 128)
        self.features_84_conv_6_fc_2 = torch.nn.modules.linear.Linear(128, 3072)
        self.features_84_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_84_conv_7 = torch.nn.modules.conv.Conv2d(3072, 512, 1, 1, 0, bias=False)
        self.features_84_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(512)
        self.features_85_conv_0 = torch.nn.modules.conv.Conv2d(512, 3072, 1, 1, 0, bias=False)
        self.features_85_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_85_conv_3 = torch.nn.modules.conv.Conv2d(3072, 3072, 3, 1, 1, groups=3072, bias=False)
        self.features_85_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_85_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1)
        self.features_85_conv_6_fc_0 = torch.nn.modules.linear.Linear(3072, 128)
        self.features_85_conv_6_fc_2 = torch.nn.modules.linear.Linear(128, 3072)
        self.features_85_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_85_conv_7 = torch.nn.modules.conv.Conv2d(3072, 512, 1, 1, 0, bias=False)
        self.features_85_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(512)
        self.features_86_conv_0 = torch.nn.modules.conv.Conv2d(512, 3072, 1, 1, 0, bias=False)
        self.features_86_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_86_conv_3 = torch.nn.modules.conv.Conv2d(3072, 3072, 3, 1, 1, groups=3072, bias=False)
        self.features_86_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_86_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1)
        self.features_86_conv_6_fc_0 = torch.nn.modules.linear.Linear(3072, 128)
        self.features_86_conv_6_fc_2 = torch.nn.modules.linear.Linear(128, 3072)
        self.features_86_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_86_conv_7 = torch.nn.modules.conv.Conv2d(3072, 512, 1, 1, 0, bias=False)
        self.features_86_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(512)
        self.features_87_conv_0 = torch.nn.modules.conv.Conv2d(512, 3072, 1, 1, 0, bias=False)
        self.features_87_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_87_conv_3 = torch.nn.modules.conv.Conv2d(3072, 3072, 3, 1, 1, groups=3072, bias=False)
        self.features_87_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_87_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1)
        self.features_87_conv_6_fc_0 = torch.nn.modules.linear.Linear(3072, 128)
        self.features_87_conv_6_fc_2 = torch.nn.modules.linear.Linear(128, 3072)
        self.features_87_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_87_conv_7 = torch.nn.modules.conv.Conv2d(3072, 512, 1, 1, 0, bias=False)
        self.features_87_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(512)
        self.features_88_conv_0 = torch.nn.modules.conv.Conv2d(512, 3072, 1, 1, 0, bias=False)
        self.features_88_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_88_conv_3 = torch.nn.modules.conv.Conv2d(3072, 3072, 3, 1, 1, groups=3072, bias=False)
        self.features_88_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_88_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1)
        self.features_88_conv_6_fc_0 = torch.nn.modules.linear.Linear(3072, 128)
        self.features_88_conv_6_fc_2 = torch.nn.modules.linear.Linear(128, 3072)
        self.features_88_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_88_conv_7 = torch.nn.modules.conv.Conv2d(3072, 512, 1, 1, 0, bias=False)
        self.features_88_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(512)
        self.features_89_conv_0 = torch.nn.modules.conv.Conv2d(512, 3072, 1, 1, 0, bias=False)
        self.features_89_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_89_conv_3 = torch.nn.modules.conv.Conv2d(3072, 3072, 3, 1, 1, groups=3072, bias=False)
        self.features_89_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_89_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1)
        self.features_89_conv_6_fc_0 = torch.nn.modules.linear.Linear(3072, 128)
        self.features_89_conv_6_fc_2 = torch.nn.modules.linear.Linear(128, 3072)
        self.features_89_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_89_conv_7 = torch.nn.modules.conv.Conv2d(3072, 512, 1, 1, 0, bias=False)
        self.features_89_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(512)
        self.features_90_conv_0 = torch.nn.modules.conv.Conv2d(512, 3072, 1, 1, 0, bias=False)
        self.features_90_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_90_conv_3 = torch.nn.modules.conv.Conv2d(3072, 3072, 3, 1, 1, groups=3072, bias=False)
        self.features_90_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_90_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1)
        self.features_90_conv_6_fc_0 = torch.nn.modules.linear.Linear(3072, 128)
        self.features_90_conv_6_fc_2 = torch.nn.modules.linear.Linear(128, 3072)
        self.features_90_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_90_conv_7 = torch.nn.modules.conv.Conv2d(3072, 512, 1, 1, 0, bias=False)
        self.features_90_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(512)
        self.features_91_conv_0 = torch.nn.modules.conv.Conv2d(512, 3072, 1, 1, 0, bias=False)
        self.features_91_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_91_conv_3 = torch.nn.modules.conv.Conv2d(3072, 3072, 3, 1, 1, groups=3072, bias=False)
        self.features_91_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_91_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1)
        self.features_91_conv_6_fc_0 = torch.nn.modules.linear.Linear(3072, 128)
        self.features_91_conv_6_fc_2 = torch.nn.modules.linear.Linear(128, 3072)
        self.features_91_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_91_conv_7 = torch.nn.modules.conv.Conv2d(3072, 512, 1, 1, 0, bias=False)
        self.features_91_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(512)
        self.features_92_conv_0 = torch.nn.modules.conv.Conv2d(512, 3072, 1, 1, 0, bias=False)
        self.features_92_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_92_conv_3 = torch.nn.modules.conv.Conv2d(3072, 3072, 3, 1, 1, groups=3072, bias=False)
        self.features_92_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_92_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1)
        self.features_92_conv_6_fc_0 = torch.nn.modules.linear.Linear(3072, 128)
        self.features_92_conv_6_fc_2 = torch.nn.modules.linear.Linear(128, 3072)
        self.features_92_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_92_conv_7 = torch.nn.modules.conv.Conv2d(3072, 512, 1, 1, 0, bias=False)
        self.features_92_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(512)
        self.features_93_conv_0 = torch.nn.modules.conv.Conv2d(512, 3072, 1, 1, 0, bias=False)
        self.features_93_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_93_conv_3 = torch.nn.modules.conv.Conv2d(3072, 3072, 3, 1, 1, groups=3072, bias=False)
        self.features_93_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3072)
        self.features_93_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1)
        self.features_93_conv_6_fc_0 = torch.nn.modules.linear.Linear(3072, 128)
        self.features_93_conv_6_fc_2 = torch.nn.modules.linear.Linear(128, 3072)
        self.features_93_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_93_conv_7 = torch.nn.modules.conv.Conv2d(3072, 640, 1, 1, 0, bias=False)
        self.features_93_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(640)
        self.features_94_conv_0 = torch.nn.modules.conv.Conv2d(640, 3840, 1, 1, 0, bias=False)
        self.features_94_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3840)
        self.features_94_conv_3 = torch.nn.modules.conv.Conv2d(3840, 3840, 3, 1, 1, groups=3840, bias=False)
        self.features_94_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3840)
        self.features_94_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1)
        self.features_94_conv_6_fc_0 = torch.nn.modules.linear.Linear(3840, 160)
        self.features_94_conv_6_fc_2 = torch.nn.modules.linear.Linear(160, 3840)
        self.features_94_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_94_conv_7 = torch.nn.modules.conv.Conv2d(3840, 640, 1, 1, 0, bias=False)
        self.features_94_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(640)
        self.features_95_conv_0 = torch.nn.modules.conv.Conv2d(640, 3840, 1, 1, 0, bias=False)
        self.features_95_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3840)
        self.features_95_conv_3 = torch.nn.modules.conv.Conv2d(3840, 3840, 3, 1, 1, groups=3840, bias=False)
        self.features_95_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3840)
        self.features_95_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1)
        self.features_95_conv_6_fc_0 = torch.nn.modules.linear.Linear(3840, 160)
        self.features_95_conv_6_fc_2 = torch.nn.modules.linear.Linear(160, 3840)
        self.features_95_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_95_conv_7 = torch.nn.modules.conv.Conv2d(3840, 640, 1, 1, 0, bias=False)
        self.features_95_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(640)
        self.features_96_conv_0 = torch.nn.modules.conv.Conv2d(640, 3840, 1, 1, 0, bias=False)
        self.features_96_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3840)
        self.features_96_conv_3 = torch.nn.modules.conv.Conv2d(3840, 3840, 3, 1, 1, groups=3840, bias=False)
        self.features_96_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3840)
        self.features_96_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1)
        self.features_96_conv_6_fc_0 = torch.nn.modules.linear.Linear(3840, 160)
        self.features_96_conv_6_fc_2 = torch.nn.modules.linear.Linear(160, 3840)
        self.features_96_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_96_conv_7 = torch.nn.modules.conv.Conv2d(3840, 640, 1, 1, 0, bias=False)
        self.features_96_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(640)
        self.features_97_conv_0 = torch.nn.modules.conv.Conv2d(640, 3840, 1, 1, 0, bias=False)
        self.features_97_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3840)
        self.features_97_conv_3 = torch.nn.modules.conv.Conv2d(3840, 3840, 3, 1, 1, groups=3840, bias=False)
        self.features_97_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3840)
        self.features_97_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1)
        self.features_97_conv_6_fc_0 = torch.nn.modules.linear.Linear(3840, 160)
        self.features_97_conv_6_fc_2 = torch.nn.modules.linear.Linear(160, 3840)
        self.features_97_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_97_conv_7 = torch.nn.modules.conv.Conv2d(3840, 640, 1, 1, 0, bias=False)
        self.features_97_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(640)
        self.features_98_conv_0 = torch.nn.modules.conv.Conv2d(640, 3840, 1, 1, 0, bias=False)
        self.features_98_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3840)
        self.features_98_conv_3 = torch.nn.modules.conv.Conv2d(3840, 3840, 3, 1, 1, groups=3840, bias=False)
        self.features_98_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3840)
        self.features_98_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1)
        self.features_98_conv_6_fc_0 = torch.nn.modules.linear.Linear(3840, 160)
        self.features_98_conv_6_fc_2 = torch.nn.modules.linear.Linear(160, 3840)
        self.features_98_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_98_conv_7 = torch.nn.modules.conv.Conv2d(3840, 640, 1, 1, 0, bias=False)
        self.features_98_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(640)
        self.features_99_conv_0 = torch.nn.modules.conv.Conv2d(640, 3840, 1, 1, 0, bias=False)
        self.features_99_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3840)
        self.features_99_conv_3 = torch.nn.modules.conv.Conv2d(3840, 3840, 3, 1, 1, groups=3840, bias=False)
        self.features_99_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3840)
        self.features_99_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1)
        self.features_99_conv_6_fc_0 = torch.nn.modules.linear.Linear(3840, 160)
        self.features_99_conv_6_fc_2 = torch.nn.modules.linear.Linear(160, 3840)
        self.features_99_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_99_conv_7 = torch.nn.modules.conv.Conv2d(3840, 640, 1, 1, 0, bias=False)
        self.features_99_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(640)
        self.features_100_conv_0 = torch.nn.modules.conv.Conv2d(640, 3840, 1, 1, 0, bias=False)
        self.features_100_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3840)
        self.features_100_conv_3 = torch.nn.modules.conv.Conv2d(3840, 3840, 3, 1, 1, groups=3840, bias=False)
        self.features_100_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3840)
        self.features_100_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1)
        self.features_100_conv_6_fc_0 = torch.nn.modules.linear.Linear(3840, 160)
        self.features_100_conv_6_fc_2 = torch.nn.modules.linear.Linear(160, 3840)
        self.features_100_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid()
        self.features_100_conv_7 = torch.nn.modules.conv.Conv2d(3840, 640, 1, 1, 0, bias=False)
        self.features_100_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(640)
        self.conv_0 = torch.nn.modules.conv.Conv2d(640, 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)
        features_2_conv_0 = self.features_2_conv_0(features_1_conv_4)
        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_1 = features_1_conv_4.__add__(features_2_conv_4)
        features_3_conv_0 = self.features_3_conv_0(add_1)
        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_2 = add_1.__add__(features_3_conv_4)
        features_4_conv_0 = self.features_4_conv_0(add_2)
        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 = add_2.__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)
        features_6_conv_0 = self.features_6_conv_0(features_5_conv_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_4 = features_5_conv_4.__add__(features_6_conv_4)
        features_7_conv_0 = self.features_7_conv_0(add_4)
        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_5 = add_4.__add__(features_7_conv_4)
        features_8_conv_0 = self.features_8_conv_0(add_5)
        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 = add_5.__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)
        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)
        features_14_conv_0 = self.features_14_conv_0(features_13_conv_4)
        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)
        add_11 = features_13_conv_4.__add__(features_14_conv_4)
        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_16 = torch.sigmoid(features_15_conv_1)
        mul_16 = features_15_conv_1.__mul__(sigmoid_16)
        features_15_conv_3 = self.features_15_conv_3(mul_16)
        features_15_conv_4 = self.features_15_conv_4(features_15_conv_3)
        add_12 = add_11.__add__(features_15_conv_4)
        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_17 = torch.sigmoid(features_16_conv_1)
        mul_17 = features_16_conv_1.__mul__(sigmoid_17)
        features_16_conv_3 = self.features_16_conv_3(mul_17)
        features_16_conv_4 = self.features_16_conv_4(features_16_conv_3)
        add_13 = add_12.__add__(features_16_conv_4)
        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_18 = torch.sigmoid(features_17_conv_1)
        mul_18 = features_17_conv_1.__mul__(sigmoid_18)
        features_17_conv_3 = self.features_17_conv_3(mul_18)
        features_17_conv_4 = self.features_17_conv_4(features_17_conv_3)
        add_14 = add_13.__add__(features_17_conv_4)
        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_19 = torch.sigmoid(features_18_conv_1)
        mul_19 = features_18_conv_1.__mul__(sigmoid_19)
        features_18_conv_3 = self.features_18_conv_3(mul_19)
        features_18_conv_4 = self.features_18_conv_4(features_18_conv_3)
        add_15 = add_14.__add__(features_18_conv_4)
        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_20 = torch.sigmoid(features_19_conv_1)
        mul_20 = features_19_conv_1.__mul__(sigmoid_20)
        features_19_conv_3 = self.features_19_conv_3(mul_20)
        features_19_conv_4 = self.features_19_conv_4(features_19_conv_3)
        add_16 = add_15.__add__(features_19_conv_4)
        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_21 = torch.sigmoid(features_20_conv_1)
        mul_21 = features_20_conv_1.__mul__(sigmoid_21)
        features_20_conv_3 = self.features_20_conv_3(mul_21)
        features_20_conv_4 = self.features_20_conv_4(features_20_conv_3)
        add_17 = add_16.__add__(features_20_conv_4)
        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_22 = torch.sigmoid(features_21_conv_1)
        mul_22 = features_21_conv_1.__mul__(sigmoid_22)
        features_21_conv_3 = self.features_21_conv_3(mul_22)
        features_21_conv_4 = self.features_21_conv_4(features_21_conv_3)
        sigmoid_23 = torch.sigmoid(features_21_conv_4)
        mul_23 = features_21_conv_4.__mul__(sigmoid_23)
        size_1 = mul_23.size()
        features_21_conv_6_avg_pool = self.features_21_conv_6_avg_pool(mul_23)
        view_1 = features_21_conv_6_avg_pool.view(size_1[0], size_1[1])
        features_21_conv_6_fc_0 = self.features_21_conv_6_fc_0(view_1)
        sigmoid_24 = torch.sigmoid(features_21_conv_6_fc_0)
        mul_24 = features_21_conv_6_fc_0.__mul__(sigmoid_24)
        features_21_conv_6_fc_2 = self.features_21_conv_6_fc_2(mul_24)
        features_21_conv_6_fc_3 = self.features_21_conv_6_fc_3(features_21_conv_6_fc_2)
        view_2 = features_21_conv_6_fc_3.view(size_1[0], size_1[1], 1, 1)
        mul_25 = mul_23.__mul__(view_2)
        features_21_conv_7 = self.features_21_conv_7(mul_25)
        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_25 = torch.sigmoid(features_22_conv_1)
        mul_26 = features_22_conv_1.__mul__(sigmoid_25)
        features_22_conv_3 = self.features_22_conv_3(mul_26)
        features_22_conv_4 = self.features_22_conv_4(features_22_conv_3)
        sigmoid_26 = torch.sigmoid(features_22_conv_4)
        mul_27 = features_22_conv_4.__mul__(sigmoid_26)
        size_2 = mul_27.size()
        features_22_conv_6_avg_pool = self.features_22_conv_6_avg_pool(mul_27)
        view_3 = features_22_conv_6_avg_pool.view(size_2[0], size_2[1])
        features_22_conv_6_fc_0 = self.features_22_conv_6_fc_0(view_3)
        sigmoid_27 = torch.sigmoid(features_22_conv_6_fc_0)
        mul_28 = features_22_conv_6_fc_0.__mul__(sigmoid_27)
        features_22_conv_6_fc_2 = self.features_22_conv_6_fc_2(mul_28)
        features_22_conv_6_fc_3 = self.features_22_conv_6_fc_3(features_22_conv_6_fc_2)
        view_4 = features_22_conv_6_fc_3.view(size_2[0], size_2[1], 1, 1)
        mul_29 = mul_27.__mul__(view_4)
        features_22_conv_7 = self.features_22_conv_7(mul_29)
        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_28 = torch.sigmoid(features_23_conv_1)
        mul_30 = features_23_conv_1.__mul__(sigmoid_28)
        features_23_conv_3 = self.features_23_conv_3(mul_30)
        features_23_conv_4 = self.features_23_conv_4(features_23_conv_3)
        sigmoid_29 = torch.sigmoid(features_23_conv_4)
        mul_31 = features_23_conv_4.__mul__(sigmoid_29)
        size_3 = mul_31.size()
        features_23_conv_6_avg_pool = self.features_23_conv_6_avg_pool(mul_31)
        view_5 = features_23_conv_6_avg_pool.view(size_3[0], size_3[1])
        features_23_conv_6_fc_0 = self.features_23_conv_6_fc_0(view_5)
        sigmoid_30 = torch.sigmoid(features_23_conv_6_fc_0)
        mul_32 = features_23_conv_6_fc_0.__mul__(sigmoid_30)
        features_23_conv_6_fc_2 = self.features_23_conv_6_fc_2(mul_32)
        features_23_conv_6_fc_3 = self.features_23_conv_6_fc_3(features_23_conv_6_fc_2)
        view_6 = features_23_conv_6_fc_3.view(size_3[0], size_3[1], 1, 1)
        mul_33 = mul_31.__mul__(view_6)
        features_23_conv_7 = self.features_23_conv_7(mul_33)
        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_31 = torch.sigmoid(features_24_conv_1)
        mul_34 = features_24_conv_1.__mul__(sigmoid_31)
        features_24_conv_3 = self.features_24_conv_3(mul_34)
        features_24_conv_4 = self.features_24_conv_4(features_24_conv_3)
        sigmoid_32 = torch.sigmoid(features_24_conv_4)
        mul_35 = features_24_conv_4.__mul__(sigmoid_32)
        size_4 = mul_35.size()
        features_24_conv_6_avg_pool = self.features_24_conv_6_avg_pool(mul_35)
        view_7 = features_24_conv_6_avg_pool.view(size_4[0], size_4[1])
        features_24_conv_6_fc_0 = self.features_24_conv_6_fc_0(view_7)
        sigmoid_33 = torch.sigmoid(features_24_conv_6_fc_0)
        mul_36 = features_24_conv_6_fc_0.__mul__(sigmoid_33)
        features_24_conv_6_fc_2 = self.features_24_conv_6_fc_2(mul_36)
        features_24_conv_6_fc_3 = self.features_24_conv_6_fc_3(features_24_conv_6_fc_2)
        view_8 = features_24_conv_6_fc_3.view(size_4[0], size_4[1], 1, 1)
        mul_37 = mul_35.__mul__(view_8)
        features_24_conv_7 = self.features_24_conv_7(mul_37)
        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_34 = torch.sigmoid(features_25_conv_1)
        mul_38 = features_25_conv_1.__mul__(sigmoid_34)
        features_25_conv_3 = self.features_25_conv_3(mul_38)
        features_25_conv_4 = self.features_25_conv_4(features_25_conv_3)
        sigmoid_35 = torch.sigmoid(features_25_conv_4)
        mul_39 = features_25_conv_4.__mul__(sigmoid_35)
        size_5 = mul_39.size()
        features_25_conv_6_avg_pool = self.features_25_conv_6_avg_pool(mul_39)
        view_9 = features_25_conv_6_avg_pool.view(size_5[0], size_5[1])
        features_25_conv_6_fc_0 = self.features_25_conv_6_fc_0(view_9)
        sigmoid_36 = torch.sigmoid(features_25_conv_6_fc_0)
        mul_40 = features_25_conv_6_fc_0.__mul__(sigmoid_36)
        features_25_conv_6_fc_2 = self.features_25_conv_6_fc_2(mul_40)
        features_25_conv_6_fc_3 = self.features_25_conv_6_fc_3(features_25_conv_6_fc_2)
        view_10 = features_25_conv_6_fc_3.view(size_5[0], size_5[1], 1, 1)
        mul_41 = mul_39.__mul__(view_10)
        features_25_conv_7 = self.features_25_conv_7(mul_41)
        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_37 = torch.sigmoid(features_26_conv_1)
        mul_42 = features_26_conv_1.__mul__(sigmoid_37)
        features_26_conv_3 = self.features_26_conv_3(mul_42)
        features_26_conv_4 = self.features_26_conv_4(features_26_conv_3)
        sigmoid_38 = torch.sigmoid(features_26_conv_4)
        mul_43 = features_26_conv_4.__mul__(sigmoid_38)
        size_6 = mul_43.size()
        features_26_conv_6_avg_pool = self.features_26_conv_6_avg_pool(mul_43)
        view_11 = features_26_conv_6_avg_pool.view(size_6[0], size_6[1])
        features_26_conv_6_fc_0 = self.features_26_conv_6_fc_0(view_11)
        sigmoid_39 = torch.sigmoid(features_26_conv_6_fc_0)
        mul_44 = features_26_conv_6_fc_0.__mul__(sigmoid_39)
        features_26_conv_6_fc_2 = self.features_26_conv_6_fc_2(mul_44)
        features_26_conv_6_fc_3 = self.features_26_conv_6_fc_3(features_26_conv_6_fc_2)
        view_12 = features_26_conv_6_fc_3.view(size_6[0], size_6[1], 1, 1)
        mul_45 = mul_43.__mul__(view_12)
        features_26_conv_7 = self.features_26_conv_7(mul_45)
        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_40 = torch.sigmoid(features_27_conv_1)
        mul_46 = features_27_conv_1.__mul__(sigmoid_40)
        features_27_conv_3 = self.features_27_conv_3(mul_46)
        features_27_conv_4 = self.features_27_conv_4(features_27_conv_3)
        sigmoid_41 = torch.sigmoid(features_27_conv_4)
        mul_47 = features_27_conv_4.__mul__(sigmoid_41)
        size_7 = mul_47.size()
        features_27_conv_6_avg_pool = self.features_27_conv_6_avg_pool(mul_47)
        view_13 = features_27_conv_6_avg_pool.view(size_7[0], size_7[1])
        features_27_conv_6_fc_0 = self.features_27_conv_6_fc_0(view_13)
        sigmoid_42 = torch.sigmoid(features_27_conv_6_fc_0)
        mul_48 = features_27_conv_6_fc_0.__mul__(sigmoid_42)
        features_27_conv_6_fc_2 = self.features_27_conv_6_fc_2(mul_48)
        features_27_conv_6_fc_3 = self.features_27_conv_6_fc_3(features_27_conv_6_fc_2)
        view_14 = features_27_conv_6_fc_3.view(size_7[0], size_7[1], 1, 1)
        mul_49 = mul_47.__mul__(view_14)
        features_27_conv_7 = self.features_27_conv_7(mul_49)
        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_43 = torch.sigmoid(features_28_conv_1)
        mul_50 = features_28_conv_1.__mul__(sigmoid_43)
        features_28_conv_3 = self.features_28_conv_3(mul_50)
        features_28_conv_4 = self.features_28_conv_4(features_28_conv_3)
        sigmoid_44 = torch.sigmoid(features_28_conv_4)
        mul_51 = features_28_conv_4.__mul__(sigmoid_44)
        size_8 = mul_51.size()
        features_28_conv_6_avg_pool = self.features_28_conv_6_avg_pool(mul_51)
        view_15 = features_28_conv_6_avg_pool.view(size_8[0], size_8[1])
        features_28_conv_6_fc_0 = self.features_28_conv_6_fc_0(view_15)
        sigmoid_45 = torch.sigmoid(features_28_conv_6_fc_0)
        mul_52 = features_28_conv_6_fc_0.__mul__(sigmoid_45)
        features_28_conv_6_fc_2 = self.features_28_conv_6_fc_2(mul_52)
        features_28_conv_6_fc_3 = self.features_28_conv_6_fc_3(features_28_conv_6_fc_2)
        view_16 = features_28_conv_6_fc_3.view(size_8[0], size_8[1], 1, 1)
        mul_53 = mul_51.__mul__(view_16)
        features_28_conv_7 = self.features_28_conv_7(mul_53)
        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_46 = torch.sigmoid(features_29_conv_1)
        mul_54 = features_29_conv_1.__mul__(sigmoid_46)
        features_29_conv_3 = self.features_29_conv_3(mul_54)
        features_29_conv_4 = self.features_29_conv_4(features_29_conv_3)
        sigmoid_47 = torch.sigmoid(features_29_conv_4)
        mul_55 = features_29_conv_4.__mul__(sigmoid_47)
        size_9 = mul_55.size()
        features_29_conv_6_avg_pool = self.features_29_conv_6_avg_pool(mul_55)
        view_17 = features_29_conv_6_avg_pool.view(size_9[0], size_9[1])
        features_29_conv_6_fc_0 = self.features_29_conv_6_fc_0(view_17)
        sigmoid_48 = torch.sigmoid(features_29_conv_6_fc_0)
        mul_56 = features_29_conv_6_fc_0.__mul__(sigmoid_48)
        features_29_conv_6_fc_2 = self.features_29_conv_6_fc_2(mul_56)
        features_29_conv_6_fc_3 = self.features_29_conv_6_fc_3(features_29_conv_6_fc_2)
        view_18 = features_29_conv_6_fc_3.view(size_9[0], size_9[1], 1, 1)
        mul_57 = mul_55.__mul__(view_18)
        features_29_conv_7 = self.features_29_conv_7(mul_57)
        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_49 = torch.sigmoid(features_30_conv_1)
        mul_58 = features_30_conv_1.__mul__(sigmoid_49)
        features_30_conv_3 = self.features_30_conv_3(mul_58)
        features_30_conv_4 = self.features_30_conv_4(features_30_conv_3)
        sigmoid_50 = torch.sigmoid(features_30_conv_4)
        mul_59 = features_30_conv_4.__mul__(sigmoid_50)
        size_10 = mul_59.size()
        features_30_conv_6_avg_pool = self.features_30_conv_6_avg_pool(mul_59)
        view_19 = features_30_conv_6_avg_pool.view(size_10[0], size_10[1])
        features_30_conv_6_fc_0 = self.features_30_conv_6_fc_0(view_19)
        sigmoid_51 = torch.sigmoid(features_30_conv_6_fc_0)
        mul_60 = features_30_conv_6_fc_0.__mul__(sigmoid_51)
        features_30_conv_6_fc_2 = self.features_30_conv_6_fc_2(mul_60)
        features_30_conv_6_fc_3 = self.features_30_conv_6_fc_3(features_30_conv_6_fc_2)
        view_20 = features_30_conv_6_fc_3.view(size_10[0], size_10[1], 1, 1)
        mul_61 = mul_59.__mul__(view_20)
        features_30_conv_7 = self.features_30_conv_7(mul_61)
        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_52 = torch.sigmoid(features_31_conv_1)
        mul_62 = features_31_conv_1.__mul__(sigmoid_52)
        features_31_conv_3 = self.features_31_conv_3(mul_62)
        features_31_conv_4 = self.features_31_conv_4(features_31_conv_3)
        sigmoid_53 = torch.sigmoid(features_31_conv_4)
        mul_63 = features_31_conv_4.__mul__(sigmoid_53)
        size_11 = mul_63.size()
        features_31_conv_6_avg_pool = self.features_31_conv_6_avg_pool(mul_63)
        view_21 = features_31_conv_6_avg_pool.view(size_11[0], size_11[1])
        features_31_conv_6_fc_0 = self.features_31_conv_6_fc_0(view_21)
        sigmoid_54 = torch.sigmoid(features_31_conv_6_fc_0)
        mul_64 = features_31_conv_6_fc_0.__mul__(sigmoid_54)
        features_31_conv_6_fc_2 = self.features_31_conv_6_fc_2(mul_64)
        features_31_conv_6_fc_3 = self.features_31_conv_6_fc_3(features_31_conv_6_fc_2)
        view_22 = features_31_conv_6_fc_3.view(size_11[0], size_11[1], 1, 1)
        mul_65 = mul_63.__mul__(view_22)
        features_31_conv_7 = self.features_31_conv_7(mul_65)
        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_55 = torch.sigmoid(features_32_conv_1)
        mul_66 = features_32_conv_1.__mul__(sigmoid_55)
        features_32_conv_3 = self.features_32_conv_3(mul_66)
        features_32_conv_4 = self.features_32_conv_4(features_32_conv_3)
        sigmoid_56 = torch.sigmoid(features_32_conv_4)
        mul_67 = features_32_conv_4.__mul__(sigmoid_56)
        size_12 = mul_67.size()
        features_32_conv_6_avg_pool = self.features_32_conv_6_avg_pool(mul_67)
        view_23 = features_32_conv_6_avg_pool.view(size_12[0], size_12[1])
        features_32_conv_6_fc_0 = self.features_32_conv_6_fc_0(view_23)
        sigmoid_57 = torch.sigmoid(features_32_conv_6_fc_0)
        mul_68 = features_32_conv_6_fc_0.__mul__(sigmoid_57)
        features_32_conv_6_fc_2 = self.features_32_conv_6_fc_2(mul_68)
        features_32_conv_6_fc_3 = self.features_32_conv_6_fc_3(features_32_conv_6_fc_2)
        view_24 = features_32_conv_6_fc_3.view(size_12[0], size_12[1], 1, 1)
        mul_69 = mul_67.__mul__(view_24)
        features_32_conv_7 = self.features_32_conv_7(mul_69)
        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_58 = torch.sigmoid(features_33_conv_1)
        mul_70 = features_33_conv_1.__mul__(sigmoid_58)
        features_33_conv_3 = self.features_33_conv_3(mul_70)
        features_33_conv_4 = self.features_33_conv_4(features_33_conv_3)
        sigmoid_59 = torch.sigmoid(features_33_conv_4)
        mul_71 = features_33_conv_4.__mul__(sigmoid_59)
        size_13 = mul_71.size()
        features_33_conv_6_avg_pool = self.features_33_conv_6_avg_pool(mul_71)
        view_25 = features_33_conv_6_avg_pool.view(size_13[0], size_13[1])
        features_33_conv_6_fc_0 = self.features_33_conv_6_fc_0(view_25)
        sigmoid_60 = torch.sigmoid(features_33_conv_6_fc_0)
        mul_72 = features_33_conv_6_fc_0.__mul__(sigmoid_60)
        features_33_conv_6_fc_2 = self.features_33_conv_6_fc_2(mul_72)
        features_33_conv_6_fc_3 = self.features_33_conv_6_fc_3(features_33_conv_6_fc_2)
        view_26 = features_33_conv_6_fc_3.view(size_13[0], size_13[1], 1, 1)
        mul_73 = mul_71.__mul__(view_26)
        features_33_conv_7 = self.features_33_conv_7(mul_73)
        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_61 = torch.sigmoid(features_34_conv_1)
        mul_74 = features_34_conv_1.__mul__(sigmoid_61)
        features_34_conv_3 = self.features_34_conv_3(mul_74)
        features_34_conv_4 = self.features_34_conv_4(features_34_conv_3)
        sigmoid_62 = torch.sigmoid(features_34_conv_4)
        mul_75 = features_34_conv_4.__mul__(sigmoid_62)
        size_14 = mul_75.size()
        features_34_conv_6_avg_pool = self.features_34_conv_6_avg_pool(mul_75)
        view_27 = features_34_conv_6_avg_pool.view(size_14[0], size_14[1])
        features_34_conv_6_fc_0 = self.features_34_conv_6_fc_0(view_27)
        sigmoid_63 = torch.sigmoid(features_34_conv_6_fc_0)
        mul_76 = features_34_conv_6_fc_0.__mul__(sigmoid_63)
        features_34_conv_6_fc_2 = self.features_34_conv_6_fc_2(mul_76)
        features_34_conv_6_fc_3 = self.features_34_conv_6_fc_3(features_34_conv_6_fc_2)
        view_28 = features_34_conv_6_fc_3.view(size_14[0], size_14[1], 1, 1)
        mul_77 = mul_75.__mul__(view_28)
        features_34_conv_7 = self.features_34_conv_7(mul_77)
        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_64 = torch.sigmoid(features_35_conv_1)
        mul_78 = features_35_conv_1.__mul__(sigmoid_64)
        features_35_conv_3 = self.features_35_conv_3(mul_78)
        features_35_conv_4 = self.features_35_conv_4(features_35_conv_3)
        sigmoid_65 = torch.sigmoid(features_35_conv_4)
        mul_79 = features_35_conv_4.__mul__(sigmoid_65)
        size_15 = mul_79.size()
        features_35_conv_6_avg_pool = self.features_35_conv_6_avg_pool(mul_79)
        view_29 = features_35_conv_6_avg_pool.view(size_15[0], size_15[1])
        features_35_conv_6_fc_0 = self.features_35_conv_6_fc_0(view_29)
        sigmoid_66 = torch.sigmoid(features_35_conv_6_fc_0)
        mul_80 = features_35_conv_6_fc_0.__mul__(sigmoid_66)
        features_35_conv_6_fc_2 = self.features_35_conv_6_fc_2(mul_80)
        features_35_conv_6_fc_3 = self.features_35_conv_6_fc_3(features_35_conv_6_fc_2)
        view_30 = features_35_conv_6_fc_3.view(size_15[0], size_15[1], 1, 1)
        mul_81 = mul_79.__mul__(view_30)
        features_35_conv_7 = self.features_35_conv_7(mul_81)
        features_35_conv_8 = self.features_35_conv_8(features_35_conv_7)
        add_31 = add_30.__add__(features_35_conv_8)
        features_36_conv_0 = self.features_36_conv_0(add_31)
        features_36_conv_1 = self.features_36_conv_1(features_36_conv_0)
        sigmoid_67 = torch.sigmoid(features_36_conv_1)
        mul_82 = features_36_conv_1.__mul__(sigmoid_67)
        features_36_conv_3 = self.features_36_conv_3(mul_82)
        features_36_conv_4 = self.features_36_conv_4(features_36_conv_3)
        sigmoid_68 = torch.sigmoid(features_36_conv_4)
        mul_83 = features_36_conv_4.__mul__(sigmoid_68)
        size_16 = mul_83.size()
        features_36_conv_6_avg_pool = self.features_36_conv_6_avg_pool(mul_83)
        view_31 = features_36_conv_6_avg_pool.view(size_16[0], size_16[1])
        features_36_conv_6_fc_0 = self.features_36_conv_6_fc_0(view_31)
        sigmoid_69 = torch.sigmoid(features_36_conv_6_fc_0)
        mul_84 = features_36_conv_6_fc_0.__mul__(sigmoid_69)
        features_36_conv_6_fc_2 = self.features_36_conv_6_fc_2(mul_84)
        features_36_conv_6_fc_3 = self.features_36_conv_6_fc_3(features_36_conv_6_fc_2)
        view_32 = features_36_conv_6_fc_3.view(size_16[0], size_16[1], 1, 1)
        mul_85 = mul_83.__mul__(view_32)
        features_36_conv_7 = self.features_36_conv_7(mul_85)
        features_36_conv_8 = self.features_36_conv_8(features_36_conv_7)
        add_32 = add_31.__add__(features_36_conv_8)
        features_37_conv_0 = self.features_37_conv_0(add_32)
        features_37_conv_1 = self.features_37_conv_1(features_37_conv_0)
        sigmoid_70 = torch.sigmoid(features_37_conv_1)
        mul_86 = features_37_conv_1.__mul__(sigmoid_70)
        features_37_conv_3 = self.features_37_conv_3(mul_86)
        features_37_conv_4 = self.features_37_conv_4(features_37_conv_3)
        sigmoid_71 = torch.sigmoid(features_37_conv_4)
        mul_87 = features_37_conv_4.__mul__(sigmoid_71)
        size_17 = mul_87.size()
        features_37_conv_6_avg_pool = self.features_37_conv_6_avg_pool(mul_87)
        view_33 = features_37_conv_6_avg_pool.view(size_17[0], size_17[1])
        features_37_conv_6_fc_0 = self.features_37_conv_6_fc_0(view_33)
        sigmoid_72 = torch.sigmoid(features_37_conv_6_fc_0)
        mul_88 = features_37_conv_6_fc_0.__mul__(sigmoid_72)
        features_37_conv_6_fc_2 = self.features_37_conv_6_fc_2(mul_88)
        features_37_conv_6_fc_3 = self.features_37_conv_6_fc_3(features_37_conv_6_fc_2)
        view_34 = features_37_conv_6_fc_3.view(size_17[0], size_17[1], 1, 1)
        mul_89 = mul_87.__mul__(view_34)
        features_37_conv_7 = self.features_37_conv_7(mul_89)
        features_37_conv_8 = self.features_37_conv_8(features_37_conv_7)
        features_38_conv_0 = self.features_38_conv_0(features_37_conv_8)
        features_38_conv_1 = self.features_38_conv_1(features_38_conv_0)
        sigmoid_73 = torch.sigmoid(features_38_conv_1)
        mul_90 = features_38_conv_1.__mul__(sigmoid_73)
        features_38_conv_3 = self.features_38_conv_3(mul_90)
        features_38_conv_4 = self.features_38_conv_4(features_38_conv_3)
        sigmoid_74 = torch.sigmoid(features_38_conv_4)
        mul_91 = features_38_conv_4.__mul__(sigmoid_74)
        size_18 = mul_91.size()
        features_38_conv_6_avg_pool = self.features_38_conv_6_avg_pool(mul_91)
        view_35 = features_38_conv_6_avg_pool.view(size_18[0], size_18[1])
        features_38_conv_6_fc_0 = self.features_38_conv_6_fc_0(view_35)
        sigmoid_75 = torch.sigmoid(features_38_conv_6_fc_0)
        mul_92 = features_38_conv_6_fc_0.__mul__(sigmoid_75)
        features_38_conv_6_fc_2 = self.features_38_conv_6_fc_2(mul_92)
        features_38_conv_6_fc_3 = self.features_38_conv_6_fc_3(features_38_conv_6_fc_2)
        view_36 = features_38_conv_6_fc_3.view(size_18[0], size_18[1], 1, 1)
        mul_93 = mul_91.__mul__(view_36)
        features_38_conv_7 = self.features_38_conv_7(mul_93)
        features_38_conv_8 = self.features_38_conv_8(features_38_conv_7)
        add_33 = features_37_conv_8.__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_76 = torch.sigmoid(features_39_conv_1)
        mul_94 = features_39_conv_1.__mul__(sigmoid_76)
        features_39_conv_3 = self.features_39_conv_3(mul_94)
        features_39_conv_4 = self.features_39_conv_4(features_39_conv_3)
        sigmoid_77 = torch.sigmoid(features_39_conv_4)
        mul_95 = features_39_conv_4.__mul__(sigmoid_77)
        size_19 = mul_95.size()
        features_39_conv_6_avg_pool = self.features_39_conv_6_avg_pool(mul_95)
        view_37 = features_39_conv_6_avg_pool.view(size_19[0], size_19[1])
        features_39_conv_6_fc_0 = self.features_39_conv_6_fc_0(view_37)
        sigmoid_78 = torch.sigmoid(features_39_conv_6_fc_0)
        mul_96 = features_39_conv_6_fc_0.__mul__(sigmoid_78)
        features_39_conv_6_fc_2 = self.features_39_conv_6_fc_2(mul_96)
        features_39_conv_6_fc_3 = self.features_39_conv_6_fc_3(features_39_conv_6_fc_2)
        view_38 = features_39_conv_6_fc_3.view(size_19[0], size_19[1], 1, 1)
        mul_97 = mul_95.__mul__(view_38)
        features_39_conv_7 = self.features_39_conv_7(mul_97)
        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_79 = torch.sigmoid(features_40_conv_1)
        mul_98 = features_40_conv_1.__mul__(sigmoid_79)
        features_40_conv_3 = self.features_40_conv_3(mul_98)
        features_40_conv_4 = self.features_40_conv_4(features_40_conv_3)
        sigmoid_80 = torch.sigmoid(features_40_conv_4)
        mul_99 = features_40_conv_4.__mul__(sigmoid_80)
        size_20 = mul_99.size()
        features_40_conv_6_avg_pool = self.features_40_conv_6_avg_pool(mul_99)
        view_39 = features_40_conv_6_avg_pool.view(size_20[0], size_20[1])
        features_40_conv_6_fc_0 = self.features_40_conv_6_fc_0(view_39)
        sigmoid_81 = torch.sigmoid(features_40_conv_6_fc_0)
        mul_100 = features_40_conv_6_fc_0.__mul__(sigmoid_81)
        features_40_conv_6_fc_2 = self.features_40_conv_6_fc_2(mul_100)
        features_40_conv_6_fc_3 = self.features_40_conv_6_fc_3(features_40_conv_6_fc_2)
        view_40 = features_40_conv_6_fc_3.view(size_20[0], size_20[1], 1, 1)
        mul_101 = mul_99.__mul__(view_40)
        features_40_conv_7 = self.features_40_conv_7(mul_101)
        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_82 = torch.sigmoid(features_41_conv_1)
        mul_102 = features_41_conv_1.__mul__(sigmoid_82)
        features_41_conv_3 = self.features_41_conv_3(mul_102)
        features_41_conv_4 = self.features_41_conv_4(features_41_conv_3)
        sigmoid_83 = torch.sigmoid(features_41_conv_4)
        mul_103 = features_41_conv_4.__mul__(sigmoid_83)
        size_21 = mul_103.size()
        features_41_conv_6_avg_pool = self.features_41_conv_6_avg_pool(mul_103)
        view_41 = features_41_conv_6_avg_pool.view(size_21[0], size_21[1])
        features_41_conv_6_fc_0 = self.features_41_conv_6_fc_0(view_41)
        sigmoid_84 = torch.sigmoid(features_41_conv_6_fc_0)
        mul_104 = features_41_conv_6_fc_0.__mul__(sigmoid_84)
        features_41_conv_6_fc_2 = self.features_41_conv_6_fc_2(mul_104)
        features_41_conv_6_fc_3 = self.features_41_conv_6_fc_3(features_41_conv_6_fc_2)
        view_42 = features_41_conv_6_fc_3.view(size_21[0], size_21[1], 1, 1)
        mul_105 = mul_103.__mul__(view_42)
        features_41_conv_7 = self.features_41_conv_7(mul_105)
        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_85 = torch.sigmoid(features_42_conv_1)
        mul_106 = features_42_conv_1.__mul__(sigmoid_85)
        features_42_conv_3 = self.features_42_conv_3(mul_106)
        features_42_conv_4 = self.features_42_conv_4(features_42_conv_3)
        sigmoid_86 = torch.sigmoid(features_42_conv_4)
        mul_107 = features_42_conv_4.__mul__(sigmoid_86)
        size_22 = mul_107.size()
        features_42_conv_6_avg_pool = self.features_42_conv_6_avg_pool(mul_107)
        view_43 = features_42_conv_6_avg_pool.view(size_22[0], size_22[1])
        features_42_conv_6_fc_0 = self.features_42_conv_6_fc_0(view_43)
        sigmoid_87 = torch.sigmoid(features_42_conv_6_fc_0)
        mul_108 = features_42_conv_6_fc_0.__mul__(sigmoid_87)
        features_42_conv_6_fc_2 = self.features_42_conv_6_fc_2(mul_108)
        features_42_conv_6_fc_3 = self.features_42_conv_6_fc_3(features_42_conv_6_fc_2)
        view_44 = features_42_conv_6_fc_3.view(size_22[0], size_22[1], 1, 1)
        mul_109 = mul_107.__mul__(view_44)
        features_42_conv_7 = self.features_42_conv_7(mul_109)
        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_88 = torch.sigmoid(features_43_conv_1)
        mul_110 = features_43_conv_1.__mul__(sigmoid_88)
        features_43_conv_3 = self.features_43_conv_3(mul_110)
        features_43_conv_4 = self.features_43_conv_4(features_43_conv_3)
        sigmoid_89 = torch.sigmoid(features_43_conv_4)
        mul_111 = features_43_conv_4.__mul__(sigmoid_89)
        size_23 = mul_111.size()
        features_43_conv_6_avg_pool = self.features_43_conv_6_avg_pool(mul_111)
        view_45 = features_43_conv_6_avg_pool.view(size_23[0], size_23[1])
        features_43_conv_6_fc_0 = self.features_43_conv_6_fc_0(view_45)
        sigmoid_90 = torch.sigmoid(features_43_conv_6_fc_0)
        mul_112 = features_43_conv_6_fc_0.__mul__(sigmoid_90)
        features_43_conv_6_fc_2 = self.features_43_conv_6_fc_2(mul_112)
        features_43_conv_6_fc_3 = self.features_43_conv_6_fc_3(features_43_conv_6_fc_2)
        view_46 = features_43_conv_6_fc_3.view(size_23[0], size_23[1], 1, 1)
        mul_113 = mul_111.__mul__(view_46)
        features_43_conv_7 = self.features_43_conv_7(mul_113)
        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_91 = torch.sigmoid(features_44_conv_1)
        mul_114 = features_44_conv_1.__mul__(sigmoid_91)
        features_44_conv_3 = self.features_44_conv_3(mul_114)
        features_44_conv_4 = self.features_44_conv_4(features_44_conv_3)
        sigmoid_92 = torch.sigmoid(features_44_conv_4)
        mul_115 = features_44_conv_4.__mul__(sigmoid_92)
        size_24 = mul_115.size()
        features_44_conv_6_avg_pool = self.features_44_conv_6_avg_pool(mul_115)
        view_47 = features_44_conv_6_avg_pool.view(size_24[0], size_24[1])
        features_44_conv_6_fc_0 = self.features_44_conv_6_fc_0(view_47)
        sigmoid_93 = torch.sigmoid(features_44_conv_6_fc_0)
        mul_116 = features_44_conv_6_fc_0.__mul__(sigmoid_93)
        features_44_conv_6_fc_2 = self.features_44_conv_6_fc_2(mul_116)
        features_44_conv_6_fc_3 = self.features_44_conv_6_fc_3(features_44_conv_6_fc_2)
        view_48 = features_44_conv_6_fc_3.view(size_24[0], size_24[1], 1, 1)
        mul_117 = mul_115.__mul__(view_48)
        features_44_conv_7 = self.features_44_conv_7(mul_117)
        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_94 = torch.sigmoid(features_45_conv_1)
        mul_118 = features_45_conv_1.__mul__(sigmoid_94)
        features_45_conv_3 = self.features_45_conv_3(mul_118)
        features_45_conv_4 = self.features_45_conv_4(features_45_conv_3)
        sigmoid_95 = torch.sigmoid(features_45_conv_4)
        mul_119 = features_45_conv_4.__mul__(sigmoid_95)
        size_25 = mul_119.size()
        features_45_conv_6_avg_pool = self.features_45_conv_6_avg_pool(mul_119)
        view_49 = features_45_conv_6_avg_pool.view(size_25[0], size_25[1])
        features_45_conv_6_fc_0 = self.features_45_conv_6_fc_0(view_49)
        sigmoid_96 = torch.sigmoid(features_45_conv_6_fc_0)
        mul_120 = features_45_conv_6_fc_0.__mul__(sigmoid_96)
        features_45_conv_6_fc_2 = self.features_45_conv_6_fc_2(mul_120)
        features_45_conv_6_fc_3 = self.features_45_conv_6_fc_3(features_45_conv_6_fc_2)
        view_50 = features_45_conv_6_fc_3.view(size_25[0], size_25[1], 1, 1)
        mul_121 = mul_119.__mul__(view_50)
        features_45_conv_7 = self.features_45_conv_7(mul_121)
        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_97 = torch.sigmoid(features_46_conv_1)
        mul_122 = features_46_conv_1.__mul__(sigmoid_97)
        features_46_conv_3 = self.features_46_conv_3(mul_122)
        features_46_conv_4 = self.features_46_conv_4(features_46_conv_3)
        sigmoid_98 = torch.sigmoid(features_46_conv_4)
        mul_123 = features_46_conv_4.__mul__(sigmoid_98)
        size_26 = mul_123.size()
        features_46_conv_6_avg_pool = self.features_46_conv_6_avg_pool(mul_123)
        view_51 = features_46_conv_6_avg_pool.view(size_26[0], size_26[1])
        features_46_conv_6_fc_0 = self.features_46_conv_6_fc_0(view_51)
        sigmoid_99 = torch.sigmoid(features_46_conv_6_fc_0)
        mul_124 = features_46_conv_6_fc_0.__mul__(sigmoid_99)
        features_46_conv_6_fc_2 = self.features_46_conv_6_fc_2(mul_124)
        features_46_conv_6_fc_3 = self.features_46_conv_6_fc_3(features_46_conv_6_fc_2)
        view_52 = features_46_conv_6_fc_3.view(size_26[0], size_26[1], 1, 1)
        mul_125 = mul_123.__mul__(view_52)
        features_46_conv_7 = self.features_46_conv_7(mul_125)
        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_100 = torch.sigmoid(features_47_conv_1)
        mul_126 = features_47_conv_1.__mul__(sigmoid_100)
        features_47_conv_3 = self.features_47_conv_3(mul_126)
        features_47_conv_4 = self.features_47_conv_4(features_47_conv_3)
        sigmoid_101 = torch.sigmoid(features_47_conv_4)
        mul_127 = features_47_conv_4.__mul__(sigmoid_101)
        size_27 = mul_127.size()
        features_47_conv_6_avg_pool = self.features_47_conv_6_avg_pool(mul_127)
        view_53 = features_47_conv_6_avg_pool.view(size_27[0], size_27[1])
        features_47_conv_6_fc_0 = self.features_47_conv_6_fc_0(view_53)
        sigmoid_102 = torch.sigmoid(features_47_conv_6_fc_0)
        mul_128 = features_47_conv_6_fc_0.__mul__(sigmoid_102)
        features_47_conv_6_fc_2 = self.features_47_conv_6_fc_2(mul_128)
        features_47_conv_6_fc_3 = self.features_47_conv_6_fc_3(features_47_conv_6_fc_2)
        view_54 = features_47_conv_6_fc_3.view(size_27[0], size_27[1], 1, 1)
        mul_129 = mul_127.__mul__(view_54)
        features_47_conv_7 = self.features_47_conv_7(mul_129)
        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_103 = torch.sigmoid(features_48_conv_1)
        mul_130 = features_48_conv_1.__mul__(sigmoid_103)
        features_48_conv_3 = self.features_48_conv_3(mul_130)
        features_48_conv_4 = self.features_48_conv_4(features_48_conv_3)
        sigmoid_104 = torch.sigmoid(features_48_conv_4)
        mul_131 = features_48_conv_4.__mul__(sigmoid_104)
        size_28 = mul_131.size()
        features_48_conv_6_avg_pool = self.features_48_conv_6_avg_pool(mul_131)
        view_55 = features_48_conv_6_avg_pool.view(size_28[0], size_28[1])
        features_48_conv_6_fc_0 = self.features_48_conv_6_fc_0(view_55)
        sigmoid_105 = torch.sigmoid(features_48_conv_6_fc_0)
        mul_132 = features_48_conv_6_fc_0.__mul__(sigmoid_105)
        features_48_conv_6_fc_2 = self.features_48_conv_6_fc_2(mul_132)
        features_48_conv_6_fc_3 = self.features_48_conv_6_fc_3(features_48_conv_6_fc_2)
        view_56 = features_48_conv_6_fc_3.view(size_28[0], size_28[1], 1, 1)
        mul_133 = mul_131.__mul__(view_56)
        features_48_conv_7 = self.features_48_conv_7(mul_133)
        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_106 = torch.sigmoid(features_49_conv_1)
        mul_134 = features_49_conv_1.__mul__(sigmoid_106)
        features_49_conv_3 = self.features_49_conv_3(mul_134)
        features_49_conv_4 = self.features_49_conv_4(features_49_conv_3)
        sigmoid_107 = torch.sigmoid(features_49_conv_4)
        mul_135 = features_49_conv_4.__mul__(sigmoid_107)
        size_29 = mul_135.size()
        features_49_conv_6_avg_pool = self.features_49_conv_6_avg_pool(mul_135)
        view_57 = features_49_conv_6_avg_pool.view(size_29[0], size_29[1])
        features_49_conv_6_fc_0 = self.features_49_conv_6_fc_0(view_57)
        sigmoid_108 = torch.sigmoid(features_49_conv_6_fc_0)
        mul_136 = features_49_conv_6_fc_0.__mul__(sigmoid_108)
        features_49_conv_6_fc_2 = self.features_49_conv_6_fc_2(mul_136)
        features_49_conv_6_fc_3 = self.features_49_conv_6_fc_3(features_49_conv_6_fc_2)
        view_58 = features_49_conv_6_fc_3.view(size_29[0], size_29[1], 1, 1)
        mul_137 = mul_135.__mul__(view_58)
        features_49_conv_7 = self.features_49_conv_7(mul_137)
        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_109 = torch.sigmoid(features_50_conv_1)
        mul_138 = features_50_conv_1.__mul__(sigmoid_109)
        features_50_conv_3 = self.features_50_conv_3(mul_138)
        features_50_conv_4 = self.features_50_conv_4(features_50_conv_3)
        sigmoid_110 = torch.sigmoid(features_50_conv_4)
        mul_139 = features_50_conv_4.__mul__(sigmoid_110)
        size_30 = mul_139.size()
        features_50_conv_6_avg_pool = self.features_50_conv_6_avg_pool(mul_139)
        view_59 = features_50_conv_6_avg_pool.view(size_30[0], size_30[1])
        features_50_conv_6_fc_0 = self.features_50_conv_6_fc_0(view_59)
        sigmoid_111 = torch.sigmoid(features_50_conv_6_fc_0)
        mul_140 = features_50_conv_6_fc_0.__mul__(sigmoid_111)
        features_50_conv_6_fc_2 = self.features_50_conv_6_fc_2(mul_140)
        features_50_conv_6_fc_3 = self.features_50_conv_6_fc_3(features_50_conv_6_fc_2)
        view_60 = features_50_conv_6_fc_3.view(size_30[0], size_30[1], 1, 1)
        mul_141 = mul_139.__mul__(view_60)
        features_50_conv_7 = self.features_50_conv_7(mul_141)
        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_112 = torch.sigmoid(features_51_conv_1)
        mul_142 = features_51_conv_1.__mul__(sigmoid_112)
        features_51_conv_3 = self.features_51_conv_3(mul_142)
        features_51_conv_4 = self.features_51_conv_4(features_51_conv_3)
        sigmoid_113 = torch.sigmoid(features_51_conv_4)
        mul_143 = features_51_conv_4.__mul__(sigmoid_113)
        size_31 = mul_143.size()
        features_51_conv_6_avg_pool = self.features_51_conv_6_avg_pool(mul_143)
        view_61 = features_51_conv_6_avg_pool.view(size_31[0], size_31[1])
        features_51_conv_6_fc_0 = self.features_51_conv_6_fc_0(view_61)
        sigmoid_114 = torch.sigmoid(features_51_conv_6_fc_0)
        mul_144 = features_51_conv_6_fc_0.__mul__(sigmoid_114)
        features_51_conv_6_fc_2 = self.features_51_conv_6_fc_2(mul_144)
        features_51_conv_6_fc_3 = self.features_51_conv_6_fc_3(features_51_conv_6_fc_2)
        view_62 = features_51_conv_6_fc_3.view(size_31[0], size_31[1], 1, 1)
        mul_145 = mul_143.__mul__(view_62)
        features_51_conv_7 = self.features_51_conv_7(mul_145)
        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_115 = torch.sigmoid(features_52_conv_1)
        mul_146 = features_52_conv_1.__mul__(sigmoid_115)
        features_52_conv_3 = self.features_52_conv_3(mul_146)
        features_52_conv_4 = self.features_52_conv_4(features_52_conv_3)
        sigmoid_116 = torch.sigmoid(features_52_conv_4)
        mul_147 = features_52_conv_4.__mul__(sigmoid_116)
        size_32 = mul_147.size()
        features_52_conv_6_avg_pool = self.features_52_conv_6_avg_pool(mul_147)
        view_63 = features_52_conv_6_avg_pool.view(size_32[0], size_32[1])
        features_52_conv_6_fc_0 = self.features_52_conv_6_fc_0(view_63)
        sigmoid_117 = torch.sigmoid(features_52_conv_6_fc_0)
        mul_148 = features_52_conv_6_fc_0.__mul__(sigmoid_117)
        features_52_conv_6_fc_2 = self.features_52_conv_6_fc_2(mul_148)
        features_52_conv_6_fc_3 = self.features_52_conv_6_fc_3(features_52_conv_6_fc_2)
        view_64 = features_52_conv_6_fc_3.view(size_32[0], size_32[1], 1, 1)
        mul_149 = mul_147.__mul__(view_64)
        features_52_conv_7 = self.features_52_conv_7(mul_149)
        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_118 = torch.sigmoid(features_53_conv_1)
        mul_150 = features_53_conv_1.__mul__(sigmoid_118)
        features_53_conv_3 = self.features_53_conv_3(mul_150)
        features_53_conv_4 = self.features_53_conv_4(features_53_conv_3)
        sigmoid_119 = torch.sigmoid(features_53_conv_4)
        mul_151 = features_53_conv_4.__mul__(sigmoid_119)
        size_33 = mul_151.size()
        features_53_conv_6_avg_pool = self.features_53_conv_6_avg_pool(mul_151)
        view_65 = features_53_conv_6_avg_pool.view(size_33[0], size_33[1])
        features_53_conv_6_fc_0 = self.features_53_conv_6_fc_0(view_65)
        sigmoid_120 = torch.sigmoid(features_53_conv_6_fc_0)
        mul_152 = features_53_conv_6_fc_0.__mul__(sigmoid_120)
        features_53_conv_6_fc_2 = self.features_53_conv_6_fc_2(mul_152)
        features_53_conv_6_fc_3 = self.features_53_conv_6_fc_3(features_53_conv_6_fc_2)
        view_66 = features_53_conv_6_fc_3.view(size_33[0], size_33[1], 1, 1)
        mul_153 = mul_151.__mul__(view_66)
        features_53_conv_7 = self.features_53_conv_7(mul_153)
        features_53_conv_8 = self.features_53_conv_8(features_53_conv_7)
        add_48 = add_47.__add__(features_53_conv_8)
        features_54_conv_0 = self.features_54_conv_0(add_48)
        features_54_conv_1 = self.features_54_conv_1(features_54_conv_0)
        sigmoid_121 = torch.sigmoid(features_54_conv_1)
        mul_154 = features_54_conv_1.__mul__(sigmoid_121)
        features_54_conv_3 = self.features_54_conv_3(mul_154)
        features_54_conv_4 = self.features_54_conv_4(features_54_conv_3)
        sigmoid_122 = torch.sigmoid(features_54_conv_4)
        mul_155 = features_54_conv_4.__mul__(sigmoid_122)
        size_34 = mul_155.size()
        features_54_conv_6_avg_pool = self.features_54_conv_6_avg_pool(mul_155)
        view_67 = features_54_conv_6_avg_pool.view(size_34[0], size_34[1])
        features_54_conv_6_fc_0 = self.features_54_conv_6_fc_0(view_67)
        sigmoid_123 = torch.sigmoid(features_54_conv_6_fc_0)
        mul_156 = features_54_conv_6_fc_0.__mul__(sigmoid_123)
        features_54_conv_6_fc_2 = self.features_54_conv_6_fc_2(mul_156)
        features_54_conv_6_fc_3 = self.features_54_conv_6_fc_3(features_54_conv_6_fc_2)
        view_68 = features_54_conv_6_fc_3.view(size_34[0], size_34[1], 1, 1)
        mul_157 = mul_155.__mul__(view_68)
        features_54_conv_7 = self.features_54_conv_7(mul_157)
        features_54_conv_8 = self.features_54_conv_8(features_54_conv_7)
        add_49 = add_48.__add__(features_54_conv_8)
        features_55_conv_0 = self.features_55_conv_0(add_49)
        features_55_conv_1 = self.features_55_conv_1(features_55_conv_0)
        sigmoid_124 = torch.sigmoid(features_55_conv_1)
        mul_158 = features_55_conv_1.__mul__(sigmoid_124)
        features_55_conv_3 = self.features_55_conv_3(mul_158)
        features_55_conv_4 = self.features_55_conv_4(features_55_conv_3)
        sigmoid_125 = torch.sigmoid(features_55_conv_4)
        mul_159 = features_55_conv_4.__mul__(sigmoid_125)
        size_35 = mul_159.size()
        features_55_conv_6_avg_pool = self.features_55_conv_6_avg_pool(mul_159)
        view_69 = features_55_conv_6_avg_pool.view(size_35[0], size_35[1])
        features_55_conv_6_fc_0 = self.features_55_conv_6_fc_0(view_69)
        sigmoid_126 = torch.sigmoid(features_55_conv_6_fc_0)
        mul_160 = features_55_conv_6_fc_0.__mul__(sigmoid_126)
        features_55_conv_6_fc_2 = self.features_55_conv_6_fc_2(mul_160)
        features_55_conv_6_fc_3 = self.features_55_conv_6_fc_3(features_55_conv_6_fc_2)
        view_70 = features_55_conv_6_fc_3.view(size_35[0], size_35[1], 1, 1)
        mul_161 = mul_159.__mul__(view_70)
        features_55_conv_7 = self.features_55_conv_7(mul_161)
        features_55_conv_8 = self.features_55_conv_8(features_55_conv_7)
        add_50 = add_49.__add__(features_55_conv_8)
        features_56_conv_0 = self.features_56_conv_0(add_50)
        features_56_conv_1 = self.features_56_conv_1(features_56_conv_0)
        sigmoid_127 = torch.sigmoid(features_56_conv_1)
        mul_162 = features_56_conv_1.__mul__(sigmoid_127)
        features_56_conv_3 = self.features_56_conv_3(mul_162)
        features_56_conv_4 = self.features_56_conv_4(features_56_conv_3)
        sigmoid_128 = torch.sigmoid(features_56_conv_4)
        mul_163 = features_56_conv_4.__mul__(sigmoid_128)
        size_36 = mul_163.size()
        features_56_conv_6_avg_pool = self.features_56_conv_6_avg_pool(mul_163)
        view_71 = features_56_conv_6_avg_pool.view(size_36[0], size_36[1])
        features_56_conv_6_fc_0 = self.features_56_conv_6_fc_0(view_71)
        sigmoid_129 = torch.sigmoid(features_56_conv_6_fc_0)
        mul_164 = features_56_conv_6_fc_0.__mul__(sigmoid_129)
        features_56_conv_6_fc_2 = self.features_56_conv_6_fc_2(mul_164)
        features_56_conv_6_fc_3 = self.features_56_conv_6_fc_3(features_56_conv_6_fc_2)
        view_72 = features_56_conv_6_fc_3.view(size_36[0], size_36[1], 1, 1)
        mul_165 = mul_163.__mul__(view_72)
        features_56_conv_7 = self.features_56_conv_7(mul_165)
        features_56_conv_8 = self.features_56_conv_8(features_56_conv_7)
        add_51 = add_50.__add__(features_56_conv_8)
        features_57_conv_0 = self.features_57_conv_0(add_51)
        features_57_conv_1 = self.features_57_conv_1(features_57_conv_0)
        sigmoid_130 = torch.sigmoid(features_57_conv_1)
        mul_166 = features_57_conv_1.__mul__(sigmoid_130)
        features_57_conv_3 = self.features_57_conv_3(mul_166)
        features_57_conv_4 = self.features_57_conv_4(features_57_conv_3)
        sigmoid_131 = torch.sigmoid(features_57_conv_4)
        mul_167 = features_57_conv_4.__mul__(sigmoid_131)
        size_37 = mul_167.size()
        features_57_conv_6_avg_pool = self.features_57_conv_6_avg_pool(mul_167)
        view_73 = features_57_conv_6_avg_pool.view(size_37[0], size_37[1])
        features_57_conv_6_fc_0 = self.features_57_conv_6_fc_0(view_73)
        sigmoid_132 = torch.sigmoid(features_57_conv_6_fc_0)
        mul_168 = features_57_conv_6_fc_0.__mul__(sigmoid_132)
        features_57_conv_6_fc_2 = self.features_57_conv_6_fc_2(mul_168)
        features_57_conv_6_fc_3 = self.features_57_conv_6_fc_3(features_57_conv_6_fc_2)
        view_74 = features_57_conv_6_fc_3.view(size_37[0], size_37[1], 1, 1)
        mul_169 = mul_167.__mul__(view_74)
        features_57_conv_7 = self.features_57_conv_7(mul_169)
        features_57_conv_8 = self.features_57_conv_8(features_57_conv_7)
        add_52 = add_51.__add__(features_57_conv_8)
        features_58_conv_0 = self.features_58_conv_0(add_52)
        features_58_conv_1 = self.features_58_conv_1(features_58_conv_0)
        sigmoid_133 = torch.sigmoid(features_58_conv_1)
        mul_170 = features_58_conv_1.__mul__(sigmoid_133)
        features_58_conv_3 = self.features_58_conv_3(mul_170)
        features_58_conv_4 = self.features_58_conv_4(features_58_conv_3)
        sigmoid_134 = torch.sigmoid(features_58_conv_4)
        mul_171 = features_58_conv_4.__mul__(sigmoid_134)
        size_38 = mul_171.size()
        features_58_conv_6_avg_pool = self.features_58_conv_6_avg_pool(mul_171)
        view_75 = features_58_conv_6_avg_pool.view(size_38[0], size_38[1])
        features_58_conv_6_fc_0 = self.features_58_conv_6_fc_0(view_75)
        sigmoid_135 = torch.sigmoid(features_58_conv_6_fc_0)
        mul_172 = features_58_conv_6_fc_0.__mul__(sigmoid_135)
        features_58_conv_6_fc_2 = self.features_58_conv_6_fc_2(mul_172)
        features_58_conv_6_fc_3 = self.features_58_conv_6_fc_3(features_58_conv_6_fc_2)
        view_76 = features_58_conv_6_fc_3.view(size_38[0], size_38[1], 1, 1)
        mul_173 = mul_171.__mul__(view_76)
        features_58_conv_7 = self.features_58_conv_7(mul_173)
        features_58_conv_8 = self.features_58_conv_8(features_58_conv_7)
        add_53 = add_52.__add__(features_58_conv_8)
        features_59_conv_0 = self.features_59_conv_0(add_53)
        features_59_conv_1 = self.features_59_conv_1(features_59_conv_0)
        sigmoid_136 = torch.sigmoid(features_59_conv_1)
        mul_174 = features_59_conv_1.__mul__(sigmoid_136)
        features_59_conv_3 = self.features_59_conv_3(mul_174)
        features_59_conv_4 = self.features_59_conv_4(features_59_conv_3)
        sigmoid_137 = torch.sigmoid(features_59_conv_4)
        mul_175 = features_59_conv_4.__mul__(sigmoid_137)
        size_39 = mul_175.size()
        features_59_conv_6_avg_pool = self.features_59_conv_6_avg_pool(mul_175)
        view_77 = features_59_conv_6_avg_pool.view(size_39[0], size_39[1])
        features_59_conv_6_fc_0 = self.features_59_conv_6_fc_0(view_77)
        sigmoid_138 = torch.sigmoid(features_59_conv_6_fc_0)
        mul_176 = features_59_conv_6_fc_0.__mul__(sigmoid_138)
        features_59_conv_6_fc_2 = self.features_59_conv_6_fc_2(mul_176)
        features_59_conv_6_fc_3 = self.features_59_conv_6_fc_3(features_59_conv_6_fc_2)
        view_78 = features_59_conv_6_fc_3.view(size_39[0], size_39[1], 1, 1)
        mul_177 = mul_175.__mul__(view_78)
        features_59_conv_7 = self.features_59_conv_7(mul_177)
        features_59_conv_8 = self.features_59_conv_8(features_59_conv_7)
        add_54 = add_53.__add__(features_59_conv_8)
        features_60_conv_0 = self.features_60_conv_0(add_54)
        features_60_conv_1 = self.features_60_conv_1(features_60_conv_0)
        sigmoid_139 = torch.sigmoid(features_60_conv_1)
        mul_178 = features_60_conv_1.__mul__(sigmoid_139)
        features_60_conv_3 = self.features_60_conv_3(mul_178)
        features_60_conv_4 = self.features_60_conv_4(features_60_conv_3)
        sigmoid_140 = torch.sigmoid(features_60_conv_4)
        mul_179 = features_60_conv_4.__mul__(sigmoid_140)
        size_40 = mul_179.size()
        features_60_conv_6_avg_pool = self.features_60_conv_6_avg_pool(mul_179)
        view_79 = features_60_conv_6_avg_pool.view(size_40[0], size_40[1])
        features_60_conv_6_fc_0 = self.features_60_conv_6_fc_0(view_79)
        sigmoid_141 = torch.sigmoid(features_60_conv_6_fc_0)
        mul_180 = features_60_conv_6_fc_0.__mul__(sigmoid_141)
        features_60_conv_6_fc_2 = self.features_60_conv_6_fc_2(mul_180)
        features_60_conv_6_fc_3 = self.features_60_conv_6_fc_3(features_60_conv_6_fc_2)
        view_80 = features_60_conv_6_fc_3.view(size_40[0], size_40[1], 1, 1)
        mul_181 = mul_179.__mul__(view_80)
        features_60_conv_7 = self.features_60_conv_7(mul_181)
        features_60_conv_8 = self.features_60_conv_8(features_60_conv_7)
        add_55 = add_54.__add__(features_60_conv_8)
        features_61_conv_0 = self.features_61_conv_0(add_55)
        features_61_conv_1 = self.features_61_conv_1(features_61_conv_0)
        sigmoid_142 = torch.sigmoid(features_61_conv_1)
        mul_182 = features_61_conv_1.__mul__(sigmoid_142)
        features_61_conv_3 = self.features_61_conv_3(mul_182)
        features_61_conv_4 = self.features_61_conv_4(features_61_conv_3)
        sigmoid_143 = torch.sigmoid(features_61_conv_4)
        mul_183 = features_61_conv_4.__mul__(sigmoid_143)
        size_41 = mul_183.size()
        features_61_conv_6_avg_pool = self.features_61_conv_6_avg_pool(mul_183)
        view_81 = features_61_conv_6_avg_pool.view(size_41[0], size_41[1])
        features_61_conv_6_fc_0 = self.features_61_conv_6_fc_0(view_81)
        sigmoid_144 = torch.sigmoid(features_61_conv_6_fc_0)
        mul_184 = features_61_conv_6_fc_0.__mul__(sigmoid_144)
        features_61_conv_6_fc_2 = self.features_61_conv_6_fc_2(mul_184)
        features_61_conv_6_fc_3 = self.features_61_conv_6_fc_3(features_61_conv_6_fc_2)
        view_82 = features_61_conv_6_fc_3.view(size_41[0], size_41[1], 1, 1)
        mul_185 = mul_183.__mul__(view_82)
        features_61_conv_7 = self.features_61_conv_7(mul_185)
        features_61_conv_8 = self.features_61_conv_8(features_61_conv_7)
        features_62_conv_0 = self.features_62_conv_0(features_61_conv_8)
        features_62_conv_1 = self.features_62_conv_1(features_62_conv_0)
        sigmoid_145 = torch.sigmoid(features_62_conv_1)
        mul_186 = features_62_conv_1.__mul__(sigmoid_145)
        features_62_conv_3 = self.features_62_conv_3(mul_186)
        features_62_conv_4 = self.features_62_conv_4(features_62_conv_3)
        sigmoid_146 = torch.sigmoid(features_62_conv_4)
        mul_187 = features_62_conv_4.__mul__(sigmoid_146)
        size_42 = mul_187.size()
        features_62_conv_6_avg_pool = self.features_62_conv_6_avg_pool(mul_187)
        view_83 = features_62_conv_6_avg_pool.view(size_42[0], size_42[1])
        features_62_conv_6_fc_0 = self.features_62_conv_6_fc_0(view_83)
        sigmoid_147 = torch.sigmoid(features_62_conv_6_fc_0)
        mul_188 = features_62_conv_6_fc_0.__mul__(sigmoid_147)
        features_62_conv_6_fc_2 = self.features_62_conv_6_fc_2(mul_188)
        features_62_conv_6_fc_3 = self.features_62_conv_6_fc_3(features_62_conv_6_fc_2)
        view_84 = features_62_conv_6_fc_3.view(size_42[0], size_42[1], 1, 1)
        mul_189 = mul_187.__mul__(view_84)
        features_62_conv_7 = self.features_62_conv_7(mul_189)
        features_62_conv_8 = self.features_62_conv_8(features_62_conv_7)
        add_56 = features_61_conv_8.__add__(features_62_conv_8)
        features_63_conv_0 = self.features_63_conv_0(add_56)
        features_63_conv_1 = self.features_63_conv_1(features_63_conv_0)
        sigmoid_148 = torch.sigmoid(features_63_conv_1)
        mul_190 = features_63_conv_1.__mul__(sigmoid_148)
        features_63_conv_3 = self.features_63_conv_3(mul_190)
        features_63_conv_4 = self.features_63_conv_4(features_63_conv_3)
        sigmoid_149 = torch.sigmoid(features_63_conv_4)
        mul_191 = features_63_conv_4.__mul__(sigmoid_149)
        size_43 = mul_191.size()
        features_63_conv_6_avg_pool = self.features_63_conv_6_avg_pool(mul_191)
        view_85 = features_63_conv_6_avg_pool.view(size_43[0], size_43[1])
        features_63_conv_6_fc_0 = self.features_63_conv_6_fc_0(view_85)
        sigmoid_150 = torch.sigmoid(features_63_conv_6_fc_0)
        mul_192 = features_63_conv_6_fc_0.__mul__(sigmoid_150)
        features_63_conv_6_fc_2 = self.features_63_conv_6_fc_2(mul_192)
        features_63_conv_6_fc_3 = self.features_63_conv_6_fc_3(features_63_conv_6_fc_2)
        view_86 = features_63_conv_6_fc_3.view(size_43[0], size_43[1], 1, 1)
        mul_193 = mul_191.__mul__(view_86)
        features_63_conv_7 = self.features_63_conv_7(mul_193)
        features_63_conv_8 = self.features_63_conv_8(features_63_conv_7)
        add_57 = add_56.__add__(features_63_conv_8)
        features_64_conv_0 = self.features_64_conv_0(add_57)
        features_64_conv_1 = self.features_64_conv_1(features_64_conv_0)
        sigmoid_151 = torch.sigmoid(features_64_conv_1)
        mul_194 = features_64_conv_1.__mul__(sigmoid_151)
        features_64_conv_3 = self.features_64_conv_3(mul_194)
        features_64_conv_4 = self.features_64_conv_4(features_64_conv_3)
        sigmoid_152 = torch.sigmoid(features_64_conv_4)
        mul_195 = features_64_conv_4.__mul__(sigmoid_152)
        size_44 = mul_195.size()
        features_64_conv_6_avg_pool = self.features_64_conv_6_avg_pool(mul_195)
        view_87 = features_64_conv_6_avg_pool.view(size_44[0], size_44[1])
        features_64_conv_6_fc_0 = self.features_64_conv_6_fc_0(view_87)
        sigmoid_153 = torch.sigmoid(features_64_conv_6_fc_0)
        mul_196 = features_64_conv_6_fc_0.__mul__(sigmoid_153)
        features_64_conv_6_fc_2 = self.features_64_conv_6_fc_2(mul_196)
        features_64_conv_6_fc_3 = self.features_64_conv_6_fc_3(features_64_conv_6_fc_2)
        view_88 = features_64_conv_6_fc_3.view(size_44[0], size_44[1], 1, 1)
        mul_197 = mul_195.__mul__(view_88)
        features_64_conv_7 = self.features_64_conv_7(mul_197)
        features_64_conv_8 = self.features_64_conv_8(features_64_conv_7)
        add_58 = add_57.__add__(features_64_conv_8)
        features_65_conv_0 = self.features_65_conv_0(add_58)
        features_65_conv_1 = self.features_65_conv_1(features_65_conv_0)
        sigmoid_154 = torch.sigmoid(features_65_conv_1)
        mul_198 = features_65_conv_1.__mul__(sigmoid_154)
        features_65_conv_3 = self.features_65_conv_3(mul_198)
        features_65_conv_4 = self.features_65_conv_4(features_65_conv_3)
        sigmoid_155 = torch.sigmoid(features_65_conv_4)
        mul_199 = features_65_conv_4.__mul__(sigmoid_155)
        size_45 = mul_199.size()
        features_65_conv_6_avg_pool = self.features_65_conv_6_avg_pool(mul_199)
        view_89 = features_65_conv_6_avg_pool.view(size_45[0], size_45[1])
        features_65_conv_6_fc_0 = self.features_65_conv_6_fc_0(view_89)
        sigmoid_156 = torch.sigmoid(features_65_conv_6_fc_0)
        mul_200 = features_65_conv_6_fc_0.__mul__(sigmoid_156)
        features_65_conv_6_fc_2 = self.features_65_conv_6_fc_2(mul_200)
        features_65_conv_6_fc_3 = self.features_65_conv_6_fc_3(features_65_conv_6_fc_2)
        view_90 = features_65_conv_6_fc_3.view(size_45[0], size_45[1], 1, 1)
        mul_201 = mul_199.__mul__(view_90)
        features_65_conv_7 = self.features_65_conv_7(mul_201)
        features_65_conv_8 = self.features_65_conv_8(features_65_conv_7)
        add_59 = add_58.__add__(features_65_conv_8)
        features_66_conv_0 = self.features_66_conv_0(add_59)
        features_66_conv_1 = self.features_66_conv_1(features_66_conv_0)
        sigmoid_157 = torch.sigmoid(features_66_conv_1)
        mul_202 = features_66_conv_1.__mul__(sigmoid_157)
        features_66_conv_3 = self.features_66_conv_3(mul_202)
        features_66_conv_4 = self.features_66_conv_4(features_66_conv_3)
        sigmoid_158 = torch.sigmoid(features_66_conv_4)
        mul_203 = features_66_conv_4.__mul__(sigmoid_158)
        size_46 = mul_203.size()
        features_66_conv_6_avg_pool = self.features_66_conv_6_avg_pool(mul_203)
        view_91 = features_66_conv_6_avg_pool.view(size_46[0], size_46[1])
        features_66_conv_6_fc_0 = self.features_66_conv_6_fc_0(view_91)
        sigmoid_159 = torch.sigmoid(features_66_conv_6_fc_0)
        mul_204 = features_66_conv_6_fc_0.__mul__(sigmoid_159)
        features_66_conv_6_fc_2 = self.features_66_conv_6_fc_2(mul_204)
        features_66_conv_6_fc_3 = self.features_66_conv_6_fc_3(features_66_conv_6_fc_2)
        view_92 = features_66_conv_6_fc_3.view(size_46[0], size_46[1], 1, 1)
        mul_205 = mul_203.__mul__(view_92)
        features_66_conv_7 = self.features_66_conv_7(mul_205)
        features_66_conv_8 = self.features_66_conv_8(features_66_conv_7)
        add_60 = add_59.__add__(features_66_conv_8)
        features_67_conv_0 = self.features_67_conv_0(add_60)
        features_67_conv_1 = self.features_67_conv_1(features_67_conv_0)
        sigmoid_160 = torch.sigmoid(features_67_conv_1)
        mul_206 = features_67_conv_1.__mul__(sigmoid_160)
        features_67_conv_3 = self.features_67_conv_3(mul_206)
        features_67_conv_4 = self.features_67_conv_4(features_67_conv_3)
        sigmoid_161 = torch.sigmoid(features_67_conv_4)
        mul_207 = features_67_conv_4.__mul__(sigmoid_161)
        size_47 = mul_207.size()
        features_67_conv_6_avg_pool = self.features_67_conv_6_avg_pool(mul_207)
        view_93 = features_67_conv_6_avg_pool.view(size_47[0], size_47[1])
        features_67_conv_6_fc_0 = self.features_67_conv_6_fc_0(view_93)
        sigmoid_162 = torch.sigmoid(features_67_conv_6_fc_0)
        mul_208 = features_67_conv_6_fc_0.__mul__(sigmoid_162)
        features_67_conv_6_fc_2 = self.features_67_conv_6_fc_2(mul_208)
        features_67_conv_6_fc_3 = self.features_67_conv_6_fc_3(features_67_conv_6_fc_2)
        view_94 = features_67_conv_6_fc_3.view(size_47[0], size_47[1], 1, 1)
        mul_209 = mul_207.__mul__(view_94)
        features_67_conv_7 = self.features_67_conv_7(mul_209)
        features_67_conv_8 = self.features_67_conv_8(features_67_conv_7)
        add_61 = add_60.__add__(features_67_conv_8)
        features_68_conv_0 = self.features_68_conv_0(add_61)
        features_68_conv_1 = self.features_68_conv_1(features_68_conv_0)
        sigmoid_163 = torch.sigmoid(features_68_conv_1)
        mul_210 = features_68_conv_1.__mul__(sigmoid_163)
        features_68_conv_3 = self.features_68_conv_3(mul_210)
        features_68_conv_4 = self.features_68_conv_4(features_68_conv_3)
        sigmoid_164 = torch.sigmoid(features_68_conv_4)
        mul_211 = features_68_conv_4.__mul__(sigmoid_164)
        size_48 = mul_211.size()
        features_68_conv_6_avg_pool = self.features_68_conv_6_avg_pool(mul_211)
        view_95 = features_68_conv_6_avg_pool.view(size_48[0], size_48[1])
        features_68_conv_6_fc_0 = self.features_68_conv_6_fc_0(view_95)
        sigmoid_165 = torch.sigmoid(features_68_conv_6_fc_0)
        mul_212 = features_68_conv_6_fc_0.__mul__(sigmoid_165)
        features_68_conv_6_fc_2 = self.features_68_conv_6_fc_2(mul_212)
        features_68_conv_6_fc_3 = self.features_68_conv_6_fc_3(features_68_conv_6_fc_2)
        view_96 = features_68_conv_6_fc_3.view(size_48[0], size_48[1], 1, 1)
        mul_213 = mul_211.__mul__(view_96)
        features_68_conv_7 = self.features_68_conv_7(mul_213)
        features_68_conv_8 = self.features_68_conv_8(features_68_conv_7)
        add_62 = add_61.__add__(features_68_conv_8)
        features_69_conv_0 = self.features_69_conv_0(add_62)
        features_69_conv_1 = self.features_69_conv_1(features_69_conv_0)
        sigmoid_166 = torch.sigmoid(features_69_conv_1)
        mul_214 = features_69_conv_1.__mul__(sigmoid_166)
        features_69_conv_3 = self.features_69_conv_3(mul_214)
        features_69_conv_4 = self.features_69_conv_4(features_69_conv_3)
        sigmoid_167 = torch.sigmoid(features_69_conv_4)
        mul_215 = features_69_conv_4.__mul__(sigmoid_167)
        size_49 = mul_215.size()
        features_69_conv_6_avg_pool = self.features_69_conv_6_avg_pool(mul_215)
        view_97 = features_69_conv_6_avg_pool.view(size_49[0], size_49[1])
        features_69_conv_6_fc_0 = self.features_69_conv_6_fc_0(view_97)
        sigmoid_168 = torch.sigmoid(features_69_conv_6_fc_0)
        mul_216 = features_69_conv_6_fc_0.__mul__(sigmoid_168)
        features_69_conv_6_fc_2 = self.features_69_conv_6_fc_2(mul_216)
        features_69_conv_6_fc_3 = self.features_69_conv_6_fc_3(features_69_conv_6_fc_2)
        view_98 = features_69_conv_6_fc_3.view(size_49[0], size_49[1], 1, 1)
        mul_217 = mul_215.__mul__(view_98)
        features_69_conv_7 = self.features_69_conv_7(mul_217)
        features_69_conv_8 = self.features_69_conv_8(features_69_conv_7)
        add_63 = add_62.__add__(features_69_conv_8)
        features_70_conv_0 = self.features_70_conv_0(add_63)
        features_70_conv_1 = self.features_70_conv_1(features_70_conv_0)
        sigmoid_169 = torch.sigmoid(features_70_conv_1)
        mul_218 = features_70_conv_1.__mul__(sigmoid_169)
        features_70_conv_3 = self.features_70_conv_3(mul_218)
        features_70_conv_4 = self.features_70_conv_4(features_70_conv_3)
        sigmoid_170 = torch.sigmoid(features_70_conv_4)
        mul_219 = features_70_conv_4.__mul__(sigmoid_170)
        size_50 = mul_219.size()
        features_70_conv_6_avg_pool = self.features_70_conv_6_avg_pool(mul_219)
        view_99 = features_70_conv_6_avg_pool.view(size_50[0], size_50[1])
        features_70_conv_6_fc_0 = self.features_70_conv_6_fc_0(view_99)
        sigmoid_171 = torch.sigmoid(features_70_conv_6_fc_0)
        mul_220 = features_70_conv_6_fc_0.__mul__(sigmoid_171)
        features_70_conv_6_fc_2 = self.features_70_conv_6_fc_2(mul_220)
        features_70_conv_6_fc_3 = self.features_70_conv_6_fc_3(features_70_conv_6_fc_2)
        view_100 = features_70_conv_6_fc_3.view(size_50[0], size_50[1], 1, 1)
        mul_221 = mul_219.__mul__(view_100)
        features_70_conv_7 = self.features_70_conv_7(mul_221)
        features_70_conv_8 = self.features_70_conv_8(features_70_conv_7)
        add_64 = add_63.__add__(features_70_conv_8)
        features_71_conv_0 = self.features_71_conv_0(add_64)
        features_71_conv_1 = self.features_71_conv_1(features_71_conv_0)
        sigmoid_172 = torch.sigmoid(features_71_conv_1)
        mul_222 = features_71_conv_1.__mul__(sigmoid_172)
        features_71_conv_3 = self.features_71_conv_3(mul_222)
        features_71_conv_4 = self.features_71_conv_4(features_71_conv_3)
        sigmoid_173 = torch.sigmoid(features_71_conv_4)
        mul_223 = features_71_conv_4.__mul__(sigmoid_173)
        size_51 = mul_223.size()
        features_71_conv_6_avg_pool = self.features_71_conv_6_avg_pool(mul_223)
        view_101 = features_71_conv_6_avg_pool.view(size_51[0], size_51[1])
        features_71_conv_6_fc_0 = self.features_71_conv_6_fc_0(view_101)
        sigmoid_174 = torch.sigmoid(features_71_conv_6_fc_0)
        mul_224 = features_71_conv_6_fc_0.__mul__(sigmoid_174)
        features_71_conv_6_fc_2 = self.features_71_conv_6_fc_2(mul_224)
        features_71_conv_6_fc_3 = self.features_71_conv_6_fc_3(features_71_conv_6_fc_2)
        view_102 = features_71_conv_6_fc_3.view(size_51[0], size_51[1], 1, 1)
        mul_225 = mul_223.__mul__(view_102)
        features_71_conv_7 = self.features_71_conv_7(mul_225)
        features_71_conv_8 = self.features_71_conv_8(features_71_conv_7)
        add_65 = add_64.__add__(features_71_conv_8)
        features_72_conv_0 = self.features_72_conv_0(add_65)
        features_72_conv_1 = self.features_72_conv_1(features_72_conv_0)
        sigmoid_175 = torch.sigmoid(features_72_conv_1)
        mul_226 = features_72_conv_1.__mul__(sigmoid_175)
        features_72_conv_3 = self.features_72_conv_3(mul_226)
        features_72_conv_4 = self.features_72_conv_4(features_72_conv_3)
        sigmoid_176 = torch.sigmoid(features_72_conv_4)
        mul_227 = features_72_conv_4.__mul__(sigmoid_176)
        size_52 = mul_227.size()
        features_72_conv_6_avg_pool = self.features_72_conv_6_avg_pool(mul_227)
        view_103 = features_72_conv_6_avg_pool.view(size_52[0], size_52[1])
        features_72_conv_6_fc_0 = self.features_72_conv_6_fc_0(view_103)
        sigmoid_177 = torch.sigmoid(features_72_conv_6_fc_0)
        mul_228 = features_72_conv_6_fc_0.__mul__(sigmoid_177)
        features_72_conv_6_fc_2 = self.features_72_conv_6_fc_2(mul_228)
        features_72_conv_6_fc_3 = self.features_72_conv_6_fc_3(features_72_conv_6_fc_2)
        view_104 = features_72_conv_6_fc_3.view(size_52[0], size_52[1], 1, 1)
        mul_229 = mul_227.__mul__(view_104)
        features_72_conv_7 = self.features_72_conv_7(mul_229)
        features_72_conv_8 = self.features_72_conv_8(features_72_conv_7)
        add_66 = add_65.__add__(features_72_conv_8)
        features_73_conv_0 = self.features_73_conv_0(add_66)
        features_73_conv_1 = self.features_73_conv_1(features_73_conv_0)
        sigmoid_178 = torch.sigmoid(features_73_conv_1)
        mul_230 = features_73_conv_1.__mul__(sigmoid_178)
        features_73_conv_3 = self.features_73_conv_3(mul_230)
        features_73_conv_4 = self.features_73_conv_4(features_73_conv_3)
        sigmoid_179 = torch.sigmoid(features_73_conv_4)
        mul_231 = features_73_conv_4.__mul__(sigmoid_179)
        size_53 = mul_231.size()
        features_73_conv_6_avg_pool = self.features_73_conv_6_avg_pool(mul_231)
        view_105 = features_73_conv_6_avg_pool.view(size_53[0], size_53[1])
        features_73_conv_6_fc_0 = self.features_73_conv_6_fc_0(view_105)
        sigmoid_180 = torch.sigmoid(features_73_conv_6_fc_0)
        mul_232 = features_73_conv_6_fc_0.__mul__(sigmoid_180)
        features_73_conv_6_fc_2 = self.features_73_conv_6_fc_2(mul_232)
        features_73_conv_6_fc_3 = self.features_73_conv_6_fc_3(features_73_conv_6_fc_2)
        view_106 = features_73_conv_6_fc_3.view(size_53[0], size_53[1], 1, 1)
        mul_233 = mul_231.__mul__(view_106)
        features_73_conv_7 = self.features_73_conv_7(mul_233)
        features_73_conv_8 = self.features_73_conv_8(features_73_conv_7)
        add_67 = add_66.__add__(features_73_conv_8)
        features_74_conv_0 = self.features_74_conv_0(add_67)
        features_74_conv_1 = self.features_74_conv_1(features_74_conv_0)
        sigmoid_181 = torch.sigmoid(features_74_conv_1)
        mul_234 = features_74_conv_1.__mul__(sigmoid_181)
        features_74_conv_3 = self.features_74_conv_3(mul_234)
        features_74_conv_4 = self.features_74_conv_4(features_74_conv_3)
        sigmoid_182 = torch.sigmoid(features_74_conv_4)
        mul_235 = features_74_conv_4.__mul__(sigmoid_182)
        size_54 = mul_235.size()
        features_74_conv_6_avg_pool = self.features_74_conv_6_avg_pool(mul_235)
        view_107 = features_74_conv_6_avg_pool.view(size_54[0], size_54[1])
        features_74_conv_6_fc_0 = self.features_74_conv_6_fc_0(view_107)
        sigmoid_183 = torch.sigmoid(features_74_conv_6_fc_0)
        mul_236 = features_74_conv_6_fc_0.__mul__(sigmoid_183)
        features_74_conv_6_fc_2 = self.features_74_conv_6_fc_2(mul_236)
        features_74_conv_6_fc_3 = self.features_74_conv_6_fc_3(features_74_conv_6_fc_2)
        view_108 = features_74_conv_6_fc_3.view(size_54[0], size_54[1], 1, 1)
        mul_237 = mul_235.__mul__(view_108)
        features_74_conv_7 = self.features_74_conv_7(mul_237)
        features_74_conv_8 = self.features_74_conv_8(features_74_conv_7)
        add_68 = add_67.__add__(features_74_conv_8)
        features_75_conv_0 = self.features_75_conv_0(add_68)
        features_75_conv_1 = self.features_75_conv_1(features_75_conv_0)
        sigmoid_184 = torch.sigmoid(features_75_conv_1)
        mul_238 = features_75_conv_1.__mul__(sigmoid_184)
        features_75_conv_3 = self.features_75_conv_3(mul_238)
        features_75_conv_4 = self.features_75_conv_4(features_75_conv_3)
        sigmoid_185 = torch.sigmoid(features_75_conv_4)
        mul_239 = features_75_conv_4.__mul__(sigmoid_185)
        size_55 = mul_239.size()
        features_75_conv_6_avg_pool = self.features_75_conv_6_avg_pool(mul_239)
        view_109 = features_75_conv_6_avg_pool.view(size_55[0], size_55[1])
        features_75_conv_6_fc_0 = self.features_75_conv_6_fc_0(view_109)
        sigmoid_186 = torch.sigmoid(features_75_conv_6_fc_0)
        mul_240 = features_75_conv_6_fc_0.__mul__(sigmoid_186)
        features_75_conv_6_fc_2 = self.features_75_conv_6_fc_2(mul_240)
        features_75_conv_6_fc_3 = self.features_75_conv_6_fc_3(features_75_conv_6_fc_2)
        view_110 = features_75_conv_6_fc_3.view(size_55[0], size_55[1], 1, 1)
        mul_241 = mul_239.__mul__(view_110)
        features_75_conv_7 = self.features_75_conv_7(mul_241)
        features_75_conv_8 = self.features_75_conv_8(features_75_conv_7)
        add_69 = add_68.__add__(features_75_conv_8)
        features_76_conv_0 = self.features_76_conv_0(add_69)
        features_76_conv_1 = self.features_76_conv_1(features_76_conv_0)
        sigmoid_187 = torch.sigmoid(features_76_conv_1)
        mul_242 = features_76_conv_1.__mul__(sigmoid_187)
        features_76_conv_3 = self.features_76_conv_3(mul_242)
        features_76_conv_4 = self.features_76_conv_4(features_76_conv_3)
        sigmoid_188 = torch.sigmoid(features_76_conv_4)
        mul_243 = features_76_conv_4.__mul__(sigmoid_188)
        size_56 = mul_243.size()
        features_76_conv_6_avg_pool = self.features_76_conv_6_avg_pool(mul_243)
        view_111 = features_76_conv_6_avg_pool.view(size_56[0], size_56[1])
        features_76_conv_6_fc_0 = self.features_76_conv_6_fc_0(view_111)
        sigmoid_189 = torch.sigmoid(features_76_conv_6_fc_0)
        mul_244 = features_76_conv_6_fc_0.__mul__(sigmoid_189)
        features_76_conv_6_fc_2 = self.features_76_conv_6_fc_2(mul_244)
        features_76_conv_6_fc_3 = self.features_76_conv_6_fc_3(features_76_conv_6_fc_2)
        view_112 = features_76_conv_6_fc_3.view(size_56[0], size_56[1], 1, 1)
        mul_245 = mul_243.__mul__(view_112)
        features_76_conv_7 = self.features_76_conv_7(mul_245)
        features_76_conv_8 = self.features_76_conv_8(features_76_conv_7)
        add_70 = add_69.__add__(features_76_conv_8)
        features_77_conv_0 = self.features_77_conv_0(add_70)
        features_77_conv_1 = self.features_77_conv_1(features_77_conv_0)
        sigmoid_190 = torch.sigmoid(features_77_conv_1)
        mul_246 = features_77_conv_1.__mul__(sigmoid_190)
        features_77_conv_3 = self.features_77_conv_3(mul_246)
        features_77_conv_4 = self.features_77_conv_4(features_77_conv_3)
        sigmoid_191 = torch.sigmoid(features_77_conv_4)
        mul_247 = features_77_conv_4.__mul__(sigmoid_191)
        size_57 = mul_247.size()
        features_77_conv_6_avg_pool = self.features_77_conv_6_avg_pool(mul_247)
        view_113 = features_77_conv_6_avg_pool.view(size_57[0], size_57[1])
        features_77_conv_6_fc_0 = self.features_77_conv_6_fc_0(view_113)
        sigmoid_192 = torch.sigmoid(features_77_conv_6_fc_0)
        mul_248 = features_77_conv_6_fc_0.__mul__(sigmoid_192)
        features_77_conv_6_fc_2 = self.features_77_conv_6_fc_2(mul_248)
        features_77_conv_6_fc_3 = self.features_77_conv_6_fc_3(features_77_conv_6_fc_2)
        view_114 = features_77_conv_6_fc_3.view(size_57[0], size_57[1], 1, 1)
        mul_249 = mul_247.__mul__(view_114)
        features_77_conv_7 = self.features_77_conv_7(mul_249)
        features_77_conv_8 = self.features_77_conv_8(features_77_conv_7)
        add_71 = add_70.__add__(features_77_conv_8)
        features_78_conv_0 = self.features_78_conv_0(add_71)
        features_78_conv_1 = self.features_78_conv_1(features_78_conv_0)
        sigmoid_193 = torch.sigmoid(features_78_conv_1)
        mul_250 = features_78_conv_1.__mul__(sigmoid_193)
        features_78_conv_3 = self.features_78_conv_3(mul_250)
        features_78_conv_4 = self.features_78_conv_4(features_78_conv_3)
        sigmoid_194 = torch.sigmoid(features_78_conv_4)
        mul_251 = features_78_conv_4.__mul__(sigmoid_194)
        size_58 = mul_251.size()
        features_78_conv_6_avg_pool = self.features_78_conv_6_avg_pool(mul_251)
        view_115 = features_78_conv_6_avg_pool.view(size_58[0], size_58[1])
        features_78_conv_6_fc_0 = self.features_78_conv_6_fc_0(view_115)
        sigmoid_195 = torch.sigmoid(features_78_conv_6_fc_0)
        mul_252 = features_78_conv_6_fc_0.__mul__(sigmoid_195)
        features_78_conv_6_fc_2 = self.features_78_conv_6_fc_2(mul_252)
        features_78_conv_6_fc_3 = self.features_78_conv_6_fc_3(features_78_conv_6_fc_2)
        view_116 = features_78_conv_6_fc_3.view(size_58[0], size_58[1], 1, 1)
        mul_253 = mul_251.__mul__(view_116)
        features_78_conv_7 = self.features_78_conv_7(mul_253)
        features_78_conv_8 = self.features_78_conv_8(features_78_conv_7)
        add_72 = add_71.__add__(features_78_conv_8)
        features_79_conv_0 = self.features_79_conv_0(add_72)
        features_79_conv_1 = self.features_79_conv_1(features_79_conv_0)
        sigmoid_196 = torch.sigmoid(features_79_conv_1)
        mul_254 = features_79_conv_1.__mul__(sigmoid_196)
        features_79_conv_3 = self.features_79_conv_3(mul_254)
        features_79_conv_4 = self.features_79_conv_4(features_79_conv_3)
        sigmoid_197 = torch.sigmoid(features_79_conv_4)
        mul_255 = features_79_conv_4.__mul__(sigmoid_197)
        size_59 = mul_255.size()
        features_79_conv_6_avg_pool = self.features_79_conv_6_avg_pool(mul_255)
        view_117 = features_79_conv_6_avg_pool.view(size_59[0], size_59[1])
        features_79_conv_6_fc_0 = self.features_79_conv_6_fc_0(view_117)
        sigmoid_198 = torch.sigmoid(features_79_conv_6_fc_0)
        mul_256 = features_79_conv_6_fc_0.__mul__(sigmoid_198)
        features_79_conv_6_fc_2 = self.features_79_conv_6_fc_2(mul_256)
        features_79_conv_6_fc_3 = self.features_79_conv_6_fc_3(features_79_conv_6_fc_2)
        view_118 = features_79_conv_6_fc_3.view(size_59[0], size_59[1], 1, 1)
        mul_257 = mul_255.__mul__(view_118)
        features_79_conv_7 = self.features_79_conv_7(mul_257)
        features_79_conv_8 = self.features_79_conv_8(features_79_conv_7)
        add_73 = add_72.__add__(features_79_conv_8)
        features_80_conv_0 = self.features_80_conv_0(add_73)
        features_80_conv_1 = self.features_80_conv_1(features_80_conv_0)
        sigmoid_199 = torch.sigmoid(features_80_conv_1)
        mul_258 = features_80_conv_1.__mul__(sigmoid_199)
        features_80_conv_3 = self.features_80_conv_3(mul_258)
        features_80_conv_4 = self.features_80_conv_4(features_80_conv_3)
        sigmoid_200 = torch.sigmoid(features_80_conv_4)
        mul_259 = features_80_conv_4.__mul__(sigmoid_200)
        size_60 = mul_259.size()
        features_80_conv_6_avg_pool = self.features_80_conv_6_avg_pool(mul_259)
        view_119 = features_80_conv_6_avg_pool.view(size_60[0], size_60[1])
        features_80_conv_6_fc_0 = self.features_80_conv_6_fc_0(view_119)
        sigmoid_201 = torch.sigmoid(features_80_conv_6_fc_0)
        mul_260 = features_80_conv_6_fc_0.__mul__(sigmoid_201)
        features_80_conv_6_fc_2 = self.features_80_conv_6_fc_2(mul_260)
        features_80_conv_6_fc_3 = self.features_80_conv_6_fc_3(features_80_conv_6_fc_2)
        view_120 = features_80_conv_6_fc_3.view(size_60[0], size_60[1], 1, 1)
        mul_261 = mul_259.__mul__(view_120)
        features_80_conv_7 = self.features_80_conv_7(mul_261)
        features_80_conv_8 = self.features_80_conv_8(features_80_conv_7)
        add_74 = add_73.__add__(features_80_conv_8)
        features_81_conv_0 = self.features_81_conv_0(add_74)
        features_81_conv_1 = self.features_81_conv_1(features_81_conv_0)
        sigmoid_202 = torch.sigmoid(features_81_conv_1)
        mul_262 = features_81_conv_1.__mul__(sigmoid_202)
        features_81_conv_3 = self.features_81_conv_3(mul_262)
        features_81_conv_4 = self.features_81_conv_4(features_81_conv_3)
        sigmoid_203 = torch.sigmoid(features_81_conv_4)
        mul_263 = features_81_conv_4.__mul__(sigmoid_203)
        size_61 = mul_263.size()
        features_81_conv_6_avg_pool = self.features_81_conv_6_avg_pool(mul_263)
        view_121 = features_81_conv_6_avg_pool.view(size_61[0], size_61[1])
        features_81_conv_6_fc_0 = self.features_81_conv_6_fc_0(view_121)
        sigmoid_204 = torch.sigmoid(features_81_conv_6_fc_0)
        mul_264 = features_81_conv_6_fc_0.__mul__(sigmoid_204)
        features_81_conv_6_fc_2 = self.features_81_conv_6_fc_2(mul_264)
        features_81_conv_6_fc_3 = self.features_81_conv_6_fc_3(features_81_conv_6_fc_2)
        view_122 = features_81_conv_6_fc_3.view(size_61[0], size_61[1], 1, 1)
        mul_265 = mul_263.__mul__(view_122)
        features_81_conv_7 = self.features_81_conv_7(mul_265)
        features_81_conv_8 = self.features_81_conv_8(features_81_conv_7)
        add_75 = add_74.__add__(features_81_conv_8)
        features_82_conv_0 = self.features_82_conv_0(add_75)
        features_82_conv_1 = self.features_82_conv_1(features_82_conv_0)
        sigmoid_205 = torch.sigmoid(features_82_conv_1)
        mul_266 = features_82_conv_1.__mul__(sigmoid_205)
        features_82_conv_3 = self.features_82_conv_3(mul_266)
        features_82_conv_4 = self.features_82_conv_4(features_82_conv_3)
        sigmoid_206 = torch.sigmoid(features_82_conv_4)
        mul_267 = features_82_conv_4.__mul__(sigmoid_206)
        size_62 = mul_267.size()
        features_82_conv_6_avg_pool = self.features_82_conv_6_avg_pool(mul_267)
        view_123 = features_82_conv_6_avg_pool.view(size_62[0], size_62[1])
        features_82_conv_6_fc_0 = self.features_82_conv_6_fc_0(view_123)
        sigmoid_207 = torch.sigmoid(features_82_conv_6_fc_0)
        mul_268 = features_82_conv_6_fc_0.__mul__(sigmoid_207)
        features_82_conv_6_fc_2 = self.features_82_conv_6_fc_2(mul_268)
        features_82_conv_6_fc_3 = self.features_82_conv_6_fc_3(features_82_conv_6_fc_2)
        view_124 = features_82_conv_6_fc_3.view(size_62[0], size_62[1], 1, 1)
        mul_269 = mul_267.__mul__(view_124)
        features_82_conv_7 = self.features_82_conv_7(mul_269)
        features_82_conv_8 = self.features_82_conv_8(features_82_conv_7)
        add_76 = add_75.__add__(features_82_conv_8)
        features_83_conv_0 = self.features_83_conv_0(add_76)
        features_83_conv_1 = self.features_83_conv_1(features_83_conv_0)
        sigmoid_208 = torch.sigmoid(features_83_conv_1)
        mul_270 = features_83_conv_1.__mul__(sigmoid_208)
        features_83_conv_3 = self.features_83_conv_3(mul_270)
        features_83_conv_4 = self.features_83_conv_4(features_83_conv_3)
        sigmoid_209 = torch.sigmoid(features_83_conv_4)
        mul_271 = features_83_conv_4.__mul__(sigmoid_209)
        size_63 = mul_271.size()
        features_83_conv_6_avg_pool = self.features_83_conv_6_avg_pool(mul_271)
        view_125 = features_83_conv_6_avg_pool.view(size_63[0], size_63[1])
        features_83_conv_6_fc_0 = self.features_83_conv_6_fc_0(view_125)
        sigmoid_210 = torch.sigmoid(features_83_conv_6_fc_0)
        mul_272 = features_83_conv_6_fc_0.__mul__(sigmoid_210)
        features_83_conv_6_fc_2 = self.features_83_conv_6_fc_2(mul_272)
        features_83_conv_6_fc_3 = self.features_83_conv_6_fc_3(features_83_conv_6_fc_2)
        view_126 = features_83_conv_6_fc_3.view(size_63[0], size_63[1], 1, 1)
        mul_273 = mul_271.__mul__(view_126)
        features_83_conv_7 = self.features_83_conv_7(mul_273)
        features_83_conv_8 = self.features_83_conv_8(features_83_conv_7)
        add_77 = add_76.__add__(features_83_conv_8)
        features_84_conv_0 = self.features_84_conv_0(add_77)
        features_84_conv_1 = self.features_84_conv_1(features_84_conv_0)
        sigmoid_211 = torch.sigmoid(features_84_conv_1)
        mul_274 = features_84_conv_1.__mul__(sigmoid_211)
        features_84_conv_3 = self.features_84_conv_3(mul_274)
        features_84_conv_4 = self.features_84_conv_4(features_84_conv_3)
        sigmoid_212 = torch.sigmoid(features_84_conv_4)
        mul_275 = features_84_conv_4.__mul__(sigmoid_212)
        size_64 = mul_275.size()
        features_84_conv_6_avg_pool = self.features_84_conv_6_avg_pool(mul_275)
        view_127 = features_84_conv_6_avg_pool.view(size_64[0], size_64[1])
        features_84_conv_6_fc_0 = self.features_84_conv_6_fc_0(view_127)
        sigmoid_213 = torch.sigmoid(features_84_conv_6_fc_0)
        mul_276 = features_84_conv_6_fc_0.__mul__(sigmoid_213)
        features_84_conv_6_fc_2 = self.features_84_conv_6_fc_2(mul_276)
        features_84_conv_6_fc_3 = self.features_84_conv_6_fc_3(features_84_conv_6_fc_2)
        view_128 = features_84_conv_6_fc_3.view(size_64[0], size_64[1], 1, 1)
        mul_277 = mul_275.__mul__(view_128)
        features_84_conv_7 = self.features_84_conv_7(mul_277)
        features_84_conv_8 = self.features_84_conv_8(features_84_conv_7)
        add_78 = add_77.__add__(features_84_conv_8)
        features_85_conv_0 = self.features_85_conv_0(add_78)
        features_85_conv_1 = self.features_85_conv_1(features_85_conv_0)
        sigmoid_214 = torch.sigmoid(features_85_conv_1)
        mul_278 = features_85_conv_1.__mul__(sigmoid_214)
        features_85_conv_3 = self.features_85_conv_3(mul_278)
        features_85_conv_4 = self.features_85_conv_4(features_85_conv_3)
        sigmoid_215 = torch.sigmoid(features_85_conv_4)
        mul_279 = features_85_conv_4.__mul__(sigmoid_215)
        size_65 = mul_279.size()
        features_85_conv_6_avg_pool = self.features_85_conv_6_avg_pool(mul_279)
        view_129 = features_85_conv_6_avg_pool.view(size_65[0], size_65[1])
        features_85_conv_6_fc_0 = self.features_85_conv_6_fc_0(view_129)
        sigmoid_216 = torch.sigmoid(features_85_conv_6_fc_0)
        mul_280 = features_85_conv_6_fc_0.__mul__(sigmoid_216)
        features_85_conv_6_fc_2 = self.features_85_conv_6_fc_2(mul_280)
        features_85_conv_6_fc_3 = self.features_85_conv_6_fc_3(features_85_conv_6_fc_2)
        view_130 = features_85_conv_6_fc_3.view(size_65[0], size_65[1], 1, 1)
        mul_281 = mul_279.__mul__(view_130)
        features_85_conv_7 = self.features_85_conv_7(mul_281)
        features_85_conv_8 = self.features_85_conv_8(features_85_conv_7)
        add_79 = add_78.__add__(features_85_conv_8)
        features_86_conv_0 = self.features_86_conv_0(add_79)
        features_86_conv_1 = self.features_86_conv_1(features_86_conv_0)
        sigmoid_217 = torch.sigmoid(features_86_conv_1)
        mul_282 = features_86_conv_1.__mul__(sigmoid_217)
        features_86_conv_3 = self.features_86_conv_3(mul_282)
        features_86_conv_4 = self.features_86_conv_4(features_86_conv_3)
        sigmoid_218 = torch.sigmoid(features_86_conv_4)
        mul_283 = features_86_conv_4.__mul__(sigmoid_218)
        size_66 = mul_283.size()
        features_86_conv_6_avg_pool = self.features_86_conv_6_avg_pool(mul_283)
        view_131 = features_86_conv_6_avg_pool.view(size_66[0], size_66[1])
        features_86_conv_6_fc_0 = self.features_86_conv_6_fc_0(view_131)
        sigmoid_219 = torch.sigmoid(features_86_conv_6_fc_0)
        mul_284 = features_86_conv_6_fc_0.__mul__(sigmoid_219)
        features_86_conv_6_fc_2 = self.features_86_conv_6_fc_2(mul_284)
        features_86_conv_6_fc_3 = self.features_86_conv_6_fc_3(features_86_conv_6_fc_2)
        view_132 = features_86_conv_6_fc_3.view(size_66[0], size_66[1], 1, 1)
        mul_285 = mul_283.__mul__(view_132)
        features_86_conv_7 = self.features_86_conv_7(mul_285)
        features_86_conv_8 = self.features_86_conv_8(features_86_conv_7)
        add_80 = add_79.__add__(features_86_conv_8)
        features_87_conv_0 = self.features_87_conv_0(add_80)
        features_87_conv_1 = self.features_87_conv_1(features_87_conv_0)
        sigmoid_220 = torch.sigmoid(features_87_conv_1)
        mul_286 = features_87_conv_1.__mul__(sigmoid_220)
        features_87_conv_3 = self.features_87_conv_3(mul_286)
        features_87_conv_4 = self.features_87_conv_4(features_87_conv_3)
        sigmoid_221 = torch.sigmoid(features_87_conv_4)
        mul_287 = features_87_conv_4.__mul__(sigmoid_221)
        size_67 = mul_287.size()
        features_87_conv_6_avg_pool = self.features_87_conv_6_avg_pool(mul_287)
        view_133 = features_87_conv_6_avg_pool.view(size_67[0], size_67[1])
        features_87_conv_6_fc_0 = self.features_87_conv_6_fc_0(view_133)
        sigmoid_222 = torch.sigmoid(features_87_conv_6_fc_0)
        mul_288 = features_87_conv_6_fc_0.__mul__(sigmoid_222)
        features_87_conv_6_fc_2 = self.features_87_conv_6_fc_2(mul_288)
        features_87_conv_6_fc_3 = self.features_87_conv_6_fc_3(features_87_conv_6_fc_2)
        view_134 = features_87_conv_6_fc_3.view(size_67[0], size_67[1], 1, 1)
        mul_289 = mul_287.__mul__(view_134)
        features_87_conv_7 = self.features_87_conv_7(mul_289)
        features_87_conv_8 = self.features_87_conv_8(features_87_conv_7)
        add_81 = add_80.__add__(features_87_conv_8)
        features_88_conv_0 = self.features_88_conv_0(add_81)
        features_88_conv_1 = self.features_88_conv_1(features_88_conv_0)
        sigmoid_223 = torch.sigmoid(features_88_conv_1)
        mul_290 = features_88_conv_1.__mul__(sigmoid_223)
        features_88_conv_3 = self.features_88_conv_3(mul_290)
        features_88_conv_4 = self.features_88_conv_4(features_88_conv_3)
        sigmoid_224 = torch.sigmoid(features_88_conv_4)
        mul_291 = features_88_conv_4.__mul__(sigmoid_224)
        size_68 = mul_291.size()
        features_88_conv_6_avg_pool = self.features_88_conv_6_avg_pool(mul_291)
        view_135 = features_88_conv_6_avg_pool.view(size_68[0], size_68[1])
        features_88_conv_6_fc_0 = self.features_88_conv_6_fc_0(view_135)
        sigmoid_225 = torch.sigmoid(features_88_conv_6_fc_0)
        mul_292 = features_88_conv_6_fc_0.__mul__(sigmoid_225)
        features_88_conv_6_fc_2 = self.features_88_conv_6_fc_2(mul_292)
        features_88_conv_6_fc_3 = self.features_88_conv_6_fc_3(features_88_conv_6_fc_2)
        view_136 = features_88_conv_6_fc_3.view(size_68[0], size_68[1], 1, 1)
        mul_293 = mul_291.__mul__(view_136)
        features_88_conv_7 = self.features_88_conv_7(mul_293)
        features_88_conv_8 = self.features_88_conv_8(features_88_conv_7)
        add_82 = add_81.__add__(features_88_conv_8)
        features_89_conv_0 = self.features_89_conv_0(add_82)
        features_89_conv_1 = self.features_89_conv_1(features_89_conv_0)
        sigmoid_226 = torch.sigmoid(features_89_conv_1)
        mul_294 = features_89_conv_1.__mul__(sigmoid_226)
        features_89_conv_3 = self.features_89_conv_3(mul_294)
        features_89_conv_4 = self.features_89_conv_4(features_89_conv_3)
        sigmoid_227 = torch.sigmoid(features_89_conv_4)
        mul_295 = features_89_conv_4.__mul__(sigmoid_227)
        size_69 = mul_295.size()
        features_89_conv_6_avg_pool = self.features_89_conv_6_avg_pool(mul_295)
        view_137 = features_89_conv_6_avg_pool.view(size_69[0], size_69[1])
        features_89_conv_6_fc_0 = self.features_89_conv_6_fc_0(view_137)
        sigmoid_228 = torch.sigmoid(features_89_conv_6_fc_0)
        mul_296 = features_89_conv_6_fc_0.__mul__(sigmoid_228)
        features_89_conv_6_fc_2 = self.features_89_conv_6_fc_2(mul_296)
        features_89_conv_6_fc_3 = self.features_89_conv_6_fc_3(features_89_conv_6_fc_2)
        view_138 = features_89_conv_6_fc_3.view(size_69[0], size_69[1], 1, 1)
        mul_297 = mul_295.__mul__(view_138)
        features_89_conv_7 = self.features_89_conv_7(mul_297)
        features_89_conv_8 = self.features_89_conv_8(features_89_conv_7)
        add_83 = add_82.__add__(features_89_conv_8)
        features_90_conv_0 = self.features_90_conv_0(add_83)
        features_90_conv_1 = self.features_90_conv_1(features_90_conv_0)
        sigmoid_229 = torch.sigmoid(features_90_conv_1)
        mul_298 = features_90_conv_1.__mul__(sigmoid_229)
        features_90_conv_3 = self.features_90_conv_3(mul_298)
        features_90_conv_4 = self.features_90_conv_4(features_90_conv_3)
        sigmoid_230 = torch.sigmoid(features_90_conv_4)
        mul_299 = features_90_conv_4.__mul__(sigmoid_230)
        size_70 = mul_299.size()
        features_90_conv_6_avg_pool = self.features_90_conv_6_avg_pool(mul_299)
        view_139 = features_90_conv_6_avg_pool.view(size_70[0], size_70[1])
        features_90_conv_6_fc_0 = self.features_90_conv_6_fc_0(view_139)
        sigmoid_231 = torch.sigmoid(features_90_conv_6_fc_0)
        mul_300 = features_90_conv_6_fc_0.__mul__(sigmoid_231)
        features_90_conv_6_fc_2 = self.features_90_conv_6_fc_2(mul_300)
        features_90_conv_6_fc_3 = self.features_90_conv_6_fc_3(features_90_conv_6_fc_2)
        view_140 = features_90_conv_6_fc_3.view(size_70[0], size_70[1], 1, 1)
        mul_301 = mul_299.__mul__(view_140)
        features_90_conv_7 = self.features_90_conv_7(mul_301)
        features_90_conv_8 = self.features_90_conv_8(features_90_conv_7)
        add_84 = add_83.__add__(features_90_conv_8)
        features_91_conv_0 = self.features_91_conv_0(add_84)
        features_91_conv_1 = self.features_91_conv_1(features_91_conv_0)
        sigmoid_232 = torch.sigmoid(features_91_conv_1)
        mul_302 = features_91_conv_1.__mul__(sigmoid_232)
        features_91_conv_3 = self.features_91_conv_3(mul_302)
        features_91_conv_4 = self.features_91_conv_4(features_91_conv_3)
        sigmoid_233 = torch.sigmoid(features_91_conv_4)
        mul_303 = features_91_conv_4.__mul__(sigmoid_233)
        size_71 = mul_303.size()
        features_91_conv_6_avg_pool = self.features_91_conv_6_avg_pool(mul_303)
        view_141 = features_91_conv_6_avg_pool.view(size_71[0], size_71[1])
        features_91_conv_6_fc_0 = self.features_91_conv_6_fc_0(view_141)
        sigmoid_234 = torch.sigmoid(features_91_conv_6_fc_0)
        mul_304 = features_91_conv_6_fc_0.__mul__(sigmoid_234)
        features_91_conv_6_fc_2 = self.features_91_conv_6_fc_2(mul_304)
        features_91_conv_6_fc_3 = self.features_91_conv_6_fc_3(features_91_conv_6_fc_2)
        view_142 = features_91_conv_6_fc_3.view(size_71[0], size_71[1], 1, 1)
        mul_305 = mul_303.__mul__(view_142)
        features_91_conv_7 = self.features_91_conv_7(mul_305)
        features_91_conv_8 = self.features_91_conv_8(features_91_conv_7)
        add_85 = add_84.__add__(features_91_conv_8)
        features_92_conv_0 = self.features_92_conv_0(add_85)
        features_92_conv_1 = self.features_92_conv_1(features_92_conv_0)
        sigmoid_235 = torch.sigmoid(features_92_conv_1)
        mul_306 = features_92_conv_1.__mul__(sigmoid_235)
        features_92_conv_3 = self.features_92_conv_3(mul_306)
        features_92_conv_4 = self.features_92_conv_4(features_92_conv_3)
        sigmoid_236 = torch.sigmoid(features_92_conv_4)
        mul_307 = features_92_conv_4.__mul__(sigmoid_236)
        size_72 = mul_307.size()
        features_92_conv_6_avg_pool = self.features_92_conv_6_avg_pool(mul_307)
        view_143 = features_92_conv_6_avg_pool.view(size_72[0], size_72[1])
        features_92_conv_6_fc_0 = self.features_92_conv_6_fc_0(view_143)
        sigmoid_237 = torch.sigmoid(features_92_conv_6_fc_0)
        mul_308 = features_92_conv_6_fc_0.__mul__(sigmoid_237)
        features_92_conv_6_fc_2 = self.features_92_conv_6_fc_2(mul_308)
        features_92_conv_6_fc_3 = self.features_92_conv_6_fc_3(features_92_conv_6_fc_2)
        view_144 = features_92_conv_6_fc_3.view(size_72[0], size_72[1], 1, 1)
        mul_309 = mul_307.__mul__(view_144)
        features_92_conv_7 = self.features_92_conv_7(mul_309)
        features_92_conv_8 = self.features_92_conv_8(features_92_conv_7)
        add_86 = add_85.__add__(features_92_conv_8)
        features_93_conv_0 = self.features_93_conv_0(add_86)
        features_93_conv_1 = self.features_93_conv_1(features_93_conv_0)
        sigmoid_238 = torch.sigmoid(features_93_conv_1)
        mul_310 = features_93_conv_1.__mul__(sigmoid_238)
        features_93_conv_3 = self.features_93_conv_3(mul_310)
        features_93_conv_4 = self.features_93_conv_4(features_93_conv_3)
        sigmoid_239 = torch.sigmoid(features_93_conv_4)
        mul_311 = features_93_conv_4.__mul__(sigmoid_239)
        size_73 = mul_311.size()
        features_93_conv_6_avg_pool = self.features_93_conv_6_avg_pool(mul_311)
        view_145 = features_93_conv_6_avg_pool.view(size_73[0], size_73[1])
        features_93_conv_6_fc_0 = self.features_93_conv_6_fc_0(view_145)
        sigmoid_240 = torch.sigmoid(features_93_conv_6_fc_0)
        mul_312 = features_93_conv_6_fc_0.__mul__(sigmoid_240)
        features_93_conv_6_fc_2 = self.features_93_conv_6_fc_2(mul_312)
        features_93_conv_6_fc_3 = self.features_93_conv_6_fc_3(features_93_conv_6_fc_2)
        view_146 = features_93_conv_6_fc_3.view(size_73[0], size_73[1], 1, 1)
        mul_313 = mul_311.__mul__(view_146)
        features_93_conv_7 = self.features_93_conv_7(mul_313)
        features_93_conv_8 = self.features_93_conv_8(features_93_conv_7)
        features_94_conv_0 = self.features_94_conv_0(features_93_conv_8)
        features_94_conv_1 = self.features_94_conv_1(features_94_conv_0)
        sigmoid_241 = torch.sigmoid(features_94_conv_1)
        mul_314 = features_94_conv_1.__mul__(sigmoid_241)
        features_94_conv_3 = self.features_94_conv_3(mul_314)
        features_94_conv_4 = self.features_94_conv_4(features_94_conv_3)
        sigmoid_242 = torch.sigmoid(features_94_conv_4)
        mul_315 = features_94_conv_4.__mul__(sigmoid_242)
        size_74 = mul_315.size()
        features_94_conv_6_avg_pool = self.features_94_conv_6_avg_pool(mul_315)
        view_147 = features_94_conv_6_avg_pool.view(size_74[0], size_74[1])
        features_94_conv_6_fc_0 = self.features_94_conv_6_fc_0(view_147)
        sigmoid_243 = torch.sigmoid(features_94_conv_6_fc_0)
        mul_316 = features_94_conv_6_fc_0.__mul__(sigmoid_243)
        features_94_conv_6_fc_2 = self.features_94_conv_6_fc_2(mul_316)
        features_94_conv_6_fc_3 = self.features_94_conv_6_fc_3(features_94_conv_6_fc_2)
        view_148 = features_94_conv_6_fc_3.view(size_74[0], size_74[1], 1, 1)
        mul_317 = mul_315.__mul__(view_148)
        features_94_conv_7 = self.features_94_conv_7(mul_317)
        features_94_conv_8 = self.features_94_conv_8(features_94_conv_7)
        add_87 = features_93_conv_8.__add__(features_94_conv_8)
        features_95_conv_0 = self.features_95_conv_0(add_87)
        features_95_conv_1 = self.features_95_conv_1(features_95_conv_0)
        sigmoid_244 = torch.sigmoid(features_95_conv_1)
        mul_318 = features_95_conv_1.__mul__(sigmoid_244)
        features_95_conv_3 = self.features_95_conv_3(mul_318)
        features_95_conv_4 = self.features_95_conv_4(features_95_conv_3)
        sigmoid_245 = torch.sigmoid(features_95_conv_4)
        mul_319 = features_95_conv_4.__mul__(sigmoid_245)
        size_75 = mul_319.size()
        features_95_conv_6_avg_pool = self.features_95_conv_6_avg_pool(mul_319)
        view_149 = features_95_conv_6_avg_pool.view(size_75[0], size_75[1])
        features_95_conv_6_fc_0 = self.features_95_conv_6_fc_0(view_149)
        sigmoid_246 = torch.sigmoid(features_95_conv_6_fc_0)
        mul_320 = features_95_conv_6_fc_0.__mul__(sigmoid_246)
        features_95_conv_6_fc_2 = self.features_95_conv_6_fc_2(mul_320)
        features_95_conv_6_fc_3 = self.features_95_conv_6_fc_3(features_95_conv_6_fc_2)
        view_150 = features_95_conv_6_fc_3.view(size_75[0], size_75[1], 1, 1)
        mul_321 = mul_319.__mul__(view_150)
        features_95_conv_7 = self.features_95_conv_7(mul_321)
        features_95_conv_8 = self.features_95_conv_8(features_95_conv_7)
        add_88 = add_87.__add__(features_95_conv_8)
        features_96_conv_0 = self.features_96_conv_0(add_88)
        features_96_conv_1 = self.features_96_conv_1(features_96_conv_0)
        sigmoid_247 = torch.sigmoid(features_96_conv_1)
        mul_322 = features_96_conv_1.__mul__(sigmoid_247)
        features_96_conv_3 = self.features_96_conv_3(mul_322)
        features_96_conv_4 = self.features_96_conv_4(features_96_conv_3)
        sigmoid_248 = torch.sigmoid(features_96_conv_4)
        mul_323 = features_96_conv_4.__mul__(sigmoid_248)
        size_76 = mul_323.size()
        features_96_conv_6_avg_pool = self.features_96_conv_6_avg_pool(mul_323)
        view_151 = features_96_conv_6_avg_pool.view(size_76[0], size_76[1])
        features_96_conv_6_fc_0 = self.features_96_conv_6_fc_0(view_151)
        sigmoid_249 = torch.sigmoid(features_96_conv_6_fc_0)
        mul_324 = features_96_conv_6_fc_0.__mul__(sigmoid_249)
        features_96_conv_6_fc_2 = self.features_96_conv_6_fc_2(mul_324)
        features_96_conv_6_fc_3 = self.features_96_conv_6_fc_3(features_96_conv_6_fc_2)
        view_152 = features_96_conv_6_fc_3.view(size_76[0], size_76[1], 1, 1)
        mul_325 = mul_323.__mul__(view_152)
        features_96_conv_7 = self.features_96_conv_7(mul_325)
        features_96_conv_8 = self.features_96_conv_8(features_96_conv_7)
        add_89 = add_88.__add__(features_96_conv_8)
        features_97_conv_0 = self.features_97_conv_0(add_89)
        features_97_conv_1 = self.features_97_conv_1(features_97_conv_0)
        sigmoid_250 = torch.sigmoid(features_97_conv_1)
        mul_326 = features_97_conv_1.__mul__(sigmoid_250)
        features_97_conv_3 = self.features_97_conv_3(mul_326)
        features_97_conv_4 = self.features_97_conv_4(features_97_conv_3)
        sigmoid_251 = torch.sigmoid(features_97_conv_4)
        mul_327 = features_97_conv_4.__mul__(sigmoid_251)
        size_77 = mul_327.size()
        features_97_conv_6_avg_pool = self.features_97_conv_6_avg_pool(mul_327)
        view_153 = features_97_conv_6_avg_pool.view(size_77[0], size_77[1])
        features_97_conv_6_fc_0 = self.features_97_conv_6_fc_0(view_153)
        sigmoid_252 = torch.sigmoid(features_97_conv_6_fc_0)
        mul_328 = features_97_conv_6_fc_0.__mul__(sigmoid_252)
        features_97_conv_6_fc_2 = self.features_97_conv_6_fc_2(mul_328)
        features_97_conv_6_fc_3 = self.features_97_conv_6_fc_3(features_97_conv_6_fc_2)
        view_154 = features_97_conv_6_fc_3.view(size_77[0], size_77[1], 1, 1)
        mul_329 = mul_327.__mul__(view_154)
        features_97_conv_7 = self.features_97_conv_7(mul_329)
        features_97_conv_8 = self.features_97_conv_8(features_97_conv_7)
        add_90 = add_89.__add__(features_97_conv_8)
        features_98_conv_0 = self.features_98_conv_0(add_90)
        features_98_conv_1 = self.features_98_conv_1(features_98_conv_0)
        sigmoid_253 = torch.sigmoid(features_98_conv_1)
        mul_330 = features_98_conv_1.__mul__(sigmoid_253)
        features_98_conv_3 = self.features_98_conv_3(mul_330)
        features_98_conv_4 = self.features_98_conv_4(features_98_conv_3)
        sigmoid_254 = torch.sigmoid(features_98_conv_4)
        mul_331 = features_98_conv_4.__mul__(sigmoid_254)
        size_78 = mul_331.size()
        features_98_conv_6_avg_pool = self.features_98_conv_6_avg_pool(mul_331)
        view_155 = features_98_conv_6_avg_pool.view(size_78[0], size_78[1])
        features_98_conv_6_fc_0 = self.features_98_conv_6_fc_0(view_155)
        sigmoid_255 = torch.sigmoid(features_98_conv_6_fc_0)
        mul_332 = features_98_conv_6_fc_0.__mul__(sigmoid_255)
        features_98_conv_6_fc_2 = self.features_98_conv_6_fc_2(mul_332)
        features_98_conv_6_fc_3 = self.features_98_conv_6_fc_3(features_98_conv_6_fc_2)
        view_156 = features_98_conv_6_fc_3.view(size_78[0], size_78[1], 1, 1)
        mul_333 = mul_331.__mul__(view_156)
        features_98_conv_7 = self.features_98_conv_7(mul_333)
        features_98_conv_8 = self.features_98_conv_8(features_98_conv_7)
        add_91 = add_90.__add__(features_98_conv_8)
        features_99_conv_0 = self.features_99_conv_0(add_91)
        features_99_conv_1 = self.features_99_conv_1(features_99_conv_0)
        sigmoid_256 = torch.sigmoid(features_99_conv_1)
        mul_334 = features_99_conv_1.__mul__(sigmoid_256)
        features_99_conv_3 = self.features_99_conv_3(mul_334)
        features_99_conv_4 = self.features_99_conv_4(features_99_conv_3)
        sigmoid_257 = torch.sigmoid(features_99_conv_4)
        mul_335 = features_99_conv_4.__mul__(sigmoid_257)
        size_79 = mul_335.size()
        features_99_conv_6_avg_pool = self.features_99_conv_6_avg_pool(mul_335)
        view_157 = features_99_conv_6_avg_pool.view(size_79[0], size_79[1])
        features_99_conv_6_fc_0 = self.features_99_conv_6_fc_0(view_157)
        sigmoid_258 = torch.sigmoid(features_99_conv_6_fc_0)
        mul_336 = features_99_conv_6_fc_0.__mul__(sigmoid_258)
        features_99_conv_6_fc_2 = self.features_99_conv_6_fc_2(mul_336)
        features_99_conv_6_fc_3 = self.features_99_conv_6_fc_3(features_99_conv_6_fc_2)
        view_158 = features_99_conv_6_fc_3.view(size_79[0], size_79[1], 1, 1)
        mul_337 = mul_335.__mul__(view_158)
        features_99_conv_7 = self.features_99_conv_7(mul_337)
        features_99_conv_8 = self.features_99_conv_8(features_99_conv_7)
        add_92 = add_91.__add__(features_99_conv_8)
        features_100_conv_0 = self.features_100_conv_0(add_92)
        features_100_conv_1 = self.features_100_conv_1(features_100_conv_0)
        sigmoid_259 = torch.sigmoid(features_100_conv_1)
        mul_338 = features_100_conv_1.__mul__(sigmoid_259)
        features_100_conv_3 = self.features_100_conv_3(mul_338)
        features_100_conv_4 = self.features_100_conv_4(features_100_conv_3)
        sigmoid_260 = torch.sigmoid(features_100_conv_4)
        mul_339 = features_100_conv_4.__mul__(sigmoid_260)
        size_80 = mul_339.size()
        features_100_conv_6_avg_pool = self.features_100_conv_6_avg_pool(mul_339)
        view_159 = features_100_conv_6_avg_pool.view(size_80[0], size_80[1])
        features_100_conv_6_fc_0 = self.features_100_conv_6_fc_0(view_159)
        sigmoid_261 = torch.sigmoid(features_100_conv_6_fc_0)
        mul_340 = features_100_conv_6_fc_0.__mul__(sigmoid_261)
        features_100_conv_6_fc_2 = self.features_100_conv_6_fc_2(mul_340)
        features_100_conv_6_fc_3 = self.features_100_conv_6_fc_3(features_100_conv_6_fc_2)
        view_160 = features_100_conv_6_fc_3.view(size_80[0], size_80[1], 1, 1)
        mul_341 = mul_339.__mul__(view_160)
        features_100_conv_7 = self.features_100_conv_7(mul_341)
        features_100_conv_8 = self.features_100_conv_8(features_100_conv_7)
        add_93 = add_92.__add__(features_100_conv_8)
        conv_0 = self.conv_0(add_93)
        conv_1 = self.conv_1(conv_0)
        sigmoid_262 = torch.sigmoid(conv_1)
        mul_342 = conv_1.__mul__(sigmoid_262)
        avgpool = self.avgpool(mul_342)
        size_81 = avgpool.size(0)
        view_161 = avgpool.view(size_81, -1)
        classifier = self.classifier(view_161)
        return classifier


if __name__ == "__main__":
    model = efficientnet_v2_xl()

    model.eval()
    model.cpu()

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

    output = model(dummy_input_0)
    print(output)
