models/efficientnet_v2

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)

models/efficientnet_v2_xl.py (2,727 lines of code) (raw):