models/efficientnet_v2

import torch import torch.nn import torch.functional import torch.nn.functional class efficientnet_v2_l(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, 2, 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, 96, 1, 1, 0, bias=False) self.features_12_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(96) self.features_13_conv_0 = torch.nn.modules.conv.Conv2d(96, 384, 3, 1, 1, bias=False) self.features_13_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(384) self.features_13_conv_3 = torch.nn.modules.conv.Conv2d(384, 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, 1, 1, 0, bias=False) self.features_19_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(384) self.features_19_conv_3 = torch.nn.modules.conv.Conv2d(384, 384, 3, 2, 1, groups=384, bias=False) self.features_19_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(384) self.features_19_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1) self.features_19_conv_6_fc_0 = torch.nn.modules.linear.Linear(384, 24) self.features_19_conv_6_fc_2 = torch.nn.modules.linear.Linear(24, 384) self.features_19_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_19_conv_7 = torch.nn.modules.conv.Conv2d(384, 192, 1, 1, 0, bias=False) self.features_19_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(192) self.features_20_conv_0 = torch.nn.modules.conv.Conv2d(192, 768, 1, 1, 0, bias=False) self.features_20_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(768) self.features_20_conv_3 = torch.nn.modules.conv.Conv2d(768, 768, 3, 1, 1, groups=768, bias=False) self.features_20_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(768) self.features_20_conv_6_avg_pool = torch.nn.modules.pooling.AdaptiveAvgPool2d(1) self.features_20_conv_6_fc_0 = torch.nn.modules.linear.Linear(768, 48) self.features_20_conv_6_fc_2 = torch.nn.modules.linear.Linear(48, 768) self.features_20_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_20_conv_7 = torch.nn.modules.conv.Conv2d(768, 192, 1, 1, 0, bias=False) self.features_20_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(192) self.features_21_conv_0 = torch.nn.modules.conv.Conv2d(192, 768, 1, 1, 0, bias=False) self.features_21_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(768) self.features_21_conv_3 = torch.nn.modules.conv.Conv2d(768, 768, 3, 1, 1, groups=768, bias=False) self.features_21_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(768) 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(768, 48) self.features_21_conv_6_fc_2 = torch.nn.modules.linear.Linear(48, 768) self.features_21_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_21_conv_7 = torch.nn.modules.conv.Conv2d(768, 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, 1152, 1, 1, 0, bias=False) self.features_29_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1152) self.features_29_conv_3 = torch.nn.modules.conv.Conv2d(1152, 1152, 3, 1, 1, groups=1152, bias=False) self.features_29_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1152) 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(1152, 48) self.features_29_conv_6_fc_2 = torch.nn.modules.linear.Linear(48, 1152) self.features_29_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_29_conv_7 = torch.nn.modules.conv.Conv2d(1152, 224, 1, 1, 0, bias=False) self.features_29_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(224) self.features_30_conv_0 = torch.nn.modules.conv.Conv2d(224, 1344, 1, 1, 0, bias=False) self.features_30_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1344) self.features_30_conv_3 = torch.nn.modules.conv.Conv2d(1344, 1344, 3, 1, 1, groups=1344, bias=False) self.features_30_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1344) 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(1344, 56) self.features_30_conv_6_fc_2 = torch.nn.modules.linear.Linear(56, 1344) self.features_30_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_30_conv_7 = torch.nn.modules.conv.Conv2d(1344, 224, 1, 1, 0, bias=False) self.features_30_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(224) self.features_31_conv_0 = torch.nn.modules.conv.Conv2d(224, 1344, 1, 1, 0, bias=False) self.features_31_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1344) self.features_31_conv_3 = torch.nn.modules.conv.Conv2d(1344, 1344, 3, 1, 1, groups=1344, bias=False) self.features_31_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1344) 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(1344, 56) self.features_31_conv_6_fc_2 = torch.nn.modules.linear.Linear(56, 1344) self.features_31_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_31_conv_7 = torch.nn.modules.conv.Conv2d(1344, 224, 1, 1, 0, bias=False) self.features_31_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(224) self.features_32_conv_0 = torch.nn.modules.conv.Conv2d(224, 1344, 1, 1, 0, bias=False) self.features_32_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1344) self.features_32_conv_3 = torch.nn.modules.conv.Conv2d(1344, 1344, 3, 1, 1, groups=1344, bias=False) self.features_32_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1344) 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(1344, 56) self.features_32_conv_6_fc_2 = torch.nn.modules.linear.Linear(56, 1344) self.features_32_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_32_conv_7 = torch.nn.modules.conv.Conv2d(1344, 224, 1, 1, 0, bias=False) self.features_32_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(224) self.features_33_conv_0 = torch.nn.modules.conv.Conv2d(224, 1344, 1, 1, 0, bias=False) self.features_33_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1344) self.features_33_conv_3 = torch.nn.modules.conv.Conv2d(1344, 1344, 3, 1, 1, groups=1344, bias=False) self.features_33_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1344) 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(1344, 56) self.features_33_conv_6_fc_2 = torch.nn.modules.linear.Linear(56, 1344) self.features_33_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_33_conv_7 = torch.nn.modules.conv.Conv2d(1344, 224, 1, 1, 0, bias=False) self.features_33_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(224) self.features_34_conv_0 = torch.nn.modules.conv.Conv2d(224, 1344, 1, 1, 0, bias=False) self.features_34_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1344) self.features_34_conv_3 = torch.nn.modules.conv.Conv2d(1344, 1344, 3, 1, 1, groups=1344, bias=False) self.features_34_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1344) 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(1344, 56) self.features_34_conv_6_fc_2 = torch.nn.modules.linear.Linear(56, 1344) self.features_34_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_34_conv_7 = torch.nn.modules.conv.Conv2d(1344, 224, 1, 1, 0, bias=False) self.features_34_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(224) self.features_35_conv_0 = torch.nn.modules.conv.Conv2d(224, 1344, 1, 1, 0, bias=False) self.features_35_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1344) self.features_35_conv_3 = torch.nn.modules.conv.Conv2d(1344, 1344, 3, 1, 1, groups=1344, bias=False) self.features_35_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1344) 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(1344, 56) self.features_35_conv_6_fc_2 = torch.nn.modules.linear.Linear(56, 1344) self.features_35_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_35_conv_7 = torch.nn.modules.conv.Conv2d(1344, 224, 1, 1, 0, bias=False) self.features_35_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(224) self.features_36_conv_0 = torch.nn.modules.conv.Conv2d(224, 1344, 1, 1, 0, bias=False) self.features_36_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1344) self.features_36_conv_3 = torch.nn.modules.conv.Conv2d(1344, 1344, 3, 1, 1, groups=1344, bias=False) self.features_36_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1344) 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(1344, 56) self.features_36_conv_6_fc_2 = torch.nn.modules.linear.Linear(56, 1344) self.features_36_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_36_conv_7 = torch.nn.modules.conv.Conv2d(1344, 224, 1, 1, 0, bias=False) self.features_36_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(224) self.features_37_conv_0 = torch.nn.modules.conv.Conv2d(224, 1344, 1, 1, 0, bias=False) self.features_37_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1344) self.features_37_conv_3 = torch.nn.modules.conv.Conv2d(1344, 1344, 3, 1, 1, groups=1344, bias=False) self.features_37_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1344) 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(1344, 56) self.features_37_conv_6_fc_2 = torch.nn.modules.linear.Linear(56, 1344) self.features_37_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_37_conv_7 = torch.nn.modules.conv.Conv2d(1344, 224, 1, 1, 0, bias=False) self.features_37_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(224) self.features_38_conv_0 = torch.nn.modules.conv.Conv2d(224, 1344, 1, 1, 0, bias=False) self.features_38_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1344) self.features_38_conv_3 = torch.nn.modules.conv.Conv2d(1344, 1344, 3, 1, 1, groups=1344, bias=False) self.features_38_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1344) 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(1344, 56) self.features_38_conv_6_fc_2 = torch.nn.modules.linear.Linear(56, 1344) self.features_38_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_38_conv_7 = torch.nn.modules.conv.Conv2d(1344, 224, 1, 1, 0, bias=False) self.features_38_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(224) self.features_39_conv_0 = torch.nn.modules.conv.Conv2d(224, 1344, 1, 1, 0, bias=False) self.features_39_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1344) self.features_39_conv_3 = torch.nn.modules.conv.Conv2d(1344, 1344, 3, 1, 1, groups=1344, bias=False) self.features_39_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1344) 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(1344, 56) self.features_39_conv_6_fc_2 = torch.nn.modules.linear.Linear(56, 1344) self.features_39_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_39_conv_7 = torch.nn.modules.conv.Conv2d(1344, 224, 1, 1, 0, bias=False) self.features_39_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(224) self.features_40_conv_0 = torch.nn.modules.conv.Conv2d(224, 1344, 1, 1, 0, bias=False) self.features_40_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1344) self.features_40_conv_3 = torch.nn.modules.conv.Conv2d(1344, 1344, 3, 1, 1, groups=1344, bias=False) self.features_40_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1344) 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(1344, 56) self.features_40_conv_6_fc_2 = torch.nn.modules.linear.Linear(56, 1344) self.features_40_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_40_conv_7 = torch.nn.modules.conv.Conv2d(1344, 224, 1, 1, 0, bias=False) self.features_40_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(224) self.features_41_conv_0 = torch.nn.modules.conv.Conv2d(224, 1344, 1, 1, 0, bias=False) self.features_41_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1344) self.features_41_conv_3 = torch.nn.modules.conv.Conv2d(1344, 1344, 3, 1, 1, groups=1344, bias=False) self.features_41_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1344) 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(1344, 56) self.features_41_conv_6_fc_2 = torch.nn.modules.linear.Linear(56, 1344) self.features_41_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_41_conv_7 = torch.nn.modules.conv.Conv2d(1344, 224, 1, 1, 0, bias=False) self.features_41_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(224) self.features_42_conv_0 = torch.nn.modules.conv.Conv2d(224, 1344, 1, 1, 0, bias=False) self.features_42_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1344) self.features_42_conv_3 = torch.nn.modules.conv.Conv2d(1344, 1344, 3, 1, 1, groups=1344, bias=False) self.features_42_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1344) 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(1344, 56) self.features_42_conv_6_fc_2 = torch.nn.modules.linear.Linear(56, 1344) self.features_42_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_42_conv_7 = torch.nn.modules.conv.Conv2d(1344, 224, 1, 1, 0, bias=False) self.features_42_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(224) self.features_43_conv_0 = torch.nn.modules.conv.Conv2d(224, 1344, 1, 1, 0, bias=False) self.features_43_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1344) self.features_43_conv_3 = torch.nn.modules.conv.Conv2d(1344, 1344, 3, 1, 1, groups=1344, bias=False) self.features_43_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1344) 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(1344, 56) self.features_43_conv_6_fc_2 = torch.nn.modules.linear.Linear(56, 1344) self.features_43_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_43_conv_7 = torch.nn.modules.conv.Conv2d(1344, 224, 1, 1, 0, bias=False) self.features_43_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(224) self.features_44_conv_0 = torch.nn.modules.conv.Conv2d(224, 1344, 1, 1, 0, bias=False) self.features_44_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1344) self.features_44_conv_3 = torch.nn.modules.conv.Conv2d(1344, 1344, 3, 1, 1, groups=1344, bias=False) self.features_44_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1344) 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(1344, 56) self.features_44_conv_6_fc_2 = torch.nn.modules.linear.Linear(56, 1344) self.features_44_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_44_conv_7 = torch.nn.modules.conv.Conv2d(1344, 224, 1, 1, 0, bias=False) self.features_44_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(224) self.features_45_conv_0 = torch.nn.modules.conv.Conv2d(224, 1344, 1, 1, 0, bias=False) self.features_45_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1344) self.features_45_conv_3 = torch.nn.modules.conv.Conv2d(1344, 1344, 3, 1, 1, groups=1344, bias=False) self.features_45_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1344) 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(1344, 56) self.features_45_conv_6_fc_2 = torch.nn.modules.linear.Linear(56, 1344) self.features_45_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_45_conv_7 = torch.nn.modules.conv.Conv2d(1344, 224, 1, 1, 0, bias=False) self.features_45_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(224) self.features_46_conv_0 = torch.nn.modules.conv.Conv2d(224, 1344, 1, 1, 0, bias=False) self.features_46_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1344) self.features_46_conv_3 = torch.nn.modules.conv.Conv2d(1344, 1344, 3, 1, 1, groups=1344, bias=False) self.features_46_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1344) 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(1344, 56) self.features_46_conv_6_fc_2 = torch.nn.modules.linear.Linear(56, 1344) self.features_46_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_46_conv_7 = torch.nn.modules.conv.Conv2d(1344, 224, 1, 1, 0, bias=False) self.features_46_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(224) self.features_47_conv_0 = torch.nn.modules.conv.Conv2d(224, 1344, 1, 1, 0, bias=False) self.features_47_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1344) self.features_47_conv_3 = torch.nn.modules.conv.Conv2d(1344, 1344, 3, 1, 1, groups=1344, bias=False) self.features_47_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1344) 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(1344, 56) self.features_47_conv_6_fc_2 = torch.nn.modules.linear.Linear(56, 1344) self.features_47_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_47_conv_7 = torch.nn.modules.conv.Conv2d(1344, 224, 1, 1, 0, bias=False) self.features_47_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(224) self.features_48_conv_0 = torch.nn.modules.conv.Conv2d(224, 1344, 1, 1, 0, bias=False) self.features_48_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(1344) self.features_48_conv_3 = torch.nn.modules.conv.Conv2d(1344, 1344, 3, 2, 1, groups=1344, bias=False) self.features_48_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(1344) 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(1344, 56) self.features_48_conv_6_fc_2 = torch.nn.modules.linear.Linear(56, 1344) self.features_48_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_48_conv_7 = torch.nn.modules.conv.Conv2d(1344, 384, 1, 1, 0, bias=False) self.features_48_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(384) self.features_49_conv_0 = torch.nn.modules.conv.Conv2d(384, 2304, 1, 1, 0, bias=False) self.features_49_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(2304) self.features_49_conv_3 = torch.nn.modules.conv.Conv2d(2304, 2304, 3, 1, 1, groups=2304, bias=False) self.features_49_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(2304) 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(2304, 96) self.features_49_conv_6_fc_2 = torch.nn.modules.linear.Linear(96, 2304) self.features_49_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_49_conv_7 = torch.nn.modules.conv.Conv2d(2304, 384, 1, 1, 0, bias=False) self.features_49_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(384) self.features_50_conv_0 = torch.nn.modules.conv.Conv2d(384, 2304, 1, 1, 0, bias=False) self.features_50_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(2304) self.features_50_conv_3 = torch.nn.modules.conv.Conv2d(2304, 2304, 3, 1, 1, groups=2304, bias=False) self.features_50_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(2304) 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(2304, 96) self.features_50_conv_6_fc_2 = torch.nn.modules.linear.Linear(96, 2304) self.features_50_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_50_conv_7 = torch.nn.modules.conv.Conv2d(2304, 384, 1, 1, 0, bias=False) self.features_50_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(384) self.features_51_conv_0 = torch.nn.modules.conv.Conv2d(384, 2304, 1, 1, 0, bias=False) self.features_51_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(2304) self.features_51_conv_3 = torch.nn.modules.conv.Conv2d(2304, 2304, 3, 1, 1, groups=2304, bias=False) self.features_51_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(2304) 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(2304, 96) self.features_51_conv_6_fc_2 = torch.nn.modules.linear.Linear(96, 2304) self.features_51_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_51_conv_7 = torch.nn.modules.conv.Conv2d(2304, 384, 1, 1, 0, bias=False) self.features_51_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(384) self.features_52_conv_0 = torch.nn.modules.conv.Conv2d(384, 2304, 1, 1, 0, bias=False) self.features_52_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(2304) self.features_52_conv_3 = torch.nn.modules.conv.Conv2d(2304, 2304, 3, 1, 1, groups=2304, bias=False) self.features_52_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(2304) 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(2304, 96) self.features_52_conv_6_fc_2 = torch.nn.modules.linear.Linear(96, 2304) self.features_52_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_52_conv_7 = torch.nn.modules.conv.Conv2d(2304, 384, 1, 1, 0, bias=False) self.features_52_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(384) self.features_53_conv_0 = torch.nn.modules.conv.Conv2d(384, 2304, 1, 1, 0, bias=False) self.features_53_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(2304) self.features_53_conv_3 = torch.nn.modules.conv.Conv2d(2304, 2304, 3, 1, 1, groups=2304, bias=False) self.features_53_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(2304) 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(2304, 96) self.features_53_conv_6_fc_2 = torch.nn.modules.linear.Linear(96, 2304) self.features_53_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_53_conv_7 = torch.nn.modules.conv.Conv2d(2304, 384, 1, 1, 0, bias=False) self.features_53_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(384) self.features_54_conv_0 = torch.nn.modules.conv.Conv2d(384, 2304, 1, 1, 0, bias=False) self.features_54_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(2304) self.features_54_conv_3 = torch.nn.modules.conv.Conv2d(2304, 2304, 3, 1, 1, groups=2304, bias=False) self.features_54_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(2304) 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(2304, 96) self.features_54_conv_6_fc_2 = torch.nn.modules.linear.Linear(96, 2304) self.features_54_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_54_conv_7 = torch.nn.modules.conv.Conv2d(2304, 384, 1, 1, 0, bias=False) self.features_54_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(384) self.features_55_conv_0 = torch.nn.modules.conv.Conv2d(384, 2304, 1, 1, 0, bias=False) self.features_55_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(2304) self.features_55_conv_3 = torch.nn.modules.conv.Conv2d(2304, 2304, 3, 1, 1, groups=2304, bias=False) self.features_55_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(2304) 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(2304, 96) self.features_55_conv_6_fc_2 = torch.nn.modules.linear.Linear(96, 2304) self.features_55_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_55_conv_7 = torch.nn.modules.conv.Conv2d(2304, 384, 1, 1, 0, bias=False) self.features_55_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(384) self.features_56_conv_0 = torch.nn.modules.conv.Conv2d(384, 2304, 1, 1, 0, bias=False) self.features_56_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(2304) self.features_56_conv_3 = torch.nn.modules.conv.Conv2d(2304, 2304, 3, 1, 1, groups=2304, bias=False) self.features_56_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(2304) 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(2304, 96) self.features_56_conv_6_fc_2 = torch.nn.modules.linear.Linear(96, 2304) self.features_56_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_56_conv_7 = torch.nn.modules.conv.Conv2d(2304, 384, 1, 1, 0, bias=False) self.features_56_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(384) self.features_57_conv_0 = torch.nn.modules.conv.Conv2d(384, 2304, 1, 1, 0, bias=False) self.features_57_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(2304) self.features_57_conv_3 = torch.nn.modules.conv.Conv2d(2304, 2304, 3, 1, 1, groups=2304, bias=False) self.features_57_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(2304) 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(2304, 96) self.features_57_conv_6_fc_2 = torch.nn.modules.linear.Linear(96, 2304) self.features_57_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_57_conv_7 = torch.nn.modules.conv.Conv2d(2304, 384, 1, 1, 0, bias=False) self.features_57_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(384) self.features_58_conv_0 = torch.nn.modules.conv.Conv2d(384, 2304, 1, 1, 0, bias=False) self.features_58_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(2304) self.features_58_conv_3 = torch.nn.modules.conv.Conv2d(2304, 2304, 3, 1, 1, groups=2304, bias=False) self.features_58_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(2304) 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(2304, 96) self.features_58_conv_6_fc_2 = torch.nn.modules.linear.Linear(96, 2304) self.features_58_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_58_conv_7 = torch.nn.modules.conv.Conv2d(2304, 384, 1, 1, 0, bias=False) self.features_58_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(384) self.features_59_conv_0 = torch.nn.modules.conv.Conv2d(384, 2304, 1, 1, 0, bias=False) self.features_59_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(2304) self.features_59_conv_3 = torch.nn.modules.conv.Conv2d(2304, 2304, 3, 1, 1, groups=2304, bias=False) self.features_59_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(2304) 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(2304, 96) self.features_59_conv_6_fc_2 = torch.nn.modules.linear.Linear(96, 2304) self.features_59_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_59_conv_7 = torch.nn.modules.conv.Conv2d(2304, 384, 1, 1, 0, bias=False) self.features_59_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(384) self.features_60_conv_0 = torch.nn.modules.conv.Conv2d(384, 2304, 1, 1, 0, bias=False) self.features_60_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(2304) self.features_60_conv_3 = torch.nn.modules.conv.Conv2d(2304, 2304, 3, 1, 1, groups=2304, bias=False) self.features_60_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(2304) 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(2304, 96) self.features_60_conv_6_fc_2 = torch.nn.modules.linear.Linear(96, 2304) self.features_60_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_60_conv_7 = torch.nn.modules.conv.Conv2d(2304, 384, 1, 1, 0, bias=False) self.features_60_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(384) self.features_61_conv_0 = torch.nn.modules.conv.Conv2d(384, 2304, 1, 1, 0, bias=False) self.features_61_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(2304) self.features_61_conv_3 = torch.nn.modules.conv.Conv2d(2304, 2304, 3, 1, 1, groups=2304, bias=False) self.features_61_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(2304) 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(2304, 96) self.features_61_conv_6_fc_2 = torch.nn.modules.linear.Linear(96, 2304) self.features_61_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_61_conv_7 = torch.nn.modules.conv.Conv2d(2304, 384, 1, 1, 0, bias=False) self.features_61_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(384) self.features_62_conv_0 = torch.nn.modules.conv.Conv2d(384, 2304, 1, 1, 0, bias=False) self.features_62_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(2304) self.features_62_conv_3 = torch.nn.modules.conv.Conv2d(2304, 2304, 3, 1, 1, groups=2304, bias=False) self.features_62_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(2304) 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(2304, 96) self.features_62_conv_6_fc_2 = torch.nn.modules.linear.Linear(96, 2304) self.features_62_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_62_conv_7 = torch.nn.modules.conv.Conv2d(2304, 384, 1, 1, 0, bias=False) self.features_62_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(384) self.features_63_conv_0 = torch.nn.modules.conv.Conv2d(384, 2304, 1, 1, 0, bias=False) self.features_63_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(2304) self.features_63_conv_3 = torch.nn.modules.conv.Conv2d(2304, 2304, 3, 1, 1, groups=2304, bias=False) self.features_63_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(2304) 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(2304, 96) self.features_63_conv_6_fc_2 = torch.nn.modules.linear.Linear(96, 2304) self.features_63_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_63_conv_7 = torch.nn.modules.conv.Conv2d(2304, 384, 1, 1, 0, bias=False) self.features_63_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(384) self.features_64_conv_0 = torch.nn.modules.conv.Conv2d(384, 2304, 1, 1, 0, bias=False) self.features_64_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(2304) self.features_64_conv_3 = torch.nn.modules.conv.Conv2d(2304, 2304, 3, 1, 1, groups=2304, bias=False) self.features_64_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(2304) 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(2304, 96) self.features_64_conv_6_fc_2 = torch.nn.modules.linear.Linear(96, 2304) self.features_64_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_64_conv_7 = torch.nn.modules.conv.Conv2d(2304, 384, 1, 1, 0, bias=False) self.features_64_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(384) self.features_65_conv_0 = torch.nn.modules.conv.Conv2d(384, 2304, 1, 1, 0, bias=False) self.features_65_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(2304) self.features_65_conv_3 = torch.nn.modules.conv.Conv2d(2304, 2304, 3, 1, 1, groups=2304, bias=False) self.features_65_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(2304) 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(2304, 96) self.features_65_conv_6_fc_2 = torch.nn.modules.linear.Linear(96, 2304) self.features_65_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_65_conv_7 = torch.nn.modules.conv.Conv2d(2304, 384, 1, 1, 0, bias=False) self.features_65_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(384) self.features_66_conv_0 = torch.nn.modules.conv.Conv2d(384, 2304, 1, 1, 0, bias=False) self.features_66_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(2304) self.features_66_conv_3 = torch.nn.modules.conv.Conv2d(2304, 2304, 3, 1, 1, groups=2304, bias=False) self.features_66_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(2304) 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(2304, 96) self.features_66_conv_6_fc_2 = torch.nn.modules.linear.Linear(96, 2304) self.features_66_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_66_conv_7 = torch.nn.modules.conv.Conv2d(2304, 384, 1, 1, 0, bias=False) self.features_66_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(384) self.features_67_conv_0 = torch.nn.modules.conv.Conv2d(384, 2304, 1, 1, 0, bias=False) self.features_67_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(2304) self.features_67_conv_3 = torch.nn.modules.conv.Conv2d(2304, 2304, 3, 1, 1, groups=2304, bias=False) self.features_67_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(2304) 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(2304, 96) self.features_67_conv_6_fc_2 = torch.nn.modules.linear.Linear(96, 2304) self.features_67_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_67_conv_7 = torch.nn.modules.conv.Conv2d(2304, 384, 1, 1, 0, bias=False) self.features_67_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(384) self.features_68_conv_0 = torch.nn.modules.conv.Conv2d(384, 2304, 1, 1, 0, bias=False) self.features_68_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(2304) self.features_68_conv_3 = torch.nn.modules.conv.Conv2d(2304, 2304, 3, 1, 1, groups=2304, bias=False) self.features_68_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(2304) 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(2304, 96) self.features_68_conv_6_fc_2 = torch.nn.modules.linear.Linear(96, 2304) self.features_68_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_68_conv_7 = torch.nn.modules.conv.Conv2d(2304, 384, 1, 1, 0, bias=False) self.features_68_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(384) self.features_69_conv_0 = torch.nn.modules.conv.Conv2d(384, 2304, 1, 1, 0, bias=False) self.features_69_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(2304) self.features_69_conv_3 = torch.nn.modules.conv.Conv2d(2304, 2304, 3, 1, 1, groups=2304, bias=False) self.features_69_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(2304) 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(2304, 96) self.features_69_conv_6_fc_2 = torch.nn.modules.linear.Linear(96, 2304) self.features_69_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_69_conv_7 = torch.nn.modules.conv.Conv2d(2304, 384, 1, 1, 0, bias=False) self.features_69_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(384) self.features_70_conv_0 = torch.nn.modules.conv.Conv2d(384, 2304, 1, 1, 0, bias=False) self.features_70_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(2304) self.features_70_conv_3 = torch.nn.modules.conv.Conv2d(2304, 2304, 3, 1, 1, groups=2304, bias=False) self.features_70_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(2304) 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(2304, 96) self.features_70_conv_6_fc_2 = torch.nn.modules.linear.Linear(96, 2304) self.features_70_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_70_conv_7 = torch.nn.modules.conv.Conv2d(2304, 384, 1, 1, 0, bias=False) self.features_70_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(384) self.features_71_conv_0 = torch.nn.modules.conv.Conv2d(384, 2304, 1, 1, 0, bias=False) self.features_71_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(2304) self.features_71_conv_3 = torch.nn.modules.conv.Conv2d(2304, 2304, 3, 1, 1, groups=2304, bias=False) self.features_71_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(2304) 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(2304, 96) self.features_71_conv_6_fc_2 = torch.nn.modules.linear.Linear(96, 2304) self.features_71_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_71_conv_7 = torch.nn.modules.conv.Conv2d(2304, 384, 1, 1, 0, bias=False) self.features_71_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(384) self.features_72_conv_0 = torch.nn.modules.conv.Conv2d(384, 2304, 1, 1, 0, bias=False) self.features_72_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(2304) self.features_72_conv_3 = torch.nn.modules.conv.Conv2d(2304, 2304, 3, 1, 1, groups=2304, bias=False) self.features_72_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(2304) 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(2304, 96) self.features_72_conv_6_fc_2 = torch.nn.modules.linear.Linear(96, 2304) self.features_72_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_72_conv_7 = torch.nn.modules.conv.Conv2d(2304, 384, 1, 1, 0, bias=False) self.features_72_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(384) self.features_73_conv_0 = torch.nn.modules.conv.Conv2d(384, 2304, 1, 1, 0, bias=False) self.features_73_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(2304) self.features_73_conv_3 = torch.nn.modules.conv.Conv2d(2304, 2304, 3, 1, 1, groups=2304, bias=False) self.features_73_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(2304) 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(2304, 96) self.features_73_conv_6_fc_2 = torch.nn.modules.linear.Linear(96, 2304) self.features_73_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_73_conv_7 = torch.nn.modules.conv.Conv2d(2304, 640, 1, 1, 0, bias=False) self.features_73_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(640) self.features_74_conv_0 = torch.nn.modules.conv.Conv2d(640, 3840, 1, 1, 0, bias=False) self.features_74_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3840) self.features_74_conv_3 = torch.nn.modules.conv.Conv2d(3840, 3840, 3, 1, 1, groups=3840, bias=False) self.features_74_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3840) 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(3840, 160) self.features_74_conv_6_fc_2 = torch.nn.modules.linear.Linear(160, 3840) self.features_74_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_74_conv_7 = torch.nn.modules.conv.Conv2d(3840, 640, 1, 1, 0, bias=False) self.features_74_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(640) self.features_75_conv_0 = torch.nn.modules.conv.Conv2d(640, 3840, 1, 1, 0, bias=False) self.features_75_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3840) self.features_75_conv_3 = torch.nn.modules.conv.Conv2d(3840, 3840, 3, 1, 1, groups=3840, bias=False) self.features_75_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3840) 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(3840, 160) self.features_75_conv_6_fc_2 = torch.nn.modules.linear.Linear(160, 3840) self.features_75_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_75_conv_7 = torch.nn.modules.conv.Conv2d(3840, 640, 1, 1, 0, bias=False) self.features_75_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(640) self.features_76_conv_0 = torch.nn.modules.conv.Conv2d(640, 3840, 1, 1, 0, bias=False) self.features_76_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3840) self.features_76_conv_3 = torch.nn.modules.conv.Conv2d(3840, 3840, 3, 1, 1, groups=3840, bias=False) self.features_76_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3840) 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(3840, 160) self.features_76_conv_6_fc_2 = torch.nn.modules.linear.Linear(160, 3840) self.features_76_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_76_conv_7 = torch.nn.modules.conv.Conv2d(3840, 640, 1, 1, 0, bias=False) self.features_76_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(640) self.features_77_conv_0 = torch.nn.modules.conv.Conv2d(640, 3840, 1, 1, 0, bias=False) self.features_77_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3840) self.features_77_conv_3 = torch.nn.modules.conv.Conv2d(3840, 3840, 3, 1, 1, groups=3840, bias=False) self.features_77_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3840) 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(3840, 160) self.features_77_conv_6_fc_2 = torch.nn.modules.linear.Linear(160, 3840) self.features_77_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_77_conv_7 = torch.nn.modules.conv.Conv2d(3840, 640, 1, 1, 0, bias=False) self.features_77_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(640) self.features_78_conv_0 = torch.nn.modules.conv.Conv2d(640, 3840, 1, 1, 0, bias=False) self.features_78_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3840) self.features_78_conv_3 = torch.nn.modules.conv.Conv2d(3840, 3840, 3, 1, 1, groups=3840, bias=False) self.features_78_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3840) 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(3840, 160) self.features_78_conv_6_fc_2 = torch.nn.modules.linear.Linear(160, 3840) self.features_78_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_78_conv_7 = torch.nn.modules.conv.Conv2d(3840, 640, 1, 1, 0, bias=False) self.features_78_conv_8 = torch.nn.modules.batchnorm.BatchNorm2d(640) self.features_79_conv_0 = torch.nn.modules.conv.Conv2d(640, 3840, 1, 1, 0, bias=False) self.features_79_conv_1 = torch.nn.modules.batchnorm.BatchNorm2d(3840) self.features_79_conv_3 = torch.nn.modules.conv.Conv2d(3840, 3840, 3, 1, 1, groups=3840, bias=False) self.features_79_conv_4 = torch.nn.modules.batchnorm.BatchNorm2d(3840) 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(3840, 160) self.features_79_conv_6_fc_2 = torch.nn.modules.linear.Linear(160, 3840) self.features_79_conv_6_fc_3 = torch.nn.modules.activation.Sigmoid() self.features_79_conv_7 = torch.nn.modules.conv.Conv2d(3840, 640, 1, 1, 0, bias=False) self.features_79_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) features_13_conv_0 = self.features_13_conv_0(features_12_conv_4) features_13_conv_1 = self.features_13_conv_1(features_13_conv_0) sigmoid_14 = torch.sigmoid(features_13_conv_1) mul_14 = features_13_conv_1.__mul__(sigmoid_14) features_13_conv_3 = self.features_13_conv_3(mul_14) features_13_conv_4 = self.features_13_conv_4(features_13_conv_3) add_10 = features_12_conv_4.__add__(features_13_conv_4) features_14_conv_0 = self.features_14_conv_0(add_10) features_14_conv_1 = self.features_14_conv_1(features_14_conv_0) sigmoid_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 = add_10.__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) sigmoid_21 = torch.sigmoid(features_19_conv_4) mul_21 = features_19_conv_4.__mul__(sigmoid_21) size_1 = mul_21.size() features_19_conv_6_avg_pool = self.features_19_conv_6_avg_pool(mul_21) view_1 = features_19_conv_6_avg_pool.view(size_1[0], size_1[1]) features_19_conv_6_fc_0 = self.features_19_conv_6_fc_0(view_1) sigmoid_22 = torch.sigmoid(features_19_conv_6_fc_0) mul_22 = features_19_conv_6_fc_0.__mul__(sigmoid_22) features_19_conv_6_fc_2 = self.features_19_conv_6_fc_2(mul_22) features_19_conv_6_fc_3 = self.features_19_conv_6_fc_3(features_19_conv_6_fc_2) view_2 = features_19_conv_6_fc_3.view(size_1[0], size_1[1], 1, 1) mul_23 = mul_21.__mul__(view_2) features_19_conv_7 = self.features_19_conv_7(mul_23) features_19_conv_8 = self.features_19_conv_8(features_19_conv_7) features_20_conv_0 = self.features_20_conv_0(features_19_conv_8) features_20_conv_1 = self.features_20_conv_1(features_20_conv_0) sigmoid_23 = torch.sigmoid(features_20_conv_1) mul_24 = features_20_conv_1.__mul__(sigmoid_23) features_20_conv_3 = self.features_20_conv_3(mul_24) features_20_conv_4 = self.features_20_conv_4(features_20_conv_3) sigmoid_24 = torch.sigmoid(features_20_conv_4) mul_25 = features_20_conv_4.__mul__(sigmoid_24) size_2 = mul_25.size() features_20_conv_6_avg_pool = self.features_20_conv_6_avg_pool(mul_25) view_3 = features_20_conv_6_avg_pool.view(size_2[0], size_2[1]) features_20_conv_6_fc_0 = self.features_20_conv_6_fc_0(view_3) sigmoid_25 = torch.sigmoid(features_20_conv_6_fc_0) mul_26 = features_20_conv_6_fc_0.__mul__(sigmoid_25) features_20_conv_6_fc_2 = self.features_20_conv_6_fc_2(mul_26) features_20_conv_6_fc_3 = self.features_20_conv_6_fc_3(features_20_conv_6_fc_2) view_4 = features_20_conv_6_fc_3.view(size_2[0], size_2[1], 1, 1) mul_27 = mul_25.__mul__(view_4) features_20_conv_7 = self.features_20_conv_7(mul_27) features_20_conv_8 = self.features_20_conv_8(features_20_conv_7) add_16 = features_19_conv_8.__add__(features_20_conv_8) features_21_conv_0 = self.features_21_conv_0(add_16) features_21_conv_1 = self.features_21_conv_1(features_21_conv_0) sigmoid_26 = torch.sigmoid(features_21_conv_1) mul_28 = features_21_conv_1.__mul__(sigmoid_26) features_21_conv_3 = self.features_21_conv_3(mul_28) features_21_conv_4 = self.features_21_conv_4(features_21_conv_3) sigmoid_27 = torch.sigmoid(features_21_conv_4) mul_29 = features_21_conv_4.__mul__(sigmoid_27) size_3 = mul_29.size() features_21_conv_6_avg_pool = self.features_21_conv_6_avg_pool(mul_29) view_5 = features_21_conv_6_avg_pool.view(size_3[0], size_3[1]) features_21_conv_6_fc_0 = self.features_21_conv_6_fc_0(view_5) sigmoid_28 = torch.sigmoid(features_21_conv_6_fc_0) mul_30 = features_21_conv_6_fc_0.__mul__(sigmoid_28) features_21_conv_6_fc_2 = self.features_21_conv_6_fc_2(mul_30) features_21_conv_6_fc_3 = self.features_21_conv_6_fc_3(features_21_conv_6_fc_2) view_6 = features_21_conv_6_fc_3.view(size_3[0], size_3[1], 1, 1) mul_31 = mul_29.__mul__(view_6) features_21_conv_7 = self.features_21_conv_7(mul_31) features_21_conv_8 = self.features_21_conv_8(features_21_conv_7) add_17 = add_16.__add__(features_21_conv_8) features_22_conv_0 = self.features_22_conv_0(add_17) features_22_conv_1 = self.features_22_conv_1(features_22_conv_0) sigmoid_29 = torch.sigmoid(features_22_conv_1) mul_32 = features_22_conv_1.__mul__(sigmoid_29) features_22_conv_3 = self.features_22_conv_3(mul_32) features_22_conv_4 = self.features_22_conv_4(features_22_conv_3) sigmoid_30 = torch.sigmoid(features_22_conv_4) mul_33 = features_22_conv_4.__mul__(sigmoid_30) size_4 = mul_33.size() features_22_conv_6_avg_pool = self.features_22_conv_6_avg_pool(mul_33) view_7 = features_22_conv_6_avg_pool.view(size_4[0], size_4[1]) features_22_conv_6_fc_0 = self.features_22_conv_6_fc_0(view_7) sigmoid_31 = torch.sigmoid(features_22_conv_6_fc_0) mul_34 = features_22_conv_6_fc_0.__mul__(sigmoid_31) features_22_conv_6_fc_2 = self.features_22_conv_6_fc_2(mul_34) features_22_conv_6_fc_3 = self.features_22_conv_6_fc_3(features_22_conv_6_fc_2) view_8 = features_22_conv_6_fc_3.view(size_4[0], size_4[1], 1, 1) mul_35 = mul_33.__mul__(view_8) features_22_conv_7 = self.features_22_conv_7(mul_35) features_22_conv_8 = self.features_22_conv_8(features_22_conv_7) add_18 = add_17.__add__(features_22_conv_8) features_23_conv_0 = self.features_23_conv_0(add_18) features_23_conv_1 = self.features_23_conv_1(features_23_conv_0) sigmoid_32 = torch.sigmoid(features_23_conv_1) mul_36 = features_23_conv_1.__mul__(sigmoid_32) features_23_conv_3 = self.features_23_conv_3(mul_36) features_23_conv_4 = self.features_23_conv_4(features_23_conv_3) sigmoid_33 = torch.sigmoid(features_23_conv_4) mul_37 = features_23_conv_4.__mul__(sigmoid_33) size_5 = mul_37.size() features_23_conv_6_avg_pool = self.features_23_conv_6_avg_pool(mul_37) view_9 = features_23_conv_6_avg_pool.view(size_5[0], size_5[1]) features_23_conv_6_fc_0 = self.features_23_conv_6_fc_0(view_9) sigmoid_34 = torch.sigmoid(features_23_conv_6_fc_0) mul_38 = features_23_conv_6_fc_0.__mul__(sigmoid_34) features_23_conv_6_fc_2 = self.features_23_conv_6_fc_2(mul_38) features_23_conv_6_fc_3 = self.features_23_conv_6_fc_3(features_23_conv_6_fc_2) view_10 = features_23_conv_6_fc_3.view(size_5[0], size_5[1], 1, 1) mul_39 = mul_37.__mul__(view_10) features_23_conv_7 = self.features_23_conv_7(mul_39) 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_35 = torch.sigmoid(features_24_conv_1) mul_40 = features_24_conv_1.__mul__(sigmoid_35) features_24_conv_3 = self.features_24_conv_3(mul_40) features_24_conv_4 = self.features_24_conv_4(features_24_conv_3) sigmoid_36 = torch.sigmoid(features_24_conv_4) mul_41 = features_24_conv_4.__mul__(sigmoid_36) size_6 = mul_41.size() features_24_conv_6_avg_pool = self.features_24_conv_6_avg_pool(mul_41) view_11 = features_24_conv_6_avg_pool.view(size_6[0], size_6[1]) features_24_conv_6_fc_0 = self.features_24_conv_6_fc_0(view_11) sigmoid_37 = torch.sigmoid(features_24_conv_6_fc_0) mul_42 = features_24_conv_6_fc_0.__mul__(sigmoid_37) features_24_conv_6_fc_2 = self.features_24_conv_6_fc_2(mul_42) features_24_conv_6_fc_3 = self.features_24_conv_6_fc_3(features_24_conv_6_fc_2) view_12 = features_24_conv_6_fc_3.view(size_6[0], size_6[1], 1, 1) mul_43 = mul_41.__mul__(view_12) features_24_conv_7 = self.features_24_conv_7(mul_43) 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_38 = torch.sigmoid(features_25_conv_1) mul_44 = features_25_conv_1.__mul__(sigmoid_38) features_25_conv_3 = self.features_25_conv_3(mul_44) features_25_conv_4 = self.features_25_conv_4(features_25_conv_3) sigmoid_39 = torch.sigmoid(features_25_conv_4) mul_45 = features_25_conv_4.__mul__(sigmoid_39) size_7 = mul_45.size() features_25_conv_6_avg_pool = self.features_25_conv_6_avg_pool(mul_45) view_13 = features_25_conv_6_avg_pool.view(size_7[0], size_7[1]) features_25_conv_6_fc_0 = self.features_25_conv_6_fc_0(view_13) sigmoid_40 = torch.sigmoid(features_25_conv_6_fc_0) mul_46 = features_25_conv_6_fc_0.__mul__(sigmoid_40) features_25_conv_6_fc_2 = self.features_25_conv_6_fc_2(mul_46) features_25_conv_6_fc_3 = self.features_25_conv_6_fc_3(features_25_conv_6_fc_2) view_14 = features_25_conv_6_fc_3.view(size_7[0], size_7[1], 1, 1) mul_47 = mul_45.__mul__(view_14) features_25_conv_7 = self.features_25_conv_7(mul_47) 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_41 = torch.sigmoid(features_26_conv_1) mul_48 = features_26_conv_1.__mul__(sigmoid_41) features_26_conv_3 = self.features_26_conv_3(mul_48) features_26_conv_4 = self.features_26_conv_4(features_26_conv_3) sigmoid_42 = torch.sigmoid(features_26_conv_4) mul_49 = features_26_conv_4.__mul__(sigmoid_42) size_8 = mul_49.size() features_26_conv_6_avg_pool = self.features_26_conv_6_avg_pool(mul_49) view_15 = features_26_conv_6_avg_pool.view(size_8[0], size_8[1]) features_26_conv_6_fc_0 = self.features_26_conv_6_fc_0(view_15) sigmoid_43 = torch.sigmoid(features_26_conv_6_fc_0) mul_50 = features_26_conv_6_fc_0.__mul__(sigmoid_43) features_26_conv_6_fc_2 = self.features_26_conv_6_fc_2(mul_50) features_26_conv_6_fc_3 = self.features_26_conv_6_fc_3(features_26_conv_6_fc_2) view_16 = features_26_conv_6_fc_3.view(size_8[0], size_8[1], 1, 1) mul_51 = mul_49.__mul__(view_16) features_26_conv_7 = self.features_26_conv_7(mul_51) 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_44 = torch.sigmoid(features_27_conv_1) mul_52 = features_27_conv_1.__mul__(sigmoid_44) features_27_conv_3 = self.features_27_conv_3(mul_52) features_27_conv_4 = self.features_27_conv_4(features_27_conv_3) sigmoid_45 = torch.sigmoid(features_27_conv_4) mul_53 = features_27_conv_4.__mul__(sigmoid_45) size_9 = mul_53.size() features_27_conv_6_avg_pool = self.features_27_conv_6_avg_pool(mul_53) view_17 = features_27_conv_6_avg_pool.view(size_9[0], size_9[1]) features_27_conv_6_fc_0 = self.features_27_conv_6_fc_0(view_17) sigmoid_46 = torch.sigmoid(features_27_conv_6_fc_0) mul_54 = features_27_conv_6_fc_0.__mul__(sigmoid_46) features_27_conv_6_fc_2 = self.features_27_conv_6_fc_2(mul_54) features_27_conv_6_fc_3 = self.features_27_conv_6_fc_3(features_27_conv_6_fc_2) view_18 = features_27_conv_6_fc_3.view(size_9[0], size_9[1], 1, 1) mul_55 = mul_53.__mul__(view_18) features_27_conv_7 = self.features_27_conv_7(mul_55) 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_47 = torch.sigmoid(features_28_conv_1) mul_56 = features_28_conv_1.__mul__(sigmoid_47) features_28_conv_3 = self.features_28_conv_3(mul_56) features_28_conv_4 = self.features_28_conv_4(features_28_conv_3) sigmoid_48 = torch.sigmoid(features_28_conv_4) mul_57 = features_28_conv_4.__mul__(sigmoid_48) size_10 = mul_57.size() features_28_conv_6_avg_pool = self.features_28_conv_6_avg_pool(mul_57) view_19 = features_28_conv_6_avg_pool.view(size_10[0], size_10[1]) features_28_conv_6_fc_0 = self.features_28_conv_6_fc_0(view_19) sigmoid_49 = torch.sigmoid(features_28_conv_6_fc_0) mul_58 = features_28_conv_6_fc_0.__mul__(sigmoid_49) features_28_conv_6_fc_2 = self.features_28_conv_6_fc_2(mul_58) features_28_conv_6_fc_3 = self.features_28_conv_6_fc_3(features_28_conv_6_fc_2) view_20 = features_28_conv_6_fc_3.view(size_10[0], size_10[1], 1, 1) mul_59 = mul_57.__mul__(view_20) features_28_conv_7 = self.features_28_conv_7(mul_59) 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_50 = torch.sigmoid(features_29_conv_1) mul_60 = features_29_conv_1.__mul__(sigmoid_50) features_29_conv_3 = self.features_29_conv_3(mul_60) features_29_conv_4 = self.features_29_conv_4(features_29_conv_3) sigmoid_51 = torch.sigmoid(features_29_conv_4) mul_61 = features_29_conv_4.__mul__(sigmoid_51) size_11 = mul_61.size() features_29_conv_6_avg_pool = self.features_29_conv_6_avg_pool(mul_61) view_21 = features_29_conv_6_avg_pool.view(size_11[0], size_11[1]) features_29_conv_6_fc_0 = self.features_29_conv_6_fc_0(view_21) sigmoid_52 = torch.sigmoid(features_29_conv_6_fc_0) mul_62 = features_29_conv_6_fc_0.__mul__(sigmoid_52) features_29_conv_6_fc_2 = self.features_29_conv_6_fc_2(mul_62) features_29_conv_6_fc_3 = self.features_29_conv_6_fc_3(features_29_conv_6_fc_2) view_22 = features_29_conv_6_fc_3.view(size_11[0], size_11[1], 1, 1) mul_63 = mul_61.__mul__(view_22) features_29_conv_7 = self.features_29_conv_7(mul_63) features_29_conv_8 = self.features_29_conv_8(features_29_conv_7) features_30_conv_0 = self.features_30_conv_0(features_29_conv_8) features_30_conv_1 = self.features_30_conv_1(features_30_conv_0) sigmoid_53 = torch.sigmoid(features_30_conv_1) mul_64 = features_30_conv_1.__mul__(sigmoid_53) features_30_conv_3 = self.features_30_conv_3(mul_64) features_30_conv_4 = self.features_30_conv_4(features_30_conv_3) sigmoid_54 = torch.sigmoid(features_30_conv_4) mul_65 = features_30_conv_4.__mul__(sigmoid_54) size_12 = mul_65.size() features_30_conv_6_avg_pool = self.features_30_conv_6_avg_pool(mul_65) view_23 = features_30_conv_6_avg_pool.view(size_12[0], size_12[1]) features_30_conv_6_fc_0 = self.features_30_conv_6_fc_0(view_23) sigmoid_55 = torch.sigmoid(features_30_conv_6_fc_0) mul_66 = features_30_conv_6_fc_0.__mul__(sigmoid_55) features_30_conv_6_fc_2 = self.features_30_conv_6_fc_2(mul_66) features_30_conv_6_fc_3 = self.features_30_conv_6_fc_3(features_30_conv_6_fc_2) view_24 = features_30_conv_6_fc_3.view(size_12[0], size_12[1], 1, 1) mul_67 = mul_65.__mul__(view_24) features_30_conv_7 = self.features_30_conv_7(mul_67) features_30_conv_8 = self.features_30_conv_8(features_30_conv_7) add_25 = features_29_conv_8.__add__(features_30_conv_8) features_31_conv_0 = self.features_31_conv_0(add_25) features_31_conv_1 = self.features_31_conv_1(features_31_conv_0) sigmoid_56 = torch.sigmoid(features_31_conv_1) mul_68 = features_31_conv_1.__mul__(sigmoid_56) features_31_conv_3 = self.features_31_conv_3(mul_68) features_31_conv_4 = self.features_31_conv_4(features_31_conv_3) sigmoid_57 = torch.sigmoid(features_31_conv_4) mul_69 = features_31_conv_4.__mul__(sigmoid_57) size_13 = mul_69.size() features_31_conv_6_avg_pool = self.features_31_conv_6_avg_pool(mul_69) view_25 = features_31_conv_6_avg_pool.view(size_13[0], size_13[1]) features_31_conv_6_fc_0 = self.features_31_conv_6_fc_0(view_25) sigmoid_58 = torch.sigmoid(features_31_conv_6_fc_0) mul_70 = features_31_conv_6_fc_0.__mul__(sigmoid_58) features_31_conv_6_fc_2 = self.features_31_conv_6_fc_2(mul_70) features_31_conv_6_fc_3 = self.features_31_conv_6_fc_3(features_31_conv_6_fc_2) view_26 = features_31_conv_6_fc_3.view(size_13[0], size_13[1], 1, 1) mul_71 = mul_69.__mul__(view_26) features_31_conv_7 = self.features_31_conv_7(mul_71) features_31_conv_8 = self.features_31_conv_8(features_31_conv_7) add_26 = add_25.__add__(features_31_conv_8) features_32_conv_0 = self.features_32_conv_0(add_26) features_32_conv_1 = self.features_32_conv_1(features_32_conv_0) sigmoid_59 = torch.sigmoid(features_32_conv_1) mul_72 = features_32_conv_1.__mul__(sigmoid_59) features_32_conv_3 = self.features_32_conv_3(mul_72) features_32_conv_4 = self.features_32_conv_4(features_32_conv_3) sigmoid_60 = torch.sigmoid(features_32_conv_4) mul_73 = features_32_conv_4.__mul__(sigmoid_60) size_14 = mul_73.size() features_32_conv_6_avg_pool = self.features_32_conv_6_avg_pool(mul_73) view_27 = features_32_conv_6_avg_pool.view(size_14[0], size_14[1]) features_32_conv_6_fc_0 = self.features_32_conv_6_fc_0(view_27) sigmoid_61 = torch.sigmoid(features_32_conv_6_fc_0) mul_74 = features_32_conv_6_fc_0.__mul__(sigmoid_61) features_32_conv_6_fc_2 = self.features_32_conv_6_fc_2(mul_74) features_32_conv_6_fc_3 = self.features_32_conv_6_fc_3(features_32_conv_6_fc_2) view_28 = features_32_conv_6_fc_3.view(size_14[0], size_14[1], 1, 1) mul_75 = mul_73.__mul__(view_28) features_32_conv_7 = self.features_32_conv_7(mul_75) features_32_conv_8 = self.features_32_conv_8(features_32_conv_7) add_27 = add_26.__add__(features_32_conv_8) features_33_conv_0 = self.features_33_conv_0(add_27) features_33_conv_1 = self.features_33_conv_1(features_33_conv_0) sigmoid_62 = torch.sigmoid(features_33_conv_1) mul_76 = features_33_conv_1.__mul__(sigmoid_62) features_33_conv_3 = self.features_33_conv_3(mul_76) features_33_conv_4 = self.features_33_conv_4(features_33_conv_3) sigmoid_63 = torch.sigmoid(features_33_conv_4) mul_77 = features_33_conv_4.__mul__(sigmoid_63) size_15 = mul_77.size() features_33_conv_6_avg_pool = self.features_33_conv_6_avg_pool(mul_77) view_29 = features_33_conv_6_avg_pool.view(size_15[0], size_15[1]) features_33_conv_6_fc_0 = self.features_33_conv_6_fc_0(view_29) sigmoid_64 = torch.sigmoid(features_33_conv_6_fc_0) mul_78 = features_33_conv_6_fc_0.__mul__(sigmoid_64) features_33_conv_6_fc_2 = self.features_33_conv_6_fc_2(mul_78) features_33_conv_6_fc_3 = self.features_33_conv_6_fc_3(features_33_conv_6_fc_2) view_30 = features_33_conv_6_fc_3.view(size_15[0], size_15[1], 1, 1) mul_79 = mul_77.__mul__(view_30) features_33_conv_7 = self.features_33_conv_7(mul_79) features_33_conv_8 = self.features_33_conv_8(features_33_conv_7) add_28 = add_27.__add__(features_33_conv_8) features_34_conv_0 = self.features_34_conv_0(add_28) features_34_conv_1 = self.features_34_conv_1(features_34_conv_0) sigmoid_65 = torch.sigmoid(features_34_conv_1) mul_80 = features_34_conv_1.__mul__(sigmoid_65) features_34_conv_3 = self.features_34_conv_3(mul_80) features_34_conv_4 = self.features_34_conv_4(features_34_conv_3) sigmoid_66 = torch.sigmoid(features_34_conv_4) mul_81 = features_34_conv_4.__mul__(sigmoid_66) size_16 = mul_81.size() features_34_conv_6_avg_pool = self.features_34_conv_6_avg_pool(mul_81) view_31 = features_34_conv_6_avg_pool.view(size_16[0], size_16[1]) features_34_conv_6_fc_0 = self.features_34_conv_6_fc_0(view_31) sigmoid_67 = torch.sigmoid(features_34_conv_6_fc_0) mul_82 = features_34_conv_6_fc_0.__mul__(sigmoid_67) features_34_conv_6_fc_2 = self.features_34_conv_6_fc_2(mul_82) features_34_conv_6_fc_3 = self.features_34_conv_6_fc_3(features_34_conv_6_fc_2) view_32 = features_34_conv_6_fc_3.view(size_16[0], size_16[1], 1, 1) mul_83 = mul_81.__mul__(view_32) features_34_conv_7 = self.features_34_conv_7(mul_83) features_34_conv_8 = self.features_34_conv_8(features_34_conv_7) add_29 = add_28.__add__(features_34_conv_8) features_35_conv_0 = self.features_35_conv_0(add_29) features_35_conv_1 = self.features_35_conv_1(features_35_conv_0) sigmoid_68 = torch.sigmoid(features_35_conv_1) mul_84 = features_35_conv_1.__mul__(sigmoid_68) features_35_conv_3 = self.features_35_conv_3(mul_84) features_35_conv_4 = self.features_35_conv_4(features_35_conv_3) sigmoid_69 = torch.sigmoid(features_35_conv_4) mul_85 = features_35_conv_4.__mul__(sigmoid_69) size_17 = mul_85.size() features_35_conv_6_avg_pool = self.features_35_conv_6_avg_pool(mul_85) view_33 = features_35_conv_6_avg_pool.view(size_17[0], size_17[1]) features_35_conv_6_fc_0 = self.features_35_conv_6_fc_0(view_33) sigmoid_70 = torch.sigmoid(features_35_conv_6_fc_0) mul_86 = features_35_conv_6_fc_0.__mul__(sigmoid_70) features_35_conv_6_fc_2 = self.features_35_conv_6_fc_2(mul_86) features_35_conv_6_fc_3 = self.features_35_conv_6_fc_3(features_35_conv_6_fc_2) view_34 = features_35_conv_6_fc_3.view(size_17[0], size_17[1], 1, 1) mul_87 = mul_85.__mul__(view_34) features_35_conv_7 = self.features_35_conv_7(mul_87) features_35_conv_8 = self.features_35_conv_8(features_35_conv_7) add_30 = add_29.__add__(features_35_conv_8) features_36_conv_0 = self.features_36_conv_0(add_30) features_36_conv_1 = self.features_36_conv_1(features_36_conv_0) sigmoid_71 = torch.sigmoid(features_36_conv_1) mul_88 = features_36_conv_1.__mul__(sigmoid_71) features_36_conv_3 = self.features_36_conv_3(mul_88) features_36_conv_4 = self.features_36_conv_4(features_36_conv_3) sigmoid_72 = torch.sigmoid(features_36_conv_4) mul_89 = features_36_conv_4.__mul__(sigmoid_72) size_18 = mul_89.size() features_36_conv_6_avg_pool = self.features_36_conv_6_avg_pool(mul_89) view_35 = features_36_conv_6_avg_pool.view(size_18[0], size_18[1]) features_36_conv_6_fc_0 = self.features_36_conv_6_fc_0(view_35) sigmoid_73 = torch.sigmoid(features_36_conv_6_fc_0) mul_90 = features_36_conv_6_fc_0.__mul__(sigmoid_73) features_36_conv_6_fc_2 = self.features_36_conv_6_fc_2(mul_90) features_36_conv_6_fc_3 = self.features_36_conv_6_fc_3(features_36_conv_6_fc_2) view_36 = features_36_conv_6_fc_3.view(size_18[0], size_18[1], 1, 1) mul_91 = mul_89.__mul__(view_36) features_36_conv_7 = self.features_36_conv_7(mul_91) features_36_conv_8 = self.features_36_conv_8(features_36_conv_7) add_31 = add_30.__add__(features_36_conv_8) features_37_conv_0 = self.features_37_conv_0(add_31) features_37_conv_1 = self.features_37_conv_1(features_37_conv_0) sigmoid_74 = torch.sigmoid(features_37_conv_1) mul_92 = features_37_conv_1.__mul__(sigmoid_74) features_37_conv_3 = self.features_37_conv_3(mul_92) features_37_conv_4 = self.features_37_conv_4(features_37_conv_3) sigmoid_75 = torch.sigmoid(features_37_conv_4) mul_93 = features_37_conv_4.__mul__(sigmoid_75) size_19 = mul_93.size() features_37_conv_6_avg_pool = self.features_37_conv_6_avg_pool(mul_93) view_37 = features_37_conv_6_avg_pool.view(size_19[0], size_19[1]) features_37_conv_6_fc_0 = self.features_37_conv_6_fc_0(view_37) sigmoid_76 = torch.sigmoid(features_37_conv_6_fc_0) mul_94 = features_37_conv_6_fc_0.__mul__(sigmoid_76) features_37_conv_6_fc_2 = self.features_37_conv_6_fc_2(mul_94) features_37_conv_6_fc_3 = self.features_37_conv_6_fc_3(features_37_conv_6_fc_2) view_38 = features_37_conv_6_fc_3.view(size_19[0], size_19[1], 1, 1) mul_95 = mul_93.__mul__(view_38) features_37_conv_7 = self.features_37_conv_7(mul_95) features_37_conv_8 = self.features_37_conv_8(features_37_conv_7) add_32 = add_31.__add__(features_37_conv_8) features_38_conv_0 = self.features_38_conv_0(add_32) features_38_conv_1 = self.features_38_conv_1(features_38_conv_0) sigmoid_77 = torch.sigmoid(features_38_conv_1) mul_96 = features_38_conv_1.__mul__(sigmoid_77) features_38_conv_3 = self.features_38_conv_3(mul_96) features_38_conv_4 = self.features_38_conv_4(features_38_conv_3) sigmoid_78 = torch.sigmoid(features_38_conv_4) mul_97 = features_38_conv_4.__mul__(sigmoid_78) size_20 = mul_97.size() features_38_conv_6_avg_pool = self.features_38_conv_6_avg_pool(mul_97) view_39 = features_38_conv_6_avg_pool.view(size_20[0], size_20[1]) features_38_conv_6_fc_0 = self.features_38_conv_6_fc_0(view_39) sigmoid_79 = torch.sigmoid(features_38_conv_6_fc_0) mul_98 = features_38_conv_6_fc_0.__mul__(sigmoid_79) features_38_conv_6_fc_2 = self.features_38_conv_6_fc_2(mul_98) features_38_conv_6_fc_3 = self.features_38_conv_6_fc_3(features_38_conv_6_fc_2) view_40 = features_38_conv_6_fc_3.view(size_20[0], size_20[1], 1, 1) mul_99 = mul_97.__mul__(view_40) features_38_conv_7 = self.features_38_conv_7(mul_99) features_38_conv_8 = self.features_38_conv_8(features_38_conv_7) add_33 = add_32.__add__(features_38_conv_8) features_39_conv_0 = self.features_39_conv_0(add_33) features_39_conv_1 = self.features_39_conv_1(features_39_conv_0) sigmoid_80 = torch.sigmoid(features_39_conv_1) mul_100 = features_39_conv_1.__mul__(sigmoid_80) features_39_conv_3 = self.features_39_conv_3(mul_100) features_39_conv_4 = self.features_39_conv_4(features_39_conv_3) sigmoid_81 = torch.sigmoid(features_39_conv_4) mul_101 = features_39_conv_4.__mul__(sigmoid_81) size_21 = mul_101.size() features_39_conv_6_avg_pool = self.features_39_conv_6_avg_pool(mul_101) view_41 = features_39_conv_6_avg_pool.view(size_21[0], size_21[1]) features_39_conv_6_fc_0 = self.features_39_conv_6_fc_0(view_41) sigmoid_82 = torch.sigmoid(features_39_conv_6_fc_0) mul_102 = features_39_conv_6_fc_0.__mul__(sigmoid_82) features_39_conv_6_fc_2 = self.features_39_conv_6_fc_2(mul_102) features_39_conv_6_fc_3 = self.features_39_conv_6_fc_3(features_39_conv_6_fc_2) view_42 = features_39_conv_6_fc_3.view(size_21[0], size_21[1], 1, 1) mul_103 = mul_101.__mul__(view_42) features_39_conv_7 = self.features_39_conv_7(mul_103) 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_83 = torch.sigmoid(features_40_conv_1) mul_104 = features_40_conv_1.__mul__(sigmoid_83) features_40_conv_3 = self.features_40_conv_3(mul_104) features_40_conv_4 = self.features_40_conv_4(features_40_conv_3) sigmoid_84 = torch.sigmoid(features_40_conv_4) mul_105 = features_40_conv_4.__mul__(sigmoid_84) size_22 = mul_105.size() features_40_conv_6_avg_pool = self.features_40_conv_6_avg_pool(mul_105) view_43 = features_40_conv_6_avg_pool.view(size_22[0], size_22[1]) features_40_conv_6_fc_0 = self.features_40_conv_6_fc_0(view_43) sigmoid_85 = torch.sigmoid(features_40_conv_6_fc_0) mul_106 = features_40_conv_6_fc_0.__mul__(sigmoid_85) features_40_conv_6_fc_2 = self.features_40_conv_6_fc_2(mul_106) features_40_conv_6_fc_3 = self.features_40_conv_6_fc_3(features_40_conv_6_fc_2) view_44 = features_40_conv_6_fc_3.view(size_22[0], size_22[1], 1, 1) mul_107 = mul_105.__mul__(view_44) features_40_conv_7 = self.features_40_conv_7(mul_107) 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_86 = torch.sigmoid(features_41_conv_1) mul_108 = features_41_conv_1.__mul__(sigmoid_86) features_41_conv_3 = self.features_41_conv_3(mul_108) features_41_conv_4 = self.features_41_conv_4(features_41_conv_3) sigmoid_87 = torch.sigmoid(features_41_conv_4) mul_109 = features_41_conv_4.__mul__(sigmoid_87) size_23 = mul_109.size() features_41_conv_6_avg_pool = self.features_41_conv_6_avg_pool(mul_109) view_45 = features_41_conv_6_avg_pool.view(size_23[0], size_23[1]) features_41_conv_6_fc_0 = self.features_41_conv_6_fc_0(view_45) sigmoid_88 = torch.sigmoid(features_41_conv_6_fc_0) mul_110 = features_41_conv_6_fc_0.__mul__(sigmoid_88) features_41_conv_6_fc_2 = self.features_41_conv_6_fc_2(mul_110) features_41_conv_6_fc_3 = self.features_41_conv_6_fc_3(features_41_conv_6_fc_2) view_46 = features_41_conv_6_fc_3.view(size_23[0], size_23[1], 1, 1) mul_111 = mul_109.__mul__(view_46) features_41_conv_7 = self.features_41_conv_7(mul_111) 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_89 = torch.sigmoid(features_42_conv_1) mul_112 = features_42_conv_1.__mul__(sigmoid_89) features_42_conv_3 = self.features_42_conv_3(mul_112) features_42_conv_4 = self.features_42_conv_4(features_42_conv_3) sigmoid_90 = torch.sigmoid(features_42_conv_4) mul_113 = features_42_conv_4.__mul__(sigmoid_90) size_24 = mul_113.size() features_42_conv_6_avg_pool = self.features_42_conv_6_avg_pool(mul_113) view_47 = features_42_conv_6_avg_pool.view(size_24[0], size_24[1]) features_42_conv_6_fc_0 = self.features_42_conv_6_fc_0(view_47) sigmoid_91 = torch.sigmoid(features_42_conv_6_fc_0) mul_114 = features_42_conv_6_fc_0.__mul__(sigmoid_91) features_42_conv_6_fc_2 = self.features_42_conv_6_fc_2(mul_114) features_42_conv_6_fc_3 = self.features_42_conv_6_fc_3(features_42_conv_6_fc_2) view_48 = features_42_conv_6_fc_3.view(size_24[0], size_24[1], 1, 1) mul_115 = mul_113.__mul__(view_48) features_42_conv_7 = self.features_42_conv_7(mul_115) 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_92 = torch.sigmoid(features_43_conv_1) mul_116 = features_43_conv_1.__mul__(sigmoid_92) features_43_conv_3 = self.features_43_conv_3(mul_116) features_43_conv_4 = self.features_43_conv_4(features_43_conv_3) sigmoid_93 = torch.sigmoid(features_43_conv_4) mul_117 = features_43_conv_4.__mul__(sigmoid_93) size_25 = mul_117.size() features_43_conv_6_avg_pool = self.features_43_conv_6_avg_pool(mul_117) view_49 = features_43_conv_6_avg_pool.view(size_25[0], size_25[1]) features_43_conv_6_fc_0 = self.features_43_conv_6_fc_0(view_49) sigmoid_94 = torch.sigmoid(features_43_conv_6_fc_0) mul_118 = features_43_conv_6_fc_0.__mul__(sigmoid_94) features_43_conv_6_fc_2 = self.features_43_conv_6_fc_2(mul_118) features_43_conv_6_fc_3 = self.features_43_conv_6_fc_3(features_43_conv_6_fc_2) view_50 = features_43_conv_6_fc_3.view(size_25[0], size_25[1], 1, 1) mul_119 = mul_117.__mul__(view_50) features_43_conv_7 = self.features_43_conv_7(mul_119) 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_95 = torch.sigmoid(features_44_conv_1) mul_120 = features_44_conv_1.__mul__(sigmoid_95) features_44_conv_3 = self.features_44_conv_3(mul_120) features_44_conv_4 = self.features_44_conv_4(features_44_conv_3) sigmoid_96 = torch.sigmoid(features_44_conv_4) mul_121 = features_44_conv_4.__mul__(sigmoid_96) size_26 = mul_121.size() features_44_conv_6_avg_pool = self.features_44_conv_6_avg_pool(mul_121) view_51 = features_44_conv_6_avg_pool.view(size_26[0], size_26[1]) features_44_conv_6_fc_0 = self.features_44_conv_6_fc_0(view_51) sigmoid_97 = torch.sigmoid(features_44_conv_6_fc_0) mul_122 = features_44_conv_6_fc_0.__mul__(sigmoid_97) features_44_conv_6_fc_2 = self.features_44_conv_6_fc_2(mul_122) features_44_conv_6_fc_3 = self.features_44_conv_6_fc_3(features_44_conv_6_fc_2) view_52 = features_44_conv_6_fc_3.view(size_26[0], size_26[1], 1, 1) mul_123 = mul_121.__mul__(view_52) features_44_conv_7 = self.features_44_conv_7(mul_123) 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_98 = torch.sigmoid(features_45_conv_1) mul_124 = features_45_conv_1.__mul__(sigmoid_98) features_45_conv_3 = self.features_45_conv_3(mul_124) features_45_conv_4 = self.features_45_conv_4(features_45_conv_3) sigmoid_99 = torch.sigmoid(features_45_conv_4) mul_125 = features_45_conv_4.__mul__(sigmoid_99) size_27 = mul_125.size() features_45_conv_6_avg_pool = self.features_45_conv_6_avg_pool(mul_125) view_53 = features_45_conv_6_avg_pool.view(size_27[0], size_27[1]) features_45_conv_6_fc_0 = self.features_45_conv_6_fc_0(view_53) sigmoid_100 = torch.sigmoid(features_45_conv_6_fc_0) mul_126 = features_45_conv_6_fc_0.__mul__(sigmoid_100) features_45_conv_6_fc_2 = self.features_45_conv_6_fc_2(mul_126) features_45_conv_6_fc_3 = self.features_45_conv_6_fc_3(features_45_conv_6_fc_2) view_54 = features_45_conv_6_fc_3.view(size_27[0], size_27[1], 1, 1) mul_127 = mul_125.__mul__(view_54) features_45_conv_7 = self.features_45_conv_7(mul_127) 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_101 = torch.sigmoid(features_46_conv_1) mul_128 = features_46_conv_1.__mul__(sigmoid_101) features_46_conv_3 = self.features_46_conv_3(mul_128) features_46_conv_4 = self.features_46_conv_4(features_46_conv_3) sigmoid_102 = torch.sigmoid(features_46_conv_4) mul_129 = features_46_conv_4.__mul__(sigmoid_102) size_28 = mul_129.size() features_46_conv_6_avg_pool = self.features_46_conv_6_avg_pool(mul_129) view_55 = features_46_conv_6_avg_pool.view(size_28[0], size_28[1]) features_46_conv_6_fc_0 = self.features_46_conv_6_fc_0(view_55) sigmoid_103 = torch.sigmoid(features_46_conv_6_fc_0) mul_130 = features_46_conv_6_fc_0.__mul__(sigmoid_103) features_46_conv_6_fc_2 = self.features_46_conv_6_fc_2(mul_130) features_46_conv_6_fc_3 = self.features_46_conv_6_fc_3(features_46_conv_6_fc_2) view_56 = features_46_conv_6_fc_3.view(size_28[0], size_28[1], 1, 1) mul_131 = mul_129.__mul__(view_56) features_46_conv_7 = self.features_46_conv_7(mul_131) 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_104 = torch.sigmoid(features_47_conv_1) mul_132 = features_47_conv_1.__mul__(sigmoid_104) features_47_conv_3 = self.features_47_conv_3(mul_132) features_47_conv_4 = self.features_47_conv_4(features_47_conv_3) sigmoid_105 = torch.sigmoid(features_47_conv_4) mul_133 = features_47_conv_4.__mul__(sigmoid_105) size_29 = mul_133.size() features_47_conv_6_avg_pool = self.features_47_conv_6_avg_pool(mul_133) view_57 = features_47_conv_6_avg_pool.view(size_29[0], size_29[1]) features_47_conv_6_fc_0 = self.features_47_conv_6_fc_0(view_57) sigmoid_106 = torch.sigmoid(features_47_conv_6_fc_0) mul_134 = features_47_conv_6_fc_0.__mul__(sigmoid_106) features_47_conv_6_fc_2 = self.features_47_conv_6_fc_2(mul_134) features_47_conv_6_fc_3 = self.features_47_conv_6_fc_3(features_47_conv_6_fc_2) view_58 = features_47_conv_6_fc_3.view(size_29[0], size_29[1], 1, 1) mul_135 = mul_133.__mul__(view_58) features_47_conv_7 = self.features_47_conv_7(mul_135) 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_107 = torch.sigmoid(features_48_conv_1) mul_136 = features_48_conv_1.__mul__(sigmoid_107) features_48_conv_3 = self.features_48_conv_3(mul_136) features_48_conv_4 = self.features_48_conv_4(features_48_conv_3) sigmoid_108 = torch.sigmoid(features_48_conv_4) mul_137 = features_48_conv_4.__mul__(sigmoid_108) size_30 = mul_137.size() features_48_conv_6_avg_pool = self.features_48_conv_6_avg_pool(mul_137) view_59 = features_48_conv_6_avg_pool.view(size_30[0], size_30[1]) features_48_conv_6_fc_0 = self.features_48_conv_6_fc_0(view_59) sigmoid_109 = torch.sigmoid(features_48_conv_6_fc_0) mul_138 = features_48_conv_6_fc_0.__mul__(sigmoid_109) features_48_conv_6_fc_2 = self.features_48_conv_6_fc_2(mul_138) features_48_conv_6_fc_3 = self.features_48_conv_6_fc_3(features_48_conv_6_fc_2) view_60 = features_48_conv_6_fc_3.view(size_30[0], size_30[1], 1, 1) mul_139 = mul_137.__mul__(view_60) features_48_conv_7 = self.features_48_conv_7(mul_139) features_48_conv_8 = self.features_48_conv_8(features_48_conv_7) features_49_conv_0 = self.features_49_conv_0(features_48_conv_8) features_49_conv_1 = self.features_49_conv_1(features_49_conv_0) sigmoid_110 = torch.sigmoid(features_49_conv_1) mul_140 = features_49_conv_1.__mul__(sigmoid_110) features_49_conv_3 = self.features_49_conv_3(mul_140) features_49_conv_4 = self.features_49_conv_4(features_49_conv_3) sigmoid_111 = torch.sigmoid(features_49_conv_4) mul_141 = features_49_conv_4.__mul__(sigmoid_111) size_31 = mul_141.size() features_49_conv_6_avg_pool = self.features_49_conv_6_avg_pool(mul_141) view_61 = features_49_conv_6_avg_pool.view(size_31[0], size_31[1]) features_49_conv_6_fc_0 = self.features_49_conv_6_fc_0(view_61) sigmoid_112 = torch.sigmoid(features_49_conv_6_fc_0) mul_142 = features_49_conv_6_fc_0.__mul__(sigmoid_112) features_49_conv_6_fc_2 = self.features_49_conv_6_fc_2(mul_142) features_49_conv_6_fc_3 = self.features_49_conv_6_fc_3(features_49_conv_6_fc_2) view_62 = features_49_conv_6_fc_3.view(size_31[0], size_31[1], 1, 1) mul_143 = mul_141.__mul__(view_62) features_49_conv_7 = self.features_49_conv_7(mul_143) features_49_conv_8 = self.features_49_conv_8(features_49_conv_7) add_43 = features_48_conv_8.__add__(features_49_conv_8) features_50_conv_0 = self.features_50_conv_0(add_43) features_50_conv_1 = self.features_50_conv_1(features_50_conv_0) sigmoid_113 = torch.sigmoid(features_50_conv_1) mul_144 = features_50_conv_1.__mul__(sigmoid_113) features_50_conv_3 = self.features_50_conv_3(mul_144) features_50_conv_4 = self.features_50_conv_4(features_50_conv_3) sigmoid_114 = torch.sigmoid(features_50_conv_4) mul_145 = features_50_conv_4.__mul__(sigmoid_114) size_32 = mul_145.size() features_50_conv_6_avg_pool = self.features_50_conv_6_avg_pool(mul_145) view_63 = features_50_conv_6_avg_pool.view(size_32[0], size_32[1]) features_50_conv_6_fc_0 = self.features_50_conv_6_fc_0(view_63) sigmoid_115 = torch.sigmoid(features_50_conv_6_fc_0) mul_146 = features_50_conv_6_fc_0.__mul__(sigmoid_115) features_50_conv_6_fc_2 = self.features_50_conv_6_fc_2(mul_146) features_50_conv_6_fc_3 = self.features_50_conv_6_fc_3(features_50_conv_6_fc_2) view_64 = features_50_conv_6_fc_3.view(size_32[0], size_32[1], 1, 1) mul_147 = mul_145.__mul__(view_64) features_50_conv_7 = self.features_50_conv_7(mul_147) features_50_conv_8 = self.features_50_conv_8(features_50_conv_7) add_44 = add_43.__add__(features_50_conv_8) features_51_conv_0 = self.features_51_conv_0(add_44) features_51_conv_1 = self.features_51_conv_1(features_51_conv_0) sigmoid_116 = torch.sigmoid(features_51_conv_1) mul_148 = features_51_conv_1.__mul__(sigmoid_116) features_51_conv_3 = self.features_51_conv_3(mul_148) features_51_conv_4 = self.features_51_conv_4(features_51_conv_3) sigmoid_117 = torch.sigmoid(features_51_conv_4) mul_149 = features_51_conv_4.__mul__(sigmoid_117) size_33 = mul_149.size() features_51_conv_6_avg_pool = self.features_51_conv_6_avg_pool(mul_149) view_65 = features_51_conv_6_avg_pool.view(size_33[0], size_33[1]) features_51_conv_6_fc_0 = self.features_51_conv_6_fc_0(view_65) sigmoid_118 = torch.sigmoid(features_51_conv_6_fc_0) mul_150 = features_51_conv_6_fc_0.__mul__(sigmoid_118) features_51_conv_6_fc_2 = self.features_51_conv_6_fc_2(mul_150) features_51_conv_6_fc_3 = self.features_51_conv_6_fc_3(features_51_conv_6_fc_2) view_66 = features_51_conv_6_fc_3.view(size_33[0], size_33[1], 1, 1) mul_151 = mul_149.__mul__(view_66) features_51_conv_7 = self.features_51_conv_7(mul_151) features_51_conv_8 = self.features_51_conv_8(features_51_conv_7) add_45 = add_44.__add__(features_51_conv_8) features_52_conv_0 = self.features_52_conv_0(add_45) features_52_conv_1 = self.features_52_conv_1(features_52_conv_0) sigmoid_119 = torch.sigmoid(features_52_conv_1) mul_152 = features_52_conv_1.__mul__(sigmoid_119) features_52_conv_3 = self.features_52_conv_3(mul_152) features_52_conv_4 = self.features_52_conv_4(features_52_conv_3) sigmoid_120 = torch.sigmoid(features_52_conv_4) mul_153 = features_52_conv_4.__mul__(sigmoid_120) size_34 = mul_153.size() features_52_conv_6_avg_pool = self.features_52_conv_6_avg_pool(mul_153) view_67 = features_52_conv_6_avg_pool.view(size_34[0], size_34[1]) features_52_conv_6_fc_0 = self.features_52_conv_6_fc_0(view_67) sigmoid_121 = torch.sigmoid(features_52_conv_6_fc_0) mul_154 = features_52_conv_6_fc_0.__mul__(sigmoid_121) features_52_conv_6_fc_2 = self.features_52_conv_6_fc_2(mul_154) features_52_conv_6_fc_3 = self.features_52_conv_6_fc_3(features_52_conv_6_fc_2) view_68 = features_52_conv_6_fc_3.view(size_34[0], size_34[1], 1, 1) mul_155 = mul_153.__mul__(view_68) features_52_conv_7 = self.features_52_conv_7(mul_155) features_52_conv_8 = self.features_52_conv_8(features_52_conv_7) add_46 = add_45.__add__(features_52_conv_8) features_53_conv_0 = self.features_53_conv_0(add_46) features_53_conv_1 = self.features_53_conv_1(features_53_conv_0) sigmoid_122 = torch.sigmoid(features_53_conv_1) mul_156 = features_53_conv_1.__mul__(sigmoid_122) features_53_conv_3 = self.features_53_conv_3(mul_156) features_53_conv_4 = self.features_53_conv_4(features_53_conv_3) sigmoid_123 = torch.sigmoid(features_53_conv_4) mul_157 = features_53_conv_4.__mul__(sigmoid_123) size_35 = mul_157.size() features_53_conv_6_avg_pool = self.features_53_conv_6_avg_pool(mul_157) view_69 = features_53_conv_6_avg_pool.view(size_35[0], size_35[1]) features_53_conv_6_fc_0 = self.features_53_conv_6_fc_0(view_69) sigmoid_124 = torch.sigmoid(features_53_conv_6_fc_0) mul_158 = features_53_conv_6_fc_0.__mul__(sigmoid_124) features_53_conv_6_fc_2 = self.features_53_conv_6_fc_2(mul_158) features_53_conv_6_fc_3 = self.features_53_conv_6_fc_3(features_53_conv_6_fc_2) view_70 = features_53_conv_6_fc_3.view(size_35[0], size_35[1], 1, 1) mul_159 = mul_157.__mul__(view_70) features_53_conv_7 = self.features_53_conv_7(mul_159) features_53_conv_8 = self.features_53_conv_8(features_53_conv_7) add_47 = add_46.__add__(features_53_conv_8) features_54_conv_0 = self.features_54_conv_0(add_47) features_54_conv_1 = self.features_54_conv_1(features_54_conv_0) sigmoid_125 = torch.sigmoid(features_54_conv_1) mul_160 = features_54_conv_1.__mul__(sigmoid_125) features_54_conv_3 = self.features_54_conv_3(mul_160) features_54_conv_4 = self.features_54_conv_4(features_54_conv_3) sigmoid_126 = torch.sigmoid(features_54_conv_4) mul_161 = features_54_conv_4.__mul__(sigmoid_126) size_36 = mul_161.size() features_54_conv_6_avg_pool = self.features_54_conv_6_avg_pool(mul_161) view_71 = features_54_conv_6_avg_pool.view(size_36[0], size_36[1]) features_54_conv_6_fc_0 = self.features_54_conv_6_fc_0(view_71) sigmoid_127 = torch.sigmoid(features_54_conv_6_fc_0) mul_162 = features_54_conv_6_fc_0.__mul__(sigmoid_127) features_54_conv_6_fc_2 = self.features_54_conv_6_fc_2(mul_162) features_54_conv_6_fc_3 = self.features_54_conv_6_fc_3(features_54_conv_6_fc_2) view_72 = features_54_conv_6_fc_3.view(size_36[0], size_36[1], 1, 1) mul_163 = mul_161.__mul__(view_72) features_54_conv_7 = self.features_54_conv_7(mul_163) features_54_conv_8 = self.features_54_conv_8(features_54_conv_7) add_48 = add_47.__add__(features_54_conv_8) features_55_conv_0 = self.features_55_conv_0(add_48) features_55_conv_1 = self.features_55_conv_1(features_55_conv_0) sigmoid_128 = torch.sigmoid(features_55_conv_1) mul_164 = features_55_conv_1.__mul__(sigmoid_128) features_55_conv_3 = self.features_55_conv_3(mul_164) features_55_conv_4 = self.features_55_conv_4(features_55_conv_3) sigmoid_129 = torch.sigmoid(features_55_conv_4) mul_165 = features_55_conv_4.__mul__(sigmoid_129) size_37 = mul_165.size() features_55_conv_6_avg_pool = self.features_55_conv_6_avg_pool(mul_165) view_73 = features_55_conv_6_avg_pool.view(size_37[0], size_37[1]) features_55_conv_6_fc_0 = self.features_55_conv_6_fc_0(view_73) sigmoid_130 = torch.sigmoid(features_55_conv_6_fc_0) mul_166 = features_55_conv_6_fc_0.__mul__(sigmoid_130) features_55_conv_6_fc_2 = self.features_55_conv_6_fc_2(mul_166) features_55_conv_6_fc_3 = self.features_55_conv_6_fc_3(features_55_conv_6_fc_2) view_74 = features_55_conv_6_fc_3.view(size_37[0], size_37[1], 1, 1) mul_167 = mul_165.__mul__(view_74) features_55_conv_7 = self.features_55_conv_7(mul_167) features_55_conv_8 = self.features_55_conv_8(features_55_conv_7) add_49 = add_48.__add__(features_55_conv_8) features_56_conv_0 = self.features_56_conv_0(add_49) features_56_conv_1 = self.features_56_conv_1(features_56_conv_0) sigmoid_131 = torch.sigmoid(features_56_conv_1) mul_168 = features_56_conv_1.__mul__(sigmoid_131) features_56_conv_3 = self.features_56_conv_3(mul_168) features_56_conv_4 = self.features_56_conv_4(features_56_conv_3) sigmoid_132 = torch.sigmoid(features_56_conv_4) mul_169 = features_56_conv_4.__mul__(sigmoid_132) size_38 = mul_169.size() features_56_conv_6_avg_pool = self.features_56_conv_6_avg_pool(mul_169) view_75 = features_56_conv_6_avg_pool.view(size_38[0], size_38[1]) features_56_conv_6_fc_0 = self.features_56_conv_6_fc_0(view_75) sigmoid_133 = torch.sigmoid(features_56_conv_6_fc_0) mul_170 = features_56_conv_6_fc_0.__mul__(sigmoid_133) features_56_conv_6_fc_2 = self.features_56_conv_6_fc_2(mul_170) features_56_conv_6_fc_3 = self.features_56_conv_6_fc_3(features_56_conv_6_fc_2) view_76 = features_56_conv_6_fc_3.view(size_38[0], size_38[1], 1, 1) mul_171 = mul_169.__mul__(view_76) features_56_conv_7 = self.features_56_conv_7(mul_171) features_56_conv_8 = self.features_56_conv_8(features_56_conv_7) add_50 = add_49.__add__(features_56_conv_8) features_57_conv_0 = self.features_57_conv_0(add_50) features_57_conv_1 = self.features_57_conv_1(features_57_conv_0) sigmoid_134 = torch.sigmoid(features_57_conv_1) mul_172 = features_57_conv_1.__mul__(sigmoid_134) features_57_conv_3 = self.features_57_conv_3(mul_172) features_57_conv_4 = self.features_57_conv_4(features_57_conv_3) sigmoid_135 = torch.sigmoid(features_57_conv_4) mul_173 = features_57_conv_4.__mul__(sigmoid_135) size_39 = mul_173.size() features_57_conv_6_avg_pool = self.features_57_conv_6_avg_pool(mul_173) view_77 = features_57_conv_6_avg_pool.view(size_39[0], size_39[1]) features_57_conv_6_fc_0 = self.features_57_conv_6_fc_0(view_77) sigmoid_136 = torch.sigmoid(features_57_conv_6_fc_0) mul_174 = features_57_conv_6_fc_0.__mul__(sigmoid_136) features_57_conv_6_fc_2 = self.features_57_conv_6_fc_2(mul_174) features_57_conv_6_fc_3 = self.features_57_conv_6_fc_3(features_57_conv_6_fc_2) view_78 = features_57_conv_6_fc_3.view(size_39[0], size_39[1], 1, 1) mul_175 = mul_173.__mul__(view_78) features_57_conv_7 = self.features_57_conv_7(mul_175) features_57_conv_8 = self.features_57_conv_8(features_57_conv_7) add_51 = add_50.__add__(features_57_conv_8) features_58_conv_0 = self.features_58_conv_0(add_51) features_58_conv_1 = self.features_58_conv_1(features_58_conv_0) sigmoid_137 = torch.sigmoid(features_58_conv_1) mul_176 = features_58_conv_1.__mul__(sigmoid_137) features_58_conv_3 = self.features_58_conv_3(mul_176) features_58_conv_4 = self.features_58_conv_4(features_58_conv_3) sigmoid_138 = torch.sigmoid(features_58_conv_4) mul_177 = features_58_conv_4.__mul__(sigmoid_138) size_40 = mul_177.size() features_58_conv_6_avg_pool = self.features_58_conv_6_avg_pool(mul_177) view_79 = features_58_conv_6_avg_pool.view(size_40[0], size_40[1]) features_58_conv_6_fc_0 = self.features_58_conv_6_fc_0(view_79) sigmoid_139 = torch.sigmoid(features_58_conv_6_fc_0) mul_178 = features_58_conv_6_fc_0.__mul__(sigmoid_139) features_58_conv_6_fc_2 = self.features_58_conv_6_fc_2(mul_178) features_58_conv_6_fc_3 = self.features_58_conv_6_fc_3(features_58_conv_6_fc_2) view_80 = features_58_conv_6_fc_3.view(size_40[0], size_40[1], 1, 1) mul_179 = mul_177.__mul__(view_80) features_58_conv_7 = self.features_58_conv_7(mul_179) features_58_conv_8 = self.features_58_conv_8(features_58_conv_7) add_52 = add_51.__add__(features_58_conv_8) features_59_conv_0 = self.features_59_conv_0(add_52) features_59_conv_1 = self.features_59_conv_1(features_59_conv_0) sigmoid_140 = torch.sigmoid(features_59_conv_1) mul_180 = features_59_conv_1.__mul__(sigmoid_140) features_59_conv_3 = self.features_59_conv_3(mul_180) features_59_conv_4 = self.features_59_conv_4(features_59_conv_3) sigmoid_141 = torch.sigmoid(features_59_conv_4) mul_181 = features_59_conv_4.__mul__(sigmoid_141) size_41 = mul_181.size() features_59_conv_6_avg_pool = self.features_59_conv_6_avg_pool(mul_181) view_81 = features_59_conv_6_avg_pool.view(size_41[0], size_41[1]) features_59_conv_6_fc_0 = self.features_59_conv_6_fc_0(view_81) sigmoid_142 = torch.sigmoid(features_59_conv_6_fc_0) mul_182 = features_59_conv_6_fc_0.__mul__(sigmoid_142) features_59_conv_6_fc_2 = self.features_59_conv_6_fc_2(mul_182) features_59_conv_6_fc_3 = self.features_59_conv_6_fc_3(features_59_conv_6_fc_2) view_82 = features_59_conv_6_fc_3.view(size_41[0], size_41[1], 1, 1) mul_183 = mul_181.__mul__(view_82) features_59_conv_7 = self.features_59_conv_7(mul_183) features_59_conv_8 = self.features_59_conv_8(features_59_conv_7) add_53 = add_52.__add__(features_59_conv_8) features_60_conv_0 = self.features_60_conv_0(add_53) features_60_conv_1 = self.features_60_conv_1(features_60_conv_0) sigmoid_143 = torch.sigmoid(features_60_conv_1) mul_184 = features_60_conv_1.__mul__(sigmoid_143) features_60_conv_3 = self.features_60_conv_3(mul_184) features_60_conv_4 = self.features_60_conv_4(features_60_conv_3) sigmoid_144 = torch.sigmoid(features_60_conv_4) mul_185 = features_60_conv_4.__mul__(sigmoid_144) size_42 = mul_185.size() features_60_conv_6_avg_pool = self.features_60_conv_6_avg_pool(mul_185) view_83 = features_60_conv_6_avg_pool.view(size_42[0], size_42[1]) features_60_conv_6_fc_0 = self.features_60_conv_6_fc_0(view_83) sigmoid_145 = torch.sigmoid(features_60_conv_6_fc_0) mul_186 = features_60_conv_6_fc_0.__mul__(sigmoid_145) features_60_conv_6_fc_2 = self.features_60_conv_6_fc_2(mul_186) features_60_conv_6_fc_3 = self.features_60_conv_6_fc_3(features_60_conv_6_fc_2) view_84 = features_60_conv_6_fc_3.view(size_42[0], size_42[1], 1, 1) mul_187 = mul_185.__mul__(view_84) features_60_conv_7 = self.features_60_conv_7(mul_187) features_60_conv_8 = self.features_60_conv_8(features_60_conv_7) add_54 = add_53.__add__(features_60_conv_8) features_61_conv_0 = self.features_61_conv_0(add_54) features_61_conv_1 = self.features_61_conv_1(features_61_conv_0) sigmoid_146 = torch.sigmoid(features_61_conv_1) mul_188 = features_61_conv_1.__mul__(sigmoid_146) features_61_conv_3 = self.features_61_conv_3(mul_188) features_61_conv_4 = self.features_61_conv_4(features_61_conv_3) sigmoid_147 = torch.sigmoid(features_61_conv_4) mul_189 = features_61_conv_4.__mul__(sigmoid_147) size_43 = mul_189.size() features_61_conv_6_avg_pool = self.features_61_conv_6_avg_pool(mul_189) view_85 = features_61_conv_6_avg_pool.view(size_43[0], size_43[1]) features_61_conv_6_fc_0 = self.features_61_conv_6_fc_0(view_85) sigmoid_148 = torch.sigmoid(features_61_conv_6_fc_0) mul_190 = features_61_conv_6_fc_0.__mul__(sigmoid_148) features_61_conv_6_fc_2 = self.features_61_conv_6_fc_2(mul_190) features_61_conv_6_fc_3 = self.features_61_conv_6_fc_3(features_61_conv_6_fc_2) view_86 = features_61_conv_6_fc_3.view(size_43[0], size_43[1], 1, 1) mul_191 = mul_189.__mul__(view_86) features_61_conv_7 = self.features_61_conv_7(mul_191) features_61_conv_8 = self.features_61_conv_8(features_61_conv_7) add_55 = add_54.__add__(features_61_conv_8) features_62_conv_0 = self.features_62_conv_0(add_55) features_62_conv_1 = self.features_62_conv_1(features_62_conv_0) sigmoid_149 = torch.sigmoid(features_62_conv_1) mul_192 = features_62_conv_1.__mul__(sigmoid_149) features_62_conv_3 = self.features_62_conv_3(mul_192) features_62_conv_4 = self.features_62_conv_4(features_62_conv_3) sigmoid_150 = torch.sigmoid(features_62_conv_4) mul_193 = features_62_conv_4.__mul__(sigmoid_150) size_44 = mul_193.size() features_62_conv_6_avg_pool = self.features_62_conv_6_avg_pool(mul_193) view_87 = features_62_conv_6_avg_pool.view(size_44[0], size_44[1]) features_62_conv_6_fc_0 = self.features_62_conv_6_fc_0(view_87) sigmoid_151 = torch.sigmoid(features_62_conv_6_fc_0) mul_194 = features_62_conv_6_fc_0.__mul__(sigmoid_151) features_62_conv_6_fc_2 = self.features_62_conv_6_fc_2(mul_194) features_62_conv_6_fc_3 = self.features_62_conv_6_fc_3(features_62_conv_6_fc_2) view_88 = features_62_conv_6_fc_3.view(size_44[0], size_44[1], 1, 1) mul_195 = mul_193.__mul__(view_88) features_62_conv_7 = self.features_62_conv_7(mul_195) features_62_conv_8 = self.features_62_conv_8(features_62_conv_7) add_56 = add_55.__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_152 = torch.sigmoid(features_63_conv_1) mul_196 = features_63_conv_1.__mul__(sigmoid_152) features_63_conv_3 = self.features_63_conv_3(mul_196) features_63_conv_4 = self.features_63_conv_4(features_63_conv_3) sigmoid_153 = torch.sigmoid(features_63_conv_4) mul_197 = features_63_conv_4.__mul__(sigmoid_153) size_45 = mul_197.size() features_63_conv_6_avg_pool = self.features_63_conv_6_avg_pool(mul_197) view_89 = features_63_conv_6_avg_pool.view(size_45[0], size_45[1]) features_63_conv_6_fc_0 = self.features_63_conv_6_fc_0(view_89) sigmoid_154 = torch.sigmoid(features_63_conv_6_fc_0) mul_198 = features_63_conv_6_fc_0.__mul__(sigmoid_154) features_63_conv_6_fc_2 = self.features_63_conv_6_fc_2(mul_198) features_63_conv_6_fc_3 = self.features_63_conv_6_fc_3(features_63_conv_6_fc_2) view_90 = features_63_conv_6_fc_3.view(size_45[0], size_45[1], 1, 1) mul_199 = mul_197.__mul__(view_90) features_63_conv_7 = self.features_63_conv_7(mul_199) 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_155 = torch.sigmoid(features_64_conv_1) mul_200 = features_64_conv_1.__mul__(sigmoid_155) features_64_conv_3 = self.features_64_conv_3(mul_200) features_64_conv_4 = self.features_64_conv_4(features_64_conv_3) sigmoid_156 = torch.sigmoid(features_64_conv_4) mul_201 = features_64_conv_4.__mul__(sigmoid_156) size_46 = mul_201.size() features_64_conv_6_avg_pool = self.features_64_conv_6_avg_pool(mul_201) view_91 = features_64_conv_6_avg_pool.view(size_46[0], size_46[1]) features_64_conv_6_fc_0 = self.features_64_conv_6_fc_0(view_91) sigmoid_157 = torch.sigmoid(features_64_conv_6_fc_0) mul_202 = features_64_conv_6_fc_0.__mul__(sigmoid_157) features_64_conv_6_fc_2 = self.features_64_conv_6_fc_2(mul_202) features_64_conv_6_fc_3 = self.features_64_conv_6_fc_3(features_64_conv_6_fc_2) view_92 = features_64_conv_6_fc_3.view(size_46[0], size_46[1], 1, 1) mul_203 = mul_201.__mul__(view_92) features_64_conv_7 = self.features_64_conv_7(mul_203) 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_158 = torch.sigmoid(features_65_conv_1) mul_204 = features_65_conv_1.__mul__(sigmoid_158) features_65_conv_3 = self.features_65_conv_3(mul_204) features_65_conv_4 = self.features_65_conv_4(features_65_conv_3) sigmoid_159 = torch.sigmoid(features_65_conv_4) mul_205 = features_65_conv_4.__mul__(sigmoid_159) size_47 = mul_205.size() features_65_conv_6_avg_pool = self.features_65_conv_6_avg_pool(mul_205) view_93 = features_65_conv_6_avg_pool.view(size_47[0], size_47[1]) features_65_conv_6_fc_0 = self.features_65_conv_6_fc_0(view_93) sigmoid_160 = torch.sigmoid(features_65_conv_6_fc_0) mul_206 = features_65_conv_6_fc_0.__mul__(sigmoid_160) features_65_conv_6_fc_2 = self.features_65_conv_6_fc_2(mul_206) features_65_conv_6_fc_3 = self.features_65_conv_6_fc_3(features_65_conv_6_fc_2) view_94 = features_65_conv_6_fc_3.view(size_47[0], size_47[1], 1, 1) mul_207 = mul_205.__mul__(view_94) features_65_conv_7 = self.features_65_conv_7(mul_207) 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_161 = torch.sigmoid(features_66_conv_1) mul_208 = features_66_conv_1.__mul__(sigmoid_161) features_66_conv_3 = self.features_66_conv_3(mul_208) features_66_conv_4 = self.features_66_conv_4(features_66_conv_3) sigmoid_162 = torch.sigmoid(features_66_conv_4) mul_209 = features_66_conv_4.__mul__(sigmoid_162) size_48 = mul_209.size() features_66_conv_6_avg_pool = self.features_66_conv_6_avg_pool(mul_209) view_95 = features_66_conv_6_avg_pool.view(size_48[0], size_48[1]) features_66_conv_6_fc_0 = self.features_66_conv_6_fc_0(view_95) sigmoid_163 = torch.sigmoid(features_66_conv_6_fc_0) mul_210 = features_66_conv_6_fc_0.__mul__(sigmoid_163) features_66_conv_6_fc_2 = self.features_66_conv_6_fc_2(mul_210) features_66_conv_6_fc_3 = self.features_66_conv_6_fc_3(features_66_conv_6_fc_2) view_96 = features_66_conv_6_fc_3.view(size_48[0], size_48[1], 1, 1) mul_211 = mul_209.__mul__(view_96) features_66_conv_7 = self.features_66_conv_7(mul_211) 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_164 = torch.sigmoid(features_67_conv_1) mul_212 = features_67_conv_1.__mul__(sigmoid_164) features_67_conv_3 = self.features_67_conv_3(mul_212) features_67_conv_4 = self.features_67_conv_4(features_67_conv_3) sigmoid_165 = torch.sigmoid(features_67_conv_4) mul_213 = features_67_conv_4.__mul__(sigmoid_165) size_49 = mul_213.size() features_67_conv_6_avg_pool = self.features_67_conv_6_avg_pool(mul_213) view_97 = features_67_conv_6_avg_pool.view(size_49[0], size_49[1]) features_67_conv_6_fc_0 = self.features_67_conv_6_fc_0(view_97) sigmoid_166 = torch.sigmoid(features_67_conv_6_fc_0) mul_214 = features_67_conv_6_fc_0.__mul__(sigmoid_166) features_67_conv_6_fc_2 = self.features_67_conv_6_fc_2(mul_214) features_67_conv_6_fc_3 = self.features_67_conv_6_fc_3(features_67_conv_6_fc_2) view_98 = features_67_conv_6_fc_3.view(size_49[0], size_49[1], 1, 1) mul_215 = mul_213.__mul__(view_98) features_67_conv_7 = self.features_67_conv_7(mul_215) 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_167 = torch.sigmoid(features_68_conv_1) mul_216 = features_68_conv_1.__mul__(sigmoid_167) features_68_conv_3 = self.features_68_conv_3(mul_216) features_68_conv_4 = self.features_68_conv_4(features_68_conv_3) sigmoid_168 = torch.sigmoid(features_68_conv_4) mul_217 = features_68_conv_4.__mul__(sigmoid_168) size_50 = mul_217.size() features_68_conv_6_avg_pool = self.features_68_conv_6_avg_pool(mul_217) view_99 = features_68_conv_6_avg_pool.view(size_50[0], size_50[1]) features_68_conv_6_fc_0 = self.features_68_conv_6_fc_0(view_99) sigmoid_169 = torch.sigmoid(features_68_conv_6_fc_0) mul_218 = features_68_conv_6_fc_0.__mul__(sigmoid_169) features_68_conv_6_fc_2 = self.features_68_conv_6_fc_2(mul_218) features_68_conv_6_fc_3 = self.features_68_conv_6_fc_3(features_68_conv_6_fc_2) view_100 = features_68_conv_6_fc_3.view(size_50[0], size_50[1], 1, 1) mul_219 = mul_217.__mul__(view_100) features_68_conv_7 = self.features_68_conv_7(mul_219) 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_170 = torch.sigmoid(features_69_conv_1) mul_220 = features_69_conv_1.__mul__(sigmoid_170) features_69_conv_3 = self.features_69_conv_3(mul_220) features_69_conv_4 = self.features_69_conv_4(features_69_conv_3) sigmoid_171 = torch.sigmoid(features_69_conv_4) mul_221 = features_69_conv_4.__mul__(sigmoid_171) size_51 = mul_221.size() features_69_conv_6_avg_pool = self.features_69_conv_6_avg_pool(mul_221) view_101 = features_69_conv_6_avg_pool.view(size_51[0], size_51[1]) features_69_conv_6_fc_0 = self.features_69_conv_6_fc_0(view_101) sigmoid_172 = torch.sigmoid(features_69_conv_6_fc_0) mul_222 = features_69_conv_6_fc_0.__mul__(sigmoid_172) features_69_conv_6_fc_2 = self.features_69_conv_6_fc_2(mul_222) features_69_conv_6_fc_3 = self.features_69_conv_6_fc_3(features_69_conv_6_fc_2) view_102 = features_69_conv_6_fc_3.view(size_51[0], size_51[1], 1, 1) mul_223 = mul_221.__mul__(view_102) features_69_conv_7 = self.features_69_conv_7(mul_223) 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_173 = torch.sigmoid(features_70_conv_1) mul_224 = features_70_conv_1.__mul__(sigmoid_173) features_70_conv_3 = self.features_70_conv_3(mul_224) features_70_conv_4 = self.features_70_conv_4(features_70_conv_3) sigmoid_174 = torch.sigmoid(features_70_conv_4) mul_225 = features_70_conv_4.__mul__(sigmoid_174) size_52 = mul_225.size() features_70_conv_6_avg_pool = self.features_70_conv_6_avg_pool(mul_225) view_103 = features_70_conv_6_avg_pool.view(size_52[0], size_52[1]) features_70_conv_6_fc_0 = self.features_70_conv_6_fc_0(view_103) sigmoid_175 = torch.sigmoid(features_70_conv_6_fc_0) mul_226 = features_70_conv_6_fc_0.__mul__(sigmoid_175) features_70_conv_6_fc_2 = self.features_70_conv_6_fc_2(mul_226) features_70_conv_6_fc_3 = self.features_70_conv_6_fc_3(features_70_conv_6_fc_2) view_104 = features_70_conv_6_fc_3.view(size_52[0], size_52[1], 1, 1) mul_227 = mul_225.__mul__(view_104) features_70_conv_7 = self.features_70_conv_7(mul_227) 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_176 = torch.sigmoid(features_71_conv_1) mul_228 = features_71_conv_1.__mul__(sigmoid_176) features_71_conv_3 = self.features_71_conv_3(mul_228) features_71_conv_4 = self.features_71_conv_4(features_71_conv_3) sigmoid_177 = torch.sigmoid(features_71_conv_4) mul_229 = features_71_conv_4.__mul__(sigmoid_177) size_53 = mul_229.size() features_71_conv_6_avg_pool = self.features_71_conv_6_avg_pool(mul_229) view_105 = features_71_conv_6_avg_pool.view(size_53[0], size_53[1]) features_71_conv_6_fc_0 = self.features_71_conv_6_fc_0(view_105) sigmoid_178 = torch.sigmoid(features_71_conv_6_fc_0) mul_230 = features_71_conv_6_fc_0.__mul__(sigmoid_178) features_71_conv_6_fc_2 = self.features_71_conv_6_fc_2(mul_230) features_71_conv_6_fc_3 = self.features_71_conv_6_fc_3(features_71_conv_6_fc_2) view_106 = features_71_conv_6_fc_3.view(size_53[0], size_53[1], 1, 1) mul_231 = mul_229.__mul__(view_106) features_71_conv_7 = self.features_71_conv_7(mul_231) 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_179 = torch.sigmoid(features_72_conv_1) mul_232 = features_72_conv_1.__mul__(sigmoid_179) features_72_conv_3 = self.features_72_conv_3(mul_232) features_72_conv_4 = self.features_72_conv_4(features_72_conv_3) sigmoid_180 = torch.sigmoid(features_72_conv_4) mul_233 = features_72_conv_4.__mul__(sigmoid_180) size_54 = mul_233.size() features_72_conv_6_avg_pool = self.features_72_conv_6_avg_pool(mul_233) view_107 = features_72_conv_6_avg_pool.view(size_54[0], size_54[1]) features_72_conv_6_fc_0 = self.features_72_conv_6_fc_0(view_107) sigmoid_181 = torch.sigmoid(features_72_conv_6_fc_0) mul_234 = features_72_conv_6_fc_0.__mul__(sigmoid_181) features_72_conv_6_fc_2 = self.features_72_conv_6_fc_2(mul_234) features_72_conv_6_fc_3 = self.features_72_conv_6_fc_3(features_72_conv_6_fc_2) view_108 = features_72_conv_6_fc_3.view(size_54[0], size_54[1], 1, 1) mul_235 = mul_233.__mul__(view_108) features_72_conv_7 = self.features_72_conv_7(mul_235) 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_182 = torch.sigmoid(features_73_conv_1) mul_236 = features_73_conv_1.__mul__(sigmoid_182) features_73_conv_3 = self.features_73_conv_3(mul_236) features_73_conv_4 = self.features_73_conv_4(features_73_conv_3) sigmoid_183 = torch.sigmoid(features_73_conv_4) mul_237 = features_73_conv_4.__mul__(sigmoid_183) size_55 = mul_237.size() features_73_conv_6_avg_pool = self.features_73_conv_6_avg_pool(mul_237) view_109 = features_73_conv_6_avg_pool.view(size_55[0], size_55[1]) features_73_conv_6_fc_0 = self.features_73_conv_6_fc_0(view_109) sigmoid_184 = torch.sigmoid(features_73_conv_6_fc_0) mul_238 = features_73_conv_6_fc_0.__mul__(sigmoid_184) features_73_conv_6_fc_2 = self.features_73_conv_6_fc_2(mul_238) features_73_conv_6_fc_3 = self.features_73_conv_6_fc_3(features_73_conv_6_fc_2) view_110 = features_73_conv_6_fc_3.view(size_55[0], size_55[1], 1, 1) mul_239 = mul_237.__mul__(view_110) features_73_conv_7 = self.features_73_conv_7(mul_239) features_73_conv_8 = self.features_73_conv_8(features_73_conv_7) features_74_conv_0 = self.features_74_conv_0(features_73_conv_8) features_74_conv_1 = self.features_74_conv_1(features_74_conv_0) sigmoid_185 = torch.sigmoid(features_74_conv_1) mul_240 = features_74_conv_1.__mul__(sigmoid_185) features_74_conv_3 = self.features_74_conv_3(mul_240) features_74_conv_4 = self.features_74_conv_4(features_74_conv_3) sigmoid_186 = torch.sigmoid(features_74_conv_4) mul_241 = features_74_conv_4.__mul__(sigmoid_186) size_56 = mul_241.size() features_74_conv_6_avg_pool = self.features_74_conv_6_avg_pool(mul_241) view_111 = features_74_conv_6_avg_pool.view(size_56[0], size_56[1]) features_74_conv_6_fc_0 = self.features_74_conv_6_fc_0(view_111) sigmoid_187 = torch.sigmoid(features_74_conv_6_fc_0) mul_242 = features_74_conv_6_fc_0.__mul__(sigmoid_187) features_74_conv_6_fc_2 = self.features_74_conv_6_fc_2(mul_242) features_74_conv_6_fc_3 = self.features_74_conv_6_fc_3(features_74_conv_6_fc_2) view_112 = features_74_conv_6_fc_3.view(size_56[0], size_56[1], 1, 1) mul_243 = mul_241.__mul__(view_112) features_74_conv_7 = self.features_74_conv_7(mul_243) features_74_conv_8 = self.features_74_conv_8(features_74_conv_7) add_67 = features_73_conv_8.__add__(features_74_conv_8) features_75_conv_0 = self.features_75_conv_0(add_67) features_75_conv_1 = self.features_75_conv_1(features_75_conv_0) sigmoid_188 = torch.sigmoid(features_75_conv_1) mul_244 = features_75_conv_1.__mul__(sigmoid_188) features_75_conv_3 = self.features_75_conv_3(mul_244) features_75_conv_4 = self.features_75_conv_4(features_75_conv_3) sigmoid_189 = torch.sigmoid(features_75_conv_4) mul_245 = features_75_conv_4.__mul__(sigmoid_189) size_57 = mul_245.size() features_75_conv_6_avg_pool = self.features_75_conv_6_avg_pool(mul_245) view_113 = features_75_conv_6_avg_pool.view(size_57[0], size_57[1]) features_75_conv_6_fc_0 = self.features_75_conv_6_fc_0(view_113) sigmoid_190 = torch.sigmoid(features_75_conv_6_fc_0) mul_246 = features_75_conv_6_fc_0.__mul__(sigmoid_190) features_75_conv_6_fc_2 = self.features_75_conv_6_fc_2(mul_246) features_75_conv_6_fc_3 = self.features_75_conv_6_fc_3(features_75_conv_6_fc_2) view_114 = features_75_conv_6_fc_3.view(size_57[0], size_57[1], 1, 1) mul_247 = mul_245.__mul__(view_114) features_75_conv_7 = self.features_75_conv_7(mul_247) features_75_conv_8 = self.features_75_conv_8(features_75_conv_7) add_68 = add_67.__add__(features_75_conv_8) features_76_conv_0 = self.features_76_conv_0(add_68) features_76_conv_1 = self.features_76_conv_1(features_76_conv_0) sigmoid_191 = torch.sigmoid(features_76_conv_1) mul_248 = features_76_conv_1.__mul__(sigmoid_191) features_76_conv_3 = self.features_76_conv_3(mul_248) features_76_conv_4 = self.features_76_conv_4(features_76_conv_3) sigmoid_192 = torch.sigmoid(features_76_conv_4) mul_249 = features_76_conv_4.__mul__(sigmoid_192) size_58 = mul_249.size() features_76_conv_6_avg_pool = self.features_76_conv_6_avg_pool(mul_249) view_115 = features_76_conv_6_avg_pool.view(size_58[0], size_58[1]) features_76_conv_6_fc_0 = self.features_76_conv_6_fc_0(view_115) sigmoid_193 = torch.sigmoid(features_76_conv_6_fc_0) mul_250 = features_76_conv_6_fc_0.__mul__(sigmoid_193) features_76_conv_6_fc_2 = self.features_76_conv_6_fc_2(mul_250) features_76_conv_6_fc_3 = self.features_76_conv_6_fc_3(features_76_conv_6_fc_2) view_116 = features_76_conv_6_fc_3.view(size_58[0], size_58[1], 1, 1) mul_251 = mul_249.__mul__(view_116) features_76_conv_7 = self.features_76_conv_7(mul_251) features_76_conv_8 = self.features_76_conv_8(features_76_conv_7) add_69 = add_68.__add__(features_76_conv_8) features_77_conv_0 = self.features_77_conv_0(add_69) features_77_conv_1 = self.features_77_conv_1(features_77_conv_0) sigmoid_194 = torch.sigmoid(features_77_conv_1) mul_252 = features_77_conv_1.__mul__(sigmoid_194) features_77_conv_3 = self.features_77_conv_3(mul_252) features_77_conv_4 = self.features_77_conv_4(features_77_conv_3) sigmoid_195 = torch.sigmoid(features_77_conv_4) mul_253 = features_77_conv_4.__mul__(sigmoid_195) size_59 = mul_253.size() features_77_conv_6_avg_pool = self.features_77_conv_6_avg_pool(mul_253) view_117 = features_77_conv_6_avg_pool.view(size_59[0], size_59[1]) features_77_conv_6_fc_0 = self.features_77_conv_6_fc_0(view_117) sigmoid_196 = torch.sigmoid(features_77_conv_6_fc_0) mul_254 = features_77_conv_6_fc_0.__mul__(sigmoid_196) features_77_conv_6_fc_2 = self.features_77_conv_6_fc_2(mul_254) features_77_conv_6_fc_3 = self.features_77_conv_6_fc_3(features_77_conv_6_fc_2) view_118 = features_77_conv_6_fc_3.view(size_59[0], size_59[1], 1, 1) mul_255 = mul_253.__mul__(view_118) features_77_conv_7 = self.features_77_conv_7(mul_255) features_77_conv_8 = self.features_77_conv_8(features_77_conv_7) add_70 = add_69.__add__(features_77_conv_8) features_78_conv_0 = self.features_78_conv_0(add_70) features_78_conv_1 = self.features_78_conv_1(features_78_conv_0) sigmoid_197 = torch.sigmoid(features_78_conv_1) mul_256 = features_78_conv_1.__mul__(sigmoid_197) features_78_conv_3 = self.features_78_conv_3(mul_256) features_78_conv_4 = self.features_78_conv_4(features_78_conv_3) sigmoid_198 = torch.sigmoid(features_78_conv_4) mul_257 = features_78_conv_4.__mul__(sigmoid_198) size_60 = mul_257.size() features_78_conv_6_avg_pool = self.features_78_conv_6_avg_pool(mul_257) view_119 = features_78_conv_6_avg_pool.view(size_60[0], size_60[1]) features_78_conv_6_fc_0 = self.features_78_conv_6_fc_0(view_119) sigmoid_199 = torch.sigmoid(features_78_conv_6_fc_0) mul_258 = features_78_conv_6_fc_0.__mul__(sigmoid_199) features_78_conv_6_fc_2 = self.features_78_conv_6_fc_2(mul_258) features_78_conv_6_fc_3 = self.features_78_conv_6_fc_3(features_78_conv_6_fc_2) view_120 = features_78_conv_6_fc_3.view(size_60[0], size_60[1], 1, 1) mul_259 = mul_257.__mul__(view_120) features_78_conv_7 = self.features_78_conv_7(mul_259) features_78_conv_8 = self.features_78_conv_8(features_78_conv_7) add_71 = add_70.__add__(features_78_conv_8) features_79_conv_0 = self.features_79_conv_0(add_71) features_79_conv_1 = self.features_79_conv_1(features_79_conv_0) sigmoid_200 = torch.sigmoid(features_79_conv_1) mul_260 = features_79_conv_1.__mul__(sigmoid_200) features_79_conv_3 = self.features_79_conv_3(mul_260) features_79_conv_4 = self.features_79_conv_4(features_79_conv_3) sigmoid_201 = torch.sigmoid(features_79_conv_4) mul_261 = features_79_conv_4.__mul__(sigmoid_201) size_61 = mul_261.size() features_79_conv_6_avg_pool = self.features_79_conv_6_avg_pool(mul_261) view_121 = features_79_conv_6_avg_pool.view(size_61[0], size_61[1]) features_79_conv_6_fc_0 = self.features_79_conv_6_fc_0(view_121) sigmoid_202 = torch.sigmoid(features_79_conv_6_fc_0) mul_262 = features_79_conv_6_fc_0.__mul__(sigmoid_202) features_79_conv_6_fc_2 = self.features_79_conv_6_fc_2(mul_262) features_79_conv_6_fc_3 = self.features_79_conv_6_fc_3(features_79_conv_6_fc_2) view_122 = features_79_conv_6_fc_3.view(size_61[0], size_61[1], 1, 1) mul_263 = mul_261.__mul__(view_122) features_79_conv_7 = self.features_79_conv_7(mul_263) features_79_conv_8 = self.features_79_conv_8(features_79_conv_7) add_72 = add_71.__add__(features_79_conv_8) conv_0 = self.conv_0(add_72) conv_1 = self.conv_1(conv_0) sigmoid_203 = torch.sigmoid(conv_1) mul_264 = conv_1.__mul__(sigmoid_203) avgpool = self.avgpool(mul_264) size_62 = avgpool.size(0) view_123 = avgpool.view(size_62, -1) classifier = self.classifier(view_123) return classifier if __name__ == "__main__": model = efficientnet_v2_l() 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_l.py (2,116 lines of code) (raw):