models/efficientnet_v2_l.py [696:786]:
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        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)
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models/efficientnet_v2_xl.py [894:984]:
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        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)
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