from import_sets import *


class ConvFrontend(nn.Module):

    def __init__(self):
        super(ConvFrontend, self).__init__()
        self.conv = nn.Conv3d(3, 64, (5, 7, 7), stride=(1, 2, 2), padding=(
            2, 3, 3))
        self.norm = nn.BatchNorm3d(64)
        self.pool = nn.MaxPool3d((1, 3, 3), stride=(1, 2, 2), padding=(0, 1, 1)
            )

    def forward(self, input):
        output = self.conv(input)
        output = self.norm(output)
        output = F.relu(output)
        output = self.pool(output)
        return output

08c6002022b7539867733f2fded6a045389c8bd3
<mask token>


class ConvFrontend(nn.Module):
    <mask token>
    <mask token>

<mask token>


class ConvFrontend(nn.Module):
    <mask token>

    def forward(self, input):
        output = self.conv(input)
        output = self.norm(output)
        output = F.relu(output)
        output = self.pool(output)
        return output

<mask token>


class ConvFrontend(nn.Module):

    def __init__(self):
        super(ConvFrontend, self).__init__()
        self.conv = nn.Conv3d(3, 64, (5, 7, 7), stride=(1, 2, 2), padding=(
            2, 3, 3))
        self.norm = nn.BatchNorm3d(64)
        self.pool = nn.MaxPool3d((1, 3, 3), stride=(1, 2, 2), padding=(0, 1, 1)
            )

    def forward(self, input):
        output = self.conv(input)
        output = self.norm(output)
        output = F.relu(output)
        output = self.pool(output)
        return output

from import_sets import *


class ConvFrontend(nn.Module):

    def __init__(self):
        super(ConvFrontend, self).__init__()
        self.conv = nn.Conv3d(3, 64, (5, 7, 7), stride=(1, 2, 2), padding=(
            2, 3, 3))
        self.norm = nn.BatchNorm3d(64)
        self.pool = nn.MaxPool3d((1, 3, 3), stride=(1, 2, 2), padding=(0, 1, 1)
            )

    def forward(self, input):
        output = self.conv(input)
        output = self.norm(output)
        output = F.relu(output)
        output = self.pool(output)
        return output
