5343706adcad4d3d0d920fd7391614dc0f701cc2,pytorch/models/nasnet.py,ReductionCell1,__init__,#ReductionCell1#Any#Any#Any#Any#,630

Before Change

            out_channels=out_channels_right))
        self.conv_1x1.add_module("bn", nasnet_batch_norm(channels=out_channels_right))

        self.comb_iter_0_left = BranchSeparables(out_channels_right, out_channels_right, 5, 2, 2, name="specific", bias=False)
        self.comb_iter_0_right = BranchSeparables(out_channels_right, out_channels_right, 7, 2, 3, name="specific", bias=False)

        self.comb_iter_1_left = MaxPoolPad()
        self.comb_iter_1_right = BranchSeparables(out_channels_right, out_channels_right, 7, 2, 3, name="specific", bias=False)

        self.comb_iter_2_left = AvgPoolPad()
        self.comb_iter_2_right = BranchSeparables(out_channels_right, out_channels_right, 5, 2, 2, name="specific", bias=False)

        self.comb_iter_3_right = nasnet_avgpool3x3_s1()

        self.comb_iter_4_left = BranchSeparables(out_channels_right, out_channels_right, 3, 1, 1, name="specific", bias=False)
        self.comb_iter_4_right =MaxPoolPad()

    def forward(self, x, x_prev):
        x_left = self.conv_prev_1x1(x_prev)

After Change

        self.comb_iter_3_right = nasnet_avgpool3x3_s1()

        self.comb_iter_4_left = branch_separables_k3_s1_p1(
            in_channels=out_channels_right,
            out_channels=out_channels_right,
            name="specific")
        self.comb_iter_4_right =MaxPoolPad()

    def forward(self, x, x_prev):
        x_left = self.conv_prev_1x1(x_prev)

Instances