def _change_in_channels(self, in_channels):
        """Adjust model's first convolution layer to in_channels, if in_channels not equals 3.

        Args:
            in_channels (int): Input data's channel number.
        """
        if in_channels != 3:
            Conv2d = get_same_padding_conv2d(image_size=self._global_params.image_size)
            out_channels = round_filters(32, self._global_params)
            self._conv_stem = Conv2d(in_channels, out_channels, kernel_size=3, stride=2, bias=False)
Adjust model's first convolution layer to in_channels, if in_channels not equals 3.

        Args:
            in_channels (int): Input data's channel number.
        
efficientnet_pytorch/model.py