Function _make_same_padder

monai/networks/nets/efficientnet.py:850–871

Helper for initializing ConstantPadNd with SAME padding similar to Tensorflow. Uses output of _get_same_padding_conv_nd() to get the padding size. This function is generalized for MONAI's N-Dimensional spatial operations (e.g. Conv1D, Conv2D, Conv3D) Args: conv_op: nn.Conv

(conv_op: nn.Conv1d | nn.Conv2d | nn.Conv3d, image_size: list[int])

def _make_same_padder(conv_op: nn.Conv1d | nn.Conv2d | nn.Conv3d, image_size: list[int]):
    """
    Helper for initializing ConstantPadNd with SAME padding similar to Tensorflow.
    Uses output of _get_same_padding_conv_nd() to get the padding size.

    This function is generalized for MONAI's N-Dimensional spatial operations (e.g. Conv1D, Conv2D, Conv3D)

    Args:
        conv_op: nn.ConvNd operation to extract parameters for op from
        image_size: input image/feature spatial size

    Returns:
        If padding required then nn.ConstandNd() padder initialized to paddings otherwise nn.Identity()
    """
    # calculate padding required
    padding: list[int] = _get_same_padding_conv_nd(image_size, conv_op.kernel_size, conv_op.dilation, conv_op.stride)

    # initialize and return padder
    padder = Pad["constantpad", len(padding) // 2]
    if sum(padding) > 0:
        return padder(padding=padding, value=0.0)
    return nn.Identity()


def _round_filters(filters: int, width_coefficient: float | None, depth_divisor: float) -> int: