#!/usr/bin/env python3
# -*- coding: utf-8 -*-
__author__ = "Christian Heider Nielsen"
__doc__ = r"""
Created on 23/07/2020
"""
import math
from typing import Tuple, Union
__all__ = ["transp_conv2d_output_shape", "transp_conv2d_padding_sizes"]
from warg import replicate
[docs]def transp_conv2d_output_shape(
h_w: Union[int, Tuple[int, int]],
kernel_size: Union[int, Tuple[int, int]] = 1,
stride: Union[int, Tuple[int, int]] = 1,
pad: Union[int, Tuple[int, int]] = 0,
dilation: Union[int, Tuple[int, int]] = 1,
out_pad: Union[int, Tuple[int, int]] = 0,
) -> Tuple[int, int]:
"""description"""
(h_w, kernel_size, stride, pad, dilation, out_pad) = (
replicate(h_w),
replicate(kernel_size),
replicate(stride),
replicate(pad),
replicate(dilation),
replicate(out_pad),
)
pad = (replicate(pad[0]), replicate(pad[1]))
h = (
(h_w[0] - 1) * stride[0]
- sum(pad[0])
+ dilation[0] * (kernel_size[0] - 1)
+ out_pad[0]
+ 1
)
w = (
(h_w[1] - 1) * stride[1]
- sum(pad[1])
+ dilation[1] * (kernel_size[1] - 1)
+ out_pad[1]
+ 1
)
return h, w
[docs]def transp_conv2d_padding_sizes(
h_w_in: Union[int, Tuple[int, int]],
h_w_out: Union[int, Tuple[int, int]],
kernel_size: Union[int, Tuple[int, int]] = 1,
stride: Union[int, Tuple[int, int]] = 1,
dilation: Union[int, Tuple[int, int]] = 1,
out_pad: Union[int, Tuple[int, int]] = 0,
) -> Tuple[Tuple[int, int], Tuple[int, int]]:
"""description"""
(h_w_in, h_w_out, kernel_size, stride, dilation, out_pad) = (
replicate(h_w_in),
replicate(h_w_out),
replicate(kernel_size),
replicate(stride),
replicate(dilation),
replicate(out_pad),
)
p_h = (
-(
h_w_out[0]
- 1
- out_pad[0]
- dilation[0] * (kernel_size[0] - 1)
- (h_w_in[0] - 1) * stride[0]
)
/ 2
)
p_w = (
-(
h_w_out[1]
- 1
- out_pad[1]
- dilation[1] * (kernel_size[1] - 1)
- (h_w_in[1] - 1) * stride[1]
)
/ 2
)
return (
(math.floor(p_h / 2), math.ceil(p_h / 2)),
(math.floor(p_w / 2), math.ceil(p_w / 2)),
)
if __name__ == "__main__":
print(transp_conv2d_output_shape(105, 10))