#!/usr/bin/python3
# -*- coding: utf-8 -*-
import torch
import torch.nn as nn


inputs = torch.randn(size=(1, 1, 16000))

conv1d = nn.Conv1d(
    in_channels=1,
    out_channels=1,
    kernel_size=3,
    stride=2,
    padding=0,
    dilation=1,
)
conv1dt = nn.ConvTranspose1d(
    in_channels=1,
    out_channels=1,
    kernel_size=3,
    stride=2,
    padding=0,
    output_padding=1,
    dilation=1,
)

x = conv1d.forward(inputs)

print(x.shape)

x = conv1dt.forward(x)
print(x.shape)
print(x[:, :, 0])
print(x[:, :, -2])
print(x[:, :, -1])


if __name__ == "__main__":
    pass