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# Any copyright is dedicated to the Public Domain.
# https://creativecommons.org/publicdomain/zero/1.0/
# Written by Francois Fleuret <francois@fleuret.org>
import os
import random
import torch


class PScan(torch.autograd.Function):
    @staticmethod

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from torch import Tensor
from typing import Callable, List, Optional, Tuple
import math
import warnings
import torch
import torch.nn as nn
import torch.nn.functional as F

class CSigmoid(nn.Module):
    def forward(self, input: Tensor) -> Tensor:

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import torch
import torch.nn as nn
import torch.nn.functional as F

class CausalConv1d(nn.Conv1d):
    def __init__(self, in_channels, out_channels, kernel_size, stride=1, enable_padding=False, dilation=1, groups=1, bias=True):
        if enable_padding == True:
            self.__padding = (kernel_size - 1) * dilation
        else:
            self.__padding = 0