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from math import sqrt
from typing import OrderedDict
import torch
from torch import nn
from torch.nn import functional as F


class MultivariateEmbedding(nn.Module):
    def __init__(self,
                embeddings: nn.ModuleDict,

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# docker build -t dlkit -f dlkit.dockerfile .
# docker run -itd --gpus all -p 8888:8888 -p 6006:6006 --ipc host -v ~/workspace/dlkit1:/workspace --name dlkit1 dlkit

FROM pytorch/pytorch:2.2.1-cuda12.1-cudnn8-runtime

ENV SHELL=/bin/bash

WORKDIR /workspace

RUN pip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple

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"""
A script for labeling where in a audio file is sounding.

Dependenicy:
pip install torch torchaudio
"""

import torch
from torch.nn import functional as F
import torchaudio

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import torch


class Sampler:
    def __init__(self,
                top_k: int,
                top_p: float,
                temperature: float,
                repetition_penalty: float):
        self.top_k = top_k

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#ifndef _META_NUMERIC_
#define _META_NUMERIC_

#include <iostream>
#include <string>


namespace metanumeric {

#define UNARY_ASGN_OPTS          \

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import torch
import torch.nn as nn
import torch.nn.functional as F
import torchaudio
import numpy as np


def get_fourier_basis(win_length, window_func=torch.hann_window):
    # Create kernels for STFT, initialized to Fourier basis
    n_basis = win_length // 2 + 1

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# https://arxiv.org/pdf/1810.11921.pdf
from typing import Dict
from itertools import product
import torch
from torch import nn
import torch.nn.functional as F


class AutoInt(nn.Module):
    def __init__(self,

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# https://arxiv.org/pdf/2102.12994.pdf

from typing import Dict
from itertools import permutations
import torch
from torch import nn
from math import sqrt


class FMFM(nn.Module):

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from typing import List
from itertools import chain
import torch
from torch import nn


class Transpose(nn.Module):
    def __init__(self, *args):
        super().__init__()

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from typing import List
from itertools import chain
import torch
from torch import nn


class Transpose(nn.Module):
    def __init__(self, *args):
        super().__init__()