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<!-- Cal inline embed code begins -->
<div style="width:100%;height:100%;overflow:scroll" id="my-cal-inline"></div>
<script type="text/javascript">
  (function (C, A, L) { let p = function (a, ar) { a.q.push(ar); }; let d = C.document; C.Cal = C.Cal || function () { let cal = C.Cal; let ar = arguments; if (!cal.loaded) { cal.ns = {}; cal.q = cal.q || []; d.head.appendChild(d.createElement("script")).src = A; cal.loaded = true; } if (ar[0] === L) { const api = function () { p(api, arguments); }; const namespace = ar[1]; api.q = api.q || []; typeof namespace === "string" ? (cal.ns[namespace] = api) && p(api, ar) : p(cal, ar); return; } p(cal, ar); }; })(window, "https://app.cal.com/embed/embed.js", "init");
Cal("init", "just-chat", {origin:"https://cal.com"});

  Cal.ns["just-chat"]("inline", {
	elementOrSelector:"#my-cal-inline",
	calLink: "leima/just-chat",
	layout: "month_view"

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import numpy as np
import plotly.offline as pyo
import plotly.graph_objs as go

# Generate a random signal
np.random.seed(42)
random_signal = np.random.normal(size=100)

# Offset the line length by the marker size to avoid overlapping
marker_offset = 0.04

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import torch
from torch.utils.data import Dataset


class FakeTimeSeriesDataset(Dataset):
    def __init__(self, sequence_length, input_length, prediction_length, nodes) -> None:
        super().__init__()

        self.sequence_length = sequence_length
        self.prediction_length = prediction_length

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name: Docs
on:
  push:
    branches: [ master ]
  pull_request:
    branches: [ master ]

jobs:
  build:
    name: Build docs

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import json
import os
import random

import requests
from loguru import logger
from requests.adapters import HTTPAdapter
from requests.packages.urllib3.util.retry import Retry

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import matplotlib.pyplot as plt
import torch
from pathlib import Path
import torchvision
import torchvision.transforms as transforms
from loguru import logger
from torch import nn
import click

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from itertools import combinations


class Graph(object):
    """A graph object 
    """

    def __init__(self, source_nodes, target_nodes, weights=None):

        if not isinstance(source_nodes, list):

emptymalei

# This is an experiment
# It is not working
FROM redis:4.0.2-alpine

RUN apk add --no-cache python3 py3-pip
RUN pip3 install click
RUN pip3 install redis

RUN mkdir app
COPY . /app

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# This script is based on the article:
# https://dev.to/fuadrafid/fastapi-the-good-the-bad-and-the-ugly-20ob
# The task is to gather three subreddit top articles and show them as the return
# If we do this in squential code, this will be much slows than the gather method used here.

from fastapi import FastAPI
import json
import asyncio
import time
import aiohttp