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import streamlit as st
import urllib.request
import json
import pandas as pd
from datetime import datetime, date

# Configure the page
st.set_page_config(
    page_title="Page title",
    layout="wide"

ejones18

#!/usr/bin/env python
# coding: utf-8
# Ref: https://github.com/Azure-Samples/cognitive-services-speech-sdk/blob/master/samples/batch/python/python-client/main.py

import logging
import sys
import requests
import time
import swagger_client

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import time

import azure.cognitiveservices.speech as speechsdk

def conversation_transcriber_recognition_canceled_cb(evt: speechsdk.SessionEventArgs):
    print('Canceled event')

def conversation_transcriber_session_stopped_cb(evt: speechsdk.SessionEventArgs):
    print('SessionStopped event')

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import argparse

parser = argparse.ArgumentParser()
parser.add_argument('-o', '--output', default='output.txt', help='The name of the output file')

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import argparse

parser = argparse.ArgumentParser()
parser.add_argument('-f', '--files', nargs='+', help='The names of the files to process')

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parser = argparse.ArgumentParser()
parser.add_argument('filename', help='The name of the file to process')

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import keras

# Define a model with dropout layers
model = keras.models.Sequential()
model.add(keras.layers.Dropout(0.02))
model.add(keras.layers.Dense(64, activation='relu'))
model.add(keras.layers.Dropout(0.5))
model.add(keras.layers.Dense(64, activation='relu'))
model.add(keras.layers.Dense(10, activation='softmax'))

ejones18

from genericpath import exists
import os

import torch

from kale.loaddata import mnistm as mn
from kale.loaddata.dataset_access import split_by_ratios
from kale.utils.print import pprint_without_newline, pprint
from kale.pipeline import mpca_trainer as mpca_train
from PIL import Image, ImageFilter

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def addition(x: int, y: int):
    """
    Add two numbers together.

    Parameters
    ----------
    `x` : int
      First number to be part of the operation.
    `y` : int
      Second number to be part of the operation.

ejones18

var data_ = []
var chart = null;

$( document ).ready(function() {
    refresh_weather_data()
    setInterval(function() { refresh_weather_data() }, 300000);
});

function refresh_weather_data() {
    $.ajax({