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from fastapi import FastAPI
from fastapi.responses import HTMLResponse
import gradio as gr

app = FastAPI()

HELLO_ROUTE = "/hello"
GOODBYE_ROUTE = "/goodbye"

index_html = '''

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import io
from typing import Any, Callable, Iterator, Tuple, Union

import cv2
from google.cloud import storage
import numpy as np
from PIL import Image
import tarfile

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import logging

from typing import Any, Dict, Type


class Registry:
    """
    A factory register pattern
    
    How to Use this Pattern

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#!/bin/bash
# Add a timestamp to the python's output.
# Example:
# dpython -c "[print(i) for i in range(5)]"
# [2019-01-20 14:19:39]  0
# [2019-01-20 14:19:39]  1
# [2019-01-20 14:19:39]  2
# [2019-01-20 14:19:39]  3
# [2019-01-20 14:19:39]  4
# Setup:

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from multiprocessing import Process, Manager, Pool
from multiprocessing.managers import AutoProxy
from typing import Any, List, Optional, Tuple


END_OF_QUEUE = None


class WorkersPool:
    

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# FizzBuzz
print(*[(('','Fizz')[i%3==0] + ('','Buzz')[i%5==0]) if (i%3==0 or i%5==0) else  i for i in range(1, 101)], sep="\n")

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from tensorflow.keras.models import Model
from tensorflow.keras.layers import Input

def split_model(model, split_layer_name=None, split_layer_index=None):
    """
    Split a trained model for predictions.

    If `split_layer_name` and `split_layer_index` are both provided, `split_layer_index` will take precedence.
    Indices are based on order of horizontal graph traversal (bottom-up).

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Favorites

0. numpy
1. pandas
2. matplotlib
3. opencv
4. tensorflow
5. scipy
6. scikit-learn
7. scikit-image
8. Pillow

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name: graph
source code: |-
  #input: '111#1#11#11#11#1#111#111#11'
  #input: '1#11'
  input: '11#11#1'
  #input: '11###1'
  #input: '111'
  blank: ' '
  start state: check_zero_nodes
  table:

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name: binary palindrome enumerator
source code: |
  # Adds 1 to a binary number.
  input: ''
  blank: ' '
  start state: setup_a
  table:
    # binary generator
    setup_a:
      ' '     : {write: '#', L: setup_b}