att288

import json
import os

import numpy as np
import pandas as pd
import tensorflow as tf
from keras import backend as K
from keras.models import load_model

from rest_framework.decorators import api_view

att288

def _load_model_from_path(path):
    global gGraph
    global gModel
    gGraph = tf.get_default_graph()
    gModel = load_model(path)  # keras function
    
_load_model_from_path('path_to_model')

att288

###################################################
# settings.py/the file where to load the models
###################################################
def load_model_from_path(path):
    graph = tf.get_default_graph()
    model = load_model(path)
    return graph, model

def load_all_models():
    global gModelObjs # each object is a tuple of graph, model

att288

def fibonacci_sequence(n):
    curr_val = 0
    next_val = 1
    for i in range(n):
        yield curr_val
        curr_val, next_val = next_val, curr_val + next_val

if __name__ == '__main__':
    fib_seq = []
    for fn in fibonacci_sequence(10):

att288

def multiplier(n):
    step = None
    result = 1
    for i in range(1, n+1):
        if step is None:
            step = 1
        result *= (i*step)
        print(f"i:{i}, step={step}")
        step = yield result 

att288

def my_gen_1(n):  
    for i in range(n):
        yield f'g1: {i}'

def my_gen_2(n):  
    for j in range(n):
        yield f'g2: {-j}'

def my_gen_master(n):  
    yield from my_gen_1(n)

att288

def fib(n):
  if n == 0:
    return 0
  if n == 1:
    return 1

  fn_2 = 0
  fn_1 = 1

  for i in range(n-1):

att288

# recursion

def fib(n):
  if n==0:
    return 0
  if n==1:
    return 1
  return fib(n-1) + fib(n-2)

att288

# DP
fib_seq = [0, 1]
  
def fib(n):
  if n == 0:
    return 0
  if n == 1:
    return 1
  
  if len(fib_seq) == n-1:

att288

class Example:
  @classmethod
  def foo(cls, arg1, arg2, ...):
    pass