amitjamadagni

[ Info: CUDA is on
[ Info: Epoch 1
ERROR: LoadError: Scalar indexing is disallowed.
Invocation of getindex resulted in scalar indexing of a GPU array.
This is typically caused by calling an iterating implementation of a method.
Such implementations *do not* execute on the GPU, but very slowly on the CPU,
and therefore are only permitted from the REPL for prototyping purposes.
If you did intend to index this array, annotate the caller with @allowscalar.
Stacktrace:
  [1] error(s::String)

amitjamadagni

import numpy as np
import random as rand
from numpy.linalg import inv
from numpy.linalg import norm
from scipy.optimize import minimize
from scipy.optimize import linprog
import warnings
import time
import sys
from memory_profiler import profile

amitjamadagni

Line #    Mem usage    Increment   Line Contents
================================================
   320     37.2 MiB      0.0 MiB   @profile
   321                             def func():
   322     37.2 MiB      0.0 MiB       n_products = input("Enter the number of products (that is add +1 to the actual number) : ")
   323     37.2 MiB      0.0 MiB       time_steps = input("Enter the number of time steps (should be equal to the above number of products) : ")
   324     37.2 MiB      0.0 MiB       demand_mat = input("Enter the demand matrix with time instance as columns and products as rows : ")
   325     37.2 MiB      0.0 MiB       max_price = input("Enter the maximum price for each product as an array : ")
   326     37.2 MiB      0.0 MiB       min_price = input("Enter the minimum price for each product as an array : ")
   327     37.2 MiB      0.0 MiB       print "Creating the pricing object "

amitjamadagni

import numpy as np
import random as rand
from numpy.linalg import inv
from numpy.linalg import norm
from scipy.optimize import minimize
from scipy.optimize import linprog
import warnings
import time
import sys

amitjamadagni

import numpy as np
import random as rand
from numpy.linalg import inv
from numpy.linalg import norm
from scipy.optimize import minimize
from scipy.optimize import linprog
import warnings
import time
import sys

amitjamadagni

import numpy as np
import random as rand
from numpy.linalg import inv
from numpy.linalg import norm
from scipy.optimize import minimize
from scipy.optimize import linprog
import warnings
import time
import sys

amitjamadagni

import numpy as np
import random as rand
from numpy.linalg import inv
from numpy.linalg import norm
from scipy.optimize import minimize
from scipy.optimize import linprog
import warnings
import time
import sys

amitjamadagni

import numpy as np
import random as rand
import multiprocessing
import logging
import warnings
import os
import time
import sys
from numpy.linalg import inv
from numpy.linalg import norm

amitjamadagni

import numpy as np
import random as rand
from numpy.linalg import inv
from numpy.linalg import norm
from scipy.optimize import minimize
from scipy.optimize import linprog
import warnings
import time
import sys

amitjamadagni

import numpy as np
import random as rand
from numpy.linalg import inv
from numpy.linalg import norm
from scipy.optimize import minimize
from scipy.optimize import linprog
import warnings
import time
import sys