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import tensorflow as tf
from tensorflow.python.framework import ops
import numpy as np

# Define custom py_func which takes also a grad op as argument:
def py_func(func, inp, Tout, stateful=True, name=None, grad=None):
    
    # Need to generate a unique name to avoid duplicates:
    rnd_name = 'PyFuncGrad' + str(np.random.randint(0, 1E+8))
    

harpone

import numpy as np
cimport cython
cimport numpy as np
 
from libc.stdint cimport uint32_t, int32_t
from libc.math cimport sqrt
from libc.math cimport fabs
from libc.math cimport pow
 
 

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def simulation(L = 0, N = 100000, dt = 1E-3, init = .1):
    """Simulate a stochastic differential equation.
    """
 
    #Set up some parameters:
    f1 = .1
    g1 = .01
    g2 = .1
    
    dW = np.random.randn(N)*np.sqrt(dt)

harpone

# Same with Cython:
import numpy as np
cimport cython
cimport numpy as np

from libc.stdint cimport uint32_t, int32_t
from libc.math cimport sqrt
from libc.math cimport fabs
from libc.math cimport pow