coords[i] is a list containing 3 elements x,y,z and I want to get the derivative of G[i] w.r.t. each of x,y,z partially i.e. $\frac{\partial (G[i])}{\partial x_{i}}$, in some sort of a functional form like f(x) so that I can pass a scalar x to f().
This is one of the functions I am using as one of my inputs to a Neural Network and I want to find the partial derivative of my NN w.r.t to x. Hence, I am trying to find  $ \frac{\partial (NN)}{\partial (G1[i])} . \frac{\partial (G1[i])}{\partial (x_{i})} $
import pytorch 
def sym1(coords):
	global avg
	global eeta
	global Rs
	global e
	R_avg=Rc
	G1=[]
	for i,m in enumerate(coords):
		G1.append(0)
		Ri=np.array(coords[i])
		for j in range(i,len(coords)):
			if(i!=j):
				Rj=np.array(coords[j])
				Rij=Ri-Rj
				Rij_norm=np.linalg.norm(Rij)
				sum1=e**(-eeta*((Rij_norm-Rs)**2))
				sum2=cutoff(Rij_norm)
				summation=sum1*sum2
				G1[i]=G1[i]+summation

	return G1