What is the gradient function in theano?

This recipe explains what is gradient function in theano.

Recipe Objective - What is gradient function in theano?

Gradient function is used to calculate the derivative of some expression. Let's create a function to find out the derivative of some expression y with respect to its parameter x. To do this we will use the macro tt.grad. For instance, we can compute the gradient of 2x^3 with respect to x. Note that: d(2x^3)/dx = 6x^2.

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Example -

# Import libraries
import theano
from theano import tensor
from theano import pp

# Creating a scalar
x = tensor.dscalar('x')

# Creating 'y' expression
y = (2 * x ** 3)

# Computing derivative
derivative = tensor.grad(y, x)

# Print out the gradient
pp(derivative)

# Convert the expression into a callable object that takes 'x' as input and computes a value for 'derivative'
fun = theano.function([x], derivative)

# Calling function
fun(4)

Output -
array(96.)

In this way, we can compute derivatives using gradient function in theano.

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