TypeError: minimize() missing 1 required positional argument: 'var_list'

This error occurs when the `minimize` function is called without providing the required argument `var_list`.

The `minimize` function is used to minimize a scalar function of one or more variables using optimization algorithms. The `var_list` argument is used to specify the variables that the function should be minimized with respect to.

To fix this error, make sure to provide the `var_list` argument when calling the `minimize` function. The `var_list` argument should be a list of variables that the function should be minimized with respect to.

Here is an example of how to use the `minimize` function with the `var_list` argument:

import tensorflow as tf

# Define the function to be minimized
def f(x, y):
    return x**2 + y**2

# Define the variables to be minimized with respect to
x = tf.Variable(1.0)
y = tf.Variable(2.0)
var_list = [x, y]

# Define the optimizer
optimizer = tf.optimizers.Adam()

# Minimize the function
minimizer = optimizer.minimize(lambda: f(x, y), var_list=var_list)

# Run the minimizer
for i in range(100):
    minimizer.run()

# Print the final values of x and y
print("x =", x.numpy())
print("y =", y.numpy())