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SPO Class

The SPO class implements the Spiral Optimization (SPO) algorithm. This algorithm is used for optimization towards a target string.

Attributes

  • goal (torch.Tensor): The goal string to be optimized.
  • m (int): Number of search points.
  • k_max (int): Maximum number of iterations.
  • n_dim (int): Length of the goal string.
  • points (torch.Tensor): The search points.
  • center (torch.Tensor): The center point.

Methods

__init__(self, goal: str = None, m: int = 10, k_max: int = 1000)

The constructor for the SPO class. Initializes the search points and the center.

Parameters

  • goal (str, optional): The goal string to be optimized.
  • m (int, optional): Number of search points. Default is 10.
  • k_max (int, optional): Maximum number of iterations. Default is 1000.

Example

spo = SPO(goal="Hello SPO", m=100, k_max=1000)

_step_rate(self, k)

Defines the step rate function.

Parameters

  • k (int): Current iteration.

Returns

  • step_rate (float): Step rate for the current iteration.

Example

step_rate = spo._step_rate(k)

_update_points(self, k)

Updates the search points based on the spiral model.

Parameters

  • k (int): Current iteration.

Example

spo._update_points(k)

_update_center(self)

Finds the best search point and sets it as the new center.

Example

spo._update_center()

optimize(self)

Runs the optimization loop. Updates the search points and the center for a given number of iterations.

Example

spo.optimize()

best_string(self)

Converts the best found point to its string representation.

Returns

  • best_string (str): The best string.

Example

best_string = spo.best_string()
print("Best Matched String:", best_string)

Usage Examples

Example 1: Optimize a String

In this example, we will optimize the string "Attention is all you need" using 100 search points and 1000 iterations.

spo = SPO(goal="Attention is all you need", m=100, k_max=1000)
spo.optimize()
print("Best Matched String:", spo.best_string())

Example 2: Using a Different Goal String

In this example, we will optimize the string "Hello, World!" using 100 search points and 1000 iterations.

spo = SPO(goal="Hello, World!", m=100, k_max=1000)
spo.optimize()
print("Best Matched String:", spo.best_string())

Example 3: Using a Different Number of Search Points

In this example, we will optimize the string "Attention is all you need" using 200 search points and 1000 iterations.

spo = SPO(goal="Attention is all you need", m=200, k_max=1000)
spo.optimize()
print("Best Matched String:", spo.best_string())