code: def convert_to_prices(
      param: "ModelParameters", log_returns: "np.array"
  ) -> "np.array":
      """Converts a sequence of log returns into normal returns (exponentiation)
      and then computes a price sequence given a starting price, param.all_s0.
  
      Parameters
      ----------
      param: `ModelParameters`
          The model parameters.
      log_returns : `np.array`
          The log returns.
  
      Returns
      -------
      `np.array`
          The price sequence.
      """
      returns = np.exp(log_returns)
      # A sequence of prices starting with param.all_s0
      price_sequence = [param.all_s0]
      for i in range(1, len(returns)):
          # Add the price at t-1 * return at t
          price_sequence += [price_sequence[i - 1] * returns[i - 1]]
  
      return np.array(price_sequence)
  
file_path: tensortrade/tensortrade/stochastic/utils/helpers.py
imports: import re
  from typing import Callable
  import numpy
  import pandas
  from stochastic.processes.noise import GaussianNoise
  from tensortrade.stochastic.utils.parameters import ModelParameters, default
label_desc: Use image node_id 3 for calling a global function with example usage: convert_to_prices(param, log_returns) and returns: np