class_docstr: Stores data associated with and proxies calls to a Stan model.
  
  Returned by ``build``. Users will not instantiate this class directly.
class_docstr_tok: ["Stores","data","associated","with","and","proxies","calls","to","a","Stan","model",".","Returned","by","``","build","``",".","Users","will","not","instantiate","this","class","directly","."]
docstr: Calculate the gradient of the log posterior evaluated at
     the unconstrained parameters.
  
  Arguments:
      unconstrained_parameters: A sequence of unconstrained parameters.
  
  Returns:
      The gradient of the log posterior evaluated at the
      unconstrained parameters.
  
  Notes:
      The unconstrained parameters are passed to the log_prob_grad
      function in stan::model.
docstr_tok: ["Calculate","the","gradient","of","the","log","posterior","evaluated","at","the","unconstrained","parameters",".","Arguments",":","unconstrained_parameters",":","A","sequence","of","unconstrained","parameters",".","Returns",":","The","gradient","of","the","log","posterior","evaluated","at","the","unconstrained","parameters",".","Notes",":","The","unconstrained","parameters","are","passed","to","the","log_prob_grad","function","in","stan",":",":model","."]
code: def grad_log_prob(
      self, unconstrained_parameters: Sequence[float]
  ) -> float:
      """Calculate the gradient of the log posterior evaluated at
         the unconstrained parameters.
  
      Arguments:
          unconstrained_parameters: A sequence of unconstrained parameters.
  
      Returns:
          The gradient of the log posterior evaluated at the
          unconstrained parameters.
  
      Notes:
          The unconstrained parameters are passed to the log_prob_grad
          function in stan::model.
      """
      payload = {
          "data": self.data,
          "unconstrained_parameters": unconstrained_parameters,
      }
  
      async def go():
          async with stan.common.HttpstanClient() as client:
              resp = await client.post(
                  f"/{self.model_name}/log_prob_grad", json=payload
              )
              if resp.status != 200:
                  raise RuntimeError(resp.json())
              return resp.json()["log_prob_grad"]
  
      return asyncio.run(go())
  
imports: import asyncio
  import dataclasses
  import json
  import re
  import time
  from typing import Dict, List, Optional, Sequence, Tuple, Union, cast
  import httpstan.models
  import httpstan.schemas
  import httpstan.services.arguments
  import httpstan.utils
  import numpy
  import simdjson
  from clikit.io import ConsoleIO
  import stan.common
  import stan.fit
  import stan.plugins
label_desc: Use image node_id 9 for calling the Model obj's underlying member method code with example usage: obj.grad_log_prob(unconstrained_parameters) and returns: asyncio, resp