This repository was archived by the owner on Jan 10, 2025. It is now read-only.
This repository was archived by the owner on Jan 10, 2025. It is now read-only.
Machine Learning/Query Optimization example TypeError: logger() got an unexpected keyword argument 'curr_min_score' #385
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Description
Hello, I'm trying to run the optimization query of the Machine Learning/Query Optimization example and I'm getting this error:
Using configuration
- metric: {
"mean_reciprocal_rank": {
"k": 100,
"relevant_rating_threshold": 1
}
}
- selected method: bayesian
- default params: {}
/home/gllermaly/examples/Machine Learning/Query Optimization/venv/lib/python3.6/site-packages/elasticsearch/connection/base.py:209: ElasticsearchWarning: Elasticsearch built-in security features are not enabled. Without authentication, your cluster could be accessible to anyone. See https://www.elastic.co/guide/en/elasticsearch/reference/7.15/security-minimal-setup.html to enable security.
warnings.warn(message, category=ElasticsearchWarning)
Traceback (most recent call last):
File "bin/optimize-query", line 84, in <module>
main()
File "bin/optimize-query", line 71, in main
args.template_id, queries, qrels, logger)
File "/home/gllermaly/examples/Machine Learning/Query Optimization/qopt/optimize.py", line 223, in optimize_query
return optimize(config, objective_fn, initial_points=None, logger_fn=logger_fn)
File "/home/gllermaly/examples/Machine Learning/Query Optimization/qopt/optimize.py", line 265, in optimize
x0=initial_points)
File "/home/gllermaly/examples/Machine Learning/Query Optimization/venv/lib/python3.6/site-packages/skopt/optimizer/gp.py", line 268, in gp_minimize
callback=callback, n_jobs=n_jobs, model_queue_size=model_queue_size)
File "/home/gllermaly/examples/Machine Learning/Query Optimization/venv/lib/python3.6/site-packages/skopt/optimizer/base.py", line 304, in base_minimize
if eval_callbacks(callbacks, result):
File "/home/gllermaly/examples/Machine Learning/Query Optimization/venv/lib/python3.6/site-packages/skopt/utils.py", line 99, in eval_callbacks
decision = c(result)
File "/home/gllermaly/examples/Machine Learning/Query Optimization/qopt/optimize.py", line 176, in __call__
params=params)
TypeError: logger() got an unexpected keyword argument 'curr_min_score'
real 0m0.988s
user 0m0.927s
sys 0m0.271s
This is the method that failes
def logger(iteration, total_iterations, score, _, duration, params):
print(f" - iteration {iteration}/{total_iterations} ({duration:.04f}s) scored {score:.04f} with: {json.dumps(params)}")
If I replace the "_" with curr_min_score then throws a different error:
- iteration 39/75 (0.0159s) scored 1.0000 with: {"tie_breaker": 0.5699173276454137, "title.english|boost": 4.3273304062411615, "title|boost": 1.6393208127999483, "category|boost": 0.9826987511047194, "category.english|boost": 9.580933015419806, "descriptors|boost": 3.503736851987736, "file_name|boost": 8.566968785271335, "vendor_name|boost": 1.757893690628294, "snippet|boost": 7.494445295285921, "snippet.english|boost": 4.513989505981226, "assetId|boost": 7.035638672539559, "operator": "OR"}
Traceback (most recent call last):
File "bin/optimize-query", line 84, in <module>
main()
File "bin/optimize-query", line 71, in main
args.template_id, queries, qrels, logger)
File "/home/gllermaly/examples/Machine Learning/Query Optimization/qopt/optimize.py", line 223, in optimize_query
return optimize(config, objective_fn, initial_points=None, logger_fn=logger_fn)
File "/home/gllermaly/examples/Machine Learning/Query Optimization/qopt/optimize.py", line 265, in optimize
x0=initial_points)
File "/home/gllermaly/examples/Machine Learning/Query Optimization/venv/lib/python3.6/site-packages/skopt/optimizer/gp.py", line 268, in gp_minimize
callback=callback, n_jobs=n_jobs, model_queue_size=model_queue_size)
File "/home/gllermaly/examples/Machine Learning/Query Optimization/venv/lib/python3.6/site-packages/skopt/optimizer/base.py", line 302, in base_minimize
result = optimizer.tell(next_x, next_y)
File "/home/gllermaly/examples/Machine Learning/Query Optimization/venv/lib/python3.6/site-packages/skopt/optimizer/optimizer.py", line 493, in tell
return self._tell(x, y, fit=fit)
File "/home/gllermaly/examples/Machine Learning/Query Optimization/venv/lib/python3.6/site-packages/skopt/optimizer/optimizer.py", line 536, in _tell
est.fit(self.space.transform(self.Xi), self.yi)
File "/home/gllermaly/examples/Machine Learning/Query Optimization/venv/lib/python3.6/site-packages/skopt/learning/gaussian_process/gpr.py", line 195, in fit
super(GaussianProcessRegressor, self).fit(X, y)
File "/home/gllermaly/examples/Machine Learning/Query Optimization/venv/lib/python3.6/site-packages/sklearn/gaussian_process/_gpr.py", line 234, in fit
self.kernel_.bounds))]
File "/home/gllermaly/examples/Machine Learning/Query Optimization/venv/lib/python3.6/site-packages/sklearn/gaussian_process/_gpr.py", line 503, in _constrained_optimization
bounds=bounds)
File "/home/gllermaly/examples/Machine Learning/Query Optimization/venv/lib/python3.6/site-packages/scipy/optimize/_minimize.py", line 618, in minimize
callback=callback, **options)
File "/home/gllermaly/examples/Machine Learning/Query Optimization/venv/lib/python3.6/site-packages/scipy/optimize/lbfgsb.py", line 308, in _minimize_lbfgsb
finite_diff_rel_step=finite_diff_rel_step)
File "/home/gllermaly/examples/Machine Learning/Query Optimization/venv/lib/python3.6/site-packages/scipy/optimize/optimize.py", line 262, in _prepare_scalar_function
finite_diff_rel_step, bounds, epsilon=epsilon)
File "/home/gllermaly/examples/Machine Learning/Query Optimization/venv/lib/python3.6/site-packages/scipy/optimize/_differentiable_functions.py", line 76, in __init__
self._update_fun()
File "/home/gllermaly/examples/Machine Learning/Query Optimization/venv/lib/python3.6/site-packages/scipy/optimize/_differentiable_functions.py", line 166, in _update_fun
self._update_fun_impl()
File "/home/gllermaly/examples/Machine Learning/Query Optimization/venv/lib/python3.6/site-packages/scipy/optimize/_differentiable_functions.py", line 73, in update_fun
self.f = fun_wrapped(self.x)
File "/home/gllermaly/examples/Machine Learning/Query Optimization/venv/lib/python3.6/site-packages/scipy/optimize/_differentiable_functions.py", line 70, in fun_wrapped
return fun(x, *args)
File "/home/gllermaly/examples/Machine Learning/Query Optimization/venv/lib/python3.6/site-packages/scipy/optimize/optimize.py", line 74, in __call__
self._compute_if_needed(x, *args)
File "/home/gllermaly/examples/Machine Learning/Query Optimization/venv/lib/python3.6/site-packages/scipy/optimize/optimize.py", line 68, in _compute_if_needed
fg = self.fun(x, *args)
File "/home/gllermaly/examples/Machine Learning/Query Optimization/venv/lib/python3.6/site-packages/sklearn/gaussian_process/_gpr.py", line 225, in obj_func
theta, eval_gradient=True, clone_kernel=False)
File "/home/gllermaly/examples/Machine Learning/Query Optimization/venv/lib/python3.6/site-packages/sklearn/gaussian_process/_gpr.py", line 476, in log_marginal_likelihood
alpha = cho_solve((L, True), y_train) # Line 3
File "/home/gllermaly/examples/Machine Learning/Query Optimization/venv/lib/python3.6/site-packages/scipy/linalg/decomp_cholesky.py", line 194, in cho_solve
b1 = asarray_chkfinite(b)
File "/home/gllermaly/examples/Machine Learning/Query Optimization/venv/lib/python3.6/site-packages/numpy/lib/function_base.py", line 486, in asarray_chkfinite
"array must not contain infs or NaNs")
ValueError: array must not contain infs or NaNs
It fails in the iteration number 39 , and num_initial_points
is set to 40 as the default , num_iterations
set to 70
Any advice would be appreciated.
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