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Unable to run code #1132
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Activity
This appears an issue in ray. Could you try pip install "ray[tune]<2.5.0"? It passed the test in GitHub actions.
Reacted by Xiaoyao Yang, Scott Willeke and RJTTLFFT6MZJPN16Z2GBIt worked, Issue was in Kaggle env. Locally I never had that issue
i try the above step but still it is showing same error
Same issue,
AttributeError: 'ExperimentAnalysis' object has no attribute 'decode'AbhinavGaur147 Xiaoyao Yang (@xiaoyaoyang) what's the version of ray in your env?
This appears an issue in ray. Could you try pip install "ray[tune]<2.5.0"? It passed the test in GitHub actions.
Chi Wang (@sonichi) thanks for reply, it was ray==2.6.1. Tried change the version and it works, but I also got another strange error
prefer=default(None) is not a valid backend hint, expected one of ('processes', 'threads', None).solve that byjoblibwith older version also I thinkdo we have dependency files for each release? figure I could just grab that and install.. ( I could upload mine for 2.0.0)
This appears an issue in ray. Could you try pip install "ray[tune]<2.5.0"? It passed the test in GitHub actions.
Chi Wang (@sonichi) thanks for reply, it was ray==2.6.1. Tried change the version and it works, but I also got another strange error
prefer=default(None) is not a valid backend hint, expected one of ('processes', 'threads', None).solve that byjoblibwith older version also I thinkdo we have dependency files for each release? figure I could just grab that and install.. ( I could upload mine for 2.0.0)
The optional dependencies are specified in setup.py and documented in https://microsoft.github.io/FLAML/docs/Installation. For example, the [ray] option specifies the ray versions needed if ray is needed.
Reacted by Xiaoyao YangThis problem still persists as I use Kaggle Notebook. Can someone help with the right configuration here after testing in Kaggle?
In the Python environment on Kaggle, you can solve the problem using the following code:
!pip install flaml !pip install ray[tune]==2.4.0Reacted by Shivam MauryaAttach my error log for ref, confirmed that swtich to ray==2.7.1 solve the issue, but you have to restart the kernel/ clear cache somehow.. Otherwise below error..
with training_log_writer(log_file_name, append_log) as save_helper: 1924 self._training_log = save_helper -> 1925 self._search() 1926 else: 1927 self._training_log = None File /opt/conda/lib/python3.10/site-packages/flaml/automl/automl.py:2482, in AutoML._search(self) 2480 state.best_config = state.init_config[0] if state.init_config else {} 2481 elif self._use_ray is False and self._use_spark is False: -> 2482 self._search_sequential() 2483 else: 2484 self._search_parallel() File /opt/conda/lib/python3.10/site-packages/flaml/automl/automl.py:2271, in AutoML._search_sequential(self) 2267 time_budget_s = ( 2268 min(budget_left, self._state.train_time_limit or np.inf) if self._state.time_budget >= 0 else None 2269 ) 2270 if self._hpo_method in ("bs", "cfo", "grid", "cfocat", "random"): -> 2271 algo = SearchAlgo( 2272 metric="val_loss", 2273 mode="min", 2274 space=search_space, 2275 points_to_evaluate=points_to_evaluate, 2276 low_cost_partial_config=low_cost_partial_config, 2277 cat_hp_cost=search_state.cat_hp_cost, 2278 resource_attr=resource_attr, 2279 min_resource=min_resource, 2280 max_resource=max_resource, 2281 config_constraints=[(learner_class.size, "<=", self._mem_thres)], 2282 metric_constraints=self.metric_constraints, 2283 seed=self._seed, 2284 allow_empty_config=True, 2285 time_budget_s=time_budget_s, 2286 num_samples=self._max_iter, 2287 ) 2288 else: 2289 # if self._hpo_method is optuna, sometimes the search space and the initial config dimension do not match 2290 # need to remove the extra keys from the search space to be consistent with the initial config 2291 converted_space = SearchAlgo.convert_search_space(search_space) File /opt/conda/lib/python3.10/site-packages/flaml/tune/searcher/blendsearch.py:203, in BlendSearch.__init__(self, metric, mode, space, low_cost_partial_config, cat_hp_cost, points_to_evaluate, evaluated_rewards, time_budget_s, num_samples, resource_attr, min_resource, max_resource, reduction_factor, global_search_alg, config_constraints, metric_constraints, seed, cost_attr, cost_budget, experimental, lexico_objectives, use_incumbent_result_in_evaluation, allow_empty_config) 201 if space: 202 add_cost_to_space(space, init_config, self._cat_hp_cost) --> 203 self._ls = self.LocalSearch( 204 init_config, File /opt/conda/lib/python3.10/site-packages/flaml/tune/searcher/flow2.py:109, in FLOW2.__init__(self, init_config, metric, mode, space, resource_attr, min_resource, max_resource, resource_multiple_factor, cost_attr, seed, lexico_objectives) 106 else: 107 mode = "min" --> 109 super(FLOW2, self).__init__(metric=metric, mode=mode) 110 # internally minimizes, so "max" => -1 111 if mode == "max": File /opt/conda/lib/python3.10/site-packages/ray/tune/search/searcher.py:83, in Searcher.__init__(self, metric, mode) 78 def __init__( 79 self, 80 metric: Optional[str] = None, 81 mode: Optional[str] = None, 82 ): ---> 83 tag_searcher(self) 84 self._metric = metric 85 self._mode = mode File /opt/conda/lib/python3.10/site-packages/ray/air/_internal/usage.py:122, in tag_searcher(searcher) 120 record_extra_usage_tag(TagKey.TUNE_SEARCHER, searcher_name) 121 else: --> 122 assert False, ( 123 "Not expecting a non-BasicVariantGenerator, " 124 "non-Searcher type passed in for `tag_searcher`." 125 ) AssertionError: Not expecting a non-BasicVariantGenerator, non-Searcher type passed in for `tag_searcher`.Reacted by RJTTLFFT6MZJPN16Z2GBSame issue,
AttributeError: 'ExperimentAnalysis' object has no attribute 'decode'thank you! it is normal working. i update [ray]
automl.fit(X_train, y_train, task="regression",metric='rmse',time_budget=3600)
[flaml.automl.logger: 07-17 14:34:05] {1693} INFO - task = regression
[flaml.automl.logger: 07-17 14:34:05] {1700} INFO - Data split method: uniform
[flaml.automl.logger: 07-17 14:34:05] {1703} INFO - Evaluation method: holdout
[flaml.automl.logger: 07-17 14:34:05] {1801} INFO - Minimizing error metric: rmse
[flaml.automl.logger: 07-17 14:34:06] {1911} INFO - List of ML learners in AutoML Run: ['lgbm', 'rf', 'catboost', 'xgboost', 'extra_tree', 'xgb_limitdepth']
[flaml.automl.logger: 07-17 14:34:06] {2221} INFO - iteration 0, current learner lgbm
AttributeError Traceback (most recent call last)
Cell In[36], line 1
----> 1 automl.fit(X_train, y_train, task="regression",metric='rmse',time_budget=3600)
File /opt/conda/lib/python3.10/site-packages/flaml/automl/automl.py:1939, in AutoML.fit(self, X_train, y_train, dataframe, label, metric, task, n_jobs, log_file_name, estimator_list, time_budget, max_iter, sample, ensemble, eval_method, log_type, model_history, split_ratio, n_splits, log_training_metric, mem_thres, pred_time_limit, train_time_limit, X_val, y_val, sample_weight_val, groups_val, groups, verbose, retrain_full, split_type, learner_selector, hpo_method, starting_points, seed, n_concurrent_trials, keep_search_state, preserve_checkpoint, early_stop, force_cancel, append_log, auto_augment, min_sample_size, use_ray, use_spark, free_mem_ratio, metric_constraints, custom_hp, cv_score_agg_func, skip_transform, mlflow_logging, fit_kwargs_by_estimator, **fit_kwargs)
1937 else:
1938 self._training_log = None
-> 1939 self._search()
1940 if self._best_estimator:
1941 logger.info("fit succeeded")
File /opt/conda/lib/python3.10/site-packages/flaml/automl/automl.py:2485, in AutoML._search(self)
2483 state.best_config = state.init_config[0] if state.init_config else {}
2484 elif self._use_ray is False and self._use_spark is False:
-> 2485 self._search_sequential()
2486 else:
2487 self._search_parallel()
File /opt/conda/lib/python3.10/site-packages/flaml/automl/automl.py:2321, in AutoML._search_sequential(self)
2315 search_state.search_alg.searcher.set_search_properties(
2316 metric=None,
2317 mode=None,
2318 metric_target=self._state.best_loss,
2319 )
2320 start_run_time = time.time()
-> 2321 analysis = tune.run(
2322 search_state.training_function,
2323 search_alg=search_state.search_alg,
2324 time_budget_s=time_budget_s,
2325 verbose=max(self.verbose - 3, 0),
2326 use_ray=False,
2327 use_spark=False,
2328 )
2329 time_used = time.time() - start_run_time
2330 better = False
File /opt/conda/lib/python3.10/site-packages/flaml/tune/tune.py:797, in run(evaluation_function, config, low_cost_partial_config, cat_hp_cost, metric, mode, time_budget_s, points_to_evaluate, evaluated_rewards, resource_attr, min_resource, max_resource, reduction_factor, scheduler, search_alg, verbose, local_dir, num_samples, resources_per_trial, config_constraints, metric_constraints, max_failure, use_ray, use_spark, use_incumbent_result_in_evaluation, log_file_name, lexico_objectives, force_cancel, n_concurrent_trials, **ray_args)
795 if num_failures == upperbound_num_failures:
796 logger.warning(f"fail to sample a trial for {max_failure} times in a row, stopping.")
--> 797 analysis = ExperimentAnalysis(
798 _runner.get_trials(),
799 metric=metric,
800 mode=mode,
801 lexico_objectives=lexico_objectives,
802 )
803 return analysis
804 finally:
805 # recover the global variables in case of nested run
File /opt/conda/lib/python3.10/site-packages/flaml/tune/tune.py:45, in ExperimentAnalysis.init(self, trials, metric, mode, lexico_objectives)
43 def init(self, trials, metric, mode, lexico_objectives=None):
44 try:
---> 45 super().init(self, None, trials, metric, mode)
46 self.lexico_objectives = lexico_objectives
47 except (TypeError, ValueError):
File /opt/conda/lib/python3.10/site-packages/ray/tune/analysis/experiment_analysis.py:97, in ExperimentAnalysis.init(self, experiment_checkpoint_path, trials, default_metric, default_mode, remote_storage_path, sync_config)
92 self._remote_experiment_path: Optional[str] = None
94 # If the user passes in a remote checkpoint path,
95 # Set the remote experiment path to this path, and set
96 # the local experiment path to a temp directory.
---> 97 if not is_local_path(experiment_checkpoint_path):
98 self._remote_experiment_path = experiment_checkpoint_path
100 # Create a temp directory to store downloaded checkpoint files if
101 # they are pulled from a remote
experiment_checkpoint_path.File /opt/conda/lib/python3.10/site-packages/ray/air/_internal/remote_storage.py:167, in is_local_path(path)
164 if sys.platform == "win32":
165 return _is_local_windows_path(path)
--> 167 scheme = urllib.parse.urlparse(path).scheme
168 return scheme in ("", "file")
File /opt/conda/lib/python3.10/urllib/parse.py:399, in urlparse(url, scheme, allow_fragments)
379 def urlparse(url, scheme='', allow_fragments=True):
380 """Parse a URL into 6 components:
381 :///;?#
382
(...)
397 Note that % escapes are not expanded.
398 """
--> 399 url, scheme, _coerce_result = _coerce_args(url, scheme)
400 splitresult = urlsplit(url, scheme, allow_fragments)
401 scheme, netloc, url, query, fragment = splitresult
File /opt/conda/lib/python3.10/urllib/parse.py:136, in _coerce_args(*args)
134 if str_input:
135 return args + (_noop,)
--> 136 return _decode_args(args) + (_encode_result,)
File /opt/conda/lib/python3.10/urllib/parse.py:120, in _decode_args(args, encoding, errors)
118 def _decode_args(args, encoding=_implicit_encoding,
119 errors=_implicit_errors):
--> 120 return tuple(x.decode(encoding, errors) if x else '' for x in args)
File /opt/conda/lib/python3.10/urllib/parse.py:120, in (.0)
118 def _decode_args(args, encoding=_implicit_encoding,
119 errors=_implicit_errors):
--> 120 return tuple(x.decode(encoding, errors) if x else '' for x in args)
AttributeError: 'ExperimentAnalysis' object has no attribute 'decode'