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I didn't change anything. I just run all notebook.
I am using Windows 10, cuda 10-update 2 and Python 3.7.5. I have all necessary compliers. Auto-PyTorch successfully installed and imported.
...
Get the ConfigSpace object with all hyperparameters, conditions, default values and default ranges
TypeError Traceback (most recent call last)
in
3
4 # Get the ConfigSpace object with all hyperparameters, conditions, default values and default ranges
----> 5 hyperparameter_search_space = autonet.get_hyperparameter_search_space()
6
7 # Print all possible configuration options
are you on the master or development branch? There recently was a change of hyperparameter names which is probably the reason for this (cosine_annealing was changed to cosine_annealing_with_restarts).
I didn't change anything. I just run all notebook.
I am using Windows 10, cuda 10-update 2 and Python 3.7.5. I have all necessary compliers. Auto-PyTorch successfully installed and imported.
...
Get the ConfigSpace object with all hyperparameters, conditions, default values and default ranges
hyperparameter_search_space = autonet.get_hyperparameter_search_space()
...
4'th cell traceback:
TypeError Traceback (most recent call last)
in
3
4 # Get the ConfigSpace object with all hyperparameters, conditions, default values and default ranges
----> 5 hyperparameter_search_space = autonet.get_hyperparameter_search_space()
6
7 # Print all possible configuration options
~\Anaconda3\lib\site-packages\autopytorch-0.0.2-py3.7.egg\autoPyTorch\core\api.py in get_hyperparameter_search_space(self, X_train, Y_train, X_valid, Y_valid, **autonet_config)
101 Y_valid=Y_valid)["dataset_info"]
102
--> 103 return self.pipeline.get_hyperparameter_search_space(dataset_info=dataset_info, **pipeline_config)
104
105 @classmethod
~\Anaconda3\lib\site-packages\autopytorch-0.0.2-py3.7.egg\autoPyTorch\pipeline\base\pipeline.py in get_hyperparameter_search_space(self, dataset_info, **pipeline_config)
109 for name, node in self._pipeline_nodes.items():
110 #print("dataset_info" in pipeline_config.keys())
--> 111 config_space = node.get_hyperparameter_search_space(**pipeline_config)
112 cs.add_configuration_space(prefix=name, configuration_space=config_space, delimiter=ConfigWrapper.delimiter)
113
~\Anaconda3\lib\site-packages\autopytorch-0.0.2-py3.7.egg\autoPyTorch\pipeline\nodes\lr_scheduler_selector.py in get_hyperparameter_search_space(self, dataset_info, **pipeline_config)
56 continue
57 lr_scheduler_cs = lr_scheduler_type.get_config_space(
---> 58 **self._get_search_space_updates(prefix=lr_scheduler_name))
59 cs.add_configuration_space( prefix=lr_scheduler_name, configuration_space=lr_scheduler_cs, delimiter=ConfigWrapper.delimiter,
60 parent_hyperparameter={'parent': selector, 'value': lr_scheduler_name})
TypeError: get_config_space() got an unexpected keyword argument 'T_mult'
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