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Since RDT will be expanding the number of data types it supports, we will need a new way for the HyperTransformer to determine which transformers to apply to a specific data type. We propose the following additions:
A function, get_transformers_by_type, which iterates over all the existing Transformers and calls the get_input_type method to create a dictionary that indicates which transformers work with which data type.
A DEFAULT_TRANSFORMERS dict which may indicate what the default transformer for each data type is.
If a data type is not in the DEFAULT_TRANSFORMERS dictionary, the first transformer found is "the default".
The text was updated successfully, but these errors were encountered:
…to each data type #232 (#239)
* adding get_transformers_by_type function
* adding other attributes and fixing typo
* pr comments
* adding default transformers method
* pr comments
* adding caching and some cleanup
@amontanez24 in the above formulation, would this method in hypertransformer simply return a transformer which can process the input_type regardless whether or not that transformer output_type is ready for ML or not?
…to each data type #232 (#239)
* adding get_transformers_by_type function
* adding other attributes and fixing typo
* pr comments
* adding default transformers method
* pr comments
* adding caching and some cleanup
…to each data type #232 (#239)
* adding get_transformers_by_type function
* adding other attributes and fixing typo
* pr comments
* adding default transformers method
* pr comments
* adding caching and some cleanup
Problem Description
Since RDT will be expanding the number of data types it supports, we will need a new way for the
HyperTransformer
to determine which transformers to apply to a specific data type. We propose the following additions:get_transformers_by_type
, which iterates over all the existing Transformers and calls theget_input_type
method to create a dictionary that indicates which transformers work with which data type.DEFAULT_TRANSFORMERS
dict which may indicate what the default transformer for each data type is.DEFAULT_TRANSFORMERS
dictionary, the first transformer found is "the default".The text was updated successfully, but these errors were encountered: