make pytorch Embedding layer for time series forecasting architectures#474
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* remove remaining differences * Reg cocktails common paper modifications 5 (automl#418) * add hasttr * fix run summary
…edding) (automl#437) * add updates for apt1.0+reg_cocktails * debug loggers for checking data and network memory usage * add support for pandas, test for data passing, remove debug loggers * remove unwanted changes * : * Adjust formula to account for embedding columns * Apply suggestions from code review Co-authored-by: nabenabe0928 <47781922+nabenabe0928@users.noreply.github.com> * remove unwanted additions * Update autoPyTorch/pipeline/components/preprocessing/tabular_preprocessing/TabularColumnTransformer.py Co-authored-by: nabenabe0928 <47781922+nabenabe0928@users.noreply.github.com>
…#454) * reduce number of hyperparameters for pytorch embedding * remove todos for the preprocessing PR, and apply suggestion from code review * remove unwanted exclude in test
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Description
This is a preliminary PR for making the new PyTorch embedding implementation compatible with time series forecasting tasks (data structure, fit dictionary, and so on...). Still under construction...
Motivation and Context
How has this been tested?