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make pytorch Embedding layer for time series forecasting architectures #474

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make pytorch Embedding layer for time series forecasting architectures #474

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Types of changes

  • Breaking change (fix or feature that would cause existing functionality to not work as expected)
  • Bug fix (non-breaking change which fixes an issue)
  • New feature (non-breaking change which adds functionality)

Note that a Pull Request should only contain one of refactoring, new features or documentation changes.
Please separate these changes and send us individual PRs for each.
For more information on how to create a good pull request, please refer to The anatomy of a perfect pull request.

Checklist:

  • My code follows the code style of this project.
  • My change requires a change to the documentation.
  • I have updated the documentation accordingly.
  • Have you checked to ensure there aren't other open Pull Requests for the same update/change?
  • Have you added an explanation of what your changes do and why you'd like us to include them?
  • Have you written new tests for your core changes, as applicable?
  • Have you successfully ran tests with your changes locally?

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?

ravinkohli and others added 21 commits August 4, 2022 11:35
@ravinkohli
update eta for experiments
ec94359
@ravinkohli
add check if True is in value range
0cd5cad
@ravinkohli
Reg cocktails common paper modifications 2 (automl#417)
7919802 
* remove remaining differences

* Reg cocktails common paper modifications 5 (automl#418)

* add hasttr

* fix run summary
@ravinkohli
have working embedding from pytroch
1ccb8a1
@ravinkohli
divide columns to encode and embed based on threshold
f448408
@ravinkohli
cleanup unwanted changes
7f32ada
@ravinkohli
use shape after preprocessing in base network backbone
3918d97
@ravinkohli
remove redundant call to load datamanager
3923ad9
@ravinkohli
add init file for column splitting
dd07bcc
@ravinkohli
fix tests
0b94b9d
@ravinkohli
fix precommit and add test changes
afff387
@ravinkohli @nabenabe0928
[ADD] Calculate memory of dataset after one hot encoding (pytorch emb…
b01e558 
…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 <[email protected]>

* remove unwanted additions

* Update autoPyTorch/pipeline/components/preprocessing/tabular_preprocessing/TabularColumnTransformer.py

Co-authored-by: nabenabe0928 <[email protected]>
@ravinkohli
suggestions from review
396ff54
@ravinkohli
add preprocessed_dtype to determine double or float
d6bb8c8
@ravinkohli
test fix in progress
d4717fb
@ravinkohli
TODO: fix errors after rebase
d58dd9d
@ravinkohli
Reg cocktails apt1.0+reg cocktails pytorch embedding reduced (automl…
8e15eec 
…#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
@ravinkohli
fix embeddings after rebase
49d49c2
@ravinkohli
fix error with pytorch embeddings
1f6351e
@ravinkohli
fix redundant code
0cfc3dc
@ravinkohli
change userdefined to False
8547229
@ravinkohli ravinkohli added the enhancement New feature or request label Aug 19, 2022
@dengdifan dengdifan force-pushed the reg_cocktails-pytorch_embedding-forecasting branch from 7e19d15 to 5f9713a Compare August 22, 2022 16:07
@ravinkohli ravinkohli force-pushed the reg_cocktails-pytorch_embedding branch from cbd4d7e to 1be80d5 Compare October 25, 2022 15:44
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@dengdifan @ravinkohli