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Releases: shenweichen/DeepCTR-Torch

v0.2.9

21 Oct 13:28
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Major Features and Improvements

  1. Add multi-task models: SharedBottom, ESMM, MMOE, PLE @zanshuxun
  2. Support Python 3.9 and 3.10 @shenweichen

Bug Fixes and Other Changes

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v0.2.8

19 Jun 11:13
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v0.2.7

14 Jun 03:52
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Major Features and Improvements

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v0.2.6

04 Apr 08:48
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Major Features and Improvements

v0.2.5

12 Feb 12:38
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Bug Fixes and Other Changes

  • fix error in dcn-mix

v0.2.4

05 Dec 15:49
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Major Features and Improvements

Bug Fixes and Other Changes

  • Solve issues in #69, #87, #93, #128, #130
  • Fix regularization error in pytorch1.7,
  • improve compatibility for old version

API changes

  • Add History in deepctr_torch.callbacks

v0.2.3

18 Oct 04:51
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Major Features and Improvements

Bug Fixes and Other Changes

  • Use float64 in metric to prevent nan/inf loss when calculating logloss

API changes

  • DCN add a new parameter:
    cross_parameterization: string, "vector" or "matrix", way to parameterize the cross network.if set to "matrix" then it will be DCN-M
  • Add EarlyStopping and ModelCheckpoint in deepctr_torch.callbacks

v0.2.2

09 Oct 09:03
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Major Features and Improvements

  • Improve the reproducibility of models

Bug Fixes and Other Changes

Fix RuntimeError: one of the variables needed for gradient computation has been modified by an inplace operation: [torch.cuda.FloatTensor [128]], which is output 0 of SelectBackward, is at version 2; expected version 1 instead. Hint: enable anomaly detection to find the operation that failed to compute its gradient, with torch.autograd.set_detect_anomaly(True) in :
#88
#98
#90
#102

v0.2.1

27 Mar 15:09
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Major Features and Improvements

Add DIN and DIEN

Bug Fixes and Other Changes

  • fix bug of #63 softmax dim error in InteractingLayer

v0.2.0

31 Jan 12:38
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Major Features and Improvements

  • Refactor feature columns.

  • Different features can use different embedding_dim

  • Add linear part to some models

  • Add SequencePoolingLayer(API)

Bug Fixes and Other Changes

  • Support double precision in metric calculation by setting use_double=True in model.fit() #15

API changes

  • embedding_size parameter of models is removed.Now we must set embedding_dim(default 4) in SparseFeat or VarLenSparseFeat .