[FIX] Docker publish error

[ravinkohli]

Types of changes

• [x] Bug fix (non-breaking change which fixes an issue)

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:

• [x] My code follows the code style of this project.
• [ ] My change requires a change to the documentation.
• [ ] I have updated the documentation accordingly.

• [x] 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

Motivation and Context

How has this been tested?

[codecov[bot]]

Codecov Report

Merging #364 (b3544bf) into development (0e574af) will decrease coverage by 0.03%. The diff coverage is n/a.

@@               Coverage Diff               @@
##           development     #364      +/-   ##
===============================================
- Coverage        85.50%   85.46%   -0.04%     
===============================================
  Files              231      231              
  Lines            16303    16303              
  Branches          3009     3009              
===============================================
- Hits             13940    13934       -6     
- Misses            1524     1529       +5     
- Partials           839      840       +1     

Impacted Files	Coverage Δ
...re_preprocessing/SelectPercentileClassification.py	89.47% <0.00%> (-5.27%)	:arrow_down:
...nts/setup/network_backbone/ConvNetImageBackbone.py	96.15% <0.00%> (-3.85%)	:arrow_down:
...ecasting_encoder/seq_encoder/TransformerEncoder.py	93.61% <0.00%> (-2.13%)	:arrow_down:
...ipeline/components/setup/network_backbone/utils.py	87.31% <0.00%> (-1.50%)	:arrow_down:
autoPyTorch/datasets/base_dataset.py	80.28% <0.00%> (ø)
...one/forecasting_encoder/flat_encoder/MLPEncoder.py	94.02% <0.00%> (+2.98%)	:arrow_up:

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