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Motivation

1. The resuming of seed is too late

   For example, before the seed resuming, the dataloader and other parts have been constructed. In this situation, the sampler of dataloader uses the old seed, leading to inconsistent for resuming (especially for the iter-based training)

2. IterBasedTrainLoop is not correct for resume

   The beginning data index is 0, instead of self._iter

Modification

Load the resumed checkpoint in the __init__ of runner, and resume the seed. This modification may seem foolish, but in my option, it is the most compatible way, especially for FlexibleRunner.

BC-breaking (Optional)

Does the modification introduce changes that break the backward-compatibility of the downstream repos?
If so, please describe how it breaks the compatibility and how the downstream projects should modify their code to keep compatibility with this PR.

Use cases (Optional)

If this PR introduces a new feature, it is better to list some use cases here, and update the documentation.

Checklist

1. Pre-commit or other linting tools are used to fix the potential lint issues.
2. The modification is covered by complete unit tests. If not, please add more unit test to ensure the correctness.
3. If the modification has potential influence on downstream projects, this PR should be tested with downstream projects, like MMDetection or MMPretrain.
4. The documentation has been modified accordingly, like docstring or example tutorials.