Support recreating dataloaders during loop

[ananthsub]

Summary: Sometimes users need to recreate the dataloaders at the start of the epoch during the overall training loop. To support this, we allow users to register a creation function when creating the state for training or fitting. We pass the state as an argument since users may want to use progress information such as the progress counters to reinitialize the dataloader.

We don't add this support for evaluate or predict since those functions iterate through the corresponding dataloader just once.

For fit, this allows flexibility to reload training & evaluation dataloaders independently during if desired

Differential Revision: D40539580

[facebook-github-bot]

This pull request was exported from Phabricator. Differential Revision: D40539580

[codecov[bot]]

Codecov Report

Merging #248 (a636d89) into master (bc64893) will increase coverage by 0.11%. The diff coverage is 100.00%.

@@            Coverage Diff             @@
##           master     #248      +/-   ##
==========================================
+ Coverage   89.22%   89.34%   +0.11%     
==========================================
  Files          85       85              
  Lines        5272     5330      +58     
==========================================
+ Hits         4704     4762      +58     
  Misses        568      568              

Impacted Files	Coverage Δ
tests/runner/test_fit.py	96.98% <100.00%> (+0.36%)	:arrow_up:
tests/runner/test_train.py	100.00% <100.00%> (ø)
torchtnt/runner/evaluate.py	91.54% <100.00%> (+0.37%)	:arrow_up:
torchtnt/runner/fit.py	83.01% <100.00%> (+3.94%)	:arrow_up:
torchtnt/runner/state.py	98.93% <100.00%> (+0.04%)	:arrow_up:
torchtnt/runner/train.py	92.37% <100.00%> (+0.48%)	:arrow_up:

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[facebook-github-bot]

This pull request was exported from Phabricator. Differential Revision: D40539580

[facebook-github-bot]

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