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Add engine for unified entrypoints in downstream projects#695

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ZwwWayne wants to merge 9 commits intoopen-mmlab:masterfrom
ZwwWayne:add-engine
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Add engine for unified entrypoints in downstream projects#695
ZwwWayne wants to merge 9 commits intoopen-mmlab:masterfrom
ZwwWayne:add-engine

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@ZwwWayne
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@ZwwWayne ZwwWayne commented Dec 6, 2020

This PR adds a directory named engine in MMCV, which implements and unifies common functions for starting a training/testing process in downstream codebases. With mmcv.engine, downstream codebases like MMAction or MMClassification could directly use these functions and share a similar entry point script for training or testing a model.

This PR does not affect its dependencies' functionality, but its dependencies could update and unify their training/testing scripts after this PR is merged.

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codecov bot commented Dec 6, 2020

Codecov Report

Merging #695 (cd92f81) into master (4f0f1f9) will decrease coverage by 0.32%.
The diff coverage is 59.63%.

Impacted file tree graph

@@            Coverage Diff             @@
##           master     #695      +/-   ##
==========================================
- Coverage   64.85%   64.53%   -0.33%     
==========================================
  Files         136      139       +3     
  Lines        7989     8165     +176     
  Branches     1411     1440      +29     
==========================================
+ Hits         5181     5269      +88     
- Misses       2539     2618      +79     
- Partials      269      278       +9     
Flag Coverage Δ
unittests 64.53% <59.63%> (-0.33%) ⬇️

Flags with carried forward coverage won't be shown. Click here to find out more.

Impacted Files Coverage Δ
mmcv/engine/test.py 15.78% <15.78%> (ø)
mmcv/engine/utils.py 71.08% <71.08%> (ø)
mmcv/engine/__init__.py 100.00% <100.00%> (ø)
mmcv/runner/base_runner.py 69.01% <100.00%> (ø)
mmcv/utils/config.py 90.51% <100.00%> (+0.39%) ⬆️

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xvjiarui commented Dec 7, 2020

train.py is an empty file.

time.sleep(2) # This line can prevent deadlock problem in some cases.
for i, data in enumerate(data_loader):
with torch.no_grad():
result = model(return_loss=False, rescale=True, **data)
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This may not be applicable to all downstream codebases.

results.extend(result)

if rank == 0:
batch_size = len(result)
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Is this true for all codebases?

return results


def collect_results_cpu(result_part, size, tmpdir=None):
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Add a docstring.

return ordered_results


def collect_results_gpu(result_part, size):
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Add a docstring.



def parse_int_float_bool(val):
"""Parse string value to be integer, float, or boolean value.
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Add detailed description on:

  1. the priority
  2. some examples


def setup_cfg(args, cfg_args):
"""Set up config.

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Add a detailed description.

@ZwwWayne
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As there is a new plan. The proposal of a unified entrypoint has been deprecated and this PR is closed.

@ZwwWayne ZwwWayne closed this Apr 15, 2021
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3 participants