mirror of
https://github.com/open-mmlab/mmcv.git
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d5f190d12d
* Add MLflowLoggerHook * Add MLflowLoggerHook to __all__ * Update name * Fix tracking.MlflowClient setup * Fix log_metric * Fix mlflow_pytorch import * Handle active_run * Fix self.mlflow reference * Simplify using high level API * Fix set_experiment * Add only_if_torch_available decorator and test_mlflow_hook * Add missing import in hooks * Fix torch available check * Patch mlflow.pytorch in test * Parametrize log_model * Fix log_model parametrize * Add docstring * Move wand patch * Fix flake8 * Add regression test for non numeric metric * Only log numbers * Rename experiment_name-> exp_name * Remove pytest skip
31 lines
809 B
Python
31 lines
809 B
Python
# Copyright (c) Open-MMLab. All rights reserved.
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import os.path as osp
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import tempfile
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import warnings
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def test_save_checkpoint():
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try:
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import torch
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from torch import nn
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except ImportError:
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warnings.warn('Skipping test_save_checkpoint in the absense of torch')
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return
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import mmcv.runner
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model = nn.Linear(1, 1)
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runner = mmcv.runner.Runner(model=model, batch_processor=lambda x: x)
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with tempfile.TemporaryDirectory() as root:
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runner.save_checkpoint(root)
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latest_path = osp.join(root, 'latest.pth')
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epoch1_path = osp.join(root, 'epoch_1.pth')
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assert osp.exists(latest_path)
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assert osp.exists(epoch1_path)
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assert osp.realpath(latest_path) == osp.realpath(epoch1_path)
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torch.load(latest_path)
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