Update .pre-commit-config.yaml (#11009)
* Update .pre-commit-config.yaml Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Update __init__.py Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Update .pre-commit-config.yaml Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Pre-commit updates * Pre-commit updates --------- Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
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@@ -100,7 +100,7 @@ def run(
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pred, targets, loss, dt = [], [], 0, (Profile(), Profile(), Profile())
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n = len(dataloader) # number of batches
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action = 'validating' if dataloader.dataset.root.stem == 'val' else 'testing'
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desc = f"{pbar.desc[:-36]}{action:>36}" if pbar else f"{action}"
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desc = f'{pbar.desc[:-36]}{action:>36}' if pbar else f'{action}'
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bar = tqdm(dataloader, desc, n, not training, bar_format=TQDM_BAR_FORMAT, position=0)
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with torch.cuda.amp.autocast(enabled=device.type != 'cpu'):
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for images, labels in bar:
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@@ -123,14 +123,14 @@ def run(
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top1, top5 = acc.mean(0).tolist()
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if pbar:
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pbar.desc = f"{pbar.desc[:-36]}{loss:>12.3g}{top1:>12.3g}{top5:>12.3g}"
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pbar.desc = f'{pbar.desc[:-36]}{loss:>12.3g}{top1:>12.3g}{top5:>12.3g}'
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if verbose: # all classes
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LOGGER.info(f"{'Class':>24}{'Images':>12}{'top1_acc':>12}{'top5_acc':>12}")
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LOGGER.info(f"{'all':>24}{targets.shape[0]:>12}{top1:>12.3g}{top5:>12.3g}")
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for i, c in model.names.items():
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acc_i = acc[targets == i]
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top1i, top5i = acc_i.mean(0).tolist()
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LOGGER.info(f"{c:>24}{acc_i.shape[0]:>12}{top1i:>12.3g}{top5i:>12.3g}")
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LOGGER.info(f'{c:>24}{acc_i.shape[0]:>12}{top1i:>12.3g}{top5i:>12.3g}')
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# Print results
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t = tuple(x.t / len(dataloader.dataset.samples) * 1E3 for x in dt) # speeds per image
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@@ -165,6 +165,6 @@ def main(opt):
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run(**vars(opt))
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if __name__ == "__main__":
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if __name__ == '__main__':
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opt = parse_opt()
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main(opt)
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