[logging] Add centralized logging - Bump-up cache loads to warnings #538
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lhoestq
approved these changes
Aug 31, 2020
| @@ -1 +1 @@ | |||
| {"write_array2d": 0.07093274600629229, "read_unformated after write_array2d": 0.03530075500020757, "read_formatted_as_numpy after write_array2d": 0.10929270699853078, "read_batch_unformated after write_array2d": 0.03727920600795187, "read_batch_formatted_as_numpy after write_array2d": 0.018853643006877974, "read_col_unformated after write_array2d": 0.05644163000397384, "read_col_formatted_as_numpy after write_array2d": 0.011610292000113986, "write_nested_sequence": 1.6535991109994939, "read_unformated after write_nested_sequence": 0.3739209540071897, "read_formatted_as_numpy after write_nested_sequence": 0.40762836500653066, "read_batch_unformated after write_nested_sequence": 0.3337586460111197, "read_batch_formatted_as_numpy after write_nested_sequence": 0.054717567007173784, "read_col_unformated after write_nested_sequence": 0.3173944180016406, "read_col_formatted_as_numpy after write_nested_sequence": 0.004956340009812266, "write_flattened_sequence": 1.4975415869994322, "read_unformated after write_flattened_sequence": 0.26713552299770527, "read_formatted_as_numpy after write_flattened_sequence": 0.07673935199272819, "read_batch_unformated after write_flattened_sequence": 0.25450974798877724, "read_batch_formatted_as_numpy after write_flattened_sequence": 0.009374254994327202, "read_col_unformated after write_flattened_sequence": 0.25912448299641255, "read_col_formatted_as_numpy after write_flattened_sequence": 0.004277604995877482} | |||
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are these files supposed to be part of the PR ?
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we don't care that much I guess but let me remove them indeed
src/nlp/arrow_dataset.py
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| if os.path.exists(indices_cache_file_name) and load_from_cache_file: | ||
| if verbose: | ||
| logger.info("Loading cached shuffled indices for dataset at %s", indices_cache_file_name) | ||
| logger.warn("Loading cached shuffled indices for dataset at %s", indices_cache_file_name) |
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use logger.warning instead ? iirc warn is deprecated
src/nlp/arrow_dataset.py
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| train_indices_cache_file_name, | ||
| test_indices_cache_file_name, | ||
| ) | ||
| logger.warn( |
src/nlp/arrow_dataset.py
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| if os.path.exists(indices_cache_file_name) and load_from_cache_file: | ||
| if verbose: | ||
| logger.info("Loading cached sorted indices for dataset at %s", indices_cache_file_name) | ||
| logger.warn("Loading cached sorted indices for dataset at %s", indices_cache_file_name) |
src/nlp/arrow_dataset.py
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| if os.path.exists(cache_file_name) and load_from_cache_file: | ||
| if verbose: | ||
| logger.info("Loading cached processed dataset at %s", cache_file_name) | ||
| logger.warn("Loading cached processed dataset at %s", cache_file_name) |
src/nlp/utils/logging.py
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| def enable_propagation() -> None: | ||
| """Enable propagation of the library log outputs. | ||
| Please disable the HuggingFace Transformers's default handler to prevent double logging if the root logger has |
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what would be the issue with transformers exactly ?
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Add a
nlp.loggingmodule to set the global logging level easily. The verbosity level also controls the tqdm bars (disabled when set higher than INFO).You can use:
And use the levels: