80 lines
2.3 KiB
TOML
80 lines
2.3 KiB
TOML
[build-system]
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requires = [
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"setuptools",
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"wheel",
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]
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[tool.isort]
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known_first_party = [
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"pl_examples",
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"pytorch_lightning",
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"tests_pytorch",
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]
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profile = "black"
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line_length = 120
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force_sort_within_sections = "False"
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order_by_type = "False"
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skip = ["_notebooks"]
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[tool.black]
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line-length = 120
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exclude = '(_notebooks/.*)'
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[tool.mypy]
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files = [
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"src/pytorch_lightning",
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# TODO: Check typing in app source
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# "src/lightning_app",
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]
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install_types = "True"
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non_interactive = "True"
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disallow_untyped_defs = "True"
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ignore_missing_imports = "True"
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show_error_codes = "True"
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warn_redundant_casts = "True"
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warn_unused_configs = "True"
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warn_unused_ignores = "True"
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allow_redefinition = "True"
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# disable this rule as the Trainer attributes are defined in the connectors, not in its __init__
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disable_error_code = "attr-defined"
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# style choices
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warn_no_return = "False"
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# Ignore mypy errors for these files
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# TODO: the goal is for this to be empty
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[[tool.mypy.overrides]]
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# the list can be generated with:
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# mypy --no-error-summary 2>&1 | tr ':' ' ' | awk '{print $1}' | sort | uniq | sed 's/\.py//g; s|src/||g; s|\/|\.|g' | xargs -I {} echo '"{}",'
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module = [
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"pytorch_lightning.callbacks.progress.rich_progress",
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"pytorch_lightning.callbacks.quantization",
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"pytorch_lightning.core.datamodule",
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"pytorch_lightning.core.decorators",
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"pytorch_lightning.core.module",
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"pytorch_lightning.core.saving",
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"pytorch_lightning.demos.boring_classes",
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"pytorch_lightning.demos.mnist_datamodule",
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"pytorch_lightning.loggers.neptune",
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"pytorch_lightning.profilers.base",
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"pytorch_lightning.profilers.pytorch",
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"pytorch_lightning.profilers.simple",
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"pytorch_lightning.strategies.ddp",
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"pytorch_lightning.strategies.fully_sharded",
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"pytorch_lightning.strategies.ipu",
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"pytorch_lightning.strategies.sharded",
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"pytorch_lightning.strategies.sharded_spawn",
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"pytorch_lightning.trainer.callback_hook",
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"pytorch_lightning.trainer.connectors.callback_connector",
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"pytorch_lightning.trainer.connectors.data_connector",
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"pytorch_lightning.trainer.supporters",
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"pytorch_lightning.trainer.trainer",
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"pytorch_lightning.tuner.batch_size_scaling",
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"pytorch_lightning.utilities.auto_restart",
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"pytorch_lightning.utilities.data",
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"pytorch_lightning.utilities.meta",
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]
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ignore_errors = "True"
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