ludwig-ai--ludwig
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62 行
1.9 KiB
Python
62 行
1.9 KiB
Python
import argparse
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import logging
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import tempfile
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from ludwig.api import LudwigModel
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from ludwig.api_annotations import DeveloperAPI
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from ludwig.constants import INPUT_FEATURES, OUTPUT_FEATURES, TRAINER
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from ludwig.data.dataset_synthesizer import build_synthetic_dataset_df
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from ludwig.globals import LUDWIG_VERSION
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from ludwig.utils.print_utils import get_logging_level_registry, print_boxed, print_ludwig
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NUM_EXAMPLES = 100
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@DeveloperAPI
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def check_install(logging_level: int = logging.INFO, **kwargs):
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config = {
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INPUT_FEATURES: [
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{"name": "in1", "type": "text"},
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{"name": "in2", "type": "category"},
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{"name": "in3", "type": "number"},
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],
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OUTPUT_FEATURES: [{"name": "out1", "type": "binary"}],
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TRAINER: {"epochs": 2, "batch_size": 8},
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}
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try:
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df = build_synthetic_dataset_df(NUM_EXAMPLES, config)
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model = LudwigModel(config, logging_level=logging_level)
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with tempfile.TemporaryDirectory() as tmpdir:
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model.train(dataset=df, output_directory=tmpdir)
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except Exception:
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print_boxed("CHECK INSTALL COMPLETE... FAILURE")
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raise
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print_boxed("CHECK INSTALL COMPLETE... SUCCESS")
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@DeveloperAPI
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def cli(sys_argv):
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parser = argparse.ArgumentParser(
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description="This command checks Ludwig installation on a synthetic dataset.",
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prog="ludwig check_install",
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usage="%(prog)s [options]",
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)
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parser.add_argument(
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"-l",
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"--logging_level",
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default="warning",
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help="the level of logging to use",
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choices=["critical", "error", "warning", "info", "debug", "notset"],
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)
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args = parser.parse_args(sys_argv)
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args.logging_level = get_logging_level_registry()[args.logging_level]
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logging.getLogger("ludwig").setLevel(args.logging_level)
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print_ludwig("Check Install", LUDWIG_VERSION)
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check_install(**vars(args))
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