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64 lines
2.0 KiB
Python
64 lines
2.0 KiB
Python
import os
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import zipfile
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import pandas as pd
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import pytest
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import wget
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from ludwig.api import LudwigModel
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from ludwig.data.dataset_synthesizer import build_synthetic_dataset_df
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from ludwig.globals import MODEL_FILE_NAME
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NUM_EXAMPLES = 25
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def test_model_loaded_from_old_config_prediction_works(tmpdir):
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# Titanic model based on 0.5.3.
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old_model_url = "https://predibase-public-us-west-2.s3.us-west-2.amazonaws.com/ludwig_unit_tests/old_model.zip"
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old_model_filename = wget.download(old_model_url, tmpdir)
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with zipfile.ZipFile(old_model_filename, "r") as zip_ref:
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zip_ref.extractall(tmpdir)
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example_data = {
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"PassengerId": 892,
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"Pclass": 3,
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"Name": "Kelly, Mr. James",
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"Sex": "male",
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"Age": 34.5,
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"SibSp": 0,
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"Parch": 0,
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"Ticket": "330911",
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"Fare": 7.8292,
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"Cabin": None,
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"Embarked": "Q",
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}
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test_set = pd.DataFrame(example_data, index=[0])
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ludwig_model = LudwigModel.load(os.path.join(tmpdir, "old_model/model"))
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predictions, _ = ludwig_model.predict(dataset=test_set)
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assert predictions.to_dict()["Survived_predictions"] == {0: False}
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@pytest.mark.parametrize(
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"model_url",
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[
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"https://predibase-public-us-west-2.s3.us-west-2.amazonaws.com/ludwig_unit_tests/titanic_v07.zip",
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"https://predibase-public-us-west-2.s3.us-west-2.amazonaws.com/ludwig_unit_tests/twitter_bots_v05_1.zip",
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"https://predibase-public-us-west-2.s3.us-west-2.amazonaws.com/ludwig_unit_tests/respiratory_v05.zip",
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],
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ids=["titanic", "twitter_bots", "respiratory"],
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)
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def test_predict_deprecated_model(model_url, tmpdir):
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model_dir = os.path.join(tmpdir, MODEL_FILE_NAME)
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os.makedirs(model_dir)
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archive_path = wget.download(model_url, tmpdir)
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with zipfile.ZipFile(archive_path, "r") as zip_ref:
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zip_ref.extractall(model_dir)
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ludwig_model = LudwigModel.load(model_dir)
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df = build_synthetic_dataset_df(NUM_EXAMPLES, ludwig_model.config)
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pred_df, _ = ludwig_model.predict(df)
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assert len(pred_df) == 25
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