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* rm classification head in nlp * rm classification head in nlp * rm classification head in nlp * adding test cases for switch classification head * adding test cases for switch classification head * Update test/nlp/test_autohf_classificationhead.py Co-authored-by: Chi Wang <wang.chi@microsoft.com> * adding test cases for switch classification head * run each test separately * skip classification head test on windows * disabling wandb reporting * fix test nlp custom metric * fix test nlp custom metric * fix test nlp custom metric * fix test nlp custom metric * fix test nlp custom metric * fix test nlp custom metric * fix test nlp custom metric * fix test nlp custom metric * fix test nlp custom metric * fix test nlp custom metric * fix test nlp custom metric * Update website/docs/Examples/AutoML-NLP.md Co-authored-by: Chi Wang <wang.chi@microsoft.com> * Update website/docs/Examples/AutoML-NLP.md Co-authored-by: Chi Wang <wang.chi@microsoft.com> * fix test nlp custom metric Co-authored-by: Chi Wang <wang.chi@microsoft.com>
57 lines
1.3 KiB
Python
57 lines
1.3 KiB
Python
import sys
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import pytest
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from utils import get_toy_data_multiplechoiceclassification, get_automl_settings
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import os
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import shutil
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@pytest.mark.skipif(sys.platform == "darwin", reason="do not run on mac os")
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def test_mcc():
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from flaml import AutoML
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import requests
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(
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X_train,
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y_train,
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X_val,
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y_val,
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X_test,
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y_test,
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) = get_toy_data_multiplechoiceclassification()
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automl = AutoML()
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automl_settings = get_automl_settings()
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automl_settings["task"] = "multichoice-classification"
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automl_settings["metric"] = "accuracy"
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try:
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automl.fit(
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X_train=X_train,
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y_train=y_train,
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X_val=X_val,
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y_val=y_val,
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**automl_settings
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)
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except requests.exceptions.HTTPError:
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return
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y_pred = automl.predict(X_test)
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proba = automl.predict_proba(X_test)
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print(str(len(automl.classes_)) + " classes")
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print(y_pred)
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print(y_test)
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print(proba)
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true_count = 0
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for i, v in y_test.items():
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if y_pred[i] == v:
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true_count += 1
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accuracy = round(true_count / len(y_pred), 5)
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print("Accuracy: " + str(accuracy))
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if os.path.exists("test/data/output/"):
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shutil.rmtree("test/data/output/")
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if __name__ == "__main__":
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test_mcc()
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