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Merge branch 'microsoft:main' into main
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commit
f3a0438c86
@ -4,7 +4,10 @@ import requests
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from utils import get_toy_data_summarization, get_automl_settings
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@pytest.mark.skipif(sys.platform == "darwin", reason="do not run on mac os")
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@pytest.mark.skipif(
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sys.platform == "darwin" or sys.version < "3.7",
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reason="do not run on mac os or py < 3.7",
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)
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def test_summarization():
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# TODO: manual test for how effective postprocess_seq2seq_prediction_label is
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from flaml import AutoML
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@ -63,7 +63,6 @@ def test_starting_point_not_in_search_space():
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}
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}
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automl_settings["starting_points"] = "data:test/nlp/default/"
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del automl_settings["fit_kwargs_by_estimator"][this_estimator_name]["model_path"]
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automl.fit(X_train, y_train, **automl_settings)
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assert len(automl._search_states[this_estimator_name].init_config) == len(
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@ -90,10 +89,13 @@ def test_points_to_evaluate():
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automl = AutoML()
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automl_settings = get_automl_settings(estimator_name="transformer_ms")
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automl_settings["estimator_list"] = ["transformer_ms"]
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automl_settings["starting_points"] = "data"
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automl_settings["starting_points"] = "data:test/nlp/default/"
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del automl_settings["fit_kwargs_by_estimator"]["transformer_ms"]["model_path"]
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automl_settings["custom_hp"] = {
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"transformer_ms": {
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"model_path": {"domain": "google/electra-small-discriminator"}
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}
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}
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automl.fit(X_train, y_train, **automl_settings)
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@ -109,8 +111,6 @@ def test_zero_shot_nomodel():
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automl_settings = get_automl_settings(estimator_name)
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del automl_settings["fit_kwargs_by_estimator"][estimator_name]["model_path"]
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(
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hyperparams,
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estimator_class,
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@ -146,10 +146,6 @@ def test_build_error_portfolio(path="./test/nlp/default", strategy="greedy"):
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location = "test/nlp/default"
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X_train, y_train, X_val, y_val, X_test = get_toy_data_seqclassification()
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automl_settings = get_automl_settings(estimator_name)
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del automl_settings["fit_kwargs_by_estimator"][estimator_name]["model_path"]
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try:
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(
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hyperparams,
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@ -1514,14 +1514,23 @@ def get_automl_settings(estimator_name="transformer"):
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"use_ray": False,
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}
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automl_settings["fit_kwargs_by_estimator"] = {
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estimator_name: {
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"model_path": "google/electra-small-discriminator",
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"output_dir": "test/data/output/",
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"ckpt_per_epoch": 1,
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"fp16": False,
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if estimator_name.endswith("ms"):
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automl_settings["fit_kwargs_by_estimator"] = {
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estimator_name: {
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"output_dir": "test/data/output/",
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"ckpt_per_epoch": 1,
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"fp16": False,
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}
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}
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else:
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automl_settings["fit_kwargs_by_estimator"] = {
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estimator_name: {
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"model_path": "google/electra-small-discriminator",
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"output_dir": "test/data/output/",
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"ckpt_per_epoch": 1,
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"fp16": False,
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}
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}
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}
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automl_settings["estimator_list"] = [estimator_name]
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return automl_settings
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