From 313a5989a3e896592c0525aa0b289756046ff21d Mon Sep 17 00:00:00 2001 From: christopherbunn Date: Fri, 30 Jun 2023 13:42:59 -0400 Subject: [PATCH] Reduced processing time --- docs/source/start.ipynb | 17 +++++++++++++++- evalml/tests/automl_tests/test_automl.py | 20 +++++++++---------- .../test_automl_search_classification.py | 10 +++++----- evalml/tests/automl_tests/test_search.py | 2 +- 4 files changed, 32 insertions(+), 17 deletions(-) diff --git a/docs/source/start.ipynb b/docs/source/start.ipynb index c0627a0abd..72d6aeaa20 100644 --- a/docs/source/start.ipynb +++ b/docs/source/start.ipynb @@ -1,6 +1,7 @@ { "cells": [ { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -8,6 +9,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -26,6 +28,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -42,6 +45,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -77,6 +81,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -95,6 +100,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -102,6 +108,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -133,6 +140,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -151,6 +159,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -170,13 +179,14 @@ " y_train=y_train,\n", " problem_type=\"binary\",\n", " objective=\"f1\",\n", - " max_batches=3,\n", + " max_batches=2,\n", " verbose=False,\n", ")\n", "automl.search()" ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -184,6 +194,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -200,6 +211,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -216,6 +228,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -233,6 +246,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -250,6 +264,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ diff --git a/evalml/tests/automl_tests/test_automl.py b/evalml/tests/automl_tests/test_automl.py index 41c55b6446..ff2e495eb6 100644 --- a/evalml/tests/automl_tests/test_automl.py +++ b/evalml/tests/automl_tests/test_automl.py @@ -1861,7 +1861,7 @@ def test_pipelines_in_batch_return_none( X_train=X, y_train=y, problem_type="binary", - max_batches=3, + max_batches=2, automl_algorithm="iterative", allowed_component_graphs={"Name": [dummy_classifier_estimator_class]}, n_jobs=1, @@ -2299,7 +2299,7 @@ def test_time_series_regression_with_parameters(ts_data): allowed_component_graphs={"Name_0": ["Imputer", "Linear Regressor"]}, objective="auto", problem_configuration=problem_configuration, - max_batches=3, + max_batches=2, ) assert ( automl.automl_algorithm.search_parameters["pipeline"] == problem_configuration @@ -2344,7 +2344,7 @@ def test_automl_accepts_component_graphs(graph_type, X_y_binary): problem_type="binary", allowed_component_graphs={"Dummy_Name": component_graph}, objective="auto", - max_batches=3, + max_batches=2, ) for pipeline_ in automl.allowed_pipelines: assert isinstance(pipeline_, BinaryClassificationPipeline) @@ -4158,7 +4158,7 @@ def test_automl_drop_unknown_columns(columns, AutoMLTestEnv, X_y_binary, caplog) y_train=y, problem_type="binary", optimize_thresholds=False, - max_batches=3, + max_batches=2, verbose=True, ) env = AutoMLTestEnv("binary") @@ -4573,7 +4573,7 @@ def test_automl_passes_known_in_advance_pipeline_parameters_to_all_pipelines( X_train=X, y_train=y, problem_type=problem_type, - max_batches=3, + max_batches=2, problem_configuration={ "time_index": "date", "max_delay": 3, @@ -4624,7 +4624,7 @@ def test_cv_ranking_scores( X_train=X, y_train=y, problem_type="binary", - max_batches=3, + max_batches=2, data_splitter=data_splitter, allowed_component_graphs={"Name": [dummy_classifier_estimator_class]}, n_jobs=1, @@ -4818,7 +4818,7 @@ def test_automl_accepts_features( y_train=y, problem_type="binary", optimize_thresholds=False, - max_batches=3, + max_batches=2, features=features, automl_algorithm=automl_algorithm, ) @@ -4862,7 +4862,7 @@ def test_automl_with_empty_features_list( y_train=y, problem_type="binary", optimize_thresholds=False, - max_batches=3, + max_batches=2, features=[], automl_algorithm=automl_algorithm, ) @@ -5075,7 +5075,7 @@ def test_default_algorithm_uses_n_jobs(X_y_binary, AutoMLTestEnv): X_train=X, y_train=y, problem_type="binary", - max_batches=3, + max_batches=2, automl_algorithm="default", n_jobs=2, ) @@ -5525,7 +5525,7 @@ def test_holdout_set_results_and_rankings(caplog, AutoMLTestEnv): X_train=X, y_train=y, problem_type="binary", - max_batches=3, + max_batches=2, automl_algorithm="default", verbose=True, holdout_set_size=0.1, diff --git a/evalml/tests/automl_tests/test_automl_search_classification.py b/evalml/tests/automl_tests/test_automl_search_classification.py index 08048a6b8f..e55024dc46 100644 --- a/evalml/tests/automl_tests/test_automl_search_classification.py +++ b/evalml/tests/automl_tests/test_automl_search_classification.py @@ -1022,7 +1022,7 @@ def test_automl_search_dictionary_undersampler( optimize_thresholds=False, sampler_method="Undersampler", search_parameters=search_parameters, - max_batches=3, + max_batches=2, ) # check that the sampling dict got set properly automl.search() @@ -1077,7 +1077,7 @@ def test_automl_search_dictionary_oversampler( sampler_method="Oversampler", optimize_thresholds=False, search_parameters=search_parameters, - max_batches=3, + max_batches=2, ) # check that the sampling dict got set properly pipelines = automl.allowed_pipelines @@ -1122,7 +1122,7 @@ def test_automl_search_sampler_dictionary_keys( sampler_method=sampler, optimize_thresholds=False, search_parameters=search_parameters, - max_batches=3, + max_batches=2, ) if errors: with pytest.raises( @@ -1254,7 +1254,7 @@ def test_automl_passes_allow_long_running_models( objective="Log Loss Multiclass", allow_long_running_models=allow_long_running_models, automl_algorithm=algo, - max_batches=3, + max_batches=2, verbose=True, ) assert ( @@ -1280,7 +1280,7 @@ def test_automl_threshold_score(fraud_100): X_train, y_train, problem_type="binary", - max_batches=3, + max_batches=2, ensembling=True, verbose=False, automl_algorithm="default", diff --git a/evalml/tests/automl_tests/test_search.py b/evalml/tests/automl_tests/test_search.py index 779bd74228..15f8b0ce17 100644 --- a/evalml/tests/automl_tests/test_search.py +++ b/evalml/tests/automl_tests/test_search.py @@ -121,7 +121,7 @@ def test_search_args(mock_automl_search, mock_data_checks_validate, X_y_binary): assert automl.max_time == 42 assert automl.patience == 3 assert automl.tolerance == 0.5 - assert automl.max_batches == 4 + assert automl.max_batches == 3 assert isinstance(automl.automl_algorithm, DefaultAlgorithm) automl, _ = search(