fix: Fix HPO Grid Search comparison and name (#3927)

Author: morelen17

src/sagemaker/tuner.py

@@ -71,7 +71,7 @@
 HYPERBAND_STRATEGY_CONFIG = "HyperbandStrategyConfig"
 HYPERBAND_MIN_RESOURCE = "MinResource"
 HYPERBAND_MAX_RESOURCE = "MaxResource"
-GRID_SEARCH = "GridSearch"
+GRID_SEARCH = "Grid"
 MAX_NUMBER_OF_TRAINING_JOBS_NOT_IMPROVING = "MaxNumberOfTrainingJobsNotImproving"
 BEST_OBJECTIVE_NOT_IMPROVING = "BestObjectiveNotImproving"
 CONVERGENCE_DETECTED = "ConvergenceDetected"
@@ -645,7 +645,7 @@ def __init__(
                 evaluating training jobs. This value can be either 'Minimize' or
                 'Maximize' (default: 'Maximize').
             max_jobs (int or PipelineVariable): Maximum total number of training jobs to start for
-                the hyperparameter tuning job. The default value is unspecified fot the GridSearch
+                the hyperparameter tuning job. The default value is unspecified fot the 'Grid'
                 strategy and the default value is 1 for all others strategies (default: None).
             max_parallel_jobs (int or PipelineVariable): Maximum number of parallel training jobs to
                 start (default: 1).
@@ -741,7 +741,7 @@ def __init__(
         # For all other strategies for the backward compatibility we keep
         # the default value as 1 (previous default value).
         self.max_jobs = max_jobs
-        if max_jobs is None and strategy is not GRID_SEARCH:
+        if max_jobs is None and strategy != GRID_SEARCH:
             self.max_jobs = 1
         self.max_parallel_jobs = max_parallel_jobs
         self.max_runtime_in_seconds = max_runtime_in_seconds
@@ -1917,7 +1917,7 @@ def create(
             objective_type (str): The type of the objective metric for evaluating training jobs.
                 This value can be either 'Minimize' or 'Maximize' (default: 'Maximize').
             max_jobs (int): Maximum total number of training jobs to start for the hyperparameter
-                tuning job. The default value is unspecified fot the GridSearch strategy
+                tuning job. The default value is unspecified fot the 'Grid' strategy
                 and the value is 1 for all others strategies (default: None).
             max_parallel_jobs (int): Maximum number of parallel training jobs to start
                 (default: 1).

tests/unit/test_tuner.py

@@ -2171,7 +2171,7 @@ def test_create_tuner_with_grid_search_strategy():
         objective_metric_name_dict={ESTIMATOR_NAME: OBJECTIVE_METRIC_NAME},
         hyperparameter_ranges_dict={ESTIMATOR_NAME: HYPERPARAMETER_RANGES},
         metric_definitions_dict={ESTIMATOR_NAME: METRIC_DEFINITIONS},
-        strategy="GridSearch",
+        strategy="Grid",
         objective_type="Minimize",
         max_parallel_jobs=1,
         tags=TAGS,