chore: import upstream snapshot with attribution

doc/source/data/doc_code/key_concepts.py

@@ -0,0 +1,27 @@
+# flake8: noqa
+
+# fmt: off
+# __resource_allocation_1_begin__
+import ray
+from ray import tune
+
+# This workload will use spare cluster resources for execution.
+def objective(*args):
+    ray.data.range(10).show()
+
+# Create a cluster with 4 CPU slots available.
+ray.init(num_cpus=4)
+
+# By setting `max_concurrent_trials=3`, this ensures the cluster will always
+# have a sparse CPU for Dataset. Try setting `max_concurrent_trials=4` here,
+# and notice that the experiment will appear to hang.
+tuner = tune.Tuner(
+    tune.with_resources(objective, {"cpu": 1}),
+    tune_config=tune.TuneConfig(
+        num_samples=1,
+        max_concurrent_trials=3
+    )
+)
+tuner.fit()
+# __resource_allocation_1_end__
+# fmt: on