Add GradientEmitter to support OMG-MEGA and OG-MAP-Elites

HISTORY.md

@@ -1,5 +1,13 @@
 # History
 
+## (Forthcoming)
+
+### Changelog
+
+#### API
+
+- Add GradientOperatorEmitter to support OMG-MEGA and OG-MAP-Elites ({pr}`348`)
+
 ## 0.6.0
 
 ### Changelog

examples/sphere.py

@@ -35,6 +35,9 @@
 - `cma_me_mixed`: GridArchive with EvolutionStrategyEmitter, where half (7) of
   the emitter are using TwoStageRandomDirectionRanker and half (8) are
   TwoStageImprovementRanker.
+- `og_map_elites`: GridArchive with GradientOperatorEmitter, does not use
+  measure gradients.
+- `omg_mega`: GridArchive with GradientOperatorEmitter, uses measure gradients.
 - `cma_mega`: GridArchive with GradientArborescenceEmitter.
 - `cma_mega_adam`: GridArchive with GradientArborescenceEmitter using Adam
   Optimizer.
@@ -83,7 +86,8 @@
 
 from ribs.archives import CVTArchive, GridArchive
 from ribs.emitters import (EvolutionStrategyEmitter, GaussianEmitter,
-                           GradientArborescenceEmitter, IsoLineEmitter)
+                           GradientArborescenceEmitter, GradientOperatorEmitter,
+                           IsoLineEmitter)
 from ribs.schedulers import BanditScheduler, Scheduler
 from ribs.visualize import cvt_archive_heatmap, grid_archive_heatmap
 
@@ -417,6 +421,66 @@
             "kwargs": {}
         }
     },
+    "og_map_elites": {
+        "dim": 1_000,
+        "iters": 10_000,
+        "archive_dims": (100, 100),
+        "use_result_archive": False,
+        "is_dqd": True,
+        # Divide by 2 since half of the 36 solutions are used in ask_dqd(), and
+        # the other half are used in ask().
+        "batch_size": 36 // 2,
+        "archive": {
+            "class": GridArchive,
+            "kwargs": {
+                "threshold_min": -np.inf
+            }
+        },
+        "emitters": [{
+            "class": GradientOperatorEmitter,
+            "kwargs": {
+                "sigma": 0.5,
+                "sigma_g": 0.5,
+                "measure_gradients": False,
+                "normalize_grad": False,
+            },
+            "num_emitters": 1
+        }],
+        "scheduler": {
+            "class": Scheduler,
+            "kwargs": {}
+        }
+    },
+    "omg_mega": {
+        "dim": 1_000,
+        "iters": 10_000,
+        "archive_dims": (100, 100),
+        "use_result_archive": False,
+        "is_dqd": True,
+        # Divide by 2 since half of the 36 solutions are used in ask_dqd(), and
+        # the other half are used in ask().
+        "batch_size": 36 // 2,
+        "archive": {
+            "class": GridArchive,
+            "kwargs": {
+                "threshold_min": -np.inf
+            }
+        },
+        "emitters": [{
+            "class": GradientOperatorEmitter,
+            "kwargs": {
+                "sigma": 0.0,
+                "sigma_g": 10.0,
+                "measure_gradients": True,
+                "normalize_grad": True,
+            },
+            "num_emitters": 1
+        }],
+        "scheduler": {
+            "class": Scheduler,
+            "kwargs": {}
+        }
+    },
     "cma_mega": {
         "dim": 1_000,
         "iters": 10_000,
@@ -790,8 +854,8 @@ def sphere_main(algorithm,
 
     # Plot metrics.
     print(f"Algorithm Time (Excludes Logging and Setup): {non_logging_time}s")
-    for metric in metrics:
-        plt.plot(metrics[metric]["x"], metrics[metric]["y"])
+    for metric, values in metrics.items():
+        plt.plot(values["x"], values["y"])
         plt.title(metric)
         plt.xlabel("Iteration")
         plt.savefig(

ribs/emitters/__init__.py

@@ -16,8 +16,9 @@
     :toctree:
 
     ribs.emitters.EvolutionStrategyEmitter
-    ribs.emitters.GradientArborescenceEmitter
     ribs.emitters.GaussianEmitter
+    ribs.emitters.GradientArborescenceEmitter
+    ribs.emitters.GradientOperatorEmitter
     ribs.emitters.IsoLineEmitter
     ribs.emitters.EmitterBase
 """
@@ -26,12 +27,14 @@
 from ribs.emitters._gaussian_emitter import GaussianEmitter
 from ribs.emitters._gradient_arborescence_emitter import \
     GradientArborescenceEmitter
+from ribs.emitters._gradient_operator_emitter import GradientOperatorEmitter
 from ribs.emitters._iso_line_emitter import IsoLineEmitter
 
 __all__ = [
     "EvolutionStrategyEmitter",
-    "GradientArborescenceEmitter",
     "GaussianEmitter",
+    "GradientArborescenceEmitter",
+    "GradientOperatorEmitter",
     "IsoLineEmitter",
     "EmitterBase",
 ]

ribs/emitters/_gradient_arborescence_emitter.py

@@ -46,6 +46,11 @@ class GradientArborescenceEmitter(EmitterBase):
         calling :meth:`ask` and :meth:`tell` to communicate the gradient
         information to the emitter.
 
+    See Also:
+
+        Our DQD tutorial goes into detail on how to use this emitter:
+        :doc:`/tutorials/tom_cruise_dqd`
+
     Args:
         archive (ribs.archives.ArchiveBase): An archive to use when creating and
             inserting solutions. For instance, this can be