[tune] add back NevergradSearch (ray-project#42305)

Signed-off-by: Matthew Deng <matt@anyscale.com> Signed-off-by: tterrysun <terry@anyscale.com>
tterrysun · Feb 14, 2024 · 33b8dec · 33b8dec
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diff --git a/doc/source/conf.py b/doc/source/conf.py
@@ -476,6 +476,7 @@ def setup(app):
     "joblib",
     "lightgbm",
     "lightgbm_ray",
+    "nevergrad",
     "numpy",
     "pandas",
     "pyarrow",
@@ -540,6 +541,7 @@ def add_line(self, line: str, source: str, *lineno: int) -> None:
     "lightgbm": ("https://lightgbm.readthedocs.io/en/latest/", None),
     "mars": ("https://mars-project.readthedocs.io/en/latest/", None),
     "modin": ("https://modin.readthedocs.io/en/stable/", None),
+    "nevergrad": ("https://facebookresearch.github.io/nevergrad/", None),
     "numpy": ("https://numpy.org/doc/stable/", None),
     "pandas": ("https://pandas.pydata.org/pandas-docs/stable/", None),
     "pyarrow": ("https://arrow.apache.org/docs", None),

diff --git a/doc/source/ray-overview/examples.rst b/doc/source/ray-overview/examples.rst
@@ -336,6 +336,13 @@ Ray Examples
 
         How To Use Tune With TuneBOHB
 
+    .. grid-item-card:: :bdg-secondary:`Code example`
+        :class-item: gallery-item tuning
+        :link: /tune/examples/nevergrad_example
+        :link-type: doc
+
+        How To Use Tune With Nevergrad
+
     .. grid-item-card:: :bdg-secondary:`Code example`
         :class-item: gallery-item tuning
         :link: /tune/examples/optuna_example

diff --git a/doc/source/tune/api/suggestion.rst b/doc/source/tune/api/suggestion.rst
@@ -184,6 +184,17 @@ HyperOpt (tune.search.hyperopt.HyperOptSearch)
 
     hyperopt.HyperOptSearch
 
+.. _nevergrad:
+
+Nevergrad (tune.search.nevergrad.NevergradSearch)
+-------------------------------------------------
+
+.. autosummary::
+    :nosignatures:
+    :toctree: doc/
+
+    nevergrad.NevergradSearch
+
 .. _tune-optuna:
 
 Optuna (tune.search.optuna.OptunaSearch)

diff --git a/doc/source/tune/examples/hpo-frameworks.rst b/doc/source/tune/examples/hpo-frameworks.rst
@@ -8,6 +8,7 @@ Tune Hyperparameter Optimization Framework Examples
     HyperOpt Example <hyperopt_example>
     Bayesopt Example <bayesopt_example>
     BOHB Example <bohb_example>
+    Nevergrad Example <nevergrad_example>
     Optuna Example <optuna_example>
 
 
@@ -51,6 +52,14 @@ on each of our integrations:
 
             How To Use Tune With TuneBOHB
 
+    .. grid-item-card::
+        :img-top: ../images/nevergrad.png
+        :class-img-top: pt-2 w-75 d-block mx-auto fixed-height-img
+
+        .. button-ref:: nevergrad_example
+
+            How To Use Tune With Nevergrad
+
     .. grid-item-card::
         :img-top: ../images/optuna.png
         :class-img-top: pt-2 w-75 d-block mx-auto fixed-height-img

diff --git a/doc/source/tune/examples/includes/nevergrad_example.rst b/doc/source/tune/examples/includes/nevergrad_example.rst
@@ -0,0 +1,6 @@
+:orphan:
+
+Nevergrad Example
+~~~~~~~~~~~~~~~~~
+
+.. literalinclude:: /../../python/ray/tune/examples/nevergrad_example.py
diff --git a/doc/source/tune/examples/nevergrad_example.ipynb b/doc/source/tune/examples/nevergrad_example.ipynb
diff --git a/doc/source/tune/index.rst b/doc/source/tune/index.rst
@@ -19,7 +19,7 @@ Ray Tune: Hyperparameter Tuning
 
 Tune is a Python library for experiment execution and hyperparameter tuning at any scale.
 You can tune your favorite machine learning framework (:ref:`PyTorch <tune-pytorch-cifar-ref>`, :ref:`XGBoost <tune-xgboost-ref>`, :doc:`TensorFlow and Keras <examples/tune_mnist_keras>`, and :doc:`more <examples/index>`) by running state of the art algorithms such as :ref:`Population Based Training (PBT) <tune-scheduler-pbt>` and :ref:`HyperBand/ASHA <tune-scheduler-hyperband>`.
-Tune further integrates with a wide range of additional hyperparameter optimization tools, including :doc:`Ax <examples/ax_example>`, :doc:`BayesOpt <examples/bayesopt_example>`, :doc:`BOHB <examples/bohb_example>`, and :doc:`Optuna <examples/optuna_example>`.
+Tune further integrates with a wide range of additional hyperparameter optimization tools, including :doc:`Ax <examples/ax_example>`, :doc:`BayesOpt <examples/bayesopt_example>`, :doc:`BOHB <examples/bohb_example>`, :doc:`Nevergrad <examples/nevergrad_example>`, and :doc:`Optuna <examples/optuna_example>`.
 
 **Click on the following tabs to see code examples for various machine learning frameworks**:
 

diff --git a/doc/source/tune/key-concepts.rst b/doc/source/tune/key-concepts.rst
@@ -216,6 +216,10 @@ Here's an overview of all available search algorithms in Tune:
      - Bayesian Opt/HyperBand
      - [`BOHB <https://github.com/automl/HpBandSter>`__]
      - :doc:`/tune/examples/includes/bohb_example`
+   * - :ref:`NevergradSearch <nevergrad>`
+     - Gradient-free Optimization
+     - [`Nevergrad <https://github.com/facebookresearch/nevergrad>`__]
+     - :doc:`/tune/examples/includes/nevergrad_example`
    * - :ref:`OptunaSearch <tune-optuna>`
      - Optuna search algorithms
      - [`Optuna <https://optuna.org/>`__]

diff --git a/docker/examples/Dockerfile b/docker/examples/Dockerfile
@@ -18,6 +18,7 @@ RUN pip install --no-cache-dir -U pip \
     bayesian-optimization \
     hyperopt \
     ConfigSpace==0.4.10 \
+    nevergrad \
     scikit-optimize \
     hpbandster \
     lightgbm \

diff --git a/python/ray/air/_internal/usage.py b/python/ray/air/_internal/usage.py
@@ -32,6 +32,7 @@
     "TuneBOHB",
     "HEBOSearch",
     "HyperOptSearch",
+    "NevergradSearch",
     "OptunaSearch",
     "SkOptSearch",
     "ZOOptSearch",

diff --git a/python/ray/tune/BUILD b/python/ray/tune/BUILD
@@ -632,6 +632,15 @@ py_test(
     args = ["--smoke-test"]
 )
 
+py_test(
+    name = "nevergrad_example",
+    size = "small",
+    srcs = ["examples/nevergrad_example.py"],
+    deps = [":tune_lib"],
+    tags = ["team:ml", "exclusive", "example"],
+    args = ["--smoke-test"]
+)
+
 py_test(
     name = "optuna_define_by_run_example",
     size = "small",

diff --git a/python/ray/tune/examples/README.rst b/python/ray/tune/examples/README.rst
@@ -23,6 +23,7 @@ Search Algorithm Examples
 -------------------------
 
 - `Ax example <https://github.com/ray-project/ray/blob/master/python/ray/tune/examples/ax_example.py>`__: Optimize a Hartmann function with `Ax <https://ax.dev>`_ with 4 parallel workers.
+- `Nevergrad example <https://github.com/ray-project/ray/blob/master/python/ray/tune/examples/nevergrad_example.py>`__: Optimize a simple toy function with the gradient-free optimization package `Nevergrad <https://github.com/facebookresearch/nevergrad>`_ with 4 parallel workers.
 - `Bayesian Optimization example <https://github.com/ray-project/ray/blob/master/python/ray/tune/examples/bayesopt_example.py>`__: Optimize a simple toy function using `Bayesian Optimization <https://github.com/fmfn/BayesianOptimization>`_ with 4 parallel workers.
 
 Tensorflow/Keras Examples

diff --git a/python/ray/tune/examples/nevergrad_example.py b/python/ray/tune/examples/nevergrad_example.py
@@ -0,0 +1,75 @@
+"""This example demonstrates the usage of Nevergrad with Ray Tune.
+
+It also checks that it is usable with a separate scheduler.
+
+Requires the Nevergrad library to be installed (`pip install nevergrad`).
+"""
+import time
+
+from ray import train, tune
+from ray.tune.search import ConcurrencyLimiter
+from ray.tune.schedulers import AsyncHyperBandScheduler
+from ray.tune.search.nevergrad import NevergradSearch
+
+
+def evaluation_fn(step, width, height):
+    return (0.1 + width * step / 100) ** (-1) + height * 0.1
+
+
+def easy_objective(config):
+    # Hyperparameters
+    width, height = config["width"], config["height"]
+
+    for step in range(config["steps"]):
+        # Iterative training function - can be any arbitrary training procedure
+        intermediate_score = evaluation_fn(step, width, height)
+        # Feed the score back back to Tune.
+        train.report({"iterations": step, "mean_loss": intermediate_score})
+        time.sleep(0.1)
+
+
+if __name__ == "__main__":
+    import argparse
+    import nevergrad as ng
+
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        "--smoke-test", action="store_true", help="Finish quickly for testing"
+    )
+    args, _ = parser.parse_known_args()
+
+    # Optional: Pass the parameter space yourself
+    # space = ng.p.Dict(
+    #     width=ng.p.Scalar(lower=0, upper=20),
+    #     height=ng.p.Scalar(lower=-100, upper=100),
+    #     activation=ng.p.Choice(choices=["relu", "tanh"])
+    # )
+
+    algo = NevergradSearch(
+        optimizer=ng.optimizers.OnePlusOne,
+        # space=space,  # If you want to set the space manually
+    )
+    algo = ConcurrencyLimiter(algo, max_concurrent=4)
+
+    scheduler = AsyncHyperBandScheduler()
+
+    tuner = tune.Tuner(
+        easy_objective,
+        tune_config=tune.TuneConfig(
+            metric="mean_loss",
+            mode="min",
+            search_alg=algo,
+            scheduler=scheduler,
+            num_samples=10 if args.smoke_test else 50,
+        ),
+        run_config=train.RunConfig(name="nevergrad"),
+        param_space={
+            "steps": 100,
+            "width": tune.uniform(0, 20),
+            "height": tune.uniform(-100, 100),
+            "activation": tune.choice(["relu", "tanh"]),
+        },
+    )
+    results = tuner.fit()
+
+    print("Best hyperparameters found were: ", results.get_best_result().config)
diff --git a/python/ray/tune/search/__init__.py b/python/ray/tune/search/__init__.py
@@ -45,6 +45,12 @@ def _import_bohb_search():
     return TuneBOHB
 
 
+def _import_nevergrad_search():
+    from ray.tune.search.nevergrad.nevergrad_search import NevergradSearch
+
+    return NevergradSearch
+
+
 def _import_optuna_search():
     from ray.tune.search.optuna.optuna_search import OptunaSearch
 
@@ -71,6 +77,7 @@ def _import_hebo_search():
     "hyperopt": _import_hyperopt_search,
     "bayesopt": _import_bayesopt_search,
     "bohb": _import_bohb_search,
+    "nevergrad": _import_nevergrad_search,
     "optuna": _import_optuna_search,
     "zoopt": _import_zoopt_search,
     "hebo": _import_hebo_search,

diff --git a/python/ray/tune/search/nevergrad/__init__.py b/python/ray/tune/search/nevergrad/__init__.py
@@ -0,0 +1,3 @@
+from ray.tune.search.nevergrad.nevergrad_search import NevergradSearch
+
+__all__ = ["NevergradSearch"]