Use list instead of array (#1050)

* Use list instead of array

Numpy does not seam to support anymore non homogeneous arrays (for
shapes at least). We don't need an array, so we should rather use lists.

* Update tests/unittests/algo/test_tpe.py
* Update tox.ini
* Add namespace_packages to setup.py
* Add orion.algo.space as package
* Change pylint include pattern to include all of orion and exclude ignored paths
* Pylint
* Fix docs
* Turn orion.algo.base into a module
* Move orion.algo.parallel_strategy to orion.algo.base
* Move algo to their own modules
* Add algos packages
* Fix missing quotes
* Add missing imports
* Remove colors
* Limit numpy version pending dependencies update
* Update MANIFEST.in
* Include orion logo file
* Fix too-many-lines and f-string
* Fix Fidelity repr
* Fix doc8
* Fix config code block

Co-authored-by: Setepenre <[email protected]>
Co-authored-by: Fabrice Normandin <[email protected]>
Co-authored-by: Pierre Delaunay <[email protected]>

.github/workflows/build.yml

@@ -102,7 +102,7 @@ jobs:
           python -m pip install --upgrade pip
           pip install tox tox-gh-actions
     - name: Test with tox (and all extra dependencies)
-      run: tox -e py-all
+      run: tox -e py-all -- --color=no
     - name: Upload coverage to Codecov
       uses: codecov/codecov-action@v1
       with:
@@ -135,7 +135,7 @@ jobs:
           pip install tox tox-gh-actions
 
     - name: Test long algorithms with tox
-      run: tox -e algo -- tests/unittests/algo/long/${{ matrix.algo }}
+      run: tox -e algo -- tests/unittests/algo/long/${{ matrix.algo }} --color=no
 
     - name: Upload coverage to Codecov
       uses: codecov/codecov-action@v1
@@ -160,7 +160,7 @@ jobs:
           python -m pip install --upgrade pip
           pip install tox tox-gh-actions
     - name: Test with tox
-      run: tox -e py
+      run: tox -e py -- --color=no
     - name: Upload coverage to Codecov
       uses: codecov/codecov-action@v1
       with:
@@ -199,7 +199,7 @@ jobs:
           python -m pip install --upgrade pip
           pip install tox tox-gh-actions
       - name: Test with tox
-        run: tox -e mongodb
+        run: tox -e mongodb -- --color=no
       - name: Upload coverage to Codecov
         uses: codecov/codecov-action@v1
         with:
@@ -244,7 +244,7 @@ jobs:
           python -m pip install --upgrade pip
           pip install tox tox-gh-actions
     - name: Test with tox
-      run: tox -e backward-compatibility
+      run: tox -e backward-compatibility -- --color=no
     - name: Upload coverage to Codecov
       uses: codecov/codecov-action@v1
       with:

.pylintrc

@@ -235,7 +235,7 @@ docstring-min-length=-1
 function-rgx=^(([a-z][a-z0-9_]{2,30})|(_[a-z0-9_]*))$
 
 # Good variable names which should always be accepted, separated by a comma
-good-names=i,j,k,v,ex,Run,_,f,e
+good-names=i,j,k,v,ex,Run,_,f,e,X,y,a,b,rv
 
 # Include a hint for the correct naming format with invalid-name
 include-naming-hint=no

MANIFEST.in

@@ -32,6 +32,7 @@ recursive-include dashboard/build *
 include tests/requirements.txt
 include .pre-commit-config.yaml
 include CITATION.bib
+include docs/src/_static/logos/orion_logo.ai
 
 # Include examples
 recursive-include examples *.md *.py *.pkl *.yaml *.ipynb */requirements.txt

docs/src/conf.py

@@ -263,11 +263,11 @@
 extlinks = {
     "scipy.stats": (
         "https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.%s.html",
-        "scipy.stats",
+        "scipy.stats %s",
     ),
     "plotly": (
         "https://plotly.com/python-api-reference/generated/plotly.%s",
-        "plotly.",
+        "plotly %s",
     ),
 }
 

docs/src/user/config.rst

@@ -86,11 +86,12 @@ Full Example of Global Configuration
 ------------------------------------
 
 .. code-block:: yaml
+
     storage:
       database:
         host: orion_db.pkl
         type: pickleddb
-    
+
     experiment:
         algorithms:
             random:

setup.py

@@ -11,11 +11,27 @@
 with open("tests/requirements.txt") as f:
     tests_require = f.readlines()
 
-packages = [  # Packages must be sorted alphabetically to ease maintenance and merges.
-    "orion.algo",
-    "orion.algo.mofa",
+
+# Builtin algo plugins that are built-in
+algos = [
+    "orion.algo.asha",
+    "orion.algo.axoptimizer",
+    "orion.algo.bohb",
     "orion.algo.dehb",
+    "orion.algo.evolution_es",
+    "orion.algo.gridsearch",
+    "orion.algo.hebo",
+    "orion.algo.hyperband",
+    "orion.algo.mofa",
+    "orion.algo.nevergradoptimizer",
     "orion.algo.pbt",
+    "orion.algo.random",
+    "orion.algo.tpe",
+]
+
+packages = [  # Packages must be sorted alphabetically to ease maintenance and merges.
+    "orion.algo.base",
+    "orion.algo.space",
     "orion.analysis",
     "orion.benchmark",
     "orion.client",
@@ -85,7 +101,11 @@
     author="Epistímio",
     author_email="[email protected]",
     url="https://github.com/epistimio/orion",
-    packages=packages,
+    packages=packages + algos,
+    namespace_packages=[
+        "orion",
+        "orion.algo",
+    ],
     package_dir={"": "src"},
     data_files=dashboard_files,
     include_package_data=True,
@@ -128,7 +148,8 @@
         "cloudpickle",
         "PyYAML",
         "pymongo>=3",
-        "numpy>=1.17",
+        # Issue #1061 Pending update of hebo
+        "numpy>=1.17,<1.24",
         "scipy",
         "gitpython",
         "filelock",

src/orion/algo/asha/__init__.py

@@ -0,0 +1,9 @@
+"""ASHA hyperparameter"""
+
+from .asha import ASHA, ASHABracket, compute_budgets
+
+__all__ = [
+    "ASHA",
+    "ASHABracket",
+    "compute_budgets",
+]

src/orion/algo/asha.py → src/orion/algo/asha/asha.py

@@ -9,7 +9,6 @@
 from collections import defaultdict
 from typing import Sequence
 
-import numpy
 import numpy as np
 
 from orion.algo.hyperband import (
@@ -61,9 +60,9 @@ def compute_budgets(
         )
         num_brackets = num_rungs
 
-    budgets = numpy.logspace(
-        numpy.log(min_resources) / numpy.log(reduction_factor),
-        numpy.log(max_resources) / numpy.log(reduction_factor),
+    budgets = np.logspace(
+        np.log(min_resources) / np.log(reduction_factor),
+        np.log(max_resources) / np.log(reduction_factor),
         num_rungs,
         base=reduction_factor,
     )
@@ -122,7 +121,7 @@ class ASHA(Hyperband):
         resource required for optimisation but decreases the bias towards stragglers.
         Default: 1
     repetitions: int
-        Number of execution of ASHA. Default is numpy.inf which means to
+        Number of execution of ASHA. Default is np.inf which means to
         run ASHA until no new trials can be suggested.
 
     """
@@ -133,7 +132,7 @@ def __init__(
         seed: int | Sequence[int] | None = None,
         num_rungs: int | None = None,
         num_brackets: int = 1,
-        repetitions: int | float = numpy.inf,
+        repetitions: int | float = np.inf,
     ):
         super().__init__(space, seed=seed, repetitions=repetitions)
 
@@ -147,8 +146,8 @@ def __init__(
 
         if num_rungs is None:
             num_rungs = int(
-                numpy.log(self.max_resources / self.min_resources)
-                / numpy.log(self.reduction_factor)
+                np.log(self.max_resources / self.min_resources)
+                / np.log(self.reduction_factor)
                 + 1
             )
 
@@ -166,16 +165,18 @@ def __init__(
 
         self.seed_rng(seed)
 
+    # pylint: disable=missing-function-docstring
     def compute_bracket_idx(self, num: int) -> np.ndarray:
+        # pylint: disable=invalid-name
         def assign_resources(
             n: int, remainings: np.ndarray, totals: np.ndarray
         ) -> np.ndarray:
             if n == 0 or remainings.sum() == 0:
                 return remainings
 
             ratios = remainings / totals
-            fractions = numpy.nan_to_num(ratios / ratios.sum(), nan=0)
-            index = numpy.argmax(fractions)
+            fractions = np.nan_to_num(ratios / ratios.sum(), nan=0)
+            index = np.argmax(fractions)
             remainings[index] -= 1
             n -= 1
             if n > 0:
@@ -184,10 +185,10 @@ def assign_resources(
             return remainings
 
         assert self.brackets is not None
-        remainings = numpy.asarray(
+        remainings = np.asarray(
             [bracket.remainings for bracket in self.brackets], dtype=np.int64
         )
-        totals = numpy.asarray(
+        totals = np.asarray(
             [bracket.rungs[0]["n_trials"] for bracket in self.brackets], dtype=np.int64
         )
         remainings_after = copy.deepcopy(remainings)

src/orion/algo/axoptimizer/__init__.py

@@ -0,0 +1,8 @@
+"""AxOptimizer hyperparameter"""
+
+from .axoptimizer import AxOptimizer, import_optional
+
+__all__ = [
+    "AxOptimizer",
+    "import_optional",
+]

src/orion/algo/axoptimizer.py → src/orion/algo/axoptimizer/axoptimizer.py

@@ -18,6 +18,7 @@
     from ax.service.utils.instantiation import ObjectiveProperties
 
 if import_optional.failed:
+    # pylint: disable=invalid-name
     AxClient = None  # noqa: F811
     ObjectiveProperties = None  # noqa: F811
 

src/orion/algo/base/__init__.py

@@ -0,0 +1,6 @@
+"""Base module to create new algorithm a instantiate them"""
+
+from .base import BaseAlgorithm, algo_factory
+from .registry import Registry
+
+__all__ = ["BaseAlgorithm", "algo_factory", "Registry"]

src/orion/algo/base.py → src/orion/algo/base/base.py

@@ -20,7 +20,7 @@
 from abc import abstractmethod
 from typing import Any
 
-from orion.algo.registry import Registry
+from orion.algo.base.registry import Registry
 from orion.algo.space import Space
 from orion.core.utils import GenericFactory
 from orion.core.worker.trial import Trial
@@ -55,9 +55,9 @@ class BaseAlgorithm:
     must declare an algorithm's own parameters (tunable elements which could be set by
     configuration). This is done by passing them to `BaseAlgorithm.__init__()` by calling Python's
     super with a `Space` object as a positional argument plus algorithm's own parameters as keyword
-    arguments. The keys of the keyword arguments passed to `BaseAlgorithm.__init__()` are interpreted
-    as the algorithm's parameter names. So for example, a subclass could be as simple as this
-    (regarding the logistics, not an actual algorithm's implementation):
+    arguments. The keys of the keyword arguments passed to `BaseAlgorithm.__init__()` are
+    interpreted as the algorithm's parameter names. So for example, a subclass could be as simple
+    as this (regarding the logistics, not an actual algorithm's implementation):
 
     Examples
     --------
@@ -292,6 +292,7 @@ def is_done(self) -> bool:
         """
         return self.has_completed_max_trials or self.has_suggested_all_possible_values()
 
+    # pylint: disable=invalid-name
     def has_suggested_all_possible_values(self) -> bool:
         """Returns True if the algorithm has more trials in its registry than the number of possible
         values in the search space.
@@ -336,7 +337,7 @@ def _is_completed(trial: Trial) -> bool:
 
         return sum(map(_is_completed, self.registry)) >= self.max_trials
 
-    # pylint:disable=no-self-use,unused-argument
+    # pylint: disable=unused-argument
     def score(self, trial: Trial) -> float:
         """Allow algorithm to evaluate `trial` based on a prediction about
         this parameter set's performance.
@@ -355,7 +356,7 @@ def score(self, trial: Trial) -> float:
         """
         return 0
 
-    # pylint:disable=no-self-use,unused-argument
+    # pylint: disable=unused-argument
     def judge(self, trial: Trial, measurements: Any) -> dict | None:
         """Inform an algorithm about online `measurements` of a running trial.
 
@@ -400,7 +401,7 @@ def configuration(self) -> dict[str, Any]:
         By default, returns a dictionary containing the attributes of `self` which are also
         constructor arguments.
         """
-        dict_form = dict()
+        dict_form = {}
         for attrname in self._param_names:
             if attrname.startswith("_"):  # Do not log _space or others in conf
                 continue
@@ -415,6 +416,7 @@ def space(self) -> Space:
 
     @property
     def unwrapped(self):
+        """Return the algorithm without transforms"""
         return self