Merge branch 'master' into yaml_config_space

.github/workflows/tests.yaml

@@ -21,7 +21,7 @@ jobs:
     runs-on: ${{ matrix.os }}
 
     steps:
-      - uses: actions/checkout@v3
+      - uses: actions/checkout@v4
 
       - uses: actions/setup-python@v4
         with:

pyproject.toml

@@ -27,6 +27,7 @@ classifiers = [
   "Intended Audience :: Developers",
   "Intended Audience :: Science/Research",
   "Natural Language :: English",
+  "License :: OSI Approved :: Apache Software License",
   "Operating System :: POSIX :: Linux",
   "Operating System :: Microsoft :: Windows",
   "Operating System :: MacOS",
@@ -46,40 +47,46 @@ packages = [
 
 [tool.poetry.dependencies]
 python = ">=3.8,<3.12"
-ConfigSpace = "^0.4.19"
-grakel = "^0.1.9"
-numpy = "^1.23.0"
-pandas = "^1.3.1"
+ConfigSpace = "^0.6"
+grakel = "^0.1"
+numpy = "^1"
+pandas = "^2"
 networkx = "^2.6.3"
 nltk = "^3.6.4"
-path = "^16.2.0"
-termcolor = "^1.1.0"
-scipy = "^1.8"
+#path = "^16.2.0"
+#termcolor = "^1.1.0"
+scipy = "^1"
 torch = ">=1.7.0,<=2.1, !=2.0.1, !=2.1.0"  # fix from: https://stackoverflow.com/a/76647180
 # torch = [
 #     {version = ">=1.7.0,<=2.1", markers = "sys_platform == 'darwin'"},  # Segfaults for macOS on github actions
 #     {version = ">=1.7.0,<=2.1", markers = "sys_platform != 'darwin'"},
 # ]
-matplotlib = "^3.4"
-statsmodels = "^0.13.2"
-more-itertools = "^9.0.0"
-portalocker = "^2.6.0"
-seaborn = "^0.12.1"
-pyyaml = "^6.0"
-tensorboard = "^2.13"
-cython = "^3.0.4"
-torchvision = "<0.16.0"
+matplotlib = "^3"
+# statsmodels = "^0.13.2"
+more-itertools = "^10"
+portalocker = "^2"
+seaborn = "^0.13"
+pyyaml = "^6"
+tensorboard = "^2"
+# cython = "^3.0.4"
 
 [tool.poetry.group.dev.dependencies]
-pre-commit = "^2.10"
-mypy = "^0.930"
-pytest = "^6.2.5"
-types-PyYAML = "^6.0.12"
-typing-extensions = "^4.0.1"
-types-termcolor = "^1.1.2"
+pre-commit = "^3"
+mypy = "^1"
+pytest = "^7"
+types-PyYAML = "^6"
+typing-extensions = "^4"
+#types-termcolor = "^1.1.2"
 # jahs-bench = {git = "https://github.com/automl/jahs_bench_201.git", rev = "v1.0.2"}
 mkdocs-material = "^8.1.3"
 mike = "^1.1.2"
+torchvision = "<0.16.0"  # Used in examples
+
+
+[tool.poetry.group.experimental]
+optional = true
+
+[tool.poetry.group.experimental.dependencies]
 gpytorch = "1.8.0"
 
 [build-system]

src/metahyper/utils.py

@@ -48,6 +48,21 @@ def get_data_representation(data: Any):
         return data
 
 
+class MissingDependencyError(Exception):
+    def __init__(self, dep: str, cause: Exception, *args: Any):
+        super().__init__(dep, cause, *args)
+        self.dep = dep
+        self.__cause__ = cause  # This is what `raise a from b` does
+
+    def __str__(self) -> str:
+        return (
+            f"Some required dependency-({self.dep}) to use this optional feature is "
+            f"missing. Please, include neps[experimental] dependency group in your "
+            f"installation of neps to be able to use all the optional features."
+            f" Otherwise, just install ({self.dep})"
+        )
+
+
 class YamlSerializer:
     SUFFIX = ".yaml"
     PRE_SERIALIZE = True
@@ -97,7 +112,7 @@ def instance_from_map(
     name: str = "mapping",
     allow_any: bool = True,
     as_class: bool = False,
-    kwargs: dict = None,
+    kwargs: dict | None = None,
 ):
     """Get an instance of an class from a mapping.
 
@@ -140,6 +155,9 @@ def instance_from_map(
     else:
         raise ValueError(f"Object {request} invalid key for {name}")
 
+    if isinstance(instance, MissingDependencyError):
+        raise instance
+
     # Check if the request is a class if it is mandatory
     if (args_dict or as_class) and not is_partial_class(instance):
         raise ValueError(

src/neps/api.py

@@ -6,7 +6,7 @@
 import logging
 import warnings
 from pathlib import Path
-from typing import Callable, Literal, List
+from typing import Callable, List, Literal
 
 import ConfigSpace as CS
 
@@ -297,7 +297,7 @@ def run(
         pre_load_hooks=pre_load_hooks,
     )
 
-    if post_run_csv:
+    if post_run_summary:
         post_run_csv(root_directory, logger)
 
 

src/neps/optimizers/bayesian_optimization/models/__init__.py

@@ -1,16 +1,21 @@
-from .deepGP import DeepGP
+from metahyper.utils import MissingDependencyError
+
 from .gp import ComprehensiveGP
 from .gp_hierarchy import ComprehensiveGPHierarchy
 
+try:
+    from .deepGP import DeepGP
+except ImportError as e:
+    DeepGP = MissingDependencyError("gpytorch", e)
+
+try:
+    from .pfn import PFN_SURROGATE  # only if available locally
+except Exception as e:
+    PFN_SURROGATE = MissingDependencyError("pfn", e)
 
 SurrogateModelMapping = {
     "deep_gp": DeepGP,
     "gp": ComprehensiveGP,
     "gp_hierarchy": ComprehensiveGPHierarchy,
+    "pfn": PFN_SURROGATE,
 }
-
-try:
-    from .pfn import PFN_SURROGATE  # only if available locally
-    SurrogateModelMapping.update({"pfn": PFN_SURROGATE})
-except:
-    pass

src/neps/plot/tensorboard_eval.py

@@ -306,7 +306,7 @@ def _write_image_config(
         if resize_images is None:
             resize_images = [32, 32]
 
-        if tblogger.current_epoch and tblogger.current_epoch % counter == 0:
+        if tblogger.current_epoch >= 0 and tblogger.current_epoch % counter == 0:
             # Log every multiple of "counter"
 
             if num_images > len(image):

src/neps/search_spaces/architecture/graph.py

@@ -12,7 +12,7 @@
 import networkx as nx
 import torch
 from networkx.algorithms.dag import lexicographical_topological_sort
-from path import Path
+from pathlib import Path
 from torch import nn
 
 from ...utils.common import AttrDict

src/neps/status/status.py

@@ -339,3 +339,6 @@ def post_run_csv(root_directory: str | Path, logger=None) -> None:
         df_config_data,
         df_run_data,
     )
+
+def get_run_summary_csv(root_directory: str | Path):
+    post_run_csv(root_directory=root_directory)