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awslabs · Sep 11, 2023 · 7b4a3c2 · 7b4a3c2
1 parent 57efa0e
commit 7b4a3c2
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Showing 2 changed files with 7 additions and 16 deletions.
diff --git a/docs/source/conf.py b/docs/source/conf.py
@@ -14,6 +14,7 @@
 import os
 import shutil
 import sys
+from pathlib import Path
 
 import syne_tune
 
@@ -23,17 +24,10 @@
 
 def copy_notebooks_into_docs_folder(app):
     # .ipynb files must be inside the docs/ folder for Jupyter to be able to convert them
-    currpath = os.path.dirname(os.path.realpath(__file__))
-    source = os.path.join(currpath, "../../examples/notebooks")
-    destination = os.path.join(currpath, "notebooks")
-    print(
-        f"current path: {currpath}; source path: {source}; destination path: {destination}"
-    )
-    try:
-        shutil.rmtree(destination)
-    except OSError as e:
-        print("Error: %s - %s." % (e.filename, e.strerror))
-    shutil.copytree(source, destination)
+    source = Path(__file__).parent.parent.parent / "examples" / "notebooks"
+    destination = Path(__file__).parent / "notebooks"
+    print(f"Jupyter notebook source path: {source}; destination path: {destination}")
+    shutil.copytree(source, destination, dirs_exist_ok=True)
 
 
 def run_apidoc(app):

diff --git a/examples/notebooks/tune_xgboost.ipynb b/examples/notebooks/tune_xgboost.ipynb
@@ -36,7 +36,7 @@
    "source": [
     "from syne_tune import Tuner, StoppingCriterion\n",
     "from syne_tune.backend import PythonBackend\n",
-    "from syne_tune.config_space import randint, uniform\n",
+    "from syne_tune.config_space import randint, uniform, loguniform\n",
     "from syne_tune.optimizer.baselines import BayesianOptimization\n",
     "from syne_tune.experiments import load_experiment"
    ]
@@ -72,8 +72,6 @@
     "    import xgboost\n",
     "    import numpy as np\n",
     "\n",
-    "    eval_metric = \"merror\"\n",
-    "\n",
     "    X, y = load_digits(return_X_y=True)\n",
     "\n",
     "    X_trainval, X_test, y_trainval, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
@@ -86,7 +84,6 @@
     "        reg_lambda=reg_lambda,\n",
     "        gamma=gamma,\n",
     "        max_depth=max_depth,\n",
-    "        eval_metric=eval_metric,\n",
     "    )\n",
     "    clf.fit(X_train, y_train, eval_set=[(X_val, y_val)])\n",
     "\n",
@@ -114,7 +111,7 @@
     "config_space = {\n",
     "    \"max_depth\": randint(1,10),\n",
     "    \"gamma\": uniform(1,10),\n",
-    "    \"reg_lambda\": uniform(.0000001, 1),\n",
+    "    \"reg_lambda\": loguniform(.0000001, 1),\n",
     "    \"n_estimators\": randint(5, 15)\n",
     "}\n",
     "\n",