Merge pull request #134 from st-tech/update-version

Update version to 0.5.0

Author: usaito

benchmark/ope/README.md

@@ -53,8 +53,8 @@ numpy = "^1.21.1"
 matplotlib = "^3.4.2"
 hydra-core = "^1.1.0"
 pingouin = "^0.4.0"
-obp = "^0.4.2"
 pyieoe = "^0.1.0"
+obp = "^0.5.0"
 ```
 
 ## Files

benchmark/ope/poetry.lock

@@ -1,7 +1,7 @@
 [tool.poetry]
 name = "benchmark/ope"
 version = "0.1.0"
-description = ""
+description = "benchmarking OPE estimators on Open Bandit Dataset"
 authors = ["usaito <[email protected]>"]
 
 [tool.poetry.dependencies]
@@ -12,8 +12,8 @@ numpy = "^1.21.1"
 matplotlib = "^3.4.2"
 hydra-core = "^1.1.0"
 pingouin = "^0.4.0"
-obp = "^0.4.2"
 pyieoe = "^0.1.0"
+obp = "^0.5.0"
 
 [tool.poetry.dev-dependencies]
 flake8 = "^3.9.2"

benchmark/ope/pyproject.toml

@@ -62,7 +62,7 @@
      "output_type": "stream",
      "name": "stdout",
      "text": [
-      "0.4.1\n"
+      "0.5.0\n"
      ]
     }
    ],
@@ -261,8 +261,8 @@
      "output_type": "stream",
      "name": "stderr",
      "text": [
-      "q-func learning: 100%|██████████| 200/200 [00:17<00:00, 11.26it/s]\n",
-      "policy learning: 100%|██████████| 200/200 [00:44<00:00,  4.50it/s]\n"
+      "q-func learning: 100%|██████████| 200/200 [00:16<00:00, 11.99it/s]\n",
+      "policy learning: 100%|██████████| 200/200 [00:40<00:00,  4.93it/s]\n"
      ]
     }
    ],
@@ -299,7 +299,7 @@
      "output_type": "stream",
      "name": "stderr",
      "text": [
-      "policy learning: 100%|██████████| 200/200 [00:43<00:00,  4.56it/s]\n"
+      "policy learning: 100%|██████████| 200/200 [00:36<00:00,  5.50it/s]\n"
      ]
     }
    ],
@@ -336,8 +336,8 @@
      "output_type": "stream",
      "name": "stderr",
      "text": [
-      "q-func learning: 100%|██████████| 200/200 [00:19<00:00, 10.32it/s]\n",
-      "policy learning: 100%|██████████| 200/200 [01:03<00:00,  3.14it/s]\n"
+      "q-func learning: 100%|██████████| 200/200 [00:15<00:00, 12.70it/s]\n",
+      "policy learning: 100%|██████████| 200/200 [00:51<00:00,  3.85it/s]\n"
      ]
     }
    ],
@@ -498,9 +498,9 @@
      "output_type": "stream",
      "name": "stdout",
      "text": [
-      "policy value of NN Policy Learner with DM: 0.7404435523322302\n",
-      "policy value of NN Policy Learner with IPW: 0.7212317939160037\n",
-      "policy value of NN Policy Learner with DR: 0.7236077796319849\n",
+      "policy value of NN Policy Learner with DM: 0.7401610285643739\n",
+      "policy value of NN Policy Learner with IPW: 0.7219954182377301\n",
+      "policy value of NN Policy Learner with DR: 0.7239531174451277\n",
       "policy value of IPW Learner with Logistic Regression: 0.7225216225722526\n",
       "policy value of IPW Learner with Random Forest: 0.6826465969408197\n",
       "policy value of Unifrom Random: 0.6056038101021686\n"
@@ -538,7 +538,7 @@
  "metadata": {
   "kernelspec": {
    "name": "python3",
-   "display_name": "Python 3.9.5 64-bit ('zr-obp': pyenv)"
+   "display_name": "Python 3.9.5 64-bit ('3.9.5': pyenv)"
   },
   "language_info": {
    "codemirror_mode": {
@@ -553,7 +553,7 @@
    "version": "3.9.5"
   },
   "interpreter": {
-   "hash": "64b446a4e17784c2dc3dbe74bf0708929a003fb4822b30671d57ebdef413b716"
+   "hash": "2ff39f3b22306140fd87fd114528320b56c4f8c8e196b421a3ea939a2b6b4692"
   }
  },
  "nbformat": 4,

examples/quickstart/multiclass.ipynb

@@ -1 +1 @@
-__version__ = "0.4.1"
+__version__ = "0.5.0"