Add observation space to single item recommendation system tutorial

Summary: Add observation space to single item recommendation system tutorial Reviewed By: jb3618columbia Differential Revision: D56854463 fbshipit-source-id: 4eb24338f1b1cb881c20ceda6e39d6a944a74903
facebookresearch · May 1, 2024 · d1d4dad · d1d4dad
1 parent 33862b8
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Showing 3 changed files with 21 additions and 8 deletions.
diff --git a/pearl/api/environment.py b/pearl/api/environment.py
@@ -32,7 +32,6 @@ def action_space(self) -> ActionSpace:
         """Returns the action space of the environment."""
         pass
 
-    # FIXME: add this and in implement in all concrete subclasses
     @property
     @abstractmethod
     def observation_space(self) -> Space:

diff --git a/test/unit/test_tutorials/test_rec_system.py b/test/unit/test_tutorials/test_rec_system.py
@@ -19,6 +19,7 @@
 from pearl.api.action_space import ActionSpace
 from pearl.api.environment import Environment
 from pearl.api.observation import Observation
+from pearl.api.space import Space
 from pearl.history_summarization_modules.lstm_history_summarization_module import (
     LSTMHistorySummarizationModule,
 )
@@ -40,6 +41,7 @@
 )
 from pearl.utils.functional_utils.experimentation.set_seed import set_seed
 from pearl.utils.functional_utils.train_and_eval.online_learning import online_learning
+from pearl.utils.instantiations.spaces.box import BoxSpace
 from pearl.utils.instantiations.spaces.discrete_action import DiscreteActionSpace
 
 set_seed(0)
@@ -147,9 +149,14 @@ def __init__(
         self.state: torch.Tensor = torch.zeros((self.history_length, 100)).to(device)
         self._action_space: DiscreteActionSpace = DiscreteActionSpace(self.actions[0])
 
+    @property
     def action_space(self) -> ActionSpace:
         return DiscreteActionSpace(self.actions[0])
 
+    @property
+    def observation_space(self) -> Space:
+        return BoxSpace(low=torch.zeros((1,)), high=torch.ones((1,)))
+
     def reset(self, seed: Optional[int] = None) -> Tuple[Observation, ActionSpace]:
         self.state: torch.Tensor = torch.zeros((self.history_length, 100))
         self.t = 0

diff --git a/tutorials/single_item_recommender_system_example/single_item_recommender_system.ipynb b/tutorials/single_item_recommender_system_example/single_item_recommender_system.ipynb
@@ -36,7 +36,7 @@
       "metadata": {
         "id": "nFomZD4OjZLK"
       },
-      "execution_count": 2,
+      "execution_count": null,
       "outputs": []
     },
     {
@@ -66,7 +66,7 @@
         "id": "5i2jE98RjhK1",
         "outputId": "ad80e72d-51cb-4594-a97e-2f4cf5466667"
       },
-      "execution_count": 3,
+      "execution_count": null,
       "outputs": [
         {
           "output_type": "stream",
@@ -220,6 +220,7 @@
         "from pearl.api.action_space import ActionSpace\n",
         "from pearl.api.environment import Environment\n",
         "from pearl.api.observation import Observation\n",
+        "from pearl.api.space import Space\n",
         "from pearl.history_summarization_modules.lstm_history_summarization_module import (\n",
         "    LSTMHistorySummarizationModule,\n",
         ")\n",
@@ -241,6 +242,7 @@
         ")\n",
         "from pearl.utils.functional_utils.experimentation.set_seed import set_seed\n",
         "from pearl.utils.functional_utils.train_and_eval.online_learning import online_learning\n",
+        "from pearl.utils.instantiations.spaces.box import BoxSpace\n",
         "from pearl.utils.instantiations.spaces.discrete_action import DiscreteActionSpace\n",
         "import matplotlib.pyplot as plt\n",
         "\n",
@@ -249,7 +251,7 @@
       "metadata": {
         "id": "Lp6pRjTDjpDo"
       },
-      "execution_count": 4,
+      "execution_count": null,
       "outputs": []
     },
     {
@@ -345,9 +347,14 @@
         "        self.state: torch.Tensor = torch.zeros((self.history_length, 100)).to(device)\n",
         "        self._action_space: DiscreteActionSpace = DiscreteActionSpace(self.actions[0])\n",
         "\n",
+        "    @property\n",
         "    def action_space(self) -> ActionSpace:\n",
         "        return DiscreteActionSpace(self.actions[0])\n",
         "\n",
+        "    @property\n",
+        "    def observation_space(self) -> Space:\n",
+        "        return BoxSpace(low=torch.zeros((1,)), high=torch.ones((1,)))\n",
+        "\n",
         "    def reset(self, seed: Optional[int] = None) -> Tuple[Observation, ActionSpace]:\n",
         "        self.state: torch.Tensor = torch.zeros((self.history_length, 100))\n",
         "        self.t = 0\n",
@@ -402,7 +409,7 @@
         "id": "BYdPfGgZp8HN",
         "outputId": "6be7ab71-02d3-4d82-c66e-2ca60655efd1"
       },
-      "execution_count": 5,
+      "execution_count": null,
       "outputs": [
         {
           "output_type": "stream",
@@ -469,7 +476,7 @@
         "id": "GDnAlQQNqC7z",
         "outputId": "e55dc40f-f5ad-48ba-f5ac-e1efb3f63a1c"
       },
-      "execution_count": 6,
+      "execution_count": null,
       "outputs": [
         {
           "output_type": "stream",
@@ -1549,7 +1556,7 @@
         "id": "hewvpLU_qHhO",
         "outputId": "64d05cd0-c71b-4337-def6-441f9fbd59f5"
       },
-      "execution_count": 6,
+      "execution_count": null,
       "outputs": [
         {
           "output_type": "stream",
@@ -3635,7 +3642,7 @@
         "id": "xuuCmTfoqMg9",
         "outputId": "7fe1ee42-6697-4443-9f9a-953a1cbac5fa"
       },
-      "execution_count": 7,
+      "execution_count": null,
       "outputs": [
         {
           "output_type": "stream",