Minor fixes (#20)

* fixed error in selection of time_sku features * fixed error in force save agent * fixed parameter name for dataset * accelerated getitem method * minor fix in predict function * minor fix in predict function * enables out-of-sample experiments * print steps while testing * fixed error in normalization for oos products * fixed error in normalizing oos demand * fixed error in normalization of oos SKUs * fixed error in normalization of oos SKUs * added option for run_experiment to return score * fixed average calc tune! * implemented xgb * renaming
d3group · Sep 26, 2024 · d98888e · d98888e
1 parent 67f05b6
commit d98888e
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Showing 15 changed files with 102 additions and 19 deletions.
diff --git a/ddopnew/agents/newsvendor/erm.py b/ddopnew/agents/newsvendor/erm.py
@@ -219,7 +219,7 @@ def __init__(self,
             test_batch_size: int = 1024,
             receive_batch_dim: bool = False,
             ):
-
+        
         # Initialize default values for mutable arguments
         optimizer_params = optimizer_params or {"optimizer": "Adam", "lr": 0.01, "weight_decay": 0.0}
         dataloader_params = dataloader_params or {"batch_size": 32, "shuffle": True}

diff --git a/ddopnew/dataloaders/tabular.py b/ddopnew/dataloaders/tabular.py
@@ -307,6 +307,7 @@ def __init__(self,
         demand_normalization: Literal['minmax', 'standard', 'no_normalization'] = 'no_normalization', # 'standard' or 'minmax'
         demand_unit_size: float | None = None, # use same convention as for other dataloaders and enviornments, but here only full decimal values are allowed
         provide_additional_target: bool = False, # follows ICL convention by providing actual demand to token, with the last token receiving 0
+        permutate_inputs: bool = False, # if the inputs shall be permutated during training for meta-learning
     ):
 
         logging.info("Setting main env attributes")
@@ -317,6 +318,7 @@ def __init__(self,
         self.time_features = time_features
         self.time_SKU_features = time_SKU_features
         self.mask = mask
+        self.permutate_inputs = permutate_inputs
 
         # convert dtypes to float
         self.demand = self.demand.astype(float)
@@ -1115,6 +1117,18 @@ def __getitem__(self, idx: int):
 
         item[:,:,-extra_info:,:] = additional_info
 
+        if self.dataset_type == "train":
+            if self.permutate_inputs:
+                start_index_to_permutate = len_SKU_features
+                end_index_to_permutate = item.shape[2]
+                if self.provide_additional_target:
+                    end_index_to_permutate -= 1 # target shall always be at the end
+                indices_for_permutation = np.arange(start_index_to_permutate, end_index_to_permutate)
+                print("original order:", indices_for_permutation)
+                indices = np.random.permutation(indices_for_permutation)
+                item[:,:,(start_index_to_permutate):end_index_to_permutate,:] = item[:,:,(indices),:]
+                print("new order:", indices)
+
         if self.meta_learn_units:
             if self.dataset_type == "train":
                 if item.shape[-1] == 1:

diff --git a/nbs/00_utils/00_utils.ipynb b/nbs/00_utils/00_utils.ipynb
@@ -1239,6 +1239,10 @@
    "display_name": "python3",
    "language": "python",
    "name": "python3"
+  },
+  "language_info": {
+   "name": "python",
+   "version": "3.11.0"
   }
  },
  "nbformat": 4,

diff --git a/nbs/00_utils/01_loss_functions.ipynb b/nbs/00_utils/01_loss_functions.ipynb
@@ -266,6 +266,10 @@
    "display_name": "python3",
    "language": "python",
    "name": "python3"
+  },
+  "language_info": {
+   "name": "python",
+   "version": "3.11.0"
   }
  },
  "nbformat": 4,

diff --git a/nbs/00_utils/10_postprocessors.ipynb b/nbs/00_utils/10_postprocessors.ipynb
@@ -642,6 +642,10 @@
    "display_name": "python3",
    "language": "python",
    "name": "python3"
+  },
+  "language_info": {
+   "name": "python",
+   "version": "3.11.0"
   }
  },
  "nbformat": 4,

diff --git a/nbs/00_utils/11_obsprocessors.ipynb b/nbs/00_utils/11_obsprocessors.ipynb
@@ -643,6 +643,10 @@
    "display_name": "python3",
    "language": "python",
    "name": "python3"
+  },
+  "language_info": {
+   "name": "python",
+   "version": "3.11.0"
   }
  },
  "nbformat": 4,

diff --git a/nbs/00_utils/20_torch_loss_functions.ipynb b/nbs/00_utils/20_torch_loss_functions.ipynb
@@ -534,6 +534,10 @@
    "display_name": "python3",
    "language": "python",
    "name": "python3"
+  },
+  "language_info": {
+   "name": "python",
+   "version": "3.11.0"
   }
  },
  "nbformat": 4,

diff --git a/nbs/10_dataloaders/12_tabular_dataloaders.ipynb b/nbs/10_dataloaders/12_tabular_dataloaders.ipynb
@@ -896,6 +896,7 @@
     "        demand_normalization: Literal['minmax', 'standard', 'no_normalization'] = 'no_normalization', # 'standard' or 'minmax'\n",
     "        demand_unit_size: float | None = None, # use same convention as for other dataloaders and enviornments, but here only full decimal values are allowed\n",
     "        provide_additional_target: bool = False, # follows ICL convention by providing actual demand to token, with the last token receiving 0\n",
+    "        permutate_inputs: bool = False, # if the inputs shall be permutated during training for meta-learning\n",
     "    ):\n",
     "     \n",
     "        logging.info(\"Setting main env attributes\")\n",
@@ -906,6 +907,7 @@
     "        self.time_features = time_features\n",
     "        self.time_SKU_features = time_SKU_features\n",
     "        self.mask = mask\n",
+    "        self.permutate_inputs = permutate_inputs\n",
     "\n",
     "        # convert dtypes to float\n",
     "        self.demand = self.demand.astype(float)\n",
@@ -1704,6 +1706,18 @@
     "\n",
     "        item[:,:,-extra_info:,:] = additional_info\n",
     "\n",
+    "        if self.dataset_type == \"train\":\n",
+    "            if self.permutate_inputs:\n",
+    "                start_index_to_permutate = len_SKU_features\n",
+    "                end_index_to_permutate = item.shape[2]\n",
+    "                if self.provide_additional_target:\n",
+    "                    end_index_to_permutate -= 1 # target shall always be at the end\n",
+    "                indices_for_permutation = np.arange(start_index_to_permutate, end_index_to_permutate)\n",
+    "                print(\"original order:\", indices_for_permutation)\n",
+    "                indices = np.random.permutation(indices_for_permutation)\n",
+    "                item[:,:,(start_index_to_permutate):end_index_to_permutate,:] = item[:,:,(indices),:]\n",
+    "                print(\"new order:\", indices)\n",
+    "\n",
     "        if self.meta_learn_units:\n",
     "            if self.dataset_type == \"train\":\n",
     "                if item.shape[-1] == 1:\n",

diff --git a/nbs/21_envs_inventory/00_inventory_utils.ipynb b/nbs/21_envs_inventory/00_inventory_utils.ipynb
@@ -63,6 +63,7 @@
    "source": [
     "#| export\n",
     "class OrderPipeline():\n",
+    "   \n",
     "    \"\"\"\n",
     "    Class to handle the order pipeline in the inventory environments. It is used to keep track of the orders\n",
     "    that are placed. It can account for fixed and variable lead times.\n",
@@ -537,6 +538,10 @@
    "display_name": "python3",
    "language": "python",
    "name": "python3"
+  },
+  "language_info": {
+   "name": "python",
+   "version": "3.11.0"
   }
  },
  "nbformat": 4,

diff --git a/nbs/21_envs_inventory/20_single_period_envs.ipynb b/nbs/21_envs_inventory/20_single_period_envs.ipynb
@@ -678,7 +678,7 @@
     "\n",
     "        # print(\"env mode:\", self.mode)\n",
     "        # print(\"dataloader mode:\", self.dataloader.dataset_type)\n",
-    "        \n",
+    "\n",
     "        X_item, Y_item = self.dataloader[self.index]\n",
     "\n",
     "        # check if any value in X_item is nan.\n",
@@ -789,6 +789,10 @@
    "display_name": "python3",
    "language": "python",
    "name": "python3"
+  },
+  "language_info": {
+   "name": "python",
+   "version": "3.11.0"
   }
  },
  "nbformat": 4,

diff --git a/nbs/21_envs_inventory/30_multi_period_envs.ipynb b/nbs/21_envs_inventory/30_multi_period_envs.ipynb
@@ -534,6 +534,10 @@
    "display_name": "python3",
    "language": "python",
    "name": "python3"
+  },
+  "language_info": {
+   "name": "python",
+   "version": "3.11.0"
   }
  },
  "nbformat": 4,

diff --git a/nbs/30_experiment_functions/10_experiment_functions.ipynb b/nbs/30_experiment_functions/10_experiment_functions.ipynb
@@ -947,7 +947,10 @@
    "execution_count": null,
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "\n",
+    "\n"
+   ]
   },
   {
    "cell_type": "code",
@@ -983,6 +986,10 @@
    "display_name": "python3",
    "language": "python",
    "name": "python3"
+  },
+  "language_info": {
+   "name": "python",
+   "version": "3.11.0"
   }
  },
  "nbformat": 4,

diff --git a/nbs/30_experiment_functions/20_meta_experiment_functions.ipynb b/nbs/30_experiment_functions/20_meta_experiment_functions.ipynb
@@ -555,20 +555,6 @@
     "    return None, None"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -706,6 +692,10 @@
    "display_name": "python3",
    "language": "python",
    "name": "python3"
+  },
+  "language_info": {
+   "name": "python",
+   "version": "3.11.0"
   }
  },
  "nbformat": 4,

diff --git a/nbs/41_NV_agents/10_NV_saa_agents.ipynb b/nbs/41_NV_agents/10_NV_saa_agents.ipynb
@@ -50,7 +50,7 @@
     "from ddopnew.obsprocessors import FlattenTimeDimNumpy\n",
     "\n",
     "from sklearn.ensemble import RandomForestRegressor\n",
-    "from sklearn.utils.validation import check_array\n"
+    "from sklearn.utils.validation import check_array"
    ]
   },
   {
@@ -1654,6 +1654,27 @@
     "print(R, J)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -1670,6 +1691,10 @@
    "display_name": "python3",
    "language": "python",
    "name": "python3"
+  },
+  "language_info": {
+   "name": "python",
+   "version": "3.11.0"
   }
  },
  "nbformat": 4,

diff --git a/nbs/41_NV_agents/11_NV_erm_agents.ipynb b/nbs/41_NV_agents/11_NV_erm_agents.ipynb
@@ -261,7 +261,7 @@
     "            test_batch_size: int = 1024,\n",
     "            receive_batch_dim: bool = False,\n",
     "            ):\n",
-    "\n",
+    "        \n",
     "        # Initialize default values for mutable arguments\n",
     "        optimizer_params = optimizer_params or {\"optimizer\": \"Adam\", \"lr\": 0.01, \"weight_decay\": 0.0}\n",
     "        dataloader_params = dataloader_params or {\"batch_size\": 32, \"shuffle\": True}\n",