[MNT] after changing the modules names, run three examples successfully

examples/hed/framework_hed.py

@@ -17,7 +17,7 @@ import os
 
 from abl.utils.plog import INFO
 from abl.utils.utils import flatten, reform_idx
-from abl.models.basic_model import BasicModel, BasicDataset
+from abl.learning.basic_nn import BasicNN, BasicDataset
 
 from utils import gen_mappings, mapping_res, remapping_res
 from models.nn import SymbolNetAutoencoder
@@ -36,7 +36,7 @@ def hed_pretrain(kb, cls, recorder):
         criterion = nn.MSELoss()
         optimizer = torch.optim.RMSprop(cls_autoencoder.parameters(), lr=0.001, alpha=0.9, weight_decay=1e-6)
 
-        pretrain_model = BasicModel(cls_autoencoder, criterion, optimizer, device, save_interval=1, save_dir=recorder.save_dir, num_epochs=10, recorder=recorder)
+        pretrain_model = BasicNN(cls_autoencoder, criterion, optimizer, device, save_interval=1, save_dir=recorder.save_dir, num_epochs=10, recorder=recorder)
         pretrain_model.fit(pretrain_data_loader)
         torch.save(cls_autoencoder.base_model.state_dict(), "./weights/pretrain_weights.pth")
         cls.load_state_dict(cls_autoencoder.base_model.state_dict())

examples/hed/hed_example.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -14,12 +14,12 @@
     "import torch.nn as nn\n",
     "import torch\n",
     "\n",
-    "from abl.abducer.abducer_base import AbducerBase\n",
-    "from abl.abducer.kb import prolog_KB\n",
+    "from abl.reasoning.reasoner import ReasonerBase\n",
+    "from abl.reasoning.kb import prolog_KB\n",
     "\n",
     "from abl.utils.plog import logger\n",
-    "from abl.models.basic_nn import BasicNN\n",
-    "from abl.models.abl_model import ABLModel\n",
+    "from abl.learning.basic_nn import BasicNN\n",
+    "from abl.learning.abl_model import ABLModel\n",
     "from abl.utils.utils import reform_idx\n",
     "\n",
     "from models.nn import SymbolNet\n",
@@ -29,7 +29,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -47,17 +47,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "ERROR: /home/gaoeh/ABL-Package/examples/hed/datasets/learn_add.pl:67:9: Syntax error: Operator expected\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# Initialize knowledge base and abducer\n",
     "class HED_prolog_KB(prolog_KB):\n",
@@ -79,7 +71,7 @@
     "    \n",
     "kb = HED_prolog_KB(pseudo_label_list=[1, 0, '+', '='], pl_file='./datasets/learn_add.pl')\n",
     "\n",
-    "class HED_Abducer(AbducerBase):\n",
+    "class HED_Abducer(ReasonerBase):\n",
     "    def __init__(self, kb, dist_func='hamming'):\n",
     "        super().__init__(kb, dist_func, zoopt=True)\n",
     "    \n",

examples/hwf/hwf_example.ipynb

@@ -14,12 +14,12 @@
     "import torch.nn as nn\n",
     "import torch\n",
     "\n",
-    "from abl.abducer.abducer_base import AbducerBase\n",
-    "from abl.abducer.kb import KBBase\n",
+    "from abl.reasoning.reasoner import ReasonerBase\n",
+    "from abl.reasoning.kb import KBBase\n",
     "\n",
     "from abl.utils.plog import logger\n",
-    "from abl.models.basic_nn import BasicNN\n",
-    "from abl.models.abl_model import ABLModel\n",
+    "from abl.learning.basic_nn import BasicNN\n",
+    "from abl.learning.abl_model import ABLModel\n",
     "\n",
     "from models.nn import SymbolNet\n",
     "from datasets.get_hwf import get_hwf\n",
@@ -81,7 +81,7 @@
     "        return eval(''.join(formula))\n",
     "\n",
     "kb = HWF_KB(GKB_flag=True)\n",
-    "abducer = AbducerBase(kb)"
+    "abducer = ReasonerBase(kb)"
    ]
   },
   {

examples/mnist_add/mnist_add_example.ipynb

@@ -13,12 +13,12 @@
     "import torch.nn as nn\n",
     "import torch\n",
     "\n",
-    "from abl.abducer.abducer_base import AbducerBase\n",
-    "from abl.abducer.kb import KBBase, prolog_KB\n",
+    "from abl.reasoning.reasoner import ReasonerBase\n",
+    "from abl.reasoning.kb import KBBase, prolog_KB\n",
     "\n",
     "from abl.utils.plog import logger\n",
-    "from abl.models.basic_nn import BasicNN\n",
-    "from abl.models.abl_model import ABLModel\n",
+    "from abl.learning.basic_nn import BasicNN\n",
+    "from abl.learning.abl_model import ABLModel\n",
     "\n",
     "from models.nn import LeNet5\n",
     "from datasets.get_mnist_add import get_mnist_add\n",
@@ -60,7 +60,7 @@
     "kb = add_KB(GKB_flag=True)\n",
     "\n",
     "# kb = prolog_KB(pseudo_label_list=list(range(10)), pl_file='datasets/mnist_add/add.pl')\n",
-    "abducer = AbducerBase(kb, dist_func=\"confidence\")"
+    "abducer = ReasonerBase(kb, dist_func=\"confidence\")"
    ]
   },
   {