From 643dc64f57d295359dfdd8084a2bc0cd6f2e6183 Mon Sep 17 00:00:00 2001
From: troyyyyy <huwc@lamda.nju.edu.cn>
Date: Sun, 8 Oct 2023 15:37:47 +0800
Subject: [PATCH] [MNT] change kb parameter name in examples

---
 examples/hwf/hwf_example.ipynb             | 10 ++++-----
 examples/mnist_add/mnist_add_example.ipynb | 26 +++++++++++-----------
 2 files changed, 18 insertions(+), 18 deletions(-)

diff --git a/examples/hwf/hwf_example.ipynb b/examples/hwf/hwf_example.ipynb
index f9de708..b1ba550 100644
--- a/examples/hwf/hwf_example.ipynb
+++ b/examples/hwf/hwf_example.ipynb
@@ -49,12 +49,12 @@
     "    def __init__(\n",
     "        self, \n",
     "        pseudo_label_list=['1', '2', '3', '4', '5', '6', '7', '8', '9', '+', '-', 'times', 'div'], \n",
-    "        len_list=[1, 3, 5, 7],\n",
-    "        GKB_flag=False,\n",
+    "        prebuild_GKB=False,\n",
+    "        GKB_len_list=[1, 3, 5, 7],\n",
     "        max_err=1e-3,\n",
     "        use_cache=True\n",
     "    ):\n",
-    "        super().__init__(pseudo_label_list, len_list, GKB_flag, max_err, use_cache)\n",
+    "        super().__init__(pseudo_label_list, prebuild_GKB, GKB_len_list, max_err, use_cache)\n",
     "\n",
     "    def _valid_candidate(self, formula):\n",
     "        if len(formula) % 2 == 0:\n",
@@ -74,7 +74,7 @@
     "        formula = [mapping[f] for f in formula]\n",
     "        return eval(''.join(formula))\n",
     "\n",
-    "kb = HWF_KB(GKB_flag=True)\n",
+    "kb = HWF_KB(prebuild_GKB=True)\n",
     "abducer = ReasonerBase(kb, dist_func='confidence')"
    ]
   },
@@ -220,7 +220,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.16"
+   "version": "3.8.13"
   },
   "orig_nbformat": 4,
   "vscode": {
diff --git a/examples/mnist_add/mnist_add_example.ipynb b/examples/mnist_add/mnist_add_example.ipynb
index ade4e55..146bd88 100644
--- a/examples/mnist_add/mnist_add_example.ipynb
+++ b/examples/mnist_add/mnist_add_example.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -17,12 +17,12 @@
     "from abl.utils import ABLLogger\n",
     "\n",
     "from models.nn import LeNet5\n",
-    "from datasets.get_mnist_add import get_mnist_add"
+    "from examples.mnist_add.datasets.get_mnist_add import get_mnist_add"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -40,19 +40,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
     "# Initialize knowledge base and abducer\n",
     "class add_KB(KBBase):\n",
-    "    def __init__(self, pseudo_label_list=list(range(10)), len_list=[2], GKB_flag=False, max_err=0, use_cache=True):\n",
-    "        super().__init__(pseudo_label_list, len_list, GKB_flag, max_err, use_cache)\n",
+    "    def __init__(self, pseudo_label_list=list(range(10)), prebuild_GKB=False, GKB_len_list=[2], max_err=0, use_cache=True):\n",
+    "        super().__init__(pseudo_label_list, prebuild_GKB, GKB_len_list, max_err, use_cache)\n",
     "\n",
     "    def logic_forward(self, nums):\n",
     "        return sum(nums)\n",
     "\n",
-    "kb = add_KB(GKB_flag=True)\n",
+    "kb = add_KB(prebuild_GKB=True)\n",
     "\n",
     "# kb = prolog_KB(pseudo_label_list=list(range(10)), pl_file='datasets/mnist_add/add.pl')\n",
     "abducer = ReasonerBase(kb, dist_func=\"confidence\")"
@@ -68,7 +68,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -81,7 +81,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -109,7 +109,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -129,7 +129,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -147,7 +147,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -208,7 +208,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.16"
+   "version": "3.8.13"
   },
   "orig_nbformat": 4,
   "vscode": {