[FIX] run examples/hwf/hwf_example.ipynb after reformat examples

examples/hwf/datasets/get_hwf.py

@@ -12,7 +12,7 @@ def get_data(file, get_pseudo_label):
     if get_pseudo_label:
         Z = []
     Y = []
-    img_dir = './datasets/hwf/data/Handwritten_Math_Symbols/'
+    img_dir = './datasets/data/Handwritten_Math_Symbols/'
     with open(file) as f:
         data = json.load(f)
         for idx in range(len(data)):
@@ -36,9 +36,9 @@ def get_data(file, get_pseudo_label):
 
 def get_hwf(train = True, get_pseudo_label = False):
     if(train):
-        file = './datasets/hwf/data/expr_train.json'
+        file = './datasets/data/expr_train.json'
     else:
-        file = './datasets/hwf/data/expr_test.json'
+        file = './datasets/data/expr_test.json'
     
     return get_data(file, get_pseudo_label)
 

examples/hwf/hwf_example.ipynb

@@ -8,7 +8,7 @@
    "source": [
     "import sys\n",
     "\n",
-    "sys.path.append(\"../\")\n",
+    "sys.path.append(\"../../\")\n",
     "\n",
     "import torch.nn as nn\n",
     "import torch\n",
@@ -21,8 +21,8 @@
     "from abl.models.wabl_models import WABLBasicModel\n",
     "\n",
     "from models.nn import SymbolNet\n",
-    "from datasets.hwf.get_hwf import get_hwf\n",
-    "from abl import framework_hed"
+    "from datasets.get_hwf import get_hwf\n",
+    "from abl import framework"
    ]
   },
   {
@@ -150,7 +150,7 @@
    "outputs": [],
    "source": [
     "# Train model\n",
-    "framework_hed.train(\n",
+    "framework.train(\n",
     "    model, abducer, train_data, test_data, loop_num=15, sample_num=5000, verbose=1\n",
     ")\n",
     "\n",
@@ -175,7 +175,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.13"
+   "version": "3.8.16"
   },
   "orig_nbformat": 4
  },

examples/mnist_add/datasets/get_mnist_add.py

@@ -1,6 +1,4 @@
-import torch
 import torchvision
-from torch.utils.data import Dataset
 from torchvision.transforms import transforms
 
 def get_data(file, img_dataset, get_pseudo_label):
@@ -23,12 +21,12 @@ def get_data(file, img_dataset, get_pseudo_label):
 
 def get_mnist_add(train = True, get_pseudo_label = False):
     transform = transforms.Compose([transforms.ToTensor(), transforms.Normalize((0.1307,), (0.3081, ))])
-    img_dataset = torchvision.datasets.MNIST(root='./datasets/mnist_add/', train=train, download=True, transform=transform)
+    img_dataset = torchvision.datasets.MNIST(root='./datasets/', train=train, download=True, transform=transform)
     
     if train:
-        file = './datasets/mnist_add/train_data.txt'
+        file = './datasets/train_data.txt'
     else:
-        file = './datasets/mnist_add/test_data.txt'
+        file = './datasets/test_data.txt'
     
     return get_data(file, img_dataset, get_pseudo_label)