Fix ToC imports

apps/article.py

@@ -1,7 +1,7 @@
 import streamlit as st
 from apps.utils import read_markdown
 from streamlit_tensorboard import st_tensorboard
-from .toc import Toc
+from utils import Toc
 def app(state):
     toc = Toc()
     st.title("Table of contents")

apps/toc.py

@@ -1,29 +0,0 @@
-import streamlit as st
-
-class Toc:
-
-    def __init__(self):
-        self._items = []
-        self._placeholder = None
-    
-    def title(self, text):
-        self._markdown(text, "h1")
-
-    def header(self, text):
-        self._markdown(text, "h2", " " * 2)
-
-    def subheader(self, text):
-        self._markdown(text, "h3", " " * 4)
-
-    def placeholder(self, sidebar=False):
-        self._placeholder = st.sidebar.empty() if sidebar else st.empty()
-
-    def generate(self):
-        if self._placeholder:
-            self._placeholder.markdown("\n".join(self._items), unsafe_allow_html=True)
-    
-    def _markdown(self, text, level, space=""):
-        key = "".join(filter(str.isalnum, text)).lower()
-
-        st.markdown(f"<{level} id='{key}'>{text}</{level}>", unsafe_allow_html=True)
-        self._items.append(f"{space}* <a href='#{key}'>{text}</a>")

apps/utils.py

@@ -1,6 +1,7 @@
 import json
 import os
 import numpy as np
+import streamlit as st
 import plotly.express as px
 import torch
 from torchvision.io import read_image
@@ -8,6 +9,33 @@ from torchvision.transforms import CenterCrop, ConvertImageDtype, Normalize, Res
 from torchvision.transforms.functional import InterpolationMode
 from transformers import BertTokenizerFast
 
+class Toc:
+
+    def __init__(self):
+        self._items = []
+        self._placeholder = None
+    
+    def title(self, text):
+        self._markdown(text, "h1")
+
+    def header(self, text):
+        self._markdown(text, "h2", " " * 2)
+
+    def subheader(self, text):
+        self._markdown(text, "h3", " " * 4)
+
+    def placeholder(self, sidebar=False):
+        self._placeholder = st.sidebar.empty() if sidebar else st.empty()
+
+    def generate(self):
+        if self._placeholder:
+            self._placeholder.markdown("\n".join(self._items), unsafe_allow_html=True)
+    
+    def _markdown(self, text, level, space=""):
+        key = "".join(filter(str.isalnum, text)).lower()
+
+        st.markdown(f"<{level} id='{key}'>{text}</{level}>", unsafe_allow_html=True)
+        self._items.append(f"{space}* <a href='#{key}'>{text}</a>")
 
 class Transform(torch.nn.Module):
     def __init__(self, image_size):