remove types in datasets

Author: srush

minitorch/datasets.py

@@ -4,7 +4,7 @@
 from typing import List, Tuple
 
 
-def make_pts(N: int) -> List[Tuple[float, float]]:
+def make_pts(N):
     X = []
     for i in range(N):
         x_1 = random.random()
@@ -20,7 +20,7 @@ class Graph:
     y: List[int]
 
 
-def simple(N: int) -> Graph:
+def simple(N):
     X = make_pts(N)
     y = []
     for x_1, x_2 in X:
@@ -29,7 +29,7 @@ def simple(N: int) -> Graph:
     return Graph(N, X, y)
 
 
-def diag(N: int) -> Graph:
+def diag(N):
     X = make_pts(N)
     y = []
     for x_1, x_2 in X:
@@ -38,7 +38,7 @@ def diag(N: int) -> Graph:
     return Graph(N, X, y)
 
 
-def split(N: int) -> Graph:
+def split(N):
     X = make_pts(N)
     y = []
     for x_1, x_2 in X:
@@ -47,49 +47,39 @@ def split(N: int) -> Graph:
     return Graph(N, X, y)
 
 
-def xor(N: int) -> Graph:
+def xor(N):
     X = make_pts(N)
     y = []
     for x_1, x_2 in X:
-        y1 = 1 if ((x_1 < 0.5 and x_2 > 0.5) or (x_1 > 0.5 and x_2 < 0.5)) else 0
+        y1 = 1 if x_1 < 0.5 and x_2 > 0.5 or x_1 > 0.5 and x_2 < 0.5 else 0
         y.append(y1)
     return Graph(N, X, y)
 
 
-def circle(N: int) -> Graph:
+def circle(N):
     X = make_pts(N)
     y = []
     for x_1, x_2 in X:
-        x1, x2 = (x_1 - 0.5, x_2 - 0.5)
+        x1, x2 = x_1 - 0.5, x_2 - 0.5
         y1 = 1 if x1 * x1 + x2 * x2 > 0.1 else 0
         y.append(y1)
     return Graph(N, X, y)
 
 
-def spiral(N: int) -> Graph:
-    def x(t: float) -> float:
+def spiral(N):
+
+    def x(t):
         return t * math.cos(t) / 20.0
 
-    def y(t: float) -> float:
+    def y(t):
         return t * math.sin(t) / 20.0
-
-    X = [
-        (x(10.0 * (float(i) / (N // 2))) + 0.5, y(10.0 * (float(i) / (N // 2))) + 0.5)
-        for i in range(5 + 0, 5 + N // 2)
-    ]
-    X = X + [
-        (y(-10.0 * (float(i) / (N // 2))) + 0.5, x(-10.0 * (float(i) / (N // 2))) + 0.5)
-        for i in range(5 + 0, 5 + N // 2)
-    ]
+    X = [(x(10.0 * (float(i) / (N // 2))) + 0.5, y(10.0 * (float(i) / (N //
+        2))) + 0.5) for i in range(5 + 0, 5 + N // 2)]
+    X = X + [(y(-10.0 * (float(i) / (N // 2))) + 0.5, x(-10.0 * (float(i) /
+        (N // 2))) + 0.5) for i in range(5 + 0, 5 + N // 2)]
     y2 = [0] * (N // 2) + [1] * (N // 2)
     return Graph(N, X, y2)
 
 
-datasets = {
-    "Simple": simple,
-    "Diag": diag,
-    "Split": split,
-    "Xor": xor,
-    "Circle": circle,
-    "Spiral": spiral,
-}
+datasets = {'Simple': simple, 'Diag': diag, 'Split': split, 'Xor': xor,
+    'Circle': circle, 'Spiral': spiral}

project/app.py

@@ -19,7 +19,7 @@
 st.sidebar.markdown(
     """
 <h1 style="font-size:30pt; float: left; margin-right: 20px; margin-top: 1px;">MiniTorch</h1>{}
-""".format(get_img_tag("https://minitorch.github.io/_images/match.png", width="40")),
+""".format(get_img_tag("https://minitorch.github.io/logo-sm.png", width="40")),
     unsafe_allow_html=True,
 )
 

pyproject.toml

@@ -89,6 +89,7 @@ ignore = [
     "D401",
     "D105",
     "D415",
+    "D402",
     "D205",
     "D100",
     "D101",

requirements.extra.txt

@@ -1,10 +1,11 @@
 datasets==2.4.0
 embeddings==0.0.8
-networkx==2.4
 plotly==4.14.3
 pydot==1.4.1
 python-mnist
 streamlit==1.12.0
 streamlit-ace
 torch
 watchdog==1.0.2
+altair==4.2.2
+networkx==3.3

tests/strategies.py

@@ -14,4 +14,4 @@
 
 
 def assert_close(a: float, b: float) -> None:
-    assert minitorch.is_close(a, b), "Failure x=%f y=%f" % (a, b)
+    assert minitorch.operators.is_close(a, b), "Failure x=%f y=%f" % (a, b)