Clamp a given w to finite bounds in Conv1d/2d/3d and MeanField connections

CHANGELOG.md

@@ -6,6 +6,15 @@ see the [GitHub releases / tags](https://github.com/BindsNET/bindsnet/releases).
 
 ## [Unreleased]
 
+### Results changes (read this before upgrading)
+- `Conv1dConnection`, `Conv2dConnection`, `Conv3dConnection` and `MeanFieldConnection`
+  now clamp a `w` passed to the constructor into `[wmin, wmax]`, as `Connection` does.
+  Before, the check was reversed (`==` instead of `!=`): a given `w` was clamped only
+  when a bound was infinite, which does nothing, so with finite bounds it was never
+  clamped. Affects code that passes these classes weights outside finite bounds; their
+  starting weights are now clamped. No built-in model or example does this, and the
+  golden-output tests are unchanged.
+
 ### Added
 - Contributor rules for AI-assisted work (`CONTRIBUTING.md`, "AI-assisted
   contributions"): AI tools are welcome, a human must have read and run every change,

bindsnet/network/topology.py

@@ -880,7 +880,7 @@ def __init__(
                 w += self.wmin
             w = w.to(dtype=w_dtype)
         else:
-            if (self.wmin == -inf).any() or (self.wmax == inf).any():
+            if (self.wmin != -inf).any() or (self.wmax != inf).any():
                 w = torch.clamp(w, self.wmin, self.wmax)
             w = self.cast_dtype_if_needed(w, w_dtype)
 
@@ -1041,7 +1041,7 @@ def __init__(
                 w += self.wmin
             w = w.to(dtype=w_dtype)
         else:
-            if (self.wmin == -inf).any() or (self.wmax == inf).any():
+            if (self.wmin != -inf).any() or (self.wmax != inf).any():
                 w = torch.clamp(w, self.wmin, self.wmax)
             w = self.cast_dtype_if_needed(w, w_dtype)
 
@@ -1223,7 +1223,7 @@ def __init__(
                 w += self.wmin
             w = w.to(dtype=w_dtype)
         else:
-            if (self.wmin == -inf).any() or (self.wmax == inf).any():
+            if (self.wmin != -inf).any() or (self.wmax != inf).any():
                 w = torch.clamp(w, self.wmin, self.wmax)
             w = self.cast_dtype_if_needed(w, w_dtype)
 
@@ -2268,7 +2268,7 @@ def __init__(
                 w = self.wmin + ((torch.randn(1)[0] + 1) / 10) * (self.wmax - self.wmin)
             w = w.to(dtype=w_dtype)
         else:
-            if (self.wmin == -np.inf).any() or (self.wmax == np.inf).any():
+            if (self.wmin != -np.inf).any() or (self.wmax != np.inf).any():
                 w = torch.clamp(w, self.wmin, self.wmax)
             w = self.cast_dtype_if_needed(w, w_dtype)
         self.w = Parameter(w, requires_grad=False)

test/network/test_connections.py

@@ -1065,3 +1065,48 @@ def test_local_connection_nd_random_weights_within_per_weight_bounds(name):
         **kwargs,
     )
     assert ((conn.w >= 0) & (conn.w <= wmax)).all()
+
+
+def _given_w_out_of_bounds():
+    """Constructors of the connection types whose given w is checked against finite bounds."""
+    return {
+        "Conv1dConnection": lambda: Conv1dConnection(
+            Input(shape=(1, 6)),
+            LIFNodes(shape=(2, 4)),
+            kernel_size=3,
+            w=torch.linspace(-1.0, 2.0, 6).view(2, 1, 3),
+            wmin=0.0,
+            wmax=1.0,
+        ),
+        "Conv2dConnection": lambda: Conv2dConnection(
+            Input(shape=(1, 6, 6)),
+            LIFNodes(shape=(2, 4, 4)),
+            kernel_size=3,
+            w=torch.linspace(-1.0, 2.0, 18).view(2, 1, 3, 3),
+            wmin=0.0,
+            wmax=1.0,
+        ),
+        "Conv3dConnection": lambda: Conv3dConnection(
+            Input(shape=(1, 4, 4, 4)),
+            LIFNodes(shape=(2, 2, 2, 2)),
+            kernel_size=3,
+            w=torch.linspace(-1.0, 2.0, 54).view(2, 1, 3, 3, 3),
+            wmin=0.0,
+            wmax=1.0,
+        ),
+        "MeanFieldConnection": lambda: MeanFieldConnection(
+            Input(n=4), LIFNodes(n=3), w=torch.tensor(2.0), wmin=0.0, wmax=1.0
+        ),
+    }
+
+
+@pytest.mark.parametrize("name", list(_given_w_out_of_bounds()))
+def test_given_weights_are_clamped_to_finite_bounds(name):
+    """A w passed to the constructor is clamped into [wmin, wmax], as Connection does.
+
+    Caught: Conv1d/2d/3dConnection and MeanFieldConnection clamped a given w only when
+    a bound was infinite (== instead of !=), so with finite bounds it was never clamped.
+    """
+    conn = _given_w_out_of_bounds()[name]()
+    assert conn.w.min() >= 0.0
+    assert conn.w.max() <= 1.0