diff --git a/onnx2torch/node_converters/activations.py b/onnx2torch/node_converters/activations.py
index 374b231f..3f6f5234 100644
--- a/onnx2torch/node_converters/activations.py
+++ b/onnx2torch/node_converters/activations.py
@@ -58,7 +58,7 @@ def _forward():
             if slope.nelement() == 1 or (
                 slope.shape[0] == input_tensor.shape[1] and all(s == 1 for s in slope.shape[1:])
             ):
-                return nn.functional.prelu(input_tensor, weight=slope.view(-1))
+                return nn.functional.prelu(input_tensor, weight=slope.view(-1))  # pylint: disable=not-callable
 
             output = input_tensor.clone()
             output = output * slope
diff --git a/onnx2torch/node_converters/constant_of_shape.py b/onnx2torch/node_converters/constant_of_shape.py
index d175336b..e81a6137 100644
--- a/onnx2torch/node_converters/constant_of_shape.py
+++ b/onnx2torch/node_converters/constant_of_shape.py
@@ -29,9 +29,11 @@ def __init__(self, value: Optional[torch.Tensor] = None):
         self.register_buffer('value', value)
 
     def forward(self, shape: torch.Tensor) -> torch.Tensor:  # pylint: disable=missing-function-docstring
+        fill_value = self.value.item()
+
         return torch.full(
             size=torch.Size(shape),
-            fill_value=self.value.item(),
+            fill_value=int(fill_value) if isinstance(fill_value, bool) else fill_value,
             dtype=self.value.dtype,
             device=self.value.device,
         )
diff --git a/onnx2torch/node_converters/pad.py b/onnx2torch/node_converters/pad.py
index 66ea86f9..cb0dd1eb 100644
--- a/onnx2torch/node_converters/pad.py
+++ b/onnx2torch/node_converters/pad.py
@@ -87,7 +87,7 @@ def create_from_onnx_params(  # pylint: disable=missing-function-docstring
         return cls(pads=torch_padding, mode=torch_mode, constant_value=constant_value)
 
     def forward(self, input_tensor: torch.Tensor) -> torch.Tensor:  # pylint: disable=missing-function-docstring
-        return F.pad(
+        return F.pad(  # pylint: disable=not-callable
             input_tensor,
             mode=self.mode,
             pad=self.pads,
@@ -109,7 +109,7 @@ def forward(  # pylint: disable=missing-function-docstring
         torch_pads = _onnx_padding_to_torch(pads.tolist())
         torch_pads = _torch_padding_to_mode_format(torch_pads, self.mode)
 
-        return F.pad(input_tensor, mode=self.mode, pad=torch_pads, value=constant_value)
+        return F.pad(input_tensor, mode=self.mode, pad=torch_pads, value=constant_value)  # pylint: disable=not-callable
 
 
 @add_converter(operation_type='Pad', version=11)
diff --git a/tests/node_converters/constant_of_shape_test.py b/tests/node_converters/constant_of_shape_test.py
index 1ea1e89f..8277bb27 100644
--- a/tests/node_converters/constant_of_shape_test.py
+++ b/tests/node_converters/constant_of_shape_test.py
@@ -40,3 +40,5 @@ def test_constant_of_shape() -> None:  # pylint: disable=missing-function-docstr
         shape = np.random.randint(low=1, high=2, size=(size,))
         value = np.random.uniform(low=-10000, high=10000, size=(1,))
         _test_constant_of_shape(shape, value)
+
+    _test_constant_of_shape(np.asarray([3, 3]), np.asarray([True]))