tracel-ai/burn · error

Should be int, got bool

Error message

Should be int, got bool

What it means

BackendTensor::int() was called on a Bool tensor handle. Only the Int variant yields an int primitive, so the code panics. A boolean tensor (typically a mask or comparison result) reached a path expecting integer values.

Source

Thrown at crates/burn-dispatch/src/tensor.rs:65

    }
    /// Returns the inner float tensor primitive.
    pub fn as_float(&self) -> &B::FloatTensorPrimitive {
        match self {
            BackendTensor::Float(tensor) => tensor,
            BackendTensor::Int(_) => panic!("Should be float, got int"),
            BackendTensor::Bool(_) => panic!("Should be float, got bool"),
            BackendTensor::Quantized(_) => panic!("Should be float, got quantized"),
            #[cfg(feature = "autodiff")]
            BackendTensor::Autodiff(_) => panic!("Should be float, got autodiff"),
        }
    }

    /// Returns the inner int tensor primitive.
    pub fn int(self) -> B::IntTensorPrimitive {
        match self {
            BackendTensor::Int(tensor) => tensor,
            BackendTensor::Float(_) => panic!("Should be int, got float"),
            BackendTensor::Bool(_) => panic!("Should be int, got bool"),
            BackendTensor::Quantized(_) => panic!("Should be int, got quantized"),
            #[cfg(feature = "autodiff")]
            BackendTensor::Autodiff(_) => panic!("Should be int, got autodiff"),
        }
    }

    /// Returns the inner bool tensor primitive.
    pub fn bool(self) -> B::BoolTensorPrimitive {
        match self {
            BackendTensor::Bool(tensor) => tensor,
            BackendTensor::Float(_) => panic!("Should be bool, got float"),
            BackendTensor::Int(_) => panic!("Should be bool, got int"),
            BackendTensor::Quantized(_) => panic!("Should be bool, got quantized"),
            #[cfg(feature = "autodiff")]
            BackendTensor::Autodiff(_) => panic!("Should be bool, got autodiff"),
        }
    }

View on GitHub (pinned to d16f7ba2ed)

Solutions

1. Convert the bool tensor to int explicitly (bool_tensor.int() via the backend cast op) before the int-only call
2. Confirm the upstream op actually outputs Int rather than Bool
3. Match the BackendTensor variant at the call site and handle Bool deliberately (e.g. where/select semantics)
4. Validate dtype via TensorMetadata at the boundary

Example fix

// before
let idx = mask_handle.int(); // panics: Bool variant
// after
let idx = mask_handle.bool().int(); // explicit bool -> int cast (0/1 values)

if matches!(handle, BackendTensor::Bool(_)) {
    let idx = handle.bool().int(); // explicit 0/1 conversion
}

fn is_int<B: BackendTypes>(t: &BackendTensor<B>) -> bool {
    matches!(t, BackendTensor::Int(_))
}

When it happens

Trigger: Calling int() on a bool tensor from comparison ops (==, <, >) or logical ops; using a bool mask where integer indices/values are required; custom code treating bools as 0/1 ints without conversion.

Common situations: Using a comparison result as an index directly; PyTorch-style implicit bool->int promotion assumptions; passing mask tensors into ops implemented only for int primitives.

Related errors

• Should be bool, got float
• Should be float, got bool
• Should be int, got float
• Should be int, got quantized
• Should be int, got autodiff

AI-assisted analysis of tracel-ai/burn@d16f7ba2ed (2026-09-05). Data as JSON: /api/errors/22b3138ab37c2929. Report an issue: GitHub.