tracel-ai/burn · error

Data should have as many elements as the shape

Error message

Data should have as many elements as the shape

What it means

Shape/length invariant check in `NdArrayTensor::from_data_owned`: the flattened element count of `TensorData` does not match the product of the declared shape, so ndarray cannot view the buffer with that shape and conversion panics.

Source

Thrown at crates/burn-ndarray/src/tensor.rs:683

            dtype,
        })
    }

    /// Create a tensor with owned storage.
    ///
    /// This may or may not copy data depending on whether the underlying bytes
    /// can be reclaimed (via `try_into_vec`). If bytes are uniquely owned,
    /// no copy occurs; otherwise data is copied to a new allocation.
    fn from_data_owned(data: TensorData) -> NdArrayTensor {
        let shape = data.shape.to_vec(); // TODO: into_vec

        macro_rules! execute {
            ($data: expr, [$($dtype: pat => $ty: ty),*]) => {
                match $data.dtype {
                    $( $dtype => {
                        match data.try_into_vec::<$ty>() {
                            Ok(vec) => ArrayD::from_shape_vec(shape, vec)
                                .expect("Data should have as many elements as the shape")
                                .into_shared(),
                            Err(err) => panic!("Data should have the same element type as the tensor {err:?}"),
                        }.into()
                    }, )*
                    other => unimplemented!("Unsupported dtype {other:?}"),
                }
            };
        }

        execute!(data, [
            DType::F64 => f64, DType::F32 => f32,
            DType::I64 => i64, DType::I32 => i32, DType::I16 => i16, DType::I8 => i8,
            DType::U64 => u64, DType::U32 => u32, DType::U16 => u16, DType::U8 => u8,
            DType::Bool(BoolStore::Native) => bool
        ])
    }
}

View on GitHub (pinned to d16f7ba2ed)

Solutions

1. Verify `TensorData.shape` matches `data.len()` (or vec length) before conversion
2. Recompute the shape from the data instead of hardcoding it
3. Check for off-by-one or truncated reads when the data was produced

When it happens

Trigger: Thrown at crates/burn-ndarray/src/tensor.rs:683 when the library encounters an invalid state.

Common situations: See trigger scenarios.

AI-assisted analysis of tracel-ai/burn@d16f7ba2ed (2026-09-05). Data as JSON: /api/errors/9d3e9bfc1fb400e5. Report an issue: GitHub.