{"record":{"id":"384ee041f5d09d30","repo":"tracel-ai/burn","slug":"from-data-not-supported-for-scheme-scheme","errorCode":null,"errorMessage":"from_data not supported for scheme {scheme:?}","messagePattern":"from_data not supported for scheme (.+?)","errorType":"panic","errorClass":null,"httpStatus":null,"severity":"error","filePath":"crates/burn-ndarray/src/ops/qtensor.rs","lineNumber":72,"sourceCode":"                            qparams,\n                            global,\n                        }\n                    }\n                    QuantScheme {\n                        value:\n                            QuantValue::Q4F\n                            | QuantValue::Q4S\n                            | QuantValue::Q2F\n                            | QuantValue::Q2S\n                            | QuantValue::E2M1\n                            | QuantValue::E4M3\n                            | QuantValue::E5M2,\n                        ..\n                    }\n                    | QuantScheme {\n                        mode: QuantMode::Lookup,\n                        ..\n                    } => unimplemented!(\"from_data not supported for scheme {scheme:?}\"),\n                }\n            }\n            _ => panic!(\n                \"Invalid dtype (expected DType::QFloat, got {:?})\",\n                data.dtype\n            ),\n        }\n    }\n\n    fn quantize(\n        tensor: FloatTensor<Self>,\n        scheme: &QuantScheme,\n        qparams: QuantizationParametersPrimitive<Self>,\n    ) -> QuantizedTensor<Self> {\n        let shape = tensor.shape();\n        let data_f = tensor.into_data();\n        let scales = qparams.scales.into_data().convert::<f32>();\n        // Quantize against the scale that will actually be stored, so a save/load round trip","sourceCodeStart":54,"sourceCodeEnd":90,"githubUrl":"https://github.com/tracel-ai/burn/blob/d16f7ba2ed0d41408189384044cc886fb4c8f957/crates/burn-ndarray/src/ops/qtensor.rs#L54-L90","documentation":"Unsupported-scheme guard in the ndarray backend's `q_from_data`: quantization schemes using low-bit values (Q4F/Q4S/Q2F/Q2S) or float formats (E2M1/E4M3/E5M2) cannot be represented as ndarray quantized tensors, so constructing a quantized tensor from data with such a scheme panics.","triggerScenarios":"Thrown at crates/burn-ndarray/src/ops/qtensor.rs:72 when the library encounters an invalid state.","commonSituations":"See trigger scenarios.","solutions":["Re-quantize the data with a supported scheme (e.g., Q8S/Q8F per-tensor or per-block symmetric)","Use a backend that supports the target scheme (e.g., cubecl-based backends)","Convert the checkpoint to a supported quantization scheme before loading into ndarray"],"exampleFix":null,"handlingStrategy":"validation","validationCode":null,"typeGuard":null,"tryCatchPattern":null,"preventionTips":[],"tags":[],"backgroundTag":null,"analyzedSha":"d16f7ba2ed0d41408189384044cc886fb4c8f957","analyzedAt":"2026-09-05T13:19:14.260Z","contentChangedAt":"2026-09-05T13:19:14.260Z","schemaVersion":2},"datasetVersion":"2026-09-12T17:17:11.597Z"}