{"record":{"id":"f45204509a215f85","repo":"huggingface/candle","slug":"cannot-reshape-tensor-with-el-count-elements-to","errorCode":null,"errorMessage":"cannot reshape tensor with {el_count} elements to {s:?}","messagePattern":"cannot reshape tensor with (.+?) elements to (.+?)","errorType":"validation","errorClass":null,"httpStatus":null,"severity":"error","filePath":"candle-core/src/shape.rs","lineNumber":499,"sourceCode":"            }\n            .bt());\n        }\n        Ok(shape)\n    }\n}\n\nimpl ShapeWithOneHole for ((),) {\n    fn into_shape(self, el_count: usize) -> Result<Shape> {\n        Ok(el_count.into())\n    }\n}\n\nfn hole_size(el_count: usize, prod_d: usize, s: &dyn std::fmt::Debug) -> Result<usize> {\n    if prod_d == 0 {\n        crate::bail!(\"cannot reshape tensor of {el_count} elements to {s:?}\")\n    }\n    if !el_count.is_multiple_of(prod_d) {\n        crate::bail!(\"cannot reshape tensor with {el_count} elements to {s:?}\")\n    }\n    Ok(el_count / prod_d)\n}\n\nimpl ShapeWithOneHole for ((), usize) {\n    fn into_shape(self, el_count: usize) -> Result<Shape> {\n        let ((), d1) = self;\n        Ok((hole_size(el_count, d1, &self)?, d1).into())\n    }\n}\n\nimpl ShapeWithOneHole for (usize, ()) {\n    fn into_shape(self, el_count: usize) -> Result<Shape> {\n        let (d1, ()) = self;\n        Ok((d1, hole_size(el_count, d1, &self)?).into())\n    }\n}\n","sourceCodeStart":481,"sourceCodeEnd":517,"githubUrl":"https://github.com/huggingface/candle/blob/d5fee525bfde3273eb7c9b75fd2bc4937be867ca/candle-core/src/shape.rs#L481-L517","documentation":"When reshaping without (or beyond) a wildcard, the tensor's total element count must be divisible by the product of the requested dimensions. hole_size bails when el_count is not a multiple of prod_d, meaning the requested shape cannot tile the existing data evenly.","triggerScenarios":"Calling tensor.reshape(...)/into_shape with concrete dims whose product does not divide the tensor's element count, e.g. reshaping a 1000-element tensor to (2, 499).","commonSituations":"Hard-coded reshape sizes that assume a different batch/sequence length; forgetting a channel dim; models with dynamic batch sizes where a constant target shape no longer divides evenly.","solutions":["Use a wildcard for the unknown dimension: reshape ((,), 64) or ((), -1-equivalent) so candle infers it","Compute the target dim from el_count / known_dims instead of hard-coding","Check tensor.elem_count() and the product of the target dims before reshaping"],"exampleFix":"// before\nlet y = x.reshape((2, 499))?; // 1000 elems\n// after\nlet y = x.reshape(((), 500))?; // hole inferred as 2","handlingStrategy":"validation","validationCode":"let el = x.elem_count();\nlet prod: usize = dims.iter().product();\nif !dims.contains(&HOLE) && el % prod != 0 {\n    return Err(anyhow::anyhow!(\"cannot reshape {el} elements to {dims:?}\"));\n}","typeGuard":null,"tryCatchPattern":"let y = x.reshape(dims).or_else(|_| {\n    // retry with a hole in the first dim\n    x.reshape(((), dims[1]))\n})?;","preventionTips":["Compute reshape targets from x.elem_count() rather than hard-coded numbers","Use a hole dimension for anything batch/dynamic dependent","Add a debug assertion el_count % prod == 0 before reshape in dev builds"],"tags":["candle","reshape","shape"],"backgroundTag":"reshape-element-count-mismatch","analyzedSha":"d5fee525bfde3273eb7c9b75fd2bc4937be867ca","analyzedAt":"2026-09-02T00:15:47.023Z","contentChangedAt":null,"schemaVersion":2},"datasetVersion":"2026-09-09T06:17:21.866Z"}