Tensor Reshape Calculator
Validate PyTorch tensor reshape operations. Check if reshape, view, and permute operations are valid. See output shape and detect element count mismatches.
Built by Michael Lip
Frequently Asked Questions
What is the difference between reshape and view?
view requires contiguous memory and returns a view (shared data). reshape works on any tensor and may return a view or a copy. Use view when you want to ensure no data copy. Both require total element counts to match.
What does -1 mean in reshape?
Using -1 in one dimension tells PyTorch to infer that dimension automatically. For example, tensor.reshape(4, -1) with 24 elements gives shape (4, 6). Only one dimension can be -1.
Why does view give a contiguous error?
view requires contiguous memory. Operations like transpose and permute make tensors non-contiguous. Fix: call tensor.contiguous().view(...) or use tensor.reshape(...) which handles non-contiguous tensors.
How does permute differ from reshape?
permute reorders dimensions without changing data layout. reshape changes shape interpretation. permute(0,2,1) on shape [3,4,5] gives [3,5,4]. permute never copies data.
Is this tool free?
Yes. All HeyTensor tools are free, run in your browser, and require no signup.
About This Tool
Part of HeyTensor. All calculations run in your browser. Source code on GitHub.
Contact
Built by Michael Lip. Email [email protected].