feat: Add einsum ops #2
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Implements Einstein summation notation (einsum) for NKIPy, supporting: - Matrix multiplication and batch operations (ij,jk->ik, bij,bjk->bik) - Transpose and dimension permutation (ij->ji, ijk->kji) - Reductions and trace operations (ij->, ii->) - Outer products (i,j->ij) - Broadcasting patterns (ij,j->ij) - Complex tensor contractions (ijk,jkl->il) - N-ary operations (i,ij,j->) Implementation decomposes einsum patterns into HLO primitives: - dot_general for contractions - transpose for dimension reordering - reduce for summations - broadcast/multiply for outer products Includes comprehensive tests covering all major einsum patterns and examples demonstrating real-world usage including simplified attention mechanisms.
This script tests various einsum operations using NumPy and NKIPy. It includes matrix multiplication, batch matrix multiplication, dot product, outer product, and more, verifying results against NumPy outputs.
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Thanks for submitting this PR! The einsum support is actually a long wanted feature! We are reviewing this now and will have feedback by EOW. |
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Issue #, if available:
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Description of changes:
Adds support for core Einstein summation patterns and verification utilities.
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Verification:
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