tensordot performs a tensor contraction where each axis corresponds to a distinct summation index. Duplicate contraction axes (e.g. axes=([1, 1], [0, 0])) are mathematically invalid but currently fail later during an internal transpose, raising ValueError: axes don't match array. This PR adds early validation to reject duplicate axes explicitly, aligning the behavior with the definition of tensor contraction and other NumPy axis-handling APIs.

Current behavior:
Supplying duplicate contraction axes (e.g. axes=([1, 1], [0, 0])) causes tensordot to fail later during an internal transpose, raising ValueError: axes don't match array.

Expected behavior:
Duplicate contraction axes should be rejected explicitly, since tensor contraction requires distinct summation axes, and a clear input-validation error should be raised before any internal reshaping or transposition.