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@ -963,11 +963,13 @@ def tensordot(a, b, axes=2):
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non-negative integer_like scalar, `N`; if it is such, then the last `N` dimensions of
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`a` and the first `N` dimensions of `b` are summed over.
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Three common use cases are:
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``axes = 0`` : tensor product
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``axes = 1`` : tensor dot product
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``axes = 2`` : (default) tensor double contraction
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When axes is integer_like, the sequence for evaluation will be: first the `-Nth`
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axis in `a` and 0th axis in `b`, and the -1th axis in `a` and `Nth` axis in `b` last.
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When there is more than one axis to sum over - and they are not the last (first)
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