diff options
Diffstat (limited to 'numpy/core/einsumfunc.py')
| -rw-r--r-- | numpy/core/einsumfunc.py | 16 |
1 files changed, 12 insertions, 4 deletions
diff --git a/numpy/core/einsumfunc.py b/numpy/core/einsumfunc.py index d5fdca785..83b7d8287 100644 --- a/numpy/core/einsumfunc.py +++ b/numpy/core/einsumfunc.py @@ -1324,16 +1324,24 @@ def einsum(*operands, **kwargs): particularly significant with larger arrays: >>> a = np.ones(64).reshape(2,4,8) - >>> # Basic `einsum`: ~1520ms (benchmarked on 3.1GHz Intel i5.) + + Basic `einsum`: ~1520ms (benchmarked on 3.1GHz Intel i5.) + >>> for iteration in range(500): ... _ = np.einsum('ijk,ilm,njm,nlk,abc->',a,a,a,a,a) - >>> # Sub-optimal `einsum` (due to repeated path calculation time): ~330ms + + Sub-optimal `einsum` (due to repeated path calculation time): ~330ms + >>> for iteration in range(500): ... _ = np.einsum('ijk,ilm,njm,nlk,abc->',a,a,a,a,a, optimize='optimal') - >>> # Greedy `einsum` (faster optimal path approximation): ~160ms + + Greedy `einsum` (faster optimal path approximation): ~160ms + >>> for iteration in range(500): ... _ = np.einsum('ijk,ilm,njm,nlk,abc->',a,a,a,a,a, optimize='greedy') - >>> # Optimal `einsum` (best usage pattern in some use cases): ~110ms + + Optimal `einsum` (best usage pattern in some use cases): ~110ms + >>> path = np.einsum_path('ijk,ilm,njm,nlk,abc->',a,a,a,a,a, optimize='optimal')[0] >>> for iteration in range(500): ... _ = np.einsum('ijk,ilm,njm,nlk,abc->',a,a,a,a,a, optimize=path) |