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@seberg
Last active March 28, 2021 10:39
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import numpy as np
def object_einsum(string, *arrays):
"""Simplified object einsum, not as much error checking
does not support "..." or list input and will see "...", etc. as three times
an axes identifier, tries normal einsum first!
NOTE: This is untested, and not fast, but object type is
never really fast anyway...
"""
try:
return np.einsum(string, *arrays)
except TypeError:
pass
s = string.split('->')
in_op = s[0].split(',')
out_op = None if len(s) == 1 else s[1].replace(' ', '')
in_op = [axes.replace(' ', '') for axes in in_op]
all_axes = set()
for axes in in_op:
all_axes.update(axes)
if out_op is None:
out_op = sorted(all_axes)
else:
all_axes.update(out_op)
perm_dict = {_[1]: _[0] for _ in enumerate(all_axes)}
dims = len(perm_dict)
op_axes = []
for axes in (in_op + list((out_op,))):
op = [-1] * dims
for i, ax in enumerate(axes):
op[perm_dict[ax]] = i
op_axes.append(op)
op_flags = [('readonly',)] * len(in_op) + [('readwrite', 'allocate')]
dtypes = [np.object_] * (len(in_op) + 1) # cast all to object
nditer = np.nditer(arrays + (None,), op_axes=op_axes, flags=['buffered', 'delay_bufalloc', 'reduce_ok', 'grow_inner', 'refs_ok'], op_dtypes=dtypes, op_flags=op_flags)
nditer.operands[-1][...] = 0
nditer.reset()
for vals in nditer:
out = vals[-1]
prod = vals[0]
for value in vals[1:-1]:
prod *= value
out += prod
return nditer.operands[-1]
@ketch
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ketch commented Mar 28, 2021

I had to combine the changes made by @gugar20 and @wenlibin02 to get this to work correctly.

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