check for identical rows in different numpy arrays

Here’s a vectorised solution:

res = (a[:, None] == b).all(-1).any(-1)

print(res)

array([ True,  True, False,  True])

Note that a[:, None] == b compares each row of a with b element-wise. We then use all + any to deduce if there are any rows which are all True for each sub-array:

print(a[:, None] == b)

[[[ True  True]
  [False  True]
  [False False]]

 [[False  True]
  [ True  True]
  [False False]]

 [[False False]
  [False False]
  [False False]]

 [[False False]
  [False False]
  [ True  True]]]