contract_expression inconsistent with contract

[SebastianSemper]

I am using numpy 1.25.1 and opt_einsum 3.3.0.

Python 3.11.4 | packaged by conda-forge | (main, Jun 10 2023, 18:08:41) [Clang 15.0.7 ] on darwin
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>>> import numpy as np
>>> import opt_einsum as oe
>>> x = np.random.randn(2,3,4)
>>> y = np.random.randn(2,3)
>>> np.einsum(x, [0,1,Ellipsis], y, [0,1], [0, Ellipsis])
array([[ 0.50400543,  1.60218127, -2.32967585,  2.806769  ],
       [-1.86581498,  1.98371577, -3.15319885, -1.78047722]])
>>> oe.contract(x, [0,1,Ellipsis], y, [0,1], [0, Ellipsis])
array([[ 0.50400543,  1.60218127, -2.32967585,  2.806769  ],
       [-1.86581498,  1.98371577, -3.15319885, -1.78047722]])
>>> oe.contract_expression(x.shape, [0,1,Ellipsis], y.shape, [0,1], [0, Ellipsis])
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/opt/homebrew/Caskroom/miniconda/base/envs/finest/lib/python3.11/site-packages/opt_einsum/contract.py", line 882, in contract_expression
    return contract(subscripts, *dummy_arrays, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/homebrew/Caskroom/miniconda/base/envs/finest/lib/python3.11/site-packages/opt_einsum/contract.py", line 497, in contract
    operands, contraction_list = contract_path(*operands,
                                 ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/homebrew/Caskroom/miniconda/base/envs/finest/lib/python3.11/site-packages/opt_einsum/contract.py", line 210, in contract_path
    input_subscripts, output_subscript, operands = parser.parse_einsum_input(operands)
                                                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/homebrew/Caskroom/miniconda/base/envs/finest/lib/python3.11/site-packages/opt_einsum/parser.py", line 309, in parse_einsum_input
    if operands[num].shape == ():
       ^^^^^^^^^^^^^^^^^^^^^^^^^
ValueError: operands could not be broadcast together with shapes (3,) (0,)

I get the above error, which I assume must be some bug, since both oe.contract and np.einsum seem to be working. As a hint, this error does not occur, when using numpy 1.23.5.

Let me know, if you need any more input form me.