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# different functions defined in multiarray.py
def inner(a, b):
return numpy.ndarray([0, 0])
def vdot(a, b):
return numpy.ndarray([0, 0])
r {/builddir/build/BUILD/cloudlinux-venv-1.0.11/venv/lib/python3.11/site-packages/astroid/brain/brain_numpy_core_multiarray.py numpy_core_multiarray_transformr s r znumpy.core.multiarrayarrayzsdef array(object, dtype=None, copy=True, order='K', subok=False, ndmin=0):
return numpy.ndarray([0, 0])dotzAdef dot(a, b, out=None):
return numpy.ndarray([0, 0])
empty_likez^def empty_like(a, dtype=None, order='K', subok=True):
return numpy.ndarray((0, 0)) concatenatezVdef concatenate(arrays, axis=None, out=None):
return numpy.ndarray((0, 0))wherezNdef where(condition, x=None, y=None):
return numpy.ndarray([0, 0])emptyzRdef empty(shape, dtype=float, order='C'):
return numpy.ndarray([0, 0])bincountzTdef bincount(x, weights=None, minlength=0):
return numpy.ndarray([0, 0]) busday_countzdef busday_count(
begindates, enddates, weekmask='1111100', holidays=[], busdaycal=None, out=None
):
return numpy.ndarray([0, 0])
busday_offsetzdef busday_offset(
dates, offsets, roll='raise', weekmask='1111100', holidays=None,
busdaycal=None, out=None
):
return numpy.ndarray([0, 0])can_castz@def can_cast(from_, to, casting='safe'):
return TruecopytozNdef copyto(dst, src, casting='same_kind', where=True):
return Nonedatetime_as_stringzwdef datetime_as_string(arr, unit=None, timezone='naive', casting='same_kind'):
return numpy.ndarray([0, 0]) is_busdayz{def is_busday(dates, weekmask='1111100', holidays=None, busdaycal=None, out=None):
return numpy.ndarray([0, 0])lexsortzDdef lexsort(keys, axis=-1):
return numpy.ndarray([0, 0])may_share_memoryzBdef may_share_memory(a, b, max_work=None):
return TruepackbitszTdef packbits(a, axis=None, bitorder='big'):
return numpy.ndarray([0, 0])
shares_memoryz?def shares_memory(a, b, max_work=None):
return Truezbdef unpackbits(a, axis=None, count=None, bitorder='big'):
return numpy.ndarray([0, 0])zYdef unravel_index(indices, shape, order='C'):
return (numpy.ndarray([0, 0]),)zRdef zeros(shape, dtype=float, order='C'):
return numpy.ndarray([0, 0]))
unpackbits
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