Source code for maxframe.tensor.misc.shape

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import numpy as np

from ... import opcodes
from ...core import ExecutableTuple
from ...serialization.serializables import Int32Field
from ..core import TensorOrder
from ..datasource import tensor as astensor
from ..operators import TensorOperator, TensorOperatorMixin


class TensorGetShape(TensorOperator, TensorOperatorMixin):
    _op_type_ = opcodes.GET_SHAPE

    ndim = Int32Field("ndim")

    def __init__(self, pure_depends=None, **kw):
        super().__init__(_pure_depends=pure_depends, **kw)

    @property
    def output_limit(self):
        return self.ndim

    def __call__(self, a):
        if not np.isnan(a.size):
            return ExecutableTuple([astensor(s) for s in a.shape])

        kws = []
        for i in range(self.output_limit):
            kws.append(
                {
                    "shape": (),
                    "dtype": np.dtype(np.intc),
                    "order": TensorOrder.C_ORDER,
                    "i": i,
                }
            )
        return ExecutableTuple(self.new_tensors([a], kws=kws))




def shape(a):
    """
    Return the shape of a tensor.

    Parameters
    ----------
    a : array_like
        Input tensor.

    Returns
    -------
    shape : ExecutableTuple of tensors
        The elements of the shape tuple give the lengths of the
        corresponding array dimensions.

    Examples
    --------
    >>> import maxframe.tensor as mt

    >>> mt.shape(mt.eye(3)).execute()
    (3, 3)
    >>> mt.shape([[1, 2]]).execute()
    (1, 2)
    >>> mt.shape([0]).execute()
    (1,)
    >>> mt.shape(0).execute()
    ()

    >>> a = mt.array([(1, 2), (3, 4)], dtype=[('x', 'i4'), ('y', 'i4')])
    >>> mt.shape(a).execute()
    (2,)

    """
    a = astensor(a)
    op = TensorGetShape(ndim=a.ndim)
    return op(a)