Source code for maxframe.tensor.misc.shape

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# Licensed under the Apache License, Version 2.0 (the "License");
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#
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import numpy as np

from maxframe import opcodes
from maxframe.core import ExecutableTuple
from maxframe.serialization.serializables import Int32Field
from maxframe.tensor.core import TensorOrder
from maxframe.tensor.datasource import tensor as astensor
from maxframe.tensor.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)