Tensor.asarray

Tensor.asarray(out=None, must_be_contiguous: bool = False)[source]

Extract the data of this array as a backend-specific array/tensor.

This method is invoked when calling numpy.asarray on this tensor.

Parameters

outarray_like, optional: Array in which the result should be written in-place. Has to be contiguous and of the correct backend, dtype and device.
must_be_contiguous: bool: If this is True, then the returned array must occupy a single block of memory and the axes be ordered (in C order). Cf. numpy.ascontiguousarray. This may require making a copy. If False is given, the returned array may be a view or have transposed axes, if this allows avoiding a copy. If an out argument is provided, must_be_contiguous is irrelevant.

Returns

asarrayarray_like: Numpy array, pytorch tensor or similar with the same data type as self. If out was given, the returned object is a reference to it.

Examples

>>> space = odl.rn(3, dtype='float32')
>>> x = space.element([1, 2, 3])
>>> x.asarray()
array([ 1.,  2.,  3.], dtype=float32)
>>> out = np.empty(3, dtype='float32')
>>> result = x.asarray(out=out)
>>> out
array([ 1.,  2.,  3.], dtype=float32)
>>> result is out
True
>>> space = odl.rn((2, 3))
>>> space.one().asarray()
array([[ 1.,  1.,  1.],
       [ 1.,  1.,  1.]])