pylibraft.common.device_ndarray#
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Classes#
pylibraft.common.device_ndarray is meant to be a very lightweight |
Module Contents#
- class pylibraft.common.device_ndarray.device_ndarray(np_ndarray)#
pylibraft.common.device_ndarray is meant to be a very lightweight __cuda_array_interface__ wrapper around a numpy.ndarray.
- classmethod empty(shape, dtype=numpy.float32, order='C')#
Return a new device_ndarray of given shape and type, without initializing entries.
Parameters#
- shapeint or tuple of int
Shape of the empty array, e.g., (2, 3) or 2.
- dtypedata-type, optional
Desired output data-type for the array, e.g, numpy.int8. Default is numpy.float32.
- order{‘C’, ‘F’}, optional (default: ‘C’)
Whether to store multi-dimensional dat ain row-major (C-style) or column-major (Fortran-style) order in memory
- copy_to_host()#
Returns a new numpy.ndarray object on host with the current contents of this device_ndarray
- property __cuda_array_interface__#
Returns the __cuda_array_interface__ compliant dict for integrating with other device-enabled libraries using zero-copy semantics.
- property c_contiguous#
Is the current device_ndarray laid out in row-major format?
- property dtype#
Datatype of the current device_ndarray instance
- property f_contiguous#
Is the current device_ndarray laid out in column-major format?
- property shape#
Shape of the current device_ndarray instance
- property strides#
Strides of the current device_ndarray instance