dpnp.loadtxt¶

dpnp.loadtxt(fname, dtype=<class 'float'>, like=None, device=None, usm_type='device', sycl_queue=None, **kwargs)[source]¶

Load data from a text file.

For full documentation refer to numpy.loadtxt.

Parameters:

fnamefile, str, pathlib.Path, list of str, generator

File, filename, list, or generator to read. If the filename extension is .gz or .bz2, the file is first decompressed. Note that generators must return bytes or strings. The strings in a list or produced by a generator are treated as lines.

dtype{None, str, dtype object}, optional

Data-type of the resulting array. If None, uses a default floating point data type for the device on which the returned array is allocated. A structured data-type is not supported.

Default: float.

device{None, string, SyclDevice, SyclQueue, Device}, optional

An array API concept of device where the output array is created. device can be None, a oneAPI filter selector string, an instance of dpctl.SyclDevice corresponding to a non-partitioned SYCL device, an instance of dpctl.SyclQueue, or a dpnp.tensor.Device object returned by dpnp.ndarray.device.

Default: None.

usm_type{None, "device", "shared", "host"}, optional

The type of SYCL USM allocation for the output array.

Default: "device".

sycl_queue{None, SyclQueue}, optional

A SYCL queue to use for output array allocation and copying. The sycl_queue can be passed as None (the default), which means to get the SYCL queue from device keyword if present or to use a default queue.

Default: None.

Returns:

outdpnp.ndarray: Data read from the text file.

Limitations

Parameter like is supported only with default value None. Otherwise, the function raises NotImplementedError exception.

See also

dpnp.frombuffer: Construct array from the buffer data.
dpnp.fromstring: Construct array from the text data in a string.
dpnp.fromregex: Construct an array from a text file, using regular expression parsing.
dpnp.load: Load arrays or pickled objects from files.
dpnp.genfromtxt: Load data with missing values handled as specified.

Notes

This uses numpy.loadtxt and coerces the result to a DPNP array.

Examples

>>> import dpnp as np
>>> from io import StringIO   # StringIO behaves like a file object
>>> c = StringIO("0 1\n2 3")
>>> np.loadtxt(c)
array([[0., 1.],
       [2., 3.]])

Creating an array on a different device or with a specified usm_type

>>> c = StringIO("0 1\n2 3")
>>> x = np.loadtxt(c, dtype=np.int32) # default case
>>> x.device, x.usm_type
(Device(level_zero:gpu:0), 'device')

>>> c = StringIO("0 1\n2 3")
>>> y = np.loadtxt(c, dtype=np.int32, device='cpu')
>>> y.device, y.usm_type
(Device(opencl:cpu:0), 'device')

>>> c = StringIO("0 1\n2 3")
>>> z = np.loadtxt(c, dtype=np.int32, usm_type="host")
>>> z.device, z.usm_type
(Device(level_zero:gpu:0), 'host')