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""" |
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Array API Inspection namespace |
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This is the namespace for inspection functions as defined by the array API |
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standard. See |
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https://data-apis.org/array-api/latest/API_specification/inspection.html for |
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more details. |
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""" |
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from numpy._core import ( |
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dtype, |
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bool, |
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intp, |
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int8, |
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int16, |
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int32, |
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int64, |
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uint8, |
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uint16, |
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uint32, |
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uint64, |
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float32, |
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float64, |
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complex64, |
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complex128, |
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) |
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class __array_namespace_info__: |
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""" |
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Get the array API inspection namespace for NumPy. |
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The array API inspection namespace defines the following functions: |
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- capabilities() |
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- default_device() |
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- default_dtypes() |
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- dtypes() |
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- devices() |
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See |
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https://data-apis.org/array-api/latest/API_specification/inspection.html |
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for more details. |
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Returns |
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------- |
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info : ModuleType |
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The array API inspection namespace for NumPy. |
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Examples |
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-------- |
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>>> info = np.__array_namespace_info__() |
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>>> info.default_dtypes() |
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{'real floating': numpy.float64, |
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'complex floating': numpy.complex128, |
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'integral': numpy.int64, |
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'indexing': numpy.int64} |
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""" |
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__module__ = 'numpy' |
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def capabilities(self): |
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""" |
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Return a dictionary of array API library capabilities. |
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The resulting dictionary has the following keys: |
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- **"boolean indexing"**: boolean indicating whether an array library |
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supports boolean indexing. Always ``True`` for NumPy. |
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- **"data-dependent shapes"**: boolean indicating whether an array |
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library supports data-dependent output shapes. Always ``True`` for |
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NumPy. |
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See |
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https://data-apis.org/array-api/latest/API_specification/generated/array_api.info.capabilities.html |
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for more details. |
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See Also |
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-------- |
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__array_namespace_info__.default_device, |
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__array_namespace_info__.default_dtypes, |
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__array_namespace_info__.dtypes, |
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__array_namespace_info__.devices |
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Returns |
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------- |
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capabilities : dict |
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A dictionary of array API library capabilities. |
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Examples |
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-------- |
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>>> info = np.__array_namespace_info__() |
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>>> info.capabilities() |
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{'boolean indexing': True, |
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'data-dependent shapes': True} |
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""" |
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return { |
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"boolean indexing": True, |
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"data-dependent shapes": True, |
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} |
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def default_device(self): |
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""" |
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The default device used for new NumPy arrays. |
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For NumPy, this always returns ``'cpu'``. |
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See Also |
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-------- |
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__array_namespace_info__.capabilities, |
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__array_namespace_info__.default_dtypes, |
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__array_namespace_info__.dtypes, |
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__array_namespace_info__.devices |
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Returns |
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------- |
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device : str |
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The default device used for new NumPy arrays. |
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Examples |
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-------- |
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>>> info = np.__array_namespace_info__() |
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>>> info.default_device() |
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'cpu' |
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""" |
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return "cpu" |
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def default_dtypes(self, *, device=None): |
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""" |
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The default data types used for new NumPy arrays. |
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For NumPy, this always returns the following dictionary: |
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- **"real floating"**: ``numpy.float64`` |
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- **"complex floating"**: ``numpy.complex128`` |
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- **"integral"**: ``numpy.intp`` |
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- **"indexing"**: ``numpy.intp`` |
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Parameters |
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---------- |
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device : str, optional |
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The device to get the default data types for. For NumPy, only |
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``'cpu'`` is allowed. |
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Returns |
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------- |
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dtypes : dict |
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A dictionary describing the default data types used for new NumPy |
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arrays. |
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See Also |
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-------- |
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__array_namespace_info__.capabilities, |
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__array_namespace_info__.default_device, |
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__array_namespace_info__.dtypes, |
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__array_namespace_info__.devices |
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|
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Examples |
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-------- |
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>>> info = np.__array_namespace_info__() |
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>>> info.default_dtypes() |
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{'real floating': numpy.float64, |
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'complex floating': numpy.complex128, |
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'integral': numpy.int64, |
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'indexing': numpy.int64} |
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""" |
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if device not in ["cpu", None]: |
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raise ValueError( |
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'Device not understood. Only "cpu" is allowed, but received:' |
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f' {device}' |
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) |
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return { |
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"real floating": dtype(float64), |
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"complex floating": dtype(complex128), |
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"integral": dtype(intp), |
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"indexing": dtype(intp), |
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} |
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def dtypes(self, *, device=None, kind=None): |
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""" |
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The array API data types supported by NumPy. |
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Note that this function only returns data types that are defined by |
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the array API. |
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Parameters |
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---------- |
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device : str, optional |
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The device to get the data types for. For NumPy, only ``'cpu'`` is |
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allowed. |
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kind : str or tuple of str, optional |
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The kind of data types to return. If ``None``, all data types are |
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returned. If a string, only data types of that kind are returned. |
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If a tuple, a dictionary containing the union of the given kinds |
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is returned. The following kinds are supported: |
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- ``'bool'``: boolean data types (i.e., ``bool``). |
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- ``'signed integer'``: signed integer data types (i.e., ``int8``, |
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``int16``, ``int32``, ``int64``). |
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- ``'unsigned integer'``: unsigned integer data types (i.e., |
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``uint8``, ``uint16``, ``uint32``, ``uint64``). |
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- ``'integral'``: integer data types. Shorthand for ``('signed |
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integer', 'unsigned integer')``. |
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- ``'real floating'``: real-valued floating-point data types |
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(i.e., ``float32``, ``float64``). |
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- ``'complex floating'``: complex floating-point data types (i.e., |
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``complex64``, ``complex128``). |
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- ``'numeric'``: numeric data types. Shorthand for ``('integral', |
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'real floating', 'complex floating')``. |
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Returns |
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------- |
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dtypes : dict |
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A dictionary mapping the names of data types to the corresponding |
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NumPy data types. |
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See Also |
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-------- |
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__array_namespace_info__.capabilities, |
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__array_namespace_info__.default_device, |
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__array_namespace_info__.default_dtypes, |
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__array_namespace_info__.devices |
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Examples |
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-------- |
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>>> info = np.__array_namespace_info__() |
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>>> info.dtypes(kind='signed integer') |
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{'int8': numpy.int8, |
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'int16': numpy.int16, |
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'int32': numpy.int32, |
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'int64': numpy.int64} |
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""" |
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if device not in ["cpu", None]: |
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raise ValueError( |
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'Device not understood. Only "cpu" is allowed, but received:' |
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f' {device}' |
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) |
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if kind is None: |
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return { |
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"bool": dtype(bool), |
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"int8": dtype(int8), |
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"int16": dtype(int16), |
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"int32": dtype(int32), |
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"int64": dtype(int64), |
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"uint8": dtype(uint8), |
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"uint16": dtype(uint16), |
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"uint32": dtype(uint32), |
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"uint64": dtype(uint64), |
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"float32": dtype(float32), |
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"float64": dtype(float64), |
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"complex64": dtype(complex64), |
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"complex128": dtype(complex128), |
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} |
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if kind == "bool": |
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return {"bool": bool} |
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if kind == "signed integer": |
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return { |
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"int8": dtype(int8), |
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"int16": dtype(int16), |
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"int32": dtype(int32), |
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"int64": dtype(int64), |
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} |
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if kind == "unsigned integer": |
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return { |
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"uint8": dtype(uint8), |
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"uint16": dtype(uint16), |
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"uint32": dtype(uint32), |
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"uint64": dtype(uint64), |
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} |
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if kind == "integral": |
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return { |
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"int8": dtype(int8), |
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"int16": dtype(int16), |
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"int32": dtype(int32), |
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"int64": dtype(int64), |
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"uint8": dtype(uint8), |
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"uint16": dtype(uint16), |
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"uint32": dtype(uint32), |
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"uint64": dtype(uint64), |
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} |
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if kind == "real floating": |
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return { |
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"float32": dtype(float32), |
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"float64": dtype(float64), |
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} |
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if kind == "complex floating": |
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return { |
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"complex64": dtype(complex64), |
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"complex128": dtype(complex128), |
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} |
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if kind == "numeric": |
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return { |
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"int8": dtype(int8), |
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"int16": dtype(int16), |
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"int32": dtype(int32), |
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"int64": dtype(int64), |
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"uint8": dtype(uint8), |
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"uint16": dtype(uint16), |
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"uint32": dtype(uint32), |
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"uint64": dtype(uint64), |
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"float32": dtype(float32), |
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"float64": dtype(float64), |
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"complex64": dtype(complex64), |
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"complex128": dtype(complex128), |
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} |
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if isinstance(kind, tuple): |
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res = {} |
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for k in kind: |
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res.update(self.dtypes(kind=k)) |
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return res |
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raise ValueError(f"unsupported kind: {kind!r}") |
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def devices(self): |
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""" |
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The devices supported by NumPy. |
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For NumPy, this always returns ``['cpu']``. |
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Returns |
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------- |
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devices : list of str |
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The devices supported by NumPy. |
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|
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See Also |
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-------- |
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__array_namespace_info__.capabilities, |
|
__array_namespace_info__.default_device, |
|
__array_namespace_info__.default_dtypes, |
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__array_namespace_info__.dtypes |
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|
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Examples |
|
-------- |
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>>> info = np.__array_namespace_info__() |
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>>> info.devices() |
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['cpu'] |
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""" |
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return ["cpu"] |
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