Dolphin dtype

class dolphin.dtype(value)

Bases: Enum

Dolphin data types In order to manage the data types in Dolphin, bind dolphin types the numpy data types as well as the CUDA data types. To do so, each element from the Enum class is a tuple containing the numpy data type (numpy.dtype) and the CUDA data type (str).

uint8 = (<class 'numpy.uint8'>, 'uint8_t')

uint16 = (<class 'numpy.uint16'>, 'uint16_t')

uint32 = (<class 'numpy.uint32'>, 'uint32_t')

int8 = (<class 'numpy.int8'>, 'int8_t')

int16 = (<class 'numpy.int16'>, 'int16_t')

int32 = (<class 'numpy.int32'>, 'int32_t')

float32 = (<class 'numpy.float32'>, 'float')

float64 = (<class 'numpy.float64'>, 'double')

__call__(value: Union[int, float, number]) → dtype

In order to use the data type as a function to cast a value into a particular type, we need to implement the __call__ method.

Example:

a = dtype.uint8
a(4) -> numpy.uint8(4)

Parameters:

value (Union[int, float, numpy.number]) – The value to cast to the data type

Returns:

The numpy casted number passed as value

Return type:

numpy.dtype

property numpy_dtype: dtype

Since Dolphin data types are tuples, we need to access the first element which is the numpy data type.

Returns:

The equivalent numpy data type of Dolphin data type

Return type:

numpy.dtype

property cuda_dtype: str

Since Dolphin data types are tuples, we need to access the second element which is the CUDA data type. Which as well are standard C types.

Returns:

The equivalent CUDA data type of Dolphin data type

Return type:

str

property itemsize: int

Returns the size of the data type in bytes. Uses the numpy data type to get the size :

>>> @property
>>> def itemsize(self) -> int:
>>>     return self.numpy_dtype.itemsize

static from_numpy_dtype(numpy_dtype: dtype) → dtype

Returns the equivalent Dolphin data type from the numpy data type.

Parameters:

numpy_dtype (numpy.dtype) – The numpy data type

Returns:

The equivalent Dolphin data type

Return type:

dtype

__getitem__(key: Union[str, int]) → Union[dtype, str]

In order to dynamically access the numpy and CUDA data types, we also need to implement the __getitem__ method. if key is an integer, it will return one of the tuple element as long as the key is either 0 or 1. if key is a string, it will return the numpy or CUDA data type as long as the key is either ‘numpy_dtype’ or ‘cuda_dtype’.

Usage:

a = dtype.uint8
a[0]                  # numpy.uint8
a[1]                  # 'uint8_t'
a["numpy_dtype"]      # numpy.uint8
a["cuda_dtype"]       # 'uint8_t'

Parameters:

key (Union[str, int]) – ‘numpy_dtype’ or ‘cuda_dtype’ or a int 0 or 1

Raises:

KeyError – If the key is not valid as described above

Returns:

The numpy or CUDA data type

Return type:

Union[numpy.dtype, str]

__module__ = 'dolphin.core.dtype'