jax.numpy.can_cast

jax.numpy.can_cast(from_, to, casting='safe')

Returns True if cast between data types can occur according to the casting rule.

Parameters:

• from (dtype, dtype specifier, NumPy scalar, or array) – Data type, NumPy scalar, or array to cast from.

• to (dtype or dtype specifier) – Data type to cast to.

• casting ({'no', 'equiv', 'safe', 'same_kind', 'unsafe'}, optional) –

  Controls what kind of data casting may occur.

  • ’no’ means the data types should not be cast at all.

  • ’equiv’ means only byte-order changes are allowed.

  • ’safe’ means only casts which can preserve values are allowed.

  • ’same_kind’ means only safe casts or casts within a kind, like float64 to float32, are allowed.

  • ’unsafe’ means any data conversions may be done.

Returns:

out – True if cast can occur according to the casting rule.

Return type:

bool

Notes

Changed in version 2.0: This function does not support Python scalars anymore and does not apply any value-based logic for 0-D arrays and NumPy scalars.

See also

dtype, result_type

Examples

Basic examples

>>> import numpy as np
>>> np.can_cast(np.int32, np.int64)
True
>>> np.can_cast(np.float64, complex)
True
>>> np.can_cast(complex, float)
False

>>> np.can_cast('i8', 'f8')
True
>>> np.can_cast('i8', 'f4')
False
>>> np.can_cast('i4', 'S4')
False